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V O L U M E F I F T Y S I X

ADVANCES IN

MARINE BIOLOGY

Advances in MARINE BIOLOGY

Series Editor

DAVID W. SIMSMarine Biological Association of the United Kingdom,The Laboratory, Citadel Hill, Plymouth, United KingdomandMarine Biology and Ecology Research CentreSchool of Biological SciencesUniversity of Plymouth, Drake CircusPlymouth, United Kingdom

Editors Emeritus

LEE A. FUIMANUniversity of Texas at Austin

CRAIG M. YOUNGOregon Institute of Marine Biology

Advisory Editorial Board

ANDREW J. GOODAYSouthampton Oceanography Centre

GRAEME C. HAYSUniversity of Wales Swansea

SANDRA E. SHUMWAYUniversity of Connecticut

ROBERT B. WHITLATCHUniversity of Connecticut

V O L U M E F I F T Y S I X

ADVANCES IN

MARINE BIOLOGY

Edited by

DAVID W. SIMSMarine Biological Association of the United KingdomThe Laboratory, Citadel HillPlymouth, United KingdomandMarine Biology and Ecology Research CentreSchool of Biological SciencesUniversity of Plymouth, Drake CircusPlymouth, United Kingdom

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CONTRIBUTORS TO VOLUME 56

Andreas J. AnderssonBermuda Institute of Ocean Sciences, St. George’s GE 01, Bermuda

Avan AntiaChristian-Albrechts-University of Kiel, 24119 Kiel, Germany

Nicholas R. BatesChristian-Albrechts-University of Kiel, 24119 Kiel, Germany

Ulrich BathmannAlfred Wegener Institute, D-27570 Bremerhaven, Germany

Gregory BeaugrandSir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill,

Plymouth PL1 2PB, United Kingdom and Centre National de la Recherche

Scientifique, Laboratoire d’Oceanologie et de Geosciences, Station Marine,

Universite des Sciences et Technologies de Lille, 62930 Wimereux, France

Juan BellasDepartamento de Ecoloxıa e Bioloxıa Animal, Facultade de Ciencias do Mar,

Universidade de Vigo, 36310 Vigo, Spain

Corey J. A. BradshawThe Environment Institute and School of Earth and Environmental Sciences,

University of Adelaide, Adelaide, South Australia 5005, Australia and South

Australian Research and Development Institute, Henley Beach, South Australia

5022, Australia

Holger BrixDepartment of Atmospheric and Oceanic Sciences, University of California -

Los Angeles, Los Angeles, California 90095-1567, USA

Rik C. BuckworthFisheries, Northern Territory Department of Primary Industries, Fisheries and

Mines, Darwin, Northern Territory 0801, Australia

Stephen DyeCentre for Environment, Fisheries and Aquaculture Science (Cefas), Lowestoft,

Suffolk NR33 OHT, United Kingdom

v

Martin EdwardsSir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill,

Plymouth PL1 2PB, United Kingdom

Iain C. FieldSchool for Environmental Research, Institute of Advanced Studies, Charles Darwin

University, Darwin, Northern Territory 0909, Australia and Australian Institute of

Marine Science, Casuarina MC, Northern Territory 0811, Australia

Astrid C. FischerSir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill,

Plymouth PL1 2PB, United Kingdom

Tore FurevikGeophysical Institute, N-5007 Bergen, Norway

Reidun GangstøUniversity of Bern, 3012 Bern, Switzerland

Martin J. GennerMarine Biological Association of the United Kingdom, The Laboratory, Citadel

Hill, Plymouth PL1 2PB, United Kingdom and School of Biological Sciences,

University of Bristol, Bristol BS8 1UG, United Kingdom

Hjalmar HatunFaroese Fisheries Laboratory, FO-110 Torshavn, Faroe Islands

Stephen J. HawkinsMarine Biological Association of the United Kingdom, The Laboratory, Citadel

Hill, Plymouth PL1 2PB, United Kingdom and College of Natural Sciences,

Memorial Building, Bangor University, Gwynedd LL57 2UW, United Kingdom

Graeme C. HaysInstitute of Environmental Sustainability, Swansea University, Swansea SA2 8PP,

United Kingdom

Russell R. HopcroftInstitute of Marine Science, University of Alaska Fairbanks, Fairbanks, Alaska

99775-7220, USA

Sabine KastenAlfred Wegener Institute, D-27570 Bremerhaven, Germany

Ralph KeelingScripps CO2 Program, La Jolla, California 92093-0244, USA

Mike KendallPlymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, United

Kingdom

vi Contributors

Emily Lewis-BrownWWF-UK, Panda House, Weyside Park, Godalming, Surrey GU7 1XR, United

Kingdom

Colin J. LimpusEnvironmental Sciences, Environmental Protection Agency, Brisbane, Queensland

4002, Australia

Fred T. MackenzieDepartment of Oceanography, School of Ocean and Earth Science and Technology,

University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA

Gill MalinSchool of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ,

United Kingdom

Cecilie MauritzenNorwegian Meteorological Institute, Blindern, 0313 Oslo, Norway

Mark G. MeekanAustralian Institute of Marine Science, Casuarina MC, Northern Territory 0811,

Australia

Michael P. MeredithBritish Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom

Nova MieszkowskaMarine Biological Association of the United Kingdom, The Laboratory, Citadel

Hill, Plymouth PL1 2PB, United Kingdom

Jon OlafssonUniversity of Iceland and Marine Research Institute, IS-121 Reykjavik, Iceland

Charlie PaullMonterey Bay Aquarium Research Institute, Moss Landing, California 95039, USA

Milagros Penela-ArenazDepartamento de Ecoloxıa e Bioloxıa Animal, Facultade de Ciencias do Mar,


Elvira S. PoloczanskaClimate Adaptation Flagship, CSIRO Marine and Atmospheric Research,

Cleveland, Queensland 4163, Australia

Corinne Le QuereBritish Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom and

School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ,

United Kingdom

Contributors vii

Philip C. ReidSir Alister Hardy Foundation for Ocean Science, andMarine Biological Association

of the UK, The Laboratory, Citadel Hill, Plymouth PL1 2PB, United Kingdom;

Marine Institute, University of Plymouth, Plymouth PL4 8AA, United Kingdom

Eric RignotUniversity of California - Irvine, Croul Hall, Irvine, California 92697, USA; and

Jet Propulsion Laboratory, Pasadena, California 91214, USA

Koji ShimadaFaculty of Marine Science, Department of Ocean Sciences, Tokyo University of

Marine Science and Technology, 4-5-7, Konan, Minato-ku, Tokyo 108-8477,

Japan

David W. SimsMarine Biological Association of the United Kingdom, The Laboratory, Citadel

Hill, Plymouth PL1 2PB, United Kingdom and Marine Biology and Ecology

Research Centre, School of Biological Sciences, University of Plymouth, Drake

Circus, Plymouth PL4 8AA, United Kingdom

Mike SparrowSCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United

Kingdom

Elsa VazquezDepartamento de Ecoloxıa e Bioloxıa Animal, Facultade de Ciencias do Mar,


Meike VogtSchool of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ,

United Kingdom

Craig WallaceSCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United

Kingdom

Zhaomin WangBritish Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom

Richard WashingtonSchool of Geography and the Environment, Oxford University Centre for the

Environment (Dyson Perrins Building), University of Oxford, Oxford OX1 3QY,

United Kingdom

viii Contributors

CONTENTS

Contributors to Volume 56 v

Series Contents for Last Fifteen Years xi

1. Impacts of the Oceans on Climate Change 1

Philip C. Reid, Astrid C. Fischer, Emily Lewis-Brown, Michael P. Meredith,

Mike Sparrow, Andreas J. Andersson, Avan Antia, Nicholas R. Bates,

Ulrich Bathmann, Gregory Beaugrand, Holger Brix, Stephen Dye,

Martin Edwards, Tore Furevik, Reidun Gangstø, Hjalmar Hatun, Russell R.

Hopcroft, Mike Kendall, Sabine Kasten, Ralph Keeling, Corinne Le Quere,

Fred T. Mackenzie, Gill Malin, Cecilie Mauritzen, Jon Olafsson, Charlie Paull,

Eric Rignot, Koji Shimada, Meike Vogt, Craig Wallace, Zhaomin Wang,

and Richard Washington

1. Introduction 5

2. Ocean Physics, Temperature, Circulation, Sea-Level Rise

and the Hydrological Cycle 12

3. Primary Production: Plankton, Light and Nutrients 27

4. The Solubility, Biological and Continental Shelf Carbon Pumps 51

5. Ocean Acidification and the Carbonate Pump 62

6. A Special Case: The Arctic and Seas Adjacent to Greenland 80

7. The Southern Ocean and Climate 93

8. Climate Models 106

9. Conclusions and Recommendations 115

Appendix: Workshop Participants 126

Acknowledgements 127

References 127

2. Vulnerability of Marine Turtles to Climate Change 151

Elvira S. Poloczanska, Colin J. Limpus, and Graeme C. Hays

1. Introduction 152

2. Marine Turtle Biology and Life History 154

3. Observed and Projected Changes in Oceans and Atmosphere 159

4. Climate Change Impacts on Marine Turtles 163

5. Responses to Past Climate Change 185

6. Adaptation and Resilience 187

7. Global Trends 189

ix

8. Recommendations 189


References 191

3. Effects of Climate Change and Commercial Fishing on AtlanticCod Gadus morhua 213

Nova Mieszkowska, Martin J. Genner, Stephen J. Hawkins,

and David W. Sims

1. Introduction 214

2. Impacts of Climate Change 222

3. Impacts of Fishing 238

4. Population-Level Impacts of Fishing and Climate Change 245

5. Monitoring Status and Recovery of North Sea Cod: A Case Study 249

6. Concluding Remarks 250


References 252

4. Susceptibility of Sharks, Rays and Chimaeras toGlobal Extinction 275

Iain C. Field, Mark G. Meekan, Rik C. Buckworth,

and Corey J. A. Bradshaw

1. Introduction 277

2. Chondrichthyan Life History 281

3. Past and Present Threats 284

4. Chondrichthyan Extinction Risk 308

5. Implications of Chondrichthyan Species Loss on Ecosystem

Structure, Function and Stability 328

6. Synthesis and Knowledge Gaps 335



References 343

5. Effects of the Prestige Oil Spill on the Biota of NW Spain:5 Years of Learning 365

Milagros Penela-Arenaz, Juan Bellas, and Elsa Vazquez

1. Introduction 366

2. Effects of the Prestige Oil Spill on the Marine Biota 373

3. Conclusion 386

References 390

Taxonomic Index 397

Subject Index 401

x Contents

SERIES CONTENTS FOR LAST FIFTEEN YEARS*

Volume 30, 1994.Vincx, M., Bett, B. J., Dinet, A., Ferrero, T., Gooday, A. J., Lambs-head, P. J. D., Pfannkuche, O., Soltweddel, T. and Vanreusel, A.Meiobenthos of the deep Northeast Atlantic. pp. 1–88.

Brown, A. C. and Odendaal, F. J. The biology of oniscid isopoda ofthe genus Tylos. pp. 89–153.

Ritz, D. A. Social aggregation in pelagic invertebrates. pp. 155–216.Ferron, A. and Legget, W. C. An appraisal of condition measures formarine fish larvae. pp. 217–303.

Rogers, A. D. The biology of seamounts. pp. 305–350.

Volume 31, 1997.Gardner, J. P. A. Hybridization in the sea. pp. 1–78.Egloff, D. A., Fofonoff, P. W. and Onbe, T. Reproductive behaviourof marine cladocerans. pp. 79–167.

Dower, J. F., Miller, T. J. and Leggett, W. C. The role of microscaleturbulence in the feeding ecology of larval fish. pp. 169–220.

Brown, B. E. Adaptations of reef corals to physical environmentalstress. pp. 221–299.

Richardson, K. Harmful or exceptional phytoplankton blooms in themarine ecosystem. pp. 301–385.

Volume 32, 1997.Vinogradov, M. E. Some problems of vertical distribution of meso-and macroplankton in the ocean. pp. 1–92.

Gebruk, A. K., Galkin, S. V., Vereshchaka, A. J., Moskalev, L. I. andSouthward, A. J. Ecology and biogeography of the hydrothermalvent fauna of the Mid-Atlantic Ridge. pp. 93–144.

Parin, N. V., Mironov, A. N. and Nesis, K. N. Biology of the Nazcaand Sala y Gomez submarine ridges, an outpost of the Indo-WestPacific fauna in the eastern Pacific Ocean: composition and distri-bution of the fauna, its communities and history. pp. 145–242.

Nesis, K. N. Goniatid squids in the subarctic North Pacific: ecology,biogeography, niche diversity, and role in the ecosystem. pp. 243–324.

Vinogradova, N. G. Zoogeography of the abyssal and hadal zones.pp. 325–387.

Zezina, O. N. Biogeography of the bathyal zone. pp. 389–426.

*The full list of contents for volumes 1–37 can be found in volume 38.

xi

Sokolova, M. N. Trophic structure of abyssal macrobenthos.pp. 427–525.

Semina, H. J. An outline of the geographical distribution of oceanicphytoplankton. pp. 527–563.

Volume 33, 1998.Mauchline, J. The biology of calanoid copepods. pp. 1–660.

Volume 34, 1998.Davies, M. S. and Hawkins, S. J. Mucus from marine molluscs.pp. 1–71.

Joyeux, J. C. andWard, A. B. Constraints on coastal lagoon fisheries.pp. 73–199.

Jennings, S. and Kaiser, M. J. The effects of fishing on marineecosystems. pp. 201–352.

Tunnicliffe, V., McArthur, A. G. andMcHugh, D. A biogeographicalperspective of the deep-sea hydrothermal vent fauna. pp. 353–442.

Volume 35, 1999.Creasey, S. S. and Rogers, A. D. Population genetics of bathyal andabyssal organisms. pp. 1–151.

Brey, T. Growth performance and mortality in aquatic macrobenthicinvertebrates. pp. 153–223.

Volume 36, 1999.Shulman, G. E. and Love, R. M. The biochemical ecology of marinefishes. pp. 1–325.

Volume 37, 1999.His, E., Beiras, R. and Seaman, M. N. L. The assessment of marinepollution—bioassays with bivalve embryos and larvae. pp. 1–178.

Bailey, K. M., Quinn, T. J., Bentzen, P. and Grant, W. S. Populationstructure and dynamics of walleye pollock, Theragra chalcogramma.pp. 179–255.

Volume 38, 2000.Blaxter, J. H. S. The enhancement of marine fish stocks. pp. 1–54.Bergstrom, B. I. The biology of Pandalus. pp. 55–245.

Volume 39, 2001.Peterson, C. H. The ‘‘Exxon Valdez’’ oil spill in Alaska: acute indirectand chronic effects on the ecosystem. pp. 1–103.

Johnson, W. S., Stevens, M. and Watling, L. Reproduction anddevelopment of marine peracaridans. pp. 105–260.

xii Series Contents for Last Fifteen Years

Rodhouse, P. G., Elvidge, C. D. and Trathan, P. N. Remote sensingof the global light-fishing fleet: an analysis of interactions withoceanography, other fisheries and predators. pp. 261–303.

Volume 40, 2001.Hemmingsen, W. and MacKenzie, K. The parasite fauna of theAtlantic cod, Gadus morhua L. pp. 1–80.

Kathiresan, K. and Bingham, B. L. Biology of mangroves and man-grove ecosystems. pp. 81–251.

Zaccone, G., Kapoor, B. G., Fasulo, S. and Ainis, L. Structural,histochemical and functional aspects of the epidermis of fishes.pp. 253–348.

Volume 41, 2001.Whitfield, M. Interactions between phytoplankton and trace metalsin the ocean. pp. 1–128.

Hamel, J.-F., Conand, C., Pawson, D. L. and Mercier, A. The seacucumber Holothuria scabra (Holothuroidea: Echinodermata): itsbiology and exploitation as beche-de-Mer. pp. 129–223.

Volume 42, 2002.Zardus, J. D. Protobranch bivalves. pp. 1–65.Mikkelsen, P. M. Shelled opisthobranchs. pp. 67–136.Reynolds, P. D. The Scaphopoda. pp. 137–236.Harasewych, M. G. Pleurotomarioidean gastropods. pp. 237–294.

Volume 43, 2002.Rohde, K. Ecology and biogeography of marine parasites. pp. 1–86.Ramirez Llodra, E. Fecundity and life-history strategies in marineinvertebrates. pp. 87–170.

Brierley, A. S. and Thomas, D. N. Ecology of southern ocean packice. pp. 171–276.

Hedley, J. D. and Mumby, P. J. Biological and remote sensingperspectives of pigmentation in coral reef organisms. pp. 277–317.

Volume 44, 2003.Hirst, A. G., Roff, J. C. and Lampitt, R. S. A synthesis of growthrates in epipelagic invertebrate zooplankton. pp. 3–142.

Boletzky, S. von. Biology of early life stages in cephalopod molluscs.pp. 143–203.

Pittman, S. J. and McAlpine, C. A. Movements of marine fish anddecapod crustaceans: process, theory and application. pp. 205–294.

Cutts, C. J. Culture of harpacticoid copepods: potential as live feedfor rearing marine fish. pp. 295–315.

Series Contents for Last Fifteen Years xiii

Volume 45, 2003.Cumulative Taxonomic and Subject Index.

Volume 46, 2003.Gooday, A. J. Benthic foraminifera (Protista) as tools in deep-waterpalaeoceanography: environmental influences on faunal character-istics. pp. 1–90.

Subramoniam,T. andGunamalai, V. Breeding biologyof the intertidalsand crab, Emerita (Decapoda: Anomura). pp. 91–182

Coles, S. L. and Brown, B. E. Coral bleaching—capacity for acclima-tization and adaptation. pp. 183–223.

Dalsgaard J., St. JohnM., Kattner G., Muller-Navarra D. and HagenW. Fatty acid trophic markers in the pelagic marine environment.pp. 225–340.

Volume 47, 2004.Southward, A. J., Langmead, O., Hardman-Mountford, N. J., Aiken, J.,Boalch, G. T., Dando, P. R., Genner, M. J., Joint, I., Kendall, M. A.,Halliday, N. C., Harris, R. P., Leaper, R., Mieszkowska, N., Pingree,R. D., Richardson, A. J., Sims, D.W., Smith, T., Walne, A. W. andHawkins, S. J. Long-term oceanographic and ecological research in thewestern English Channel. pp. 1–105.

Queiroga, H. and Blanton, J. Interactions between behaviour andphysical forcing in the control of horizontal transport of decapodcrustacean larvae. pp. 107–214.

Braithwaite, R. A. and McEvoy, L. A. Marine biofouling on fishfarms and its remediation. pp. 215–252.

Frangoulis, C., Christou, E. D. and Hecq, J. H. Comparison ofmarine copepod outfluxes: nature, rate, fate and role in the carbonand nitrogen cycles. pp. 253–309.

Volume 48, 2005.Canfield, D. E., Kristensen, E. and Thamdrup, B. Aquatic Geomicro-biology. pp. 1–599.

Volume 49, 2005.Bell, J. D., Rothlisberg, P. C., Munro, J. L., Loneragan, N. R., Nash,W. J., Ward, R. D. and Andrew, N. L. Restocking and stockenhancement of marine invertebrate fisheries. pp. 1–358.

Volume 50, 2006.Lewis, J. B. Biology and ecology of the hydrocoralMillepora on coralreefs. pp. 1–55.

xiv Series Contents for Last Fifteen Years

Harborne, A. R., Mumby, P. J., Micheli, F., Perry, C. T., Dahlgren,C. P., Holmes, K. E., and Brumbaugh, D. R. The functional value ofCaribbean coral reef, seagrass and mangrove habitats to ecosystemprocesses. pp. 57–189.

Collins, M. A. and Rodhouse, P. G. K. Southern ocean cephalopods.pp. 191–265.

Tarasov, V. G. EVects of shallow-water hydrothermal venting onbiological communities of coastal marine ecosystems of the westernPacific. pp. 267–410.

Volume 51, 2006.Elena Guijarro Garcia. The fishery for Iceland scallop (Chlamysislandica) in the Northeast Atlantic. pp. 1–55.

JeVrey, M. Leis. Are larvae of demersal fishes plankton or nekton?pp. 57–141.

John C. Montgomery, Andrew Jeffs, Stephen D. Simpson, MarkMeekan and Chris Tindle. Sound as an orientation cue for thepelagic larvae of reef fishes and decapod crustaceans. pp. 143–196.

Carolin E. Arndt and Kerrie M. Swadling. Crustacea in Arcticand Antarctic sea ice: Distribution, diet and life history strategies.pp. 197–315.

Volume 52, 2007.Leys, S. P., Mackie, G. O. and Reiswig, H. M. The Biology of GlassSponges. pp. 1–145.

Garcia E. G. The Northern Shrimp (Pandalus borealis) OffshoreFishery in the Northeast Atlantic. pp. 147–266.

Fraser K. P. P. and Rogers A. D. Protein Metabolism in MarineAnimals: The underlying Mechanism of Growth. pp. 267–362.

Volume 53, 2008.Dustin J. Marshall and Michael J. Keough. The EvolutionaryEcology of Offspring Size in Marine Invertebrates. pp. 1–60.

Kerry A. Naish, Joseph E. Taylor III, Phillip S. Levin, Thomas P.Quinn, James R. Winton, Daniel Huppert, and Ray Hilborn. AnEvaluation of the Effects of Conservation and Fishery EnhancementHatcheries on Wild Populations of Salmon. pp. 61–194.

Shannon Gowans, Bernd Wursig, and Leszek Karczmarski. TheSocial Structure and Strategies of Delphinids: Predictions Basedon an Ecological Framework. pp. 195–294.

Series Contents for Last Fifteen Years xv

Volume 54, 2008.Bridget S. Green. Maternal Effects in Fish Populations. pp. 1–105.Victoria J. Wearmouth and David W. Sims. Sexual Segregation inMarine Fish, Reptiles, Birds and Mammals: Behaviour Patterns,Mechanisms and Conservation Implications. pp. 107–170.

David W. Sims. Sieving a Living: A Review of the Biology, Ecologyand Conservation Status of the Plankton-Feeding Basking SharkCetorhinus Maximus. pp. 171–220.

Charles H. Peterson, Kenneth W. Able, Christin Frieswyk DeJong,Michael F. Piehler, Charles A. Simenstad, and Joy B. Zedler.Practical Proxies for Tidal Marsh Ecosystem Services: Applicationto Injury and Restoration. pp. 221–266.

Volume 55, 2008.Annie Mercier and Jean-Francois Hamel. Introduction. pp. 1–6.Annie Mercier and Jean-Francois Hamel. Gametogenesis. pp. 7–72.Annie Mercier and Jean-Francois Hamel. Spawning. pp. 73–168.Annie Mercier and Jean-Francois Hamel. Discussion. pp. 169–194.

xvi Series Contents for Last Fifteen Years

C H A P T E R O N E

Impacts of the Oceans on

Climate Change

Philip C. Reid,*,†,‡ Astrid C. Fischer,* Emily Lewis-Brown,§

Michael P. Meredith,} Mike Sparrow,** Andreas J. Andersson,††

Avan Antia,‡‡ Nicholas R. Bates,‡‡ Ulrich Bathmann,§§

Gregory Beaugrand,*,}} Holger Brix,*** Stephen Dye,†††

Martin Edwards,* Tore Furevik,‡‡‡ Reidun Gangstø,§§§

Hjalmar Hatun,}}} Russell R. Hopcroft,**** Mike Kendall,††††

Sabine Kasten,§§ Ralph Keeling,‡‡‡‡ Corinne Le Quere,},§§§§

Fred T. Mackenzie,}}}} Gill Malin,§§§§ Cecilie Mauritzen,*****

Jon Olafsson,††††† Charlie Paull,‡‡‡‡‡ Eric Rignot,§§§§§

Koji Shimada,}}}}} Meike Vogt,§§§§ Craig Wallace,**

Zhaomin Wang,} and Richard Washington******

Contents

1. Introduction 5

1.1. Heat budget 6

1.2. Ocean circulation 6

1.3. Tropical storms 7

1.4. Storage and transfer of CO2 7

1.5. Acidification 7

Advances in Marine Biology, Volume 56 # 2009 Elsevier Ltd.

ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56001-4 All rights reserved.

* Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB,United Kingdom

{ Marine Institute, University of Plymouth, Plymouth PL4 8AA, United Kingdom{ Marine Biological Association of the UK, The Laboratory, Citadel Hill, Plymouth PL1 2PB,

United Kingdom} WWF-UK, Panda House, Weyside Park, Godalming, Surrey GU7 1XR, United Kingdom} British Antarctic Survey, High Cross, Cambridge CB3 0ET, United Kingdom** SCAR Secretariat, Scott Polar Research Institute, Cambridge CB2 1ER, United Kingdom{{ Bermuda Institute of Ocean Sciences, St. George’s GE 01, Bermuda{{ Christian-Albrechts-University of Kiel, 24119 Kiel, Germany}} Alfred Wegener Institute, D-27570 Bremerhaven, Germany}} Centre National de la Recherche Scientifique, Laboratoire d’Oceanologie et de Geosciences, Station

Marine, Universite des Sciences et Technologies de Lille, 62930 Wimereux, France*** Department of Atmospheric and Oceanic Sciences, University of California - Los Angeles, Los Angeles,

California 90095-1567, USA{{{ Centre for Environment, Fisheries and Aquaculture Science (Cefas), Lowestoft, Suffolk NR33 OHT,

United Kingdom{{{ Geophysical Institute, N-5007 Bergen, Norway

1

1.6. Polar regions 8

1.7. Plankton productivity, oxygen content and upwelling 9

1.8. Microbes 9

1.9. Nutrients 9

1.10. Sea-level rise 10

1.11. Structure of the chapter 10

1.12. Summary conclusions and recommendations 12

2. Ocean Physics, Temperature, Circulation, Sea-Level Rise and the

Hydrological Cycle 12

2.1. Changes in ocean temperature 13

2.2. Changes in salinity 16

2.3. Global circulation 17

2.4. Upwelling 22

2.5. Changing physics of tropical seas in a warming ocean 23

2.6. Sea-level rise 24

2.7. Destabilisation of ice sheets/glaciers 25

2.8. Concluding comments 26

3. Primary Production: Plankton, Light and Nutrients 27

3.1. Oceanic primary production 28

3.2. Microbial plankton 30

3.3. Phyto- and zooplankton 31

3.4. Chlorophyll and primary production 33

3.5. Plankton biodiversity functional groups and ocean biomes 34

3.6. Benthos 36

3.7. Migration of plankton, fish and benthos towards the poles 37

3.8. Oxygen 38

3.9. Nutrients in general 40

3.10. Other gases and aerosols 47


4. The Solubility, Biological and Continental Shelf Carbon Pumps 51

4.1. The ocean carbon cycle 51

4.2. Ocean carbon pumps 54

}}} University of Bern, 3012 Bern, Switzerland}}} Faroese Fisheries Laboratory. FO-110 Torshavn, Faroe Islands**** Institute of Marine Science, University of Alaska Fairbanks, Fairbanks, Alaska 99775-7220, USA{{{{ Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, United Kingdom{{{{ Scripps CO2 Program, La Jolla, California 92093-0244, USA}}}} School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom}}}} Department of Oceanography, School of Ocean and Earth Science and Technology, University of

Hawaii at Manoa, Honolulu, Hawaii 96822, USA***** Norwegian Meteorological Institute, Blindern, 0313 Oslo, Norway{{{{{ University of Iceland and Marine Research Institute, IS-121 Reykjavik, Iceland{{{{{ Monterey Bay Aquarium Research Institute, Moss Landing, California 95039, USA}}}}} University of California - Irvine, Croul Hall, Irvine, California 92697, USA; and Jet Propulsion

Laboratory, Pasadena, California 91214, USA}}}}} Faculty of Marine Science, Department of Ocean Sciences, Tokyo University of Marine Science and

Technology, 4-5-7 Konan, Minato-ku, Tokyo 108-8477, Japan****** School of Geography and the Environment, Oxford University Centre for the Environment (Dyson

Perrins Building), University of Oxford, Oxford OX1 3QY, United Kingdom

2 Philip C. Reid et al.

4.3. Role of the four ocean carbon pumps 58

4.4. Species biodiversity and functional groups 58

4.5. Global and regional information 59

4.6. Ocean fertilisation 61


5. Ocean Acidification and the Carbonate Pump 62

5.1. The buffering of climate change by the oceans 63

5.2. Carbonate formation 65

5.3. Carbonate dissolution 67

5.4. Uptake of CO2 by the ocean 69

5.5. Projected future levels of acidification 70

5.6. Regional variation in acidification 71

5.7. Carbonate pump 73

5.8. Nutrients 75

5.9. Palaeo-comparisons 76


6. A Special Case: The Arctic and Seas Adjacent to Greenland 80

6.1. Climate change in the Arctic Ocean and Subarctic seas 80

6.2. The circulation of the Arctic Ocean and sub-polar seas 82

6.3. Runoff from Arctic rivers 83

6.4. Ice formation in the Arctic 83

6.5. Observed changes in Arctic sea-ice cover 84

6.6. Trigger factors for initial sea-ice reductions 86

6.7. Projected changes in Arctic sea-ice cover 86

6.8. The Greenland ice sheet 88

6.9. Methane and feedbacks to climate change 88

6.10. Arctic ocean ecosystems 91

6.11. Modelling 92


7. The Southern Ocean and Climate 93

7.1. Role of the Southern Ocean in climate 94

7.2. Observed changes in the Southern Ocean region 97

7.3. The future 103


8. Climate Models 106

8.1. Ocean–climate feedbacks 106

8.2. Heat uptake 106

8.3. Heat transport 109

8.4. Water cycle 111

8.5. Sea-ice 111

8.6. Gas exchange/carbon uptake (CO2, N2O, DMS) 112

8.7. Retro-modelling of past climate change 113

8.8. Final comments 114

9. Conclusions and Recommendations 115

9.1. A decade ago 116

Impacts of the Oceans on Climate Change 3

9.2. Warming waters 116

9.3. Freshening waters 117

9.4. Changing ocean circulation and sea-level 117

9.5. The MOC and cooling of NW Europe 118

9.6. Tropical storms 118

9.7. Primary production, biodiversity and non-native species 119

9.8. Oxygen 119

9.9. Nutrients 120

9.10. Ocean uptake of carbon dioxide 120

9.11. Acidification 121

9.12. A special case: The Arctic 122

9.13. Methane 123

9.14. Greenland ice sheet 123

9.15. The Southern Ocean 123

9.16. Modelling 124

9.17. Final concluding comments 125

Appendix: Workshop Participants 126


References 127

Abstract

The oceans play a key role in climate regulation especially in part buffering

(neutralising) the effects of increasing levels of greenhouse gases in the atmo-

sphere and rising global temperatures. This chapter examines how the regu-

latory processes performed by the oceans alter as a response to climate change

and assesses the extent to which positive feedbacks from the ocean may

exacerbate climate change. There is clear evidence for rapid change in the

oceans. As the main heat store for the world there has been an accelerating

change in sea temperatures over the last few decades, which has contributed to

rising sea-level. The oceans are also the main store of carbon dioxide (CO2), and

are estimated to have taken up �40% of anthropogenic-sourced CO2 from the

atmosphere since the beginning of the industrial revolution. A proportion of the

carbon uptake is exported via the four ocean ‘carbon pumps’ (Solubility,

Biological, Continental Shelf and Carbonate Counter) to the deep ocean reser-

voir. Increases in sea temperature and changing planktonic systems and ocean

currents may lead to a reduction in the uptake of CO2 by the ocean; some

evidence suggests a suppression of parts of the marine carbon sink is already

underway. While the oceans have buffered climate change through the uptake

of CO2 produced by fossil fuel burning this has already had an impact on ocean

chemistry through ocean acidification and will continue to do so. Feedbacks to

climate change from acidification may result from expected impacts on marine

organisms (especially corals and calcareous plankton), ecosystems and biogeo-

chemical cycles. The polar regions of the world are showing the most rapid

responses to climate change. As a result of a strong ice–ocean influence, small

changes in temperature, salinity and ice cover may trigger large and sudden


changes in regional climate with potential downstream feedbacks to the climate

of the rest of the world. A warming Arctic Ocean may lead to further releases of

the potent greenhouse gas methane from hydrates and permafrost. The South-

ern Ocean plays a critical role in driving, modifying and regulating global

climate change via the carbon cycle and through its impact on adjacent Antarc-

tica. The Antarctic Peninsula has shown some of the most rapid rises in

atmospheric and oceanic temperature in the world, with an associated retreat

of the majority of glaciers. Parts of the West Antarctic ice sheet are deflating

rapidly, very likely due to a change in the flux of oceanic heat to the undersides

of the floating ice shelves. The final section on modelling feedbacks from the

ocean to climate change identifies limitations and priorities for model develop-

ment and associated observations. Considering the importance of the oceans to

climate change and our limited understanding of climate-related ocean

processes, our ability to measure the changes that are taking place are con-

spicuously inadequate. The chapter highlights the need for a comprehensive,

adequately funded and globally extensive ocean observing system to be imple-

mented and sustained as a high priority. Unless feedbacks from the oceans to

climate change are adequately included in climate change models, it is possible

that the mitigation actions needed to stabilise CO2 and limit temperature rise

over the next century will be underestimated.

1. Introduction

Through many natural processes and feedback mechanisms, theoceans1 regulate climate on a range of timescales, from geological andmillennial to decadal, interannual and shorter. Over the last two centuries,because of the ability of the oceans to take up heat and absorb greenhousegases such as carbon dioxide (CO2), they have partially buffered (neutra-lised) the effects of increasing levels of human-sourced greenhouse gases inthe atmosphere. There is, however, clear evidence that many of the pro-cesses that contribute to this buffering role have been changing, in somecases almost certainly as a response to climate change. These processesprovide a number of feedbacks that may be positive (reinforcing) or negative(ameliorating) to climate change.

There has been insufficient attention paid in the past to the key role thatthe oceans play in regulating climate and particularly to the feedbackmechanisms that have the potential to and, in some cases, may already beintensifying climate change. For example, the Fourth Assessment Report ofthe Intergovernmental Panel on Climate Change (IPCC) in 2007 includedas much information as was possible at that time on the ocean carbon cycle,

1 All the oceans are interconnected and are often referred to in the singular. In this chapter, the plural version isgenerally used.


but recognised that many feedback mechanisms were incompletelyincluded. This chapter explores the role of the oceans in regulating theclimate and especially those changes that can accelerate climate change andhave important implications for achieving stabilisation targets to mitigateclimate change. Some of the key issues that are addressed are summarisedbelow, followed by an outline of the structure of the chapter and a briefsummary of conclusions and recommendations.

1.1. Heat budget

Comprising 97% of the Earth’s water and covering 71% of the surface, theoceans are the main heat store for the world. Over the last few decades therehas been a rapid and accelerating change in ocean temperatures and anincrease in heat storage affecting seasonal and decadal variability in climate,heat transport, ocean circulation, stratification, biology and biogeochemistry.All of these ocean factors can lead to feedbacks to climate change.

Themain positive feedbacks derive from rising temperatures and changingsalinities. Higher temperatures are causing a loss of Arctic sea-ice, which feedsback to warming and climate change through many processes, including thepotential release of the potent greenhouse gas methane. Changes in the oceanshave led to an expansion of tropical/subtropical stratified (layered) waters,changing patterns of wind and altered ocean currents. Together these changesare likely to have led to a net reduction in the drawdown of CO2 from the airinto the ocean. However, expansion of the suboxic layers in the tropics andAtlantic Ocean (but not in the Indian Ocean) may, on the contrary, increasethe preservation of organic matter and thus provide a sink for CO2. A risingsea-level has also resulted from increasing temperatures through thermalexpansion of the oceans, as well as shrinking polar ice sheets and glaciers.Some of these feedbacks may be compounded by the impacts of oceanacidification from CO2.

1.2. Ocean circulation

Marked changes in salinity have been observed, reflecting an alteration inthe hydrological cycle of the world through changes in precipitation,evaporation, river runoff and ice melt, with especially clear reductions inthe North Atlantic, and in deeper waters and some upper layers of theSouthern Ocean. Changes in ocean temperature have also been observed,with some regions warming very rapidly. Changes in buoyancy forcing(heat and salinity) and mechanical forcing (e.g. winds and tides) have thepotential to change the large-scale circulation of the global ocean, includingits overturning circulation and horizontal flows [Thermohaline Circulation(THC)/Meridional Overturning Circulation (MOC), commonly known asthe ‘global conveyor belt’]. The general consensus from modelling


projections for the twenty-first century is that there is likely to be areduction in the strength of the Atlantic MOC by up to 50% of its currentstrength. This will not necessarily lead to a cooling of Europe, but morelikely to a slower rate of warming, because the general atmospheric warm-ing tends to dominate over the cooling expected from a reduced MOC.

Recent increases in the poleward ocean heat flux are likely to haveplayed a central role in the decline of Arctic sea-ice. The signal from thechanges in the Arctic has, and is expected to continue to, propagate souththrough subarctic seas on either side of Greenland, to modulate the Atlanticthermohaline overturning.

1.3. Tropical storms

The intensity of tropical storms has increased by 75% from 1970 to 2004 inthe North Atlantic and western North Pacific and a global increase in theirdestructiveness is documented. The possible feedback role to climatechange is still unclear, but it is expected that as global temperatures rise,storm intensity and possibly their frequency may increase.

1.4. Storage and transfer of CO2

The oceans are the main store for the greenhouse gas CO2, each year takingin about 40% of anthropogenic CO2 from the atmosphere and exportingcarbon via physical and biological processes to the deep ocean reservoir.Emissions of CO2 from human sources have already grown to over 7 GtC(gigatonnes carbon) per year. The sensitivity of atmosphere/ocean fluxes ofthe carbon cycle is particularly evident. Increases in sea surface temperature(SST) and changing biological systems and ocean currents may lead to areduction in the uptake of CO2 by the oceans. Measurements taken overthe last few decades of atmospheric greenhouse gases and ocean observationsare indicating that a reduction in the buffering capacity of the oceans isunderway in some regions. A slowing down of the ocean sink and any largechange to the different ocean carbon pumps could lead to an acceleration oflevels of atmospheric CO2 and thus to intensified climate change.

1.5. Acidification

Through the uptake of nearly 50% of CO2 produced by burning fossil fuelover time, the oceans have buffered the cause and effects of climate change.This large addition of CO2 to the oceans has also had a profound effect onocean chemistry. As CO2 dissolves into the ocean, it reacts with seawater,forming carbonic acid which causes a reduction in pH (lower alkalinity), aprocess that has been termed ‘ocean acidification’. Since the beginning ofthe industrial revolution, pH has reduced by�0.1 units (representing a 30%


increase in Hþ ions), a substantial amount considering that the units arelogarithmic. Rapid acidification is expected to continue to the extent thatin 50 years time the oceans are predicted to be less alkaline than at any timein the past 20, and likely 55, million years.

Feedbacks to climate change from ocean acidification may result fromexpected impacts on marine organisms, ecosystems and biogeochemicalcycles. Planktonic plants (phytoplankton) comprise 50% of global primaryproduction and play a crucial role in the uptake of CO2 from the atmo-sphere. There is concern that oceanic organisms will not be able to adapt tothe rate and scale of change now underway. These organisms are vital to theway the oceans draw down CO2 from the atmosphere and play a profoundrole in the biological pump and the way it transfers CO2 to the deep oceanstore. In addition, the effects of projected changes in the pH of the oceanson corals and plankton community structure are likely to have profoundimplications for biodiversity, marine living resources and again with likelyfeedback to the carbon cycle.

1.6. Polar regions

The polar regions are thought to be especially susceptible to planetary-scaleclimate change, and a number of indicators of this have been observed. Forexample, there have been considerable reductions in Arctic sea-ice, rapidlyrising temperatures at the Antarctic Peninsula, and a break-up of a numberof Antarctic ice shelves. Arctic sea-ice has retreated rapidly in recent years,whereas Antarctic sea-ice has shown a more regional pattern of change—decreasing in some sectors, but increasing in others, and with an overallsmall increase. Much of the old multi-year ice in the Arctic has beendischarged so that the ice now found there is thinner and younger. Sea-iceloss is acting as a trigger for further regional warming, potentially contribut-ing to melting of the Greenland ice sheet and release of methane, a potentgreenhouse gas. In the Arctic, release of methane frommarine and terrestrialsources is particularly likely to contribute to positive feedback effects toclimate change. In the Southern Ocean, the regional sea-ice changes havethe potential to modulate the formation of dense waters, with implicationsfor the uptake of CO2 from the atmosphere, as well as oceanic fluxes of heatand freshwater. The carbon storage capability of the circumpolar SouthernOcean is reported to have decreased in recent decades, leaving more CO2 inthe atmosphere, although investigations are ongoing into this phenomenon.

If the regional average temperature rise above Greenland increases abovesome threshold, estimated as 3 �C above pre-industrial values (whichequates to a global average temperature of 1–2 �C), it is projected that theongoing contraction of the Greenland ice sheet would be irreversible.Without effective mitigation of carbon emissions, global warming couldexceed this value during the twenty-first century, leading to a total melting


of the ice sheet and a rise of several metres in sea-level over a timescale that isestimated to take centuries to thousands of years. The rate of loss of Arcticsea-ice was underestimated in the IPCC report in 2007, which, along withomission of some feedbacks, may have led to an underestimate of the cuts inemissions of greenhouse gases necessary to stabilise climate change at givenatmospheric levels. The current rate of change in the Arctic, and its activefeedbacks, have been triggered by a relatively small increase in globalaverage temperature rise.

1.7. Plankton productivity, oxygen content and upwelling

Evidence is accumulating for increases in the intensity of upwelling in themajor upwelling regions of the world, leading to a rise in phytoplanktonproduction, anoxia and release of greenhouse gases. Anoxia is the lack ofoxygen (O2), an element that plays a direct and important role in thebiogeochemical cycling of carbon and nitrogen. It is fundamental to allaerobic organisms, including those living in the dark deep sea. Areas of theocean that stagnate can become anoxic due to the continual consumption ofO2 by living organisms. The main feedbacks to climate from plankton arevia potential reductions in CO2 drawdown and in the efficiency of thebiological pump.

1.8. Microbes

The role of microbes in climate and climate change is crucially important,but little understood and poorly quantified, especially in terms of their con-tribution to biogeochemical and nutrient cycling, microbial diversity andfeedbacks. A considerable increase in research effort is required to improveunderstanding of the impacts that microbes have on the planetary-scaleclimate system.

1.9. Nutrients

The contrast between biological and nutrient interactions within oceanicand terrestrial systems means that the oceans respond much more rapidly toclimate change and feedbacks from oceanic biology. Therefore, biogeo-chemical interactions are likely to take effect more quickly. Strong regionalchanges in nutrients are expected in the future, dependent on variability inwet precipitation, evaporation, wave storminess, mixing and the depth ofstratification. Precipitation is expected to increase especially in tropicalregions. At present, it is not possible to predict future trends because ofthe localisation of the changes and our lack of knowledge of complexecosystem interactions. It is also not clear how all the regional responseswill add up to a global mean. The subtropical gyres play a large role in


carbonate production and export to depth (carbonate and biologicalpumps) and are predicted to expand in area, but not in productivity, in awarming world.

1.10. Sea-level rise

Sea-level has been rising at the upper end of the IPCC AR4 projections andcan contribute to coastal erosion, inundation and salinification of aquifers.Sea-level rise will affect humans in many ways, including the potentialdisplacement of millions of people. Migration of populations and loss ofcoastal lands will likely lead to changes in land and resource use that have thepotential to establish further positive feedbacks to climate change.

1.11. Structure of the chapter

The chapter has been organised into sections that reflect the main oceandrivers of climate change and the variables that contribute to them, as shownschematically in Fig. 1.1. Note that this figure focuses on factors interactingwith nutrients; the real situation is more complex as the drivers may alsodirectly impact other processes independently of nutrients. Denitrificationmay also act independently and be linked to atmospheric concentrations ofCO2. The physics starts the process with recycling feedbacks at all levels.The other sections examine key elements of ocean–climate interactionscovering: Ocean Physics, Circulation and the Hydrological Cycle, PrimaryProduction: Plankton, Light and Nutrients, the Oceanic Carbon Cycle,Ocean Acidification and Modelling. An additional special focus has beenplaced on the critically important, but still under-studied polar regions, withseparate sections on the Arctic and Southern Oceans.

Throughout the chapter, our aim has been to provide an assessment ofthe key processes and feedbacks from the oceans to climate and climatechange and, where possible, prioritise their importance. Gaps in knowledgeare identified in modelling and research programmes, with a particularreference to observing systems that are needed to adequately assess thescale and speed of change. Some of the positive feedback mechanismsfrom the oceans to climate change have been insufficiently included inclimate modelling and calculations for stabilisation targets. Without these,it is possible that the stabilisation targets for climate mitigation underesti-mate the action needed to limit global temperature rise within any givenlimit. The chapter also includes in places a discussion of tipping points(sudden, possibly irreversible changes that might lead to rapid climatechange) and a brief discussion on iron fertilisation.

The work to produce this chapter was initiated by a Worldwide Fundfor Nature (WWF) sponsored workshop in London during March 2008that was attended by 30 international researchers who are experts in aspects


of the field. A list of the participants and the themes addressed at theworkshop are appended as an Appendix. The science of the chapter hasbuilt on the workshop outcomes, recent reports of the IPCC plus newinformation from the literature, as well as correspondence with expertsselected to cover (where possible) all aspects of ocean science.

While other activities, such as fishing, whaling, pollution and habitatdestruction, also impact the oceans, here we focus only on the interactionbetween the oceans and climate, without detailed account of these addi-tional impacts. The extent to which positive feedbacks may lead to apotential acceleration of climate change is assessed. Where possible anupdate and expansion on ocean information covered by IPCC is included.The chapter aims to stimulate and inform debate, provide a useful comple-ment to the work of IPCC and contribute to the preparations for the next

Atmospheric CO2, other greenhouse gases

Optical properties(light adsorption and albedo)

Ocean CO2 uptake(buffers climate)

Biological pump(organic and inorganic)

Biogas production

Speciation/biodiversity/biogeography/food web dynamics

(de)nitrifiers Nutrients

Sea surface temperature

Surface ocean pH and carbonate chemistry

Storms, mixing and upwelling Ocean circulation

Stratification

River input

Climate change

Figure 1.1 Schematic of potential relationship and links between key nutrient driversand climate change (produced by Carol Turley, Plymouth Marine Laboratory).


IPCC review. It is hoped that it will also be of value to other internationaland national organisations working on climate change and to the researchand modelling community in helping to prioritise improvements that needto be included in future research, modelling and observing programmes.

1.12. Summary conclusions and recommendations

This chapter demonstrates that the oceans are vital in regulating our climate.They have buffered climate change substantially since the beginning of theindustrial revolution, acting as a sponge to carbon dioxide and heat fromglobal warming. While it was assumed this would continue, our chaptergives a warning—even at current warming levels to date, changes underwayin our oceans may accelerate warming and its consequences to organisms,and have the potential to intensify climate change itself. In some examples,such as sea-ice loss, this process may already be underway.

A concerted effort to better understand the implications of the role of theoceans in regulating the climate is essential to better predict climate change.Where complete understanding is not possible, feedbacks from the oceansto climate change need to be taken account of when planning responses toclimate change. It is necessary to apply the precautionary principle in bothmarine and climate management until a fuller understanding is achieved.Most ocean observing programmes are still funded from research budgetsand, other than for some aspects of the physics, have a poor global coverage,especially for deeper waters and for biological and biogeochemical pro-cesses. Implementation of an improved ocean observing system is urgentlyneeded to monitor changes in the interactions between the oceans andclimate change.

2. Ocean Physics, Temperature, Circulation,

Sea-Level Rise and the Hydrological Cycle

This section describes how the large changes that have taken place inSST, ocean heat content and salinity over the last century are altering oceandensity, with effects on stability (stratification), circulation, mixing andfeedbacks to the atmosphere. The consequences of these changes for sea-level, polar ice, the frequency and intensity of tropical storms (hurricanes,cyclones and typhoons) are then examined as are connections to the mon-soons and modes of variability such as the El Nino/Southern Oscillation(ENSO). The physical changes in the oceans were well covered in theIPCC AR4 reports as much more is known about the physics of the oceansthan other subjects and more data have been collected on temperature andsalinity than any other variable.


Historically, the climate has undergone large natural change, indepen-dently of man’s influence, at global and regional scales through geologicaltime, at alternating time intervals ranging from millions to decadal to annualperiodicity (Crowley, 1996; CLIVAR brochure: http://www.clivar.org/publications/other_pubs/latest_clivar_brochure.pdf ). Natural climate vari-ability can be forced by many factors including changes outside the Earth inthe Sun and in the orbit of the Earth in relation to the Sun, and by naturalevents such as volcanic eruptions and oscillatory regional modes of varia-bility such as El Nino, the North Atlantic Oscillation (NAO) and PacificDecadal Oscillation (PDO) and the MOC (e.g. Chen et al., 2008a,b;Keenlyside et al., 2008; Shindell et al., 2003). Natural changes may alsooccur very rapidly, as evident in the ice core record of Greenland where thereturn to cold glacial temperatures in the Younger Dryas abruptly changedaround 12,000 years ago with a rapid rise in temperature of approximately8 �C in less than a decade (Brauer et al., 2008). Against this background, therise in temperature over the last 50 years cannot be explained withoutincluding human forcing. Most of the warming since the mid-twentiethcentury was considered by IPCC AR4 to be very likely due to the observedincrease in anthropogenic greenhouse gas concentrations (Alley et al.,2007).

2.1. Changes in ocean temperature

2.1.1. Sea surface temperatureOn a global scale, SST (the temperature of the upper few metres of theocean) observations have shown a progressive warming trend of �0.64 �Cover the last 50 years. A steady increase has been recorded since 1910 otherthan an apparent peak centred on 1940 (Trenberth et al., 2007). Thompsonet al. (2008) have shown recently that this peak is an artefact due to samplingbiases. Their results alter the variability, but not the long-term trend.Modelling studies predict that the trend in SST is likely to continue in thetwenty-first century, with regional variability. The regional differencesinclude enhanced warming in the Arctic, in the Indian Ocean and alongthe equator in the eastern Pacific, with a lower rate of warming in theNorthwest Atlantic and in the Southern Ocean (Meehl et al., 2007).Warming has been more pronounced in the Southern Ocean over the last50–70 years (Gille, 2002, 2008) and has changed locally around the Antarc-tic Peninsula where the very rapid atmospheric warming has been paralleledby an increase in surface ocean temperature of >1 �C in summer monthssince the 1950s (Meredith and King, 2005).

Superimposed on the global trend are natural interannual and decadalvariability. This is associated in the Atlantic, for example, with the NAOand the Atlantic Multi-decadal Oscillation (AMO), and in the Pacific withthe PDO/ENSO. Regional variability may also be marked. In the North


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Atlantic there is asymmetry across the basin with cooling in the Northwestand warming in the Northeast, until recently when the Northwest regionalso showed strong warming (Hughes et al., 2008). In the tropical Pacific,there is a general warming trend, with reduced zonal patterns and more ElNino type east to west patterns of change.

2.1.2. Ocean heat contentThe ocean’s main role in climate variability and change is its huge capacityfor the transport and storage of heat. On a global scale, ocean warmingaccounts for more than 90% of the increase in the Earth’s heat contentbetween 1961 and 2003 (Bindoff et al., 2007). For the upper 700 m of theocean (the water column from the surface to a depth of 700 m inclusive),the latter study estimates an average increase in temperature of 0.1 �C,equivalent to a flux of heat into the ocean of 0.2 � 0.06 W m�2. This largeincrease in heat storage has implications for seasonal and decadal variabilityin climate, transport and circulation by ocean currents, stratification, biol-ogy and biogeochemistry. All of these factors can lead to feedbacks toclimate change.

Because of its fundamental importance, there have been many studies ofchanges in ocean heat content. These have revealed deficiencies in bothhistorical and recent global ocean datasets. Analyses have demonstratedsignificant time-dependent biases in the expendable bathythermograph(XBT) data that dominates the historical archive since the early 1970suntil the recent advent of Argo profiling floats. Wijffels et al. (2008) haveshown that biases in the fall rate of XBTs are the dominant source of errorand that they can be reduced substantially. In addition, the recent cooling ofthe ocean (Lyman et al., 2006), reported following the introduction of thenew Argo observing system, has now been shown to be incorrect and was aresult of inadequate quality control in some of the new Argo floats as well asbiases in XBTs (Willis et al., 2007).

In addition to instrumental biases, there are also significant samplingproblems associated with an inadequate ocean database. Palmer et al. (2007)demonstrated that the accuracy of heat content estimates can be improvedby determining changes in heat content relative to an isotherm rather than afixed depth level. They estimate a warming trend of 0.12 � 0.04 W m�2

relative to the 14 �C isotherm.Both the XBT instrumental biases and the sampling issues were

addressed by Domingues et al. (2008). Compared to the assessment in themost recent IPCC report (Bindoff et al., 2007), their improved estimate ofupper-ocean warming is �50% larger for 1961–2003 and �40% smaller for1993–2003. From 1961 to 2003, their estimate of heat flux into the upper700 m of the ocean is 0.36� 0.06Wm�2. The new results for near globallyaveraged anomalies of ocean heat content (Fig. 1.2) show similar


multi-decadal variability to SST. They also reduce the large (but spurious)warming in the early 1970s and the subsequent cooling in the early 1980sthat was a feature of previous estimates and which could not be reproducedin climate simulations. Climate models which include the full range ofnatural and anthropogenic forcing factors reproduce this observed long-term trend and the decadal variability, and demonstrate that violent volcaniceruptions are responsible for significant variability in ocean heat content(Fig. 1.2). However, this new analysis suggests that climate models mayslightly underestimate the amount of ocean heat uptake in the upper 700 mfor the period 1961–2003 (Domingues et al., 2008).

Observations indicate that the deep and abyssal ocean may be absorbinglarge amounts of heat ( Johnson and Doney, 2006a,b; Johnson et al., 2007,2008; Kohl et al., 2007). Unfortunately, our historical observations and ourcurrent observing systems are inadequate to calculate quantitatively thisstorage on a global scale (Domingues et al., 2008).

There are pronounced regional patterns in ocean warming, includingindications of warming of the subtropical ocean gyres in both hemispheresand a poleward expansion of these gyres. For example, Palmer et al. (2007)suggest that the North Atlantic is a region of net heat accumulation over theperiod 1965–2004. Pronounced decadal variability is evident as a result ofwind stress changes with a deepening of the North Atlantic subtropical gyrefrom 1981 to 2005 following an earlier period from 1959 to 1981 when thethermocline shoaled (Leadbetter et al., 2007). There is also a significant deepwarming near the poleward boundary of the subtropical gyre in the SouthPacific Ocean (Roemmich et al., 2007). Recent reanalysis of the sparse

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Figure 1.2 Upper-ocean heat content (grey shading indicates an estimate of onestandard deviation error) for the upper 700 m relative to 1961. The straight line is thelinear fit for 1961–2003. The global mean stratospheric optical depth (Ammann et al.,2003) (arbitrary scale) at the bottom indicates the timing of major volcanic eruptions.The brown curve is a 3-year running average of these values, included for comparisonwith the smoothed observations. Figure modified from Domingues et al. (2008).


Southern Ocean dataset has revealed significant warming (Gille, 2008).However, much remains to be done to identify clearly these regionalpatterns to understand the dynamics underlying the changes and to evaluatethe ability of climate models to simulate the variability.

2.2. Changes in salinity

One of the clear statements in the IPCC AR4 report is that while it isimpossible to determine the precise origin of recent changes in regionalpatterns of freshening and salinification of the global ocean they are consis-tent with an enhanced hydrological cycle (Bindoff et al., 2007). This islargely a consequence of the much smaller volume of observational dataavailable for salinity compared to temperature, especially for the oceans inthe Southern Hemisphere, which form two-thirds of the global ocean area.Salinity is, however, still the most measured property in the ocean aftertemperature and provides important information on the hydrological cycle,including rates of surface freshwater fluxes, transport and ocean mixing, allof which are important components of climate dynamics. Boyer et al. (2005)reinforced at a global scale the basin-wide message of Curry et al. (2003),who showed that a systematic freshening had occurred in high-latituderegions of the Atlantic at all depths in both the southern and northernhemispheres between the periods 1955–1969 and 1985–1999 (Fig. 1.3).

The freshening was especially pronounced in the intermediate depthwaters of the Labrador Sea and in the deep outflows from the Nordic Seasvia the Faroe–Shetland Channel and Denmark Strait. In contrast, highersalinities have been recorded in the intermediate depth (1000–1200 m)waters flowing out of the Mediterranean reflecting the rising deep watersalinities recorded from this sea. It is expected that freshening will continuein the Arctic due to ice loss, but the Northwest Atlantic has undergone arapid change to higher salinities post-1998 due to changes in the circulationof the sub-polar gyre (Hatun et al., 2005; Holliday et al., 2008) and increasesin the salinity of the top 500 m have occurred in the subtropical gyre.

Freshening has also occurred in the subtropical gyres of the IndianOcean (e.g. Bindoff and McDougall, 2000). In general, surface waters inthe subtropical gyres of the Indian and Pacific Oceans have a higher salinityalthough there is evidence of freshening in the tropical Pacific (Delcroixet al., 2007). A large-scale freshening of waters in the Southern Ocean closeto Antarctica has been observed, including upper layer waters in the RossSea ( Jacobs et al., 2002) and Antarctic Bottom Water, adjacent to a largepart of East Antarctica that is derived from the Ross Sea (Rintoul, 2007).Exact causes for the overall freshening are unknown, but glacial ice meltfrom the West Antarctic ice sheet has been suggested, along with changes inthe sea-ice field of the Weddell Sea. Contributing factors to the changes in


salinity are alterations in precipitation/evaporation, freshening from meltingof ice, reduced ice formation and changes in ocean circulation.

The relative contributions of these factors to the large observed changesare still a matter of debate, although changes in evaporation/precipitationare shown to be important by Curry et al. (2003). The increasing differencesin the salinity budgets of the Atlantic and Pacific suggest a change in thefreshwater budget of the two basins. Bindoff et al. (2007) conclude thatpronounced changes in salinity reflect a modification of the Earth’s hydro-logical cycle with enhanced transport of water in the atmosphere betweenlow and higher latitudes. Combined together, the salinity and temperaturechanges alter the density distribution and thus stability (stratification) as wellas the THC of the ocean, with large potential feedbacks on regional climateand weather conditions such as temperature, storminess and rainfall patterns.

2.3. Global circulation

The world’s large-scale ocean circulation is driven by a range of forcingmechanisms (e.g. winds, heating/cooling/salinity-density) and it is techni-cally not possible to separate the currents based on their respective forcing.Nevertheless, there is a strong tradition in oceanography to consider the

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Figure 1.3 South-to-north vertical section of salinity versus depth for the westernAtlantic basin, plotted as Salinity difference averaged for the period 1985–1999 minus1955–1969. Grey colour means that sampling was not sufficient to estimate meansalinity. Acronyms are for the different water masses; see original paper. From Curryet al. (2003).


upper-ocean circulation as wind driven and that which reaches the deepoceans as density-driven. Thus, we often speak of the world’s THC as thedensity-driven circulation that interconnects all the world’s basins and allthe ocean depths (see IPCC AR4, 2007 for a definition of the THC). TheTHC cannot be measured directly in contrast to the sinking and spreadingof cold water through the MOC, which is an observable quantity.

Even so, the MOC is only observable in principle—in practice, it isprohibitively expensive to observe this circulation in all but a few limitedplaces. This is rather restrictive because the MOC does not circulate in apipe (in which case it only needs to be observed in one location), rather itrecirculates vigorously both in the surface and deep ocean. So most of theinferences about the MOC are from indirect measurements taken from thefar more abundant observations of temperature, salinity, pressure, altimetry,etc., rather than from direct current measurements. Changes in heat andfreshwater storage can be used to derive changes in transport. Throughoutthis chapter both concepts (THC and MOC) are used, but what really ismeant is the ocean’s large-scale vertical and horizontal overturningcirculation.

2.3.1. Meridional overturning circulation in the North Atlantic/Arctic2.3.1.1. Subtropical measurements Direct measurements of the heattransport associated with the Atlantic MOC indicate a maximum transportat the 26.5�N latitude (e.g. Ganachaud and Wunsch, 2000). At the samelatitude, the Gulf Stream component of the MOC is channelled through theFlorida Strait, where robust transport measurements have been maintainedsince 1980 (Baringer and Larsen, 2001). This latitude has been suggested asone of the optimum locations at which to monitor the MOC - toboth establish how the system varies naturally, and to seek evidence ofany long-term change that may be underway.

Based on measurements from ship transects over the past six decades anapparent 30% reduction in the strength of the MOC was calculated byBryden et al. (2005) (Fig. 1.4). This appears to be driven by an enhancedsouthwards re-circulation of upper waters by the subtropical gyre, and acompensatory reduction in the deep southwards return leg of the MOC fedby high-latitude, cold, dense waters. The size and rate of this reductionreceived much attention, exceeding the limits of projected changes for thesame time period based on climate model simulations (see Section 8).In response to the ongoing threat of an abrupt MOC change, and thesocietal implications this could have for Europe, an international collaborativemonitoring system was launched to provide a continuous record of AtlanticMOC strength at 26.5�N, as part of the UK-led RAPID Climate ChangeProgramme. Initial results reveal significant short-term (daily) variability inthe strength of theMOC implying that the decrease evident in the ship-based


measurements may be, at least in part, an artefact due to high-frequency‘noise’ (Cunningham et al., 2007).

2.3.1.2. Arctic/subarctic measurements The oceanic exchanges of sur-face and deep waters ‘that connect the Arctic and Atlantic oceans throughSubarctic Seas are of fundamental importance to climate’ (Dickson et al.,2008). In particular, changes that have taken place in the poleward oceanheat flux are likely to have played a central role in the decline of Arctic sea-ice (see Section 6). The signal from the changes in the Arctic has, and isexpected to continue to, propagate south through Subarctic Seas on eitherside of Greenland, to modulate the Atlantic thermohaline ‘conveyor’(Dickson et al., 2008). To measure these changes lines of moorings, supple-mented in the last decade by ADCPs (Acoustic Doppler Current Profilers)and other measurements between (1) Iceland and Greenland, (2) Icelandand the Faroe Islands, (3) The Faroe Islands and Shetland, (4) Greenland,Spitsbergen and Norway, and more recently (5) in the Canadian Archipel-ago, have been in place for some years through the Arctic–Subarctic FluxStudy (ASOF) (see http://www.asof.npolar.no) and its predecessors(Fig. 1.5). The aim of ASOF was to observe the inflow and outflow ofwater to and from the Arctic.

A successor integrated Arctic/Subarctic Seas international programme(The integrated Arctic Ocean Observing System, iAOOS) is now in place aspart of the International Polar Year (Dickson, 2006; Dickson et al., 2008).

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01950 1960 1970 1980 1990 2000 2010

Figure 1.4 Mean strength of the Atlantic MOC at 26.5�N between 1957 and 2005 andassociated error bars. Blue data points are for measurements taken from ships (Brydenet al., 2005). The red data point is an average of observations taken in the first full year ofthe RAPID monitoring array, plus error bar (Cunningham et al., 2007). Units are Sv(1 Sv¼ 1 million m3 s�1 of water passing the 26.5�N line). Values indicate a northwardsnet transport for water shallower than 1000 m.


http://www.asof.npolar.no

http://www.asof.npolar.no

The longest current meter records presently just exceed a decade, so it isdifficult to determine any evidence for a long-term trend.

There has been a pronounced increase in heat transport to the Arctic inthe last 10 years (Holliday et al., 2008; Hughes and Holliday, 2007), with themaximum being reached 5 years ago and with another pulse of heat on itsway. As the warmer water delivered to the Arctic is leaving already, the totalheat content in the Arctic is slightly decreasing, but with high interannualvariability (Dickson et al., 2008; Schauer et al., 2008).

2.3.2. Meridional overturning circulation in the SouthernOcean/Antarctica

The Southern Ocean is a key region in the THC/MOCwhere the productsof deep convection in the North Atlantic are upwelled and mixed intoshallower layers. These waters are then converted into shallow and deepreturn flows to complete the overturning circulation (see Section 7).

Profound physical changes have been observed in the water masses ofboth the shallow and deep return flows. The shallow limb of the MOC issourced towards the northern flank of the Antarctic Circumpolar Current(ACC). Here, the water that is upwelled within the ACC is converted intomode waters and intermediate waters that permeate much of the globalocean basin south of the equator with nutrient-rich water. These waters

Figure 1.5 Estimates of freshwater flux relative to S ¼ 34.8* in Arctic and SubarcticSeas as determined during the ASOF project. Units are mSv and the base map is asnapshot of modelled sea surface height courtesy W. Maslowski, NPS, Monterey(1 mSv¼ 31.546 km3 year�1; * the numbers for PE, runoff and ice melt are independentof the choice of reference salinity). From Dickson et al. (2007).


show variability in properties on a range of timescales (seasonal to decadaland longer), reflecting global and regional climate variability in their sourceregions. The formation and subduction of the mode and intermediatewaters (Fig. 1.6) is believed to be a critical process that removes anthropo-genically produced CO2 from the atmosphere and likely contributes to

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Figure 1.6 (A)Locationofmodeandintermediatewaters intheglobalocean.Low-densitymode waters of the eastern subtropical gyres—pink. The highest density mode waters,whichsubduct in thesubtropicalgyres—red.AtlanticSub-polarModeWater,NorthPacificcentral mode water and Subantarctic Mode Water (SAMW)—dark red. (B) Covering alarge area of the ocean, intermediatewaters are found below themodewater, Labrador Seaintermediatewater (LSW)—blue, North Pacific intermediate water (NPIW)—pale green,Antarctic intermediate water (AAIW)—green. These waters eventually re-emerge at thesurface far from their origin. Primary formation areas for the intermediate waters areindicated with red crosses. From Talley (1999): http://www-pord.ucsd.edu/�ltalley/papers/1990s/agu_heat/talley_agu_heat.html.


http://www-pord.ucsd.edu/~ltalley/papers/1990s/agu_heat/talley_agu_heat.html




internannual variability in global oceanic uptake. For example, 40% of theglobal ocean inventory of anthropogenic CO2 is found south of 30�S andmost of that is in the intermediate and mode water (Sabine et al., 2004a).

Changes have also been observed in the deep return flow of AntarcticBottom Water (AABW), the deepest water on the Earth (Fahrbach et al.,2006; see Fig. 1.3). This cold water forms via intense air/sea/ice interactionat the surface, sinks and then spreads northwards towards the Arctic.A freshening of the AABW has occurred off a large sector of East Antarcticathat may in part reflect melting at depth (�700 m) of Antarctic glaciers thatextend over the sea (see Section 7). The densest component of the AABWhas shown a warming trend until very recently (Fahrbach et al., 2006),while the less dense variety that can escape the Weddell Sea and penetratenorth in the Atlantic has shown a marked decadal warming (Meredith et al.,2008).

2.3.3. Slowing down of the MOC and cooling of NW EuropeThe general consensus from modelling projections for the twenty-firstcentury is that there is likely to be a reduction in the strength of the AtlanticMOC of up to 50% of its current strength. This will not lead to a coolingof Europe, but less warming. This is because the general atmosphericwarming ‘wins’ over the cooling expected from a reduced MOC. Theimpacts associated with a reduced MOC are contained in the projections ofglobal and regional climate change provided by the IPCC AR4WG report.These include a continuation of already observed changes in precipitationthat include droughts in the subtropics and increased rainfall in equatorialand high-latitude regions. The results indicate that it is unlikely that therewill be a large abrupt change in the MOC during this period (Meehl et al.,2007), although changes beyond 2100 cannot be confidently assessed.

2.4. Upwelling

Wind-driven Ekman pumping with the Coriolis force drives the fourmajor eastern boundary upwelling regions of the world: Peru, Benguela,California and Northwest Africa, supplemented by a region off NortheastAfrica in the Arabian Sea that is driven by monsoonal wind forcing. Theseregions are possibly the most productive locations in the oceans (Thomaset al., 2004) due to the high concentrations of nutrients that are brought tothe surface. Poleward divergence of water driven by the trade winds alsocauses upwelling to either side of the equator. Upwelling has a dual role inclimate modulation as regions of strong outgassing of CO2 and othergreenhouse gases (Bakun and Weeks, 2004) and as areas where thebiological pump is especially strong as a consequence of the high produc-tivity and rapid sedimentation of planktonic material to the ocean floor.A further consequence of this productivity is a reduction in oxygen levels,


with at times the establishment of extensive areas of bottom anoxia (Bakunand Weeks, 2004; Neretin, 2006; Tyson and Pearson, 1991).

It has been postulated, on the basis of palaeo-evidence, that increases incoastal upwelling and an intensified biological pump reduced levels ofatmospheric CO2 in the lead up to the Pleistocene glaciations (Berger,1985). Bakun (1990) reported an intensification of equatorward alongshorewinds and an associated upward trend in upwelling from the 1940s to 1988in all four of the eastern boundary regions. He attributed the changes torising global temperatures and predicted an increase in upwelling intensity asglobal warming progresses. A similar substantial increase in upwelling and a>300% increase in chlorophyll has occurred in the Arabian Sea due tointensified summer monsoon winds in recent years due to warming of theEurasian landmass (Goes et al., 2005). A modelling study by Hsieh and Boer(1992), however, suggests that upwelling may respond in the opposite wayto that suggested by Bakun in a warming world. Their model analysisshowed that reduced latitudinal gradients would lead to weaker upwellingand less productivity.

2.5. Changing physics of tropical seas in a warming ocean

SSTs in the tropics determine where the upward branch of the HadleyCirculation in the atmosphere is located over the oceans and the strengthof the circulation is related to the ENSO (IPCC AR4,WG 1, 2007, p. 296).For example, the Asian-Australian (AA) Monsoon (see WCRP/CLIVARflyer on the AAMonsoons, available from CLIVAR http://www.clivar.org/)is strongly influenced by changes in SST in the Indian Ocean that aremodulated by ENSO. The potential effects of tropical seas on climate changehave only been discussed briefly in this chapter and should form a follow-upstudy.

2.5.1. Tropical storms (hurricanes, cyclones, typhoons)Tropical storms play a vital role in climate by pumping a considerablequantity of heat from the ocean into the atmosphere each year, by generat-ing mixing that brings cold deep water to the surface and, through evapora-tion (Trenberth and Fasullo, 2007). During the storm, precipitation releaseslatent heat that is rapidly transported high into the atmosphere where it mayradiate into space (Emanuel, 2006). These storms act as a release valve forsolar heat caught above the sea in the humid, cloudy conditions of thesummer tropics and are generated when surface water temperatures reach athreshold of �26 �C over a depth of �50–100 m. The contribution thattropical storms may make to climate change through feedbacks related to apossible increase in their frequency and intensity is still unclear.

The intensity of tropical storms has increased by 75% from 1970 to�2004 in the North Atlantic and western North Pacific and a global


http://www.clivar.org/

http://www.clivar.org/

increase in their destructiveness is documented by Trenberth et al. (2007).They also note that the first recorded hurricane ever to cross the coast ofSouth America occurred in March 2004. Atlantic hurricane activity ishighly correlated with SST and a rise of only 0.5 �C can lead to an increaseof �40% in hurricane frequency and activity (Saunders and Lea, 2007).Regional variability in the occurrence of tropical storms is closely linked toENSO and decadal environmental changes so that there is often an alterna-tion between basins in the number of storms. For example in El Nino yearshurricane intensity decreases in the North Atlantic, far west Pacific andAustralasian regions, but increases in the remainder of the Pacific. As globaltemperatures rise it is expected that precipitation will be enhanced, as well asthe extent of the geographical area suitable for seeding storms so that globalstorm intensity and possibly frequency will likely increase.

2.6. Sea-level rise

Sea-level rise is a major impact of climate change. Ocean thermal expansionwas an important component of sea-level rise during the latter half of thetwentieth century and models project it is likely to be the largest contributingfactor in the twenty-first century.

During the Pleistocene sea-level varied from metres above to over120 m below present-day values as major ice sheets waxed and waned,particularly in the Northern Hemisphere (Berger, 2008). At the time of thelast interglacial period about 125,000 years ago, sea-level was likely 4–6 mhigher (Overpeck et al., 2006) than it was during the twentieth century, atpolar average temperatures 3–5 �C higher than present values.

The Third IPCC Assessment Report, TAR (Church et al., 2001),reported that during the disintegration of the Northern Hemisphere icesheets at the end of the last glacial maximum, sea-level rose at an average rateof 1 m per century, with peak rates of about 4 m per century.

In the longer term, these ice sheets have the potential to make the largestcontributions to sea-level rise and there is increasing concern about thepotential instability of the West Antarctic and Greenland ice sheets.

The current projections of sea-level rise are based on the SRES emissionscenarios. However, global emissions are already above (Canadell et al.,2007; Raupach et al., 2007) the highest of these scenarios and well abovestabilisation scenarios of twice pre-industrial values. Since the start of theIPCC projections in 1990, sea-level is actually rising at near the upper endof the highest IPCC Third Assessment Report projections of 2001(Rahmstorf et al., 2007).

There will also be regional changes in sea-level with some areas showinga decrease relative to the global average rise, due to circulation changes, butthere is little understanding of such variability. One regional change that islikely to have a substantial impact is that many deltaic regions around the


world are sinking as a result of reduced sediment supply, compaction ofsediments and water (and/or oil or gas) extraction.

Sea-level rise will be felt most acutely through extreme events, such asHurricane Katrina and CycloneNargis. Rising sea-level on its own (withoutany change in the intensity or frequency of extreme weather driving coastalstorm surges) will result in extreme sea-level thresholds of a given valuebeing crossed more frequently. This change in frequency can be pro-nounced. Any change in the frequency or intensity of meteorological con-ditions will also change the frequency/intensity of extreme sea-level events.

2.7. Destabilisation of ice sheets/glaciers

It is possible that rising sea-levels might destabilise buttressing ice shelvesand/or increase the proportion of glaciers that float. A retreat of thegrounding line of these glaciers may allow ice streams to speed up andpotentially contribute to a large discharge of ice from an ice sheet althoughthe mechanisms involved are still little understood. Recent research, how-ever, has documented the production of a wedge of sediment that stabilisesthe position of the grounding line indicating that sea-level rise may beimplicated in recent retreats (Alley et al., 2007; Anandakrishnan et al.,2007). A combination of basal melt and rising sea-level might, however,allow seawater to extend into sub-ice sheet basins that are presently isolatedfrom the sea and lead to accelerated subsurface melting (D. Martinson,personal communication). Enhanced submarine melting causes the ground-ing line of glaciers to retreat, reduces the buttressing of frontal ice on inlandice, and allows faster rates of ice flow to the sea (Thomas, 2004).

The melting of the glaciers in the western Antarctic Peninsula is moreinfluenced by rising temperature than by changes in sea-level. It is unclear ifocean temperature or air temperature is the more important factor, but theocean has a larger heat capacity and is in subsurface contact with the ice. Halfa degree of temperature change in ocean temperature is more significantthan half a degree change in air temperature. The recent decadal warmingof the ocean adjacent to the western Antarctic Peninsula (>1 �C in summermonths since the 1950s) is mooted to have played a significant role in theretreat of its tidewater glaciers (Meredith and King, 2005).

Surface melt of the Greenland ice sheet has increased and is projectedto increase at a faster rate than additions from higher precipitation astemperature rises. If Greenland air temperatures rise an average of 3 �C,it is predicted that the ongoing contraction of the ice sheet may be irrevers-ible (ACIA, 2005). Global warming could exceed this value during thetwenty-first century without effective mitigation of emissions. If thesetemperatures were maintained, they would lead to a virtually completeelimination of the Greenland ice sheet and a contribution to sea-level riseof up to about 7 m in the coming centuries to thousands of years.


Some recent observations suggest a (rapid) dynamic response of theGreenland and West Antarctic ice sheets (WAIS) that could result in anaccelerating contribution to sea-level rise. This is only included in an ad hocfashion in the current IPCC projections. For the Greenland ice sheet, this ishypothesised to involve surface melt water making its way to the base of theice sheet and lubricating its motion enabling the ice to slide more rapidlyinto the ocean. Glaciers in Greenland are already retreating. The sea-icethere shows no buttressing in the way that it does in Antarctica. Even so,sea-ice in the Greenland Sea has rapidly decreased over the last two decadesand the Oden ice tongue between 70 and 75�N has disappeared. InAntarctica, the WAIS is grounded below sea-level, allowing warmerocean water to melt the base of the ice sheet and potentially leading tosignificant instability. Understanding of these processes is limited. As aresult, they are not adequately included in current ice sheet models andthere is no consensus as to how quickly they could cause sea-level to rise.Note that these uncertainties are essentially one sided. That is, they couldlead to a substantially more rapid rate of sea-level rise but they would notlead to a significantly slower rate of sea-level rise.

Current projections suggest that the East Antarctic ice sheet will remaintoo cold for widespread surface melting and that it is expected to gain massfrom increased snowfall over the higher central regions. Net loss of masscould occur, however, if there was a more rapid ice discharge into the seaaround East Antarctica due to a higher rate of accumulation from snowfallover the interior or due to a warming of the coastal waters in contact withthe glaciers. The latter would increase submarine melting, which in turnwould release the grounded glaciers from their bed and allow them to flowfaster towards the sea.

2.8. Concluding comments

� Global SST has shown a progressive increasing trend over the last centurywith warmer water extending into the Arctic and parts of the SouthernOcean adjacent to Antarctica.

� There has been a large increase in the heat content of the ocean down to700 m depth.

� The deep ocean appears to be absorbing heat at an increasing rate, but theamount of heat stored is inadequately quantified because of poor sampling.

� Pronounced changes in salinity have occurred in many regions of theworld, likely reflecting a modification of the Earth’s hydrological cycle.

� Combined together, the salinity and temperature changes alter the den-sity distribution, stratification and THC/MOC with large potential feed-backs to climate.

� There is clear evidence of large changes and pronounced daily to decadalvariability in the MOC in different areas of the world.


� It is not possible at present to say if these changes on a global scale are aconsequence of a reduction in the strength of the circulation due toclimate change.

� The general consensus from modelling projections for the end of thetwenty-first century is that there is likely to be a reduction in the strengthof the Atlantic MOC by 0–50% of its current strength. This will not leadto a cooling, but less warming in Europe, with perhaps more warming inthe tropics.

� It is unlikely that there will be a large abrupt change in theMOCduring thenext century, although changes beyond 2100 cannot be confidently assessed.

� There is evidence for increases in the intensity of upwelling, leading tolarge increases in phytoplankton production, anoxia and release of green-house gases.

� The intensity of tropical storms (hurricanes, cyclones, typhoons) hasincreased by 75% in the North Atlantic and western North Pacific anda global increase in their destructiveness is documented.

� With rising sea temperature and enhanced precipitation, the area forseeding tropical storms will expand possibly leading to an increase instorm frequency and intensity.

� Since the start of the IPCC projections in 1990, sea-level is rising at near theupper endof thehighest IPCCThirdAssessmentReport projectionsof 2001.

� Historical evidence adds credibility to the possibility of an increase in therate of sea-level rise at the upper end of and beyond IPCC projections.

� If global average temperature in Greenland increases by�3 �C above pre-industrial values, a level that could be reached during the twenty-firstcentury without effective mitigation of emissions, the ongoing contrac-tion of the Greenland ice sheet may not be reversible and could result inseveral metres of sea-level rise over hundreds or thousands of years.

� Recent rapid dynamic responses of the Greenland and West Antarctic icesheets might result in a future accelerating contribution of their ice meltto sea-level rise.

� Feedbacks to climate change from sea-level rise are uncertain.� Feedbacks from sea-level rise can accelerate ice sheet loss at the coast.

3. Primary Production: Plankton, Light and

Nutrients

Microscopic marine phytoplankton form the base of the marine foodweb. They use energy from the Sun to fix CO2 and account for around 45%of global primary production. Most of the organic carbon formed is con-sumed by herbivores or respired by bacteria, the remainder, about 35%(16 Gt, Falkowski et al., 1998; 11 Gt, Denman et al., 2007; Fig. 1.7), sinks


below the upper sunlit layer every year. This section addresses the contri-bution that planktonic and benthic organisms make to carbon cycling in theocean with a commentary on the biogeochemical and other controls onprimary production. An attempt is made to synthesise and prioritise poten-tial feedbacks to climate change from the many complex processes involved.It should be remembered that any feedbacks to climate are now taking placeagainst a background of a very changed biology that has been impacted byeutrophication and hypoxia (Diaz and Rosenberg, 2008), removal of toppredators (Pinnegar et al., 2000) and overfishing (Myers and Worm, 2003).

3.1. Oceanic primary production

Production of atmospheric oxygen and fixation of carbon during photo-synthesis by phytoplankton enables the Earth to support a rich diversity ofmarine life and has strongly influenced changes in climate through geologi-cal time (Diaz and Rosenberg, 2008; Mackenzie and Lerman, 2006).Phytoplankton biomass and primary production is determined by lightavailability and access to nutrients (nitrogen, phosphate, silicic acid, iron)as well as grazing and viral lysis. Light varies with the angle of solarinsolation (latitude), season, cloud cover, level of water clarity and mixing

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Figure 1.7 Cartoon of the Biological pump modified from Falkowski and Oliver(2007). Note that CO2 is emitted from all heterotrophic organisms (e.g. zooplankton,fish and squid) and O2 is produced by phytoplankton as well as other gases such asmethane and DMS.


and is variably absorbed by different phytoplankton pigments. Superim-posed on these growth-limiting factors is a physical regulation by oceancirculation, mixed-layer dynamics and upwelling. Since�1% of light pene-trates to 100 m (a very small proportion may reach as far as 1000 m) in theopen ocean, and in productive coastal seas may only extend to 30 m or less,photosynthesis is confined to this upper layer.2 The contributors to primaryproduction vary from cyano- and eubacteria [e.g. Synechococcus, Prochloro-coccus, SAR 11 (SAR 11: a dominant cluster of marine bacterial phylotypesfirst described from the Sargasso Sea)] and eukaryotic picoplankton(0.2–2 mm in size), especially in tropical and oligotrophic oceanic waters,to eukaryotic nannoflagellates (2–10 mm) elsewhere with larger eukaryoticphytoplankton (10 to�150 mm) such as diatoms and dinoflagellates formingan important component of the biomass in upwelling regions and in borealand temperate seas. A new paradigm for primary production now exists (seeFig. 1 in Karl, 2007), which includes the above new microbial contributorsas well as photolysis (PL) of dissolved and particulate organic matter bysunlight (Fuhrman et al., 2008; Karl, 2007). This means that total primaryproduction is likely to exceed the traditional view of chlorophyll-basedgross primary production.

Plankton also plays a key role in the Biological pump (see Section 4) thatmoves organic and inorganic carbon to the deep ocean. Grazing andrecycling of nutrients by zooplankton, bacteria, archaea and viruses includ-ing reprocessing and packaging of planktonic detrital material as it sinksthrough the water column, are key processes in determining the export rateof C fixed by primary production (Steinberg et al., 2008; Yamaguchi et al.,2002). Viruses (also fungi) have an important role as terminators of planktonblooms and because of their role in the mortality of marine organisms arekey players in nutrient and energy cycles and in the structuring of microbialcommunities (Suttle, 2007). It is believed that changes in the relativestrengths of the two fluxes (Primary Production and export flux) stronglyinfluence climate and have been responsible for many of the changes inclimate in the geological past (Falkowski et al., 1998). The plankton alsochange surface albedo, increase retention of heat in the upper ocean byabsorbance and contribute to the production of other potent greenhousegases such as methane and nitrous oxide, and to reactive gases, such asdimethylsulphide (DMS) and halocarbons.

It is worth noting here some important differences between oceanic andterrestrial ecosystems. Most marine organisms are small, have rapid turnovertimes, are able to react quickly to changes in temperature, and are easilydistributed by changing ocean currents in contrast to their terrestrial equiva-lents (Sarmiento et al., 2004). In the upper waters of the open ocean,

2 http://oceanexplorer.noaa.gov/explorations/04deepscope/background/deeplight/deeplight.html


http://www.coml.org

http://www.coml.org

temperature and nutrients are strongly related (Kamykowski and Zentara,2005a,b); this is not the case on land. As a consequence, oceanic organismsreact more directly to changes in seawater composition resulting fromclimate change than terrestrial systems, and feedbacks from oceanic biologyand biogeochemical interactions are likely to take effect more quickly.

3.2. Microbial plankton

A number of major scientific breakthroughs have greatly improved under-standing of oceanic microbial diversity and ecology over the last decade(Karl, 2007). Using genetic sequencing, it has been possible for the first timeto determine the microbial (bacterial, archaeal and protist) composition ofseawater samples (e.g. Fuhrman and Davis, 1997). One litre of seawater maycontain as many as 20,000 species of bacteria, but only a very few �20dominate. The remainder form what is termed the ‘rare biosphere’ (Karl,2007; Sogin et al., 2006). Archaea are also an important component of thepicoplankton in shallow and deep waters (Herndl et al., 2005; Massana et al.,2000). It is estimated that the global oceans contain approximately1.3 � 1028 archaeal cells, equivalent to 30–40% of the estimated abundanceof bacteria (DeLong, 2007; Quinones et al., 2009). By combining geneticand isotope techniques with membrane lipid research, a range of newecological roles for microbes in the biogeochemical cycling of C, N, S, Feand many other trace elements have been demonstrated that are importantto climate change. These include anoxic oxidation of methane (AOM)(Boetius et al., 2000; Michaelis et al., 2002; Stadnitskaia et al., 2008),anaerobic ammonium oxidation (Anammox process) that releases nitrogengas from the oceans (Galan et al., 2008; Jensen et al., 2008; Kuypers et al.,2003; Sinninghe Damste et al., 2002), ammonia as an energy source forCrenarcheota so that they function as chemolitho-autotrophic organisms inthe nitrogen cycle (Agogue et al., 2008; Konneke et al., 2005; Nicol andSchleper, 2006), the discovery of new nitrogen fixing microbial organismsin the oceans (Montoya, 2004; Zehr et al., 2008), use of light as an energysource enabling massive fixation of CO2 by SAR bacteria (Eiler, 2006),widespread anoxygenic photoheterotrophy in marine bacteria, includingbacteria with bacteriochlorophyll and with proteo-rhodopsin (PR) (Bejaet al., 2002; Eiler, 2006; Gomez-Consarnau et al., 2007; Moran and Miller,2007), close syntrophic partnerships of anaerobic methane oxidising archaeaand sulphate-reducing bacteria (Boetius et al., 2000; Pernthaler et al., 2008).These new findings demonstrate the crucial importance of microbes inclimate and climate change and highlight a virtual complete absence ofunderstanding of how microbial systems will change and impact biogeo-chemical cycling with climate change. Developing an understanding of therole of microbial diversity and functioning in biogeochemical and nutrientcycling is a major challenge for the future.


3.3. Phyto- and zooplankton

The distribution, abundance, production and biodiversity of differentplankton species/groups are likely to be profoundly affected by projectedclimate-driven changes in the physical and chemical properties of the oceanincluding circulation, stratification, nutrients, light, trace metals (e.g. iron)and carbonate chemistry (Richardson, 2008). The converse will also occuras changes in plankton ecology and biodiversity can have a large and rapidimpact with important feedbacks to climate variability through their rolein the Biological, Continental Shelf and Carbonate Counter carbon pumps(see Section 4). Despite this importance, variability of these organisms on aglobal scale, other than for satellite measurements of chlorophyll, has beenpoorly studied. Long-term plankton observation programmes, other thanthe Continuous Plankton Recorder (CPR) survey (see http://www.sahfos.ac.uk/) in the North Atlantic and Southern Ocean, are non-existent inmany oceanic regions of the world.

At a global scale there is a strong negative relationship between satellite-derived primary production and SST (Behrenfeld et al., 2006), but see thequalification of Sarmiento et al. (2004), that reflects the closely coupledrelationship between ocean productivity and climate variability. One of themain reasons for this coupling is that the availability of nitrate (the principalnutrient limiting phytoplankton growth in much of the ocean) has beenfound to be negatively related to temperatures globally (Kamykowski andZentara, 2005a,b). In the North Atlantic and over multi-decadal periods,changes in phytoplankton species and communities have been associatedwith Northern Hemisphere temperature trends and variations in the NAOindex (Beaugrand and Reid, 2003). While at the interannual timescalecorrelations between temperature and phytoplankton are weak, due tohigh variance inherent in phytoplankton populations, at decadal intervalsthey are well correlated. Over the whole Northeast Atlantic there has beenan increase in phytoplankton biomass in cooler and a decrease in warmerregions (Richardson and Schoeman, 2004). This relationship is likely to be atrade-off between increased phytoplankton metabolic rates caused byhigher temperatures in cooler regions and a decrease in nutrient supply inwarmer regions (Doney, 2006). The floristic shifts associated with thiswarming move a diatom-based system towards a more flagellate-basedone (Leterme et al., 2005). In this scenario, however, it is assumed thatthe carbon sequestration will be less efficient because, unlike boreal diatom-based systems, much of the flagellate and nanoplanktonic production isremineralised near the well-mixed surface. In a warming ocean, microbialactivity is also likely to be faster leading to more rapid recycling of carbonand a less efficient Biological pump. However, due to the underlying com-plexity of biological communities and their quite often non-linear responses


http://www.sahfos.ac.uk/



to environmental variability, this makes predicting both floristic and faunisticchanges and their feedbacks to climate fraught with uncertainty.

A number of groups in the plankton, including some benthic larvalstages, have calcareous body parts (calcite, Mg calcite and aragonite).These organisms, including the algal coccolithophores (photosynthetic)and protist foraminifera (some of which are photosynthetic through symbi-osis) are major contributors to pelagic carbonates especially in the subtropi-cal gyres. Calcification (see Section 5) has the opposite effect to primaryproduction, releasing some CO2 to the water that may outgas adding to theCO2 concentration in the atmosphere.

The effects of projected changes in the pH of the oceans (acidification),in combination with rising temperature, on plankton community structureand calcification/dissolution processes are likely to have profound implica-tions for biodiversity, living marine resources and again with likely feedbackto the carbon cycle (see Sections 4 and 5). At the microbial level, thedominance of different picoplankton taxa may be affected by changes inpH and temperature with impacts on food web structure, especially inoligotrophic waters (Fu et al., 2007).

Changes in ecosystem composition, that appear to be driven by climatevariability, are already underway: examples include desertification aroundthe Mediterranean Sea (Kefi et al., 2007), shifts in North Atlantic planktonbiomass (Beaugrand et al., 2002), regime shifts in the North Pacific andNorth Sea (Chavez et al., 2003; Reid et al., 2001; Roemmich andMcGowan, 1995) and observed shifts in phytoplankton pigment distribu-tions as seen from satellite (Alvain et al., 2008). Large productivity crashesare also associated with ENSO events in the Pacific (e.g. Lavaniegos andOhman, 2007; Peterson et al., 2002). These changes when seen togetherindicate that marine ecosystems are reacting beyond what might beexpected from interannual variability. The changes also indicate that theremay be locations in the ocean that act as biological hot spots that interactwith climate change. If this is true, the identification and monitoring of suchlocations might be crucial for biodiversity, the maintenance of marineecosystem goods and services, and for carbon drawdown.

As oceans warm, primary productivity is peaking earlier in the season insome areas, with less distinctiveness between the spring, summer andautumn seasons (Edwards et al., 2001; Reid, 2005). Other parts of thefood chain are shifting geographically poleward in response to thermalstimuli, rather than tracking the seasonal shift in primary productivity(Beaugrand et al., 2002; Mackas et al., 2007). These changes are creating a‘mismatch between trophic levels and functional groups’ with implicationsfor ocean–climate interactions and living marine resources (Edwards andRichardson, 2004).


3.4. Chlorophyll and primary production

Chlorophyll a is the dominant pigment in phytoplankton. As it is relativelyeasy to determine, it has been widely used in field studies as an in situmeasure of phytoplankton biomass. With the advent of satellite instrumentssuch as the Coastal Zone Color Scanner (CZCS; 1978–1986) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS; 1997 to the present) anddevelopment of algorithms for the estimation of chlorophyll a and primaryproduction, we have a synoptic viewpoint that allows study of phytoplank-ton at the global scale (McClain et al., 2004; Fig. 1.8). It should be notedthat the satellites only measure phytoplankton in the top few metres of theocean and do not reflect the estimated �10% of marine primary productionthat takes place in the Deep Chlorophyll Maximum. In addition, it isbecoming increasingly clear that chlorophyll a, on the basis of the newmicrobial evidence cited above, is not a good proxy for primary production.

Using SeaWiFS data for 1997–2006, Behrenfeld et al. (2006) showedthat global chlorophyll and calculated net primary production (NPP)increased sharply at the beginning of the period and then declined. Thedominant signal in the data reflected changes in the 74% of the global oceanthat comprises low-latitude permanently stratified tropical and subtropicalwaters with mean annual SSTs above 15 �C. The pattern of change washighly correlated with SST and an index of ENSO climate variability. Thelink between ocean biology and the physical environment was shown tooperate via warmer upper-ocean temperatures enhancing stratification,which reduced the availability of nutrients for phytoplankton growth andvice versa.

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Figure 1.8 Global image of mean surface chlorophyll for the period 1998–2007.Processed from SeaWiFS data by Takafumi Hirata, PML.


Polovina et al. (2008), using the same SeaWiFS data, for the periodJanuary 1998–February 2007 have shown a similar expansion, especially inwinter, of the least productive areas of the ocean, the subtropical gyres. Inthe North and South Atlantic and Pacific Oceans, outside the equatorialzone, approximately 6.6 million km2 of former higher chlorophyll habitathave been replaced by low chlorophyll water. It appears that the subtropicalgyres are expanding on their current position, becoming warmer and moreoligotrophic and are likely to continue to expand as temperatures risefurther. In the Southern Ocean, Le Quere et al. (2002) show in a modellingstudy that the response of primary production to increased stratification andtemperature varies regionally and that light availability is more importantthan temperature and dust as a forcing factor. The net effect for the wholeocean is not known.

If the reductions in NPP seen within the SeaWiFS period are extra-polated on the basis of projected changes in SST and nutrients, it could leadto a substantial reduction in the productivity of the oceans over the next 100years. If these changes coincided with a reduction in the net input of CO2

and a reduction in export fluxes, there could be a large impact on thebiological pump.

A decade or more ago (e.g. Falkowski et al., 1998) modelling had alreadypredicted that primary production would reduce as stratification increasedin the oceans. From a climate change perspective, it is important to note thatthe rates of expansion of the subtropical gyres measured by Polovina et al.(2008) already far exceed recent model predictions. As a corollary,Behrenfeld et al. (2006) also note that modelling has shown that changesin ecosystem structure (e.g. taxonomy, physiology and light absorption) dueto climate variations may be as or more important than the changes in bulkintegrated satellite measures of chlorophyll. The global observing systemsneeded to measure such variability are rudimentary and concentrated in theNorthern Hemisphere at present.

A range of mesoscale processes such as eddies, fronts and their interactionwith wind are important in mixing and bringing nutrients to the surface andmay stimulate blooms (e.g. McGillicuddy et al., 2007). Similar mixing maybe induced by the passage of hurricanes (Son et al., 2007). Understanding ofmesoscale variability in oceanic waters and its potential impact on NPP,export flux and climate is poor.

3.5. Plankton biodiversity functional groups andocean biomes

There are tens of thousands of different species of viruses, bacteria, archaea,cyanobacteria, phyto- and zooplankton and other organisms in the plank-ton. Together they play a key role in ecological and biogeochemicalprocesses (Falkowski et al., 2003) that modulate the cycling of CO2.


These roles include the regulation of the settling flux of organic andinorganic carbon to the deep ocean and determining levels of reactivetrace gases and aerosols in the atmosphere as well as proxy tracers for thecarbon cycle such as O2,

13CO2 and O18O. The biodiversity also contri-butes to variability in physical processes in the ocean, including tempera-ture, stratification and mixing (Dewar et al., 2006; Le Quere et al., 2005).

To manage the complex variety of these different plankton modes inmodelling and other studies, assemblages of species are generally consoli-dated, for example, into ‘Plankton Functional Groups’ (Boyd and Doney,2002; Jin et al., 2006; Sarmiento et al., 2004). Changes in the relativeimportance of different functional groups in the plankton can stronglyimpact the biological pump. Diatoms, relatively heavy and fast sinking,would be efficient in transporting sinking carbon to the deep ocean(Smetacek, 1998; Treguer and Pondaven, 2000; Yool and Tyrrell, 2003),whereas nanoplankton (including the calcareous coccolithophores), beingsmaller as well as being rapidly ingested by heterotrophs, would be lessefficient in the biological pump. Thus, relative fluxes of diatoms versuscalcareous plankton have been implicated as one of the causes for thechanges in CO2 between glacial and interglacial periods (Harrison, 2000;Treguer and Pondaven, 2000). Several feedback effects are conceivable:higher wind speeds, that favour diatom growth, would result in increasedexport (Le Quere et al., 2007, 2008); on the other hand, increasing tem-peratures, which favour the growth of smaller phytoplankton, are thoughtto reduce export flux. New developments in the interpretation of SeaWiFSdata (e.g. Aiken et al., 2008; Alvain et al., 2005, 2006, 2008; Raitsos et al.,2008) are making possible the identification of some phytoplankton func-tional groups on a global scale.

The next step in an analysis of biological variability in the ocean and itsimportance to climate change is to determine change in different oceanprovinces (Biomes: Longhurst, 1998). Sarmiento et al. (2004) in a multi-model comparison study have divided the ocean into six different Biomesbased on physical characteristics that reflect nutrient supply (Fig. 1.9). It isclear from carbon export studies in the Southern Ocean and elsewhere(Boyd and Trull, 2007) that there is a need to increase the number ofLonghurst provinces with more precise/sensitive definitions based onmulti-disciplinary information systems including plankton assemblage data(e.g. Beaugrand et al., 2002; Devred et al., 2007). To achieve this aim animproved knowledge is needed of chemistry, mesoscale properties, spatialand temporal variability in plankton composition and production versusrecycling and export rates.

In a review by Le Quere et al. (2005), plankton functional types (PFTs)were selected among other criteria on the basis of their clear biogeochemi-cal role, quantitative importance in terms of biomass and production, well-defined environmental, physiological and nutrient control and biological


interactions. A provisional grouping of 10 different PFTs that need to besimulated in a new generation of linked ocean physics and ecosystemmodels was selected by Le Quere et al. (2005) to ‘capture importantbiogeochemical processes in the ocean’. The groups selected are involvedin, for example, bacterial remineralisation, N2 fixation, phytoplanktoncalcification, silicification and DMS production, and include three differentsize fractions of zooplankton that contribute to export via a range ofprocesses including faecal pellet and mucilaginous packages. The modellingand research strategy outlined by Le Quere et al. (2005) addressed the urgentneed to improve understanding of the interactions between the differenttypes of plankton, food web structure and export efficiency of carbon. Tosuccessfully progress such a strategy will require a new level of internationalcollaboration between modellers and marine ecologists, which has beenhistorically absent.

3.6. Benthos

Benthic ecosystems play an important role in global carbon cycles as they aresites for remineralisation, burial and calcification. They also are places wheremany of the nutrients that sustain planktonic production are regenerated.While benthic studies have been carried out worldwide, they are largelyconfined to shelf waters and are spatially and temporally patchy. The inshorebiota of Western Europe and parts of the coast of North America is well

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Figure 1.9 The distribution of six different ocean biomes: (1a) equatorial—down-welling (Eq-D), (1b) equatorial—upwelling (Eq-U), (2) subtropical gyre—permanentlystratified (ST-PS), (3) subtropical gyre—seasonally stratified (ST-SS), (4) low lati-tude—upwelling (LL-U), (5) sub-polar (SP) and (6) marginal sea-ice (Ice). FromSarmiento et al. (2004).


known but that of most of Asia, Africa and South America, especially in thetropics and subtropics, is poorly studied and the deep sea (around 97% of theworld ocean) has scarcely been sampled. As a consequence it is difficult toquantify the role of the benthos in the global carbon cycle or to identify theregional areas that are most important. Furthermore, the majority of benthicstudies have been focussed on larger bodied animals; sedimentary microbi-ology is a relatively young science and thus it is equally difficult to partitioncarbon cycling between the different elements of the benthic biota.

While there has been considerable concern about the impacts of oceanacidification on animals with calcareous body parts, some species appear tobe able to increase the rate of calcification at a lower pH (Wood et al.,2008b) although this is at some metabolic cost and may not be sustainable.Non-calcareous species are also likely to be affected as their physiology isfinely regulated and has evolved to function within relatively narrow pHand CO2 ranges (Michaelidis et al., 2005). The scale of impacts on popula-tions and assemblages resulting from a potential decline in growth andreproductive rates from ocean acidification has yet to be quantified.

3.7. Migration of plankton, fish and benthos towardsthe poles

A pronounced consequence of a warming ocean has been a polewardexpansion of the range of many species in both the Southern and NorthernHemispheres. The resulting marked changes in community structure thatare reflecting warming oceans and changes in circulation (e.g. Hatun et al.,2009) have implications for the biological pump and CO2 drawdown. Someof the strongest evidence for large-scale biogeographical changes in theoceans comes from the Continuous Plankton Recorder survey. In theNortheast Atlantic warmer water, zooplanktonic copepods have moved tothe north by 10� latitude (1000 km) within 50 years while colder waterplankton has retreated in the same direction (Beaugrand et al., 2002). Thisrepresents a mean poleward movement of between 200 and 250 km perdecade. The speed of this migration, due to advective processes, is morepronounced than any documented terrestrial study. Responses of zooplank-ton to changing water temperature have also been observed in the NorthPacific (Mackas et al., 2007), but it remains unclear if these are systematicresponses to climate change or simply related to shifts in climatic state asreflected by major climate indices such as the Pacific Decadal Oscillation.Many species of fish have also shown apparently similar northerly rangeextensions in the eastern Atlantic and North Sea, at estimated rates that areup to three times faster than terrestrial species (Brander et al., 2003; Perryet al., 2005). One of the largest biogeographical shifts ever observed for fishspecies is the dramatic increase and subsequent northerly geographicalspread of the snake pipefish (Entelurus aequoreus). Prior to 2003 this fish


was confined to the south and west of the British Isles, but it now extends asfar north as the Barents Sea and Spitzbergen (Kirby et al., 2006; Harris et al.,2007). The pelagic environment is of course three-dimensional and recentresearch has observed a movement of fish species towards deeper coolerwaters in response to climate warming (Dulvy et al., 2008). This change canbe seen as analogous to the upward altitudinal movement of terrestrialorganisms in alpine environments.

There is evidence for poleward migration of benthic species in temper-ate and sub-polar latitudes of both hemispheres; in all areas, changes thathave taken place within the last 20 years. Range expansions have beendescribed, for example, from around California (Barry et al., 1995), theBritish Isles (Mieszkowska et al., 2007), in the Bering Sea (Grebmeier et al.,2006) and off the Antarctic Peninsula (Clarke et al., 2005; Thatje, 2005).There is minimal information to indicate if tropical and subtropical species,other than possibly corals on the eastern margin of Florida, are expandingpoleward.

3.8. Oxygen

One of the most critical variables in the world’s ocean is the distribution ofdissolved O2. Oxygen plays a direct role in the biogeochemical cycling ofcarbon and nitrogen as well as being fundamental for all aerobic life,including organisms living in the dark ocean interior. If the oceans wereto stagnate, many regions of its interior would be devoid of O2 within a fewdecades as oxygen is continually being consumed by deep-dwelling organ-isms (Feely et al., 2004; Whitney et al., 2007).

A critical threshold is reached when O2 levels reach �60 mmol kg�1,below which most macro-organisms become hypoxic, that is, severely O2

stressed (Gray et al., 2002). A second threshold is crossed when O2 dropsbelow �5 mmol and nitrate becomes important in respiration, a conditiontermed ‘suboxic’. When O2 levels drop to zero, the water is termed‘anoxic’, and biogeochemical processes are then dominated by sulphate-reducing microbes.

Ocean anoxic events (OAEs) have occurred episodically throughout thegeologic record (Cohen et al., 2007; Jones and Jenkyns, 2001; Wignall andTwitchett, 1996). These episodes are defined by sedimentary evidence ofwidespread anoxia and are often associated with evidence of warmer climateconditions, rises in sea-level and occasionally with mass extinctions.Although the cause of the events remains a matter of speculation, theirexistence underscores the potential vulnerability of oceanic O2 supply inwarmer climates.

Anoxia is rare in the modern open ocean, but is important in enclosedbasins such as the Black and Baltic Seas. Hypoxic conditions occur, how-ever, at mid-depths over wide expanses of the North Pacific, in smaller


regions of the north Indian Ocean, and in the eastern tropical Atlantic andPacific Oceans. These regions are known as oxygen minimum zones(OMZs), with the low levels of O2 mostly attributable to the sluggish rateat which the subsurface is renewed by mixing with well-aerated surfacewaters (Karstensen et al., 2008). Suboxic conditions are restricted to morelimited regions of the north Indian and eastern Pacific OMZs. Hypoxic andsuboxic conditions frequently occur in coastal waters, where low subsurfaceO2 levels can be generated by natural high biological productivity in theoverlying waters or by eutrophication from agricultural runoff or sewageinputs (Diaz and Rosenberg, 1995).

Significant reductions in the O2 supply to the ocean interior and expan-sion of OMZs may result from continued anthropogenic global warming.Under business-as-usual type emission scenarios, climate models suggestthat the global ocean O2 inventory will decrease by 4–7% over the nextcentury with continued reductions after that (Matear and Hirst, 2003;Schmittner et al., 2008). The main mechanism is increased stratification ofthe surface ocean due to warming and freshening of high-latitude surfacewaters which reduces renewal rates. The details differ between models, withseveral other processes also being relevant including the direct reduction ofO2 solubility in warmer water and changes in rates of photosynthesisinfluencing the sinking flux of organic detritus into the ocean interior.The models suggest that detectible changes in O2 content due to globalwarming may already have occurred (Matear et al., 2000; Sarmiento et al.,1998).

Marked declines in subsurface O2 concentrations have been noted in 30-year records from the western North Pacific (Ono et al., 2001) and 50-yearrecords from the eastern North Pacific (Whitney et al., 2007). The largestlong-term declines (of the order 10 mmol kg�1 per decade) have been foundin layers occupied by North Pacific intermediate water (150–600 m depth),which is renewed by contact with the surface in the Sea of Okhotsk andneighboring regions. The declines have been tied to freshening surfacewaters in the renewal regions associated with a reduction in renewal rates(Mecking et al., 2006; Nakanowatari et al., 2007) and appear superimposedon decadal variability of natural origin (Andreev and Baturina, 2006;Mecking et al., 2008). As a consequence the oxic/hypoxic boundary hasshoaled from 400 to 300 m over the past 50 years (Whitney et al., 2007).

Significant O2 declines have been found in 50-year records from theOMZs in the eastern tropical Pacific and Atlantic (Stramma et al., 2008).The declines are of the order 1–3 mmol kg�1 per decade and are associatedwith a vertical expansion of the hypoxic layers. Clear evidence of long-termtrends is lacking in other regions, however, and the ability to resolve long-term trends is impaired by sparse coverage of reliable historical O2 measure-ments and by short-term or decadal variability ( Johnson and Gruber, 2007;Min and Keller, 2005). Climate models suggest that the O2 levels may


actually increase in some regions despite the decline in the global averagedue to the complex response of dissolved O2 to circulation changes (Matearand Hirst, 2003; Schmittner et al., 2008). Changes in climate may alsocontribute to increasing coastal hypoxia (Grantham et al., 2004).

The implications of a continuing global decline in global oceanic O2 toclimate change are unclear as the science is still at an early stage. Potentialimpacts of O2 on organisms and ecosystems must be considered in concertwith changes in acidity and temperature (Portner and Farrell, 2008). Furtherexpansion of the O2 minimum zones will likely adversely impact the distri-bution of fish and other commercially valuable species (Gray et al., 2002).

3.9. Nutrients in general

In addition to CO2 and light, phytoplankton growth and productivityrequires the availability of a range of nutrients. In the 1930s, Redfieldfound that the bulk elemental composition of particulate organic matter inseawater is constrained and reflects the concentration of the major elementsin seawater. This led to the adoption of the Redfield ratio 106C (car-bon):16N (nitrogen):1P (phosphorus) (and 16Si for silicic acid that isessential for diatoms) as the average elemental composition. It should bestressed that there is considerable variability around these average ratios intime, space and by species/taxa (Arrigo, 2005; Klausmeier et al., 2008).Spatial and temporal variability in nutrient availability has a profoundinfluence on the composition, biomass, seasonal cycle and spatial variabilityof phytoplankton.

The ocean basins of the world show very variable spatial concentrationpatterns for different nutrients. There have been observed changes throughtime, but these show no consistent basin-scale patterns (Bindoff et al., 2007).This lack of coherence in the data has been attributed to poor samplingcoverage and limited compatibility between the methods used through timeand by different laboratories (Bindoff et al., 2007). Kamykowski and Zentara(2005a,b), in contrast, using a calibrated temperature/nitrate relationshipfrom a range of locations, have produced anomaly charts of the differencebetween nitrate availability between 1909 and 2002 (Fig. 1.10). The figureshows the clear expansion of a shallower thermocline over much of theocean (blue) with reduced availability of nitrate. Equatorial nitrate availabil-ity linked to El Nino is evident in the Pacific and a pronounced contrastbetween the two sides of Canada is seen, in the east reflecting increasedhaline stratification.

Three large regions that together cover�20% of the ocean’s surface, theSouthern Ocean, eastern equatorial Pacific and subarctic Pacific, are char-acterised by high levels of nutrients and low chlorophyll (HNLC regions)(Aumont and Bopp, 2006). The stable chlorophyll levels in these regionshave been attributed to iron limitation or grazing control by


microzooplankton (see Section 4). It is possible that increased desertificationand land use changes in the future may lead to more aerial input of dust,including micro-nutrients such as iron, into the oceans (Mahowald et al.,1999). Other factors than iron limitation may be behind the low chlorophylllevels, however, and so the addition of iron alone may not lead to anincrease in production; it is the cumulative effect of the many changesthat is important.

There has been an enhanced riverine input of N and P to near shoreregions over the last century and especially since �1950 that in some caseshave caused eutrophication and elsewhere has been buried in organiccarbon in sediments (Smith et al., 2003). The latter study derived estimatesbased on population relationships that are three times higher than thosederived in the 1970s. As population levels rise in the future, this pattern islikely to be reinforced as higher global temperatures are expected to lead toan increased mobilisation of N and P from sediment (Mackenzie et al.,2002). Sequestration of carbon in sediments is likely to especially apply inregions subject to anoxia or hypoxia that appear to be increasing in extent(Diaz and Rosenberg, 2008). Atmospheric inputs of fixed nitrogen to theocean have also increased and have contributed to higher algal productionand nitrogen oxide (N2O) emissions from the ocean (Duce et al., 2008).Langlois et al. (2008) have shown that nitrogen fixing cyanobacteria in theNorth Atlantic were most abundant at higher temperatures (see also Stal,2009) and with enhanced inputs of atmospheric dust.

Strong regional changes in nutrients are expected in the future depen-dent on variability in wet precipitation, wave storminess, expanding OMZs,

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Figure 1.10 Map showing modelled difference in nitrate availability based on a tem-perature nitrate relationship, between October 1909 and 2002. Darker colours repre-sent greater contrasts between the years. From Kamykowski and Zentara (2005a,b).Green, nitrate in 1909 present at the surface >2002; red, nitrate in 2002 present at thesurface >1909; blue, stratification in 1909 between nitracline and surface <2002; grey,stratification in 1909 between nitracline and surface >2002.


mixing and the depth of stratification. Precipitation is expected to increaseespecially in tropical regions. At present, it is not possible to predict futuretrends in nutrients because of the localisation of the changes. It is also notclear how all the regional responses will add up to a global mean andinfluence climate change.

3.9.1. The oceanic nitrogen cycleNitrogen is a fundamental component of all organisms and essential in thechemical forms that are needed for assimilation in primary production.Understanding of the nitrogen cycle (Fig. 1.11), and especially of the roleplayed by microbes in the cycle, has increased substantially in the lastdecade. The predominant form in the ocean is nitrogen gas (N2); this gascan only be utilised by a few specialist nitrogen fixers that include the

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Figure 1.11 The global nitrogen cycle. Nitrification is a step-wise process by whichammonia (NH3) of organic origin is oxidised to nitrate ions (NO3

�). The first step (a)involves the ammonia monooxygenase (AMO) enzyme in Crenarchaeota and bacteriathat convert ammonia into hydroxylamine (NH2OH). (b) This is then processed bybacteria and possibly archaea into nitrite ions (NO2

�). (c) Other specialised bacteriacomplete nitrification by converting nitrite to nitrate. (d) Nitrate is then assimilated intoorganic matter during primary production or denitrified by other organisms to formnitrogen some of which escapes to the atmosphere. (e) Anammox bacteria can alsoconvert ammonia and nitrite into nitrogen for release to the atmosphere. (f ) Nitrogen isfixed by specialised organisms and converted to ammonia that is converted into organicmatter or oxidised as the cycle continues. The organic sources on land also apply tothe ocean and additional sources to the ocean are contributed from rivers and theatmosphere. Figure modified from Schleper (2008).


important tropical/subtropical cyanobacteria, Trichodesmium and a numberof groups of unicellular cyanobacteria (Capone et al., 2005; Stal, 2009). Inaddition, endosymbiotic associations between some diatoms and cyanobac-teria (Gomez et al., 2005) and some bacteria ( Johnston et al., 2005) may alsofix N2. ‘A new paradigm for nitrogen fixation’ (Arrigo, 2005; Karl, 2007)means that it is now recognised that the oceans contribute at least 50%, andlikely more, to global fixation than the minor contribution previouslybelieved (Stal, 2009). This percentage is likely to increase in the future astropical and subtropical waters expand, with considerable consequences forclimate through changes in nutrient ratios (stochiometry), plankton com-munities and the biological pump. Other phytoplankton groups utilise arange of reduced and oxidised forms of nitrogen (NH4

þ, NO2�, NO3

� plusorganic nitrogen). The concentration and spatial and temporal variability ofthese N forms is a key global determinant of phytoplankton biomass andrates of primary production. In energetic terms, when available, ammonium(NH4

þ) is the preferred nitrogen source. Ammonium is also the primaryform of N used by phytoplankton in the large regions of the ocean (subjectto permanent stratification) where recycling-based communities prevail andthe phytoplankton often have higher surface area-to-volume ratios. Otherimportant breakthroughs in understanding the nitrogen cycle (Fig. 1.11)include the recognition that Archaea (Crenarchaeota) as well as bacteria arecapable of oxidising ammonia and the role of the Anammox process indelivering nitrogen gas to the atmosphere (see Section 3.2).

Conversion of dissolved ammonia, nitrite and nitrate to particulate formsagainst the reverse process of denitrification appear to be generally inbalance within a 3000-year time period. There are, however, opposingviews at present on the size and relative balance between biological nitrogenfixation and denitrification in the ocean. Yool et al. (2007), for example,have shown that about half of the global uptake of nitrate by marinephytoplankton is produced by denitrification. On the basis of their resultsthey suggest that the biological pump may be less efficient than previouslyestimated. Note the additional complication, by reference to Section 3.2earlier, of the important discovery of the new Anammox denitrificationprocess and the use of NH4 as an energy source by Archaea, especially in thesurface ocean. An increased contribution to the nitrogen pool due toutilisation of N by cyanobacteria and bacteria is thought unlikely as iron isalso needed in this process (Falkowski et al., 1998).

The extent to which the availability of nitrogen will affect the ability ofthe biosphere to absorb increasing levels of atmospheric CO2 in the future isnot clear (Gruber and Galloway, 2008). There has been a large increase inthe anthropogenic input of nitrogen to the environment deriving fromindustrial processes fertilisers, animal husbandry, sewage and fossil fuelemissions. In the marine environment, many of these inputs have causedproblems in coastal waters in the form of eutrophication. Anthropogenic


emissions contribute to the build-up of greenhouse gases such as nitrousoxide, (N2O) and nitrogen trifluoride (NF3) (Forster et al., 2007; Pratherand Hsu, 2008) as well as contributing to a loss of ozone in the atmosphere.On a global scale the deposition in the ocean of anthropogenic biologicallyavailable nitrogen from atmospheric sources is likely to have stimulatedphytoplankton growth (Duce et al., 2008). The total input of these anthro-pogenic sources at 160 Tg N year�1 accounts for more than the naturalfixation of nitrogen on land (110 Tg N year�1) or in the ocean (Gruber andGalloway, 2008), but not all may be available for marine photosynthesis. Anobserved parallel development of trends in atmospheric CO2, N2O andtemperature over the last 250 years (Fig. 1.12) with good evidence forparallel changes in the Pleistocene (Fluckiger et al., 2004) emphasises theclose relationship between these two gases and their links to climate change.

A recent study has shown that cell division rate doubled and theRedfield ratios (106C/16N/1P) C/P and N/P (not C/N) of the planktoniccyanobacteria Trichodesmium changed markedly, as a response to increasinglevels of CO2 leading to an enhancement of nitrification and potentialenhanced CO2 drawdown (Barcelos e Ramos et al., 2007). It is believedunlikely, but if this proved to be a selective response in phytoplankton, ingeneral it would establish a strong negative feedback to climate, providedthe produced POC sank below the mixed layer.

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Figure 1.12 Atmospheric concentrations of N2O, CO2 and CH4 over the last 2000years showing the close parallel nature of their trends. From Forster et al. (2007) IPCCAR4 WG l.


3.9.2. The oceanic phosphorus cyclePhosphorus is an essential nutrient in primary production (Froelich et al.,1982) and is used as an energy carrier (in ATP/ADP molecules) in allorganisms (Follmi, 1996). The marine phosphorus cycle involves uptakeand assimilation of phosphate by plankton in surface waters, its release backinto the water by processes such as cell lysis and bacterial degradation and itssubsequent transport to the deep ocean via sinking of released organicmaterial, and return to the upper ocean by slow mixing (diffusion, up-and downwelling) and circulation (Tyrrell, 1999; Williams and Follows,2003). There has been a considerable debate on the influence of P and N onocean productivity during glacial cycles and consequently on atmosphericconcentrations of CO2. Recent results from deep sea cores (Tamburini andFollmi, 2009) suggest that burial of reactive P in glacial conditions isreduced and that richer P conditions characterise glacial terminations,both with a possible feedback to the carbon cycle. Models of phosphatecycling by Tyrrell (1999) indicate that while in the steady-state nitrate ismore deficient than phosphate, external inputs of P control the longer termprimary production of the global ocean. Sources of P in the oceans aredominated by river input with circa 90% of all inputs consisting of organicdebris. Outside coastal waters, P concentrations in the euphotic zone aredependent on rates of upwelling and diffusion from deep water in the ocean’sinterior as well as the concentration of P in the source water (Froelich et al.,1982). In HNLC (high nutrient low chlorophyll) and upwelling regions, PO4

is in plentiful supply, but generally not elsewhere, except during the winter intemperate and sub-polar latitudes. An exception is the eastern Mediterraneanwhere a high nitrate-to-phosphate ratio has been observed resulting inphosphate limitation of the primary production (Krom et al., 2004; Reeset al., 2006). A similar situation has been described from Station ALOHA inthe northwest Pacific sub-polar gyre where N2 fixation is possibly increasingover time due to climate-coupled changes, leading to an intensification of Pstress in this P-limited ecosystem (Karl, 2007).

3.9.3. The oceanic silicon cycleIn the oceans silicon (Si) is primarily in the dissolved inorganic oxidisedform silicic acid. When silicic acid is available, diatoms dominate phyto-plankton communities and are important because of their high sinking rates,in the export of carbon via the Biological pump. The proportions of silicateversus carbonate sedimentation have been implicated as a factor in thereduction of atmospheric CO2 concentrations by �100 ppm in glacialperiods. Work by Kohfeld et al. (2005), however, suggests that increasedgrowth of diatoms and other biological processes could account for no morethan 50% of the drawdown. Over the last 40 million years since the LateOligocene silica-rich upwelling regions have been increasing as the planet


cooled, a trend that is closely associated with the evolution of whales(Broecker and Kunzig, 2008); implications for whales and climate in awarming planet are unclear.

The supply of silicic acid to the upper illuminated layer derives fromweathering, riverine fluxes and upwelling from the ocean interior(Falkowski et al., 1998). Concentrations of silicic acid in water are highestin the Northern Hemisphere, off major river basins, in Subarctic Seas andthe Arctic Ocean, but also in the Southern Ocean where silica wells up fromdeeper water and is carried northwards by the ACC. In contrast, in thecentral ocean gyres levels of silicic acid are very low. This distribution isreflected in the distribution of the production of biogenic silicon (opal) asdiatoms and radiolaria (Fig. 1.13). As a contrast to the Northern Hemi-sphere, more than two-thirds of the global sedimented silica is depositedsouth of the Polar Front under the ACC (Smith et al., 2003; Wischmeyeret al., 2003). In a modelling study of the silicon cycle, Yool and Tyrrell(2003) show that the ecological success of diatoms varies inversely with theconcentration of silicic acid and thus through a negative feedback controlsthe cycle. However, total primary production is shown to be controlled byphosphate and not silicic acid availability.

0�

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Figure 1.13 Annual production of biogenic silicon in the oceans (g m�2 year�1).Source www.radiolaria.org.


http://www.radiolaria.org

3.9.4. Iron and dustIron is an essential element for all organisms because it is needed in a widerange of enzyme systems for processes including photosynthesis, respirationand nitrogen fixation. In HNLC regions, iron deficiency reduces growthrates, cellular chlorophyll levels, net CO2 fixation and active uptake of CO2

and HCO3� (Schulz et al., 2007). The late John Martin helped to focus

attention on the importance of iron supply to the Southern Ocean byhighlighting that this was higher in the past, which could account for asubstantial proportion of the 80-ppm drawdown in atmospheric CO2

observed between glacial and interglacial periods (Martin, 1990). In thecontemporary ocean, iron limits the growth of phytoplankton over broadareas where macronutrient concentrations remain high (Boyd et al., 2000).These include the so-called HNLC regions of the Southern Ocean, as wellas parts of the North and the Equatorial Pacific.

Iron is supplied to the oceans with soil alumino-silicates in riverineinputs, upwelling and to the open ocean via aeolian inputs of dust thatoriginate from various deserts, with lesser inputs from volcanic, anthropo-genic and meteoric sources. Drought conditions as well as changes in landuse and agricultural practice can lead to increased dust emissions. Dustinputs are particularly important for the vast open ocean regions and a keyconcern is that arid regions are very sensitive to climate change and this hasthe potential to change ocean productivity and global climate in turn( Jickells et al., 2005). However, aside from the issue of climate change, arecent study by Wagener et al. (2008) underlines the need for in-depthcomparisons of model and in situ data and a re-evaluation of predictions ofpresent and past dust inputs. They examined aerosol deposition of iron totwo remote oceanic areas in the Southern Hemisphere and concluded thatcurrent dust deposition models overestimated iron inputs and that dustdeposition is not the dominant source of iron for this large and importantHNLC region.

3.10. Other gases and aerosols

3.10.1. Methane, nitrous oxide and halocarbonsMan-made (livestock, arable farming, landfill, industry) and natural emis-sions from terrestrial environments and the sea contribute to the atmo-spheric burden of methane (CH4), nitrous oxide (N2O) and a suite ofvolatile halocarbons (compounds containing chlorine, iodine and/or bro-mine). Methane and N2O are potent greenhouse gases with global warmingpotentials about 21 and 310 times that of CO2. Methane oxidises into CO2,and continues to have a long-term global warming effect. The halocarbongases are key sea-to-air transfer compounds for the global biogeochemicalcycles of bromine, chlorine and iodine.


Global net methane emissions from oceans and freshwaters are estimatedat 10 Tg per annum. While this is only about 2% of the total global source,the marine methane cycle is nevertheless considered highly significantbecause the concomitant anaerobic methane oxidation sink ensures thatthe net flux of methane to the air is a minor fraction of the total methaneproduced (Reeburgh, 2007). Methane is produced and consumed in sea-water via microbial reactions, and also arises from geological sources includ-ing methane clathrates, hydrothermal vents, cold seeps, mud volcanoes andanaerobic methanogenesis. Considerable regional variability is evident overthe ocean that has much lower levels than over the land (Fig. 1.14). TheBlack Sea stands out for having high surface methane concentrations andfluxes. Until recently, methane production was thought to require strictlyanaerobic conditions. The origin of the methane distributed in oxygenatedsurface ocean waters was considered a paradox, and it was assumed thatmethane production was limited to anoxic environments in digestive tractsand faecal pellets. However, recently Karl et al. (2008) have shown thatmethane is a by-product of the aerobic microbial breakdown of methylpho-sphonate (CH5O3P), and they suggest that marine methane productioncould increase with global warming-induced increases in stratification andnutrient limitation.

The oceans, particularly the sediments of continental slope regions, areestimated to harbour 2000 Gt of carbon as methane gas and icy solids knownas methane clathrates or hydrates (Buffett and Archer, 2004). It has beensuggested that catastrophic release of methane from this store caused abrupt

Surface methane (ppmv)

1.6 1.66 1.72 1.78 1.84

Figure 1.14 Global map of surface methane concentrations. From NASA: Credit:GMAO Chemical Forecasts and GEOS GHEM NRT Simulations for ICARTT.


climate warming in the past and there are concerns that a warmer futureclimate could destabilise this reservoir and trigger further warming (seeSection 6).

N2O production is enhanced in areas where oxygen levels are depletedand nitrate fuels denitrification. These conditions are combined in upwell-ing areas and it has been suggested that the global expansion of hypoxic/anoxic zones (Chan et al., 2008) is leading to increased production of N2Oand the accumulation of this radiatively active trace gas in the atmosphere(Naqvi et al., 2000).

If the mid-water depths of the ocean are shut off from ocean ventilation,CH4 and N2O will be increasingly produced and as a gas will bubble uptowards the surface. An increase of even a small amount of N2O enteringthe atmosphere could have large implications. The possible role that anincrease in sea areas subject to hypoxia/anoxia (as in the Black and Balticseas or in upwelling regions such as the Arabian Sea) might play as acontribution to climate change is not clear.

Some halocarbons are man-made, but many are derived from seaweeds,microalgae and/or extracellular photochemical reactions. They break downphotochemically in the troposphere to form halogen radicals which destroyozone and produce halogen oxides. Ozone is a major precursor for hydroxyl(OH) radicals and its removal from the system impairs the atmosphericcleansing of pollutants including methane. It has been suggested that BrOinteracts with DMS (see below) reducing its cooling effect on climate viaaerosol production (von Glasow et al., 2004) whereas iodine oxides con-tribute to the formation and growth of marine aerosol (O’Dowd andLeeuw, 2007). The deep ocean may be an important source region forhalocarbons and other gases, but little work has been done in this area.

3.10.2. AerosolsThe burning of fossil fuels, including in shipping, releases SO2 to the airwhere it is oxidised to form sulphate aerosol. This acts to cool the climatedirectly, because the aerosol particles reflect solar radiation back into space,and indirectly as sulphate particles can also act as condensation nucleiinfluencing cloud formation and the radiative properties of clouds. Naturalemissions of sulphur are dominated by marine biological production ofdimethylsulphide [DMS; (CH3)2S] with sporadic minor emissions fromvolcanoes. Other sources of marine aerosol such as sea salt, other biogenicgases (e.g. iodinated gases and isoprene) or organic matter produced inphytoplankton blooms may also serve as cloud concentration nuclei(CCN). The combined response of all marine aerosol sources as a potentialfeedback to climate change is still unclear.

Between 15 and 33 � 1012 g of the volatile sulphur trace gas DMS areemitted annually from the ocean to the atmosphere. This is equivalent to�27–60% of the estimated flux of sulphur from anthropogenic sources and


makes DMS a significant compound in the global sulphur cycle (Kettle andAndreae, 2000), especially when set against the evidence that man-madeemissions in many areas have declined since 1989 (Andreae et al., 2005).Using a modelling approach, Vallina et al. (2007) estimated that globally theDMS contribution to CCN was �30% of the total CCN numbers deter-mined from satellite data.

In the oceans, DMS is derived from dimethylsulphoniopropionate[(CH3)2S

þH2CH2COO�; DMSP] that is produced by some marine phy-toplankton, especially the Prymnesiophyceae and Dinophyceae (Stefelset al., 2007). Release of DMSP and DMS to seawater occurs duringphytoplankton cell death, grazing and viral mortality and may be passivelyand/or actively released. Most is utilised by bacteria or oxidised via photo-chemical processes and the amount of DMS emitted to the air is a fewpercent of the total DMSP and DMS pool. Recent work suggests that UVlight enhances DMS production by phytoplankton and decreases bacterialturnover of DMSP. Climate change could impact on DMS production andemissions via changes in wind intensity, ocean circulation, light field, therelative abundance of DMSP-rich and DMSP-poor phytoplankton types,levels of marine productivity and food web functioning.

It is well accepted that sulphate aerosols arising from volcanic and fossilfuel-derived sulphur emissions influence the climate by reducing radiativeforcing by direct reflection of radiation back into space and through CCN(Andreae et al., 2005), but as yet modelling studies have not reached trueconsensus on whether DMS has a significant influence on the Earth’sclimate. Gunson et al. (2006) used a coupled ocean–atmosphere generalcirculation model with an atmospheric sulphur cycle and tested how climatemight respond to altered DMS emissions. They altered DMS emissionsto half the control simulation value and this increased radiative forcing by3 W m�2 and surface air temperature by 1.6 �C. Using a 2� CO2 scenario,Bopp et al. (2004) estimated a 3% increase in global DMS flux that wouldgive a minor negative feedback of about �0.05 W m�2, but the regionalvariation in the model output was large (�15% to 30%) and a substantialradiative forcing of �1.5 W m�2 was suggested for 40–50�S in summer.Kloster et al. (2007) also found large regional-scale variability and theirmodels predicted a 10% reduction in the global annual mean DMS seasurface concentration and the DMS flux for 2061–2090 compared to 1861–1890, but the atmospheric DMS burden was reduced by only 3% becauseDMS would have a longer lifetime in air with a warmer climate. Again theSouthern Ocean was identified as a vulnerable region, with DMSlevels reduced by 40% and DMS concentrations were also reduced in themid- and low-latitude regions because of nutrient limitation associated withincreased stratification.



� Marine methane production by plankton could increase with globalwarming-induced increases in stratification and nutrient limitation.

� There has been a pronounced expansion of the large low productivityregions of the world (subtropical gyres), which already far exceeds thepredictions of models.

� Extrapolation on the basis of projected changes in sea surface temperatureand nutrients could lead to a substantial reduction in the productivity of theoceans and the efficiency of the Biological pump over the next 100 years.

� The role of microbes in climate and climate change is crucially important,but little understood and poorly quantified. Developing an understandingof their contribution to biogeochemical and nutrient cycling and micro-bial diversity is a major challenge for the future.

� Shifts from a diatom to a flagellate dominated system in temperatelatitudes and increased microbial remineralisation in a warming oceanare expected to lead to a less efficient Biological pump.

� If these changes caused a reduction in the net input of atmospheric CO2

to the oceans, there would be a strong positive feedback to climatechange.

� Large changes have been observed in marine ecosystems in many differ-ent parts of the oceans; when seen together they indicate that they arereacting beyond what might be expected from interannual variability.

� Modelling has shown that changes in ecosystem structure (e.g. types ofplankton, physiology, light absorption, food web structure) and exportefficiency may be as or more important to understanding interactions withclimate than changes in bulk-integrated satellite measures of chlorophyll.The global observing systems needed to measure such variability arerudimentary and concentrated in the Northern Hemisphere at present.

� The oceans are a major producer of sulphur particulates which seed cloudformation. Changes in the production of all aerosols as seas warm hasimplications for global warming, but the net effect is unclear.

� Mismatch between trophic levels and functional groups has implicationsfor ocean–climate interactions, including CO2 drawdown.

4. The Solubility, Biological and Continental

Shelf Carbon Pumps

4.1. The ocean carbon cycle

The carbon cycle is crucial to climate because it governs the amount of theimportant greenhouse gases such as CO2 and CH4 in the atmosphere.Methane provides a continuous, transitory supplement as it is slowly


converted to CO2 in the atmosphere over approximately a 10-year period.The oceans play a crucial role in this cycle as the main reservoir for carbon(32,000 Pg estimated as stored in the deep ocean), other than the long-termstorage of carbon in the Earth’s crust. Feedbacks from the ocean carboncycle and relevant processes are discussed Denman et al. (2007). To quotefrom the IPCC report, ‘‘small changes in the large ocean carbon reservoircan induce significant changes in atmospheric CO2 concentration’’ and theoceans can also buffer ‘‘perturbations in atmospheric pCO2’’.

In the pre-industrial Holocene there was an approximate time- andspace-averaged equilibrium between CO2 in the atmosphere and dissolvedin the surface ocean. The regional differences in partial pressure in seawaterCO2 are due to interactions between biological, chemical and physicalprocesses. Anthropogenic CO2 release to the atmosphere has resulted in anet flux of CO2 from the atmosphere to the ocean that occurred on top ofan already active oceanic carbon cycle (Fig. 1.15). Anthropogenic CO2 isabsorbed into the water by direct solubilisation, with the dissolved carbonsubsequently distributed to depth by mixing and ocean currents.

The contribution that biology makes is still far from understood. Forexample, it is not known if CO2 drawdown increases if plankton are moreproductive and/or if functional groups such as diatoms are more dominant.Introduced CO2 reacts with water to produce carbonic acid. Subsequentre-equilibration of the dissolved inorganic carbon (DIC) system results inan increase in the concentration of CO2 and carbonic acid, a smallerproportionate (but greater in absolute terms) increase in bicarbonateions, and a decrease in carbonate ions and pH. There is a marked differ-ence in the concentration of DIC between the deep ocean and the mixedlayer at �500 m (Raven and Falkowski, 1999; Fig. 1.16) reflecting netautotrophy of surface waters and net heterotrophy in deep waters thatresults in a huge reservoir of DIC in the deep ocean. The DIC istransported, directly or as dissolved organic (DOC), particulate organic(POC) or inorganic (PIC) carbon, to the deep ocean by four processescollectively known as ‘carbon pumps’. In the upwelling regions of theworld, cold DIC-rich waters from the deep ocean recirculate to thesurface where CO2 outgases to the atmosphere to complete the oceancarbon cycle.

The four ‘carbon pumps’ (Solubility, Biological, Continental Shelf andCarbonate Counter) sequester CO2, largely as DIC at the surface of theocean, with additional transfer through the intermediarie POC, DOC andCaCO3 PIC to the deep ocean reservoir that is mostly comprised of DIC.To some extent the Continental Shelf and Carbonate Counter pumps canbe considered as subsidiary versions of the Biological pump. The CarbonateCounter pump will be covered more fully in Section 5.


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Figure 1.15 Climatological mean distribution of CO2 flux (g C m�2 month�1)between the air and sea or vice versa for February (A) and August (B) in the referenceyear 2000. The wind speed data are from the 1979–2005 NCEP/DOE AMIP-IIReanalysis, and the gas transfer coefficient is computed using a (wind speed) squareddependence. Positive values (yellow–orange–red) indicate sea-to-air fluxes, and nega-tive values (blue–magenta) indicate air-to-sea fluxes. Ice field data are from NCEP/DOE-2 Reanalysis Data (2005). An annual flux of 1.4� 0.7 Pg C year�1 is obtained forthe global ocean by a summation of 12 monthly maps that were produced fromapproximately 12 million measurements. Figure from Takahashi et al. (2009).


4.2. Ocean carbon pumps

4.2.1. Solubility pumpThis pump operates most efficiently at low temperatures where the uptakeof CO2 as DIC is much higher due to increased solubility and at highlatitudes where water downwells. This process only occurs in the sub-polarseas of the North Atlantic (not in the North Pacific) and in the SouthernOcean. When ice is formed in these polar regions, the released dense brinessink rapidly carrying with them DIC-rich water. Dense water may also beformed below pancake ice, for example in the Greenland Sea or in Arcticpolynyas (a polynya is a large area of open water surrounded by sea-ice).A similar process takes place over the Arctic shelf as new ice is formed each

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Figure 1.16 Vertical profiles of dissolved inorganic carbon (DIC) in the ocean. CurveA is a theoretical profile from prior to the industrial revolution with an atmosphericCO2 concentration of 280 ppm. Curve B is a similar calculated profile for the year 1995,with atmospheric CO2 at 360 ppm. The difference between these two curves is theintegrated oceanic uptake of CO2 from anthropogenic emissions since the beginning ofthe industrial revolution, assuming that biological processes have been in steady state(i.e. not materially affected by the net influx of CO2). Curve C is a representativeprofile of measured DIC from the central Pacific Ocean. The difference between curvesC and B is the contribution of biological processes to the uptake of CO2 in the steadystate (i.e. the contribution of the ‘Biological pump’ to the DIC pool). Figure redrawnfrom Raven and Falkowski (1999).


year with the carbon-rich brines flowing along the bottom and over theshelf edge into the deep ocean. In such regions of deep water formation,carbon is delivered at high concentrations to the deep ocean where the deepcirculation (MOC) carries it around the world and keeps it out of contactwith the atmosphere for up to 1000 years. It has been estimated that about25–50% of the steep vertical gradient in DIC (Fig. 1.16) is contributed bythis pump. In regions where subtropical mode and intermediate waters areformed (see Section 2), usually by wintertime convective mixing, uptake ofCO2 by the Solubility pump provides an intermediate (up to decades)carbon sink (Bates et al., 2002; Sabine et al., 2004a). Sabine et al. (2004a)show, for example, that 40% of the global ocean inventory of anthropogenicCO2 is found south of 30�S and most of that is stored in intermediate andmode water.

The fact that CO2 solubility reduces with higher temperatures andsalinity is of key relevance to climate change. It is estimated that the Solubilitypump has become less efficient in the northern North Atlantic (Sabine et al.,2004a) due to the warmer temperatures that have occurred over thelast decade or more and supported by the observed reduction in the densityof the deep water found in the Norwegian Sea. A similar reduction inuptake has recently been described for the shallower Japan Sea (Park et al.,2008).

Changes over the last few decades in the large-scale atmospheric circu-lation of the Southern Hemisphere (Thompson and Solomon, 2002) arereflected in the leading mode of Southern Hemisphere climate variability,the Southern Annular Mode (SAM; Thompson and Wallace, 2000). Inter-annual variability and trends in the SAM also have been shown to drivesubstantial variability in ocean circulation with a poleward shift and intensi-fication of westerly winds, in upper-ocean biology, and in the uptake andrelease of CO2 to and from the Southern Ocean (Lovenduski and Gruber,2005; Lovenduski et al., 2007, 2008). Model simulations suggest that thetrend towards more positive SAM conditions has led to a reduction in thestrength of the Southern Ocean CO2 sink (Lenton and Matear, 2007;Lovenduski et al., 2007, 2008) by anomalous outgassing due to an increasein upwelling. This hypothesis has been supported by the inversion ofatmospheric CO2 data (Le Quere et al., 2007), but remains a subject ofintense discussion. While doubts have been raised about the sensitivity ofthe inversion method to the choice of stations used (Law et al., 2008), of theocean model to the forcing used (Law et al., 2008; Lovenduski et al., 2008),and whether the ‘saturation’ of the Southern Ocean sink is likely tocontinue in the future (Zickfeld et al., 2008), the results, for example, LeQuere et al. (2008) underscore the potential sensitivity of the global carboncycle to changes in the circulation of the Southern Ocean. A number ofclimate change experiments reinforce this message by suggesting thatincreased greenhouse gases may, in turn, drive long-term changes towards


a more positive SAM state (e.g. Kushner et al., 2001; Miller et al., 2006).Thus, the Southern Ocean carbon cycle, in connection with SouthernHemisphere atmosphere–ocean circulation, winds and stratification couldgive rise to a positive feedback that would enhance global warming(Friedlingstein, 2008; Lovenduski and Ito, 2009).

4.2.2. Biological pumpThrough this pump CO2 fixed by photosynthesis is transferred to the deepocean primarily as dead organisms (including the organic skeletal), faecalmaterial (POC), and carbonate skeletons (PIC; note that calcification pro-duces CO2). This results in sequestration (storage) of carbon for periods ofdecades to centuries (depending on the depth of remineralisation) or evenmore permanently in the sediments. Longer-term sequestration may be inthe form of organic matter, such as the type of material that is ultimately thesource of oil and natural gas. A small proportion of the total annualproduction of the plankton ends up in the deep ocean, but there is strongevidence to suggest that this pump contributes importantly to the differentlevels of atmospheric CO2 found between glacial and interglacial periods(Raven and Falkowski, 1999). Plankton can act as ballast for the export ofcarbon to the deep ocean with the organisms that have mineralised skeletalparts playing an important role. Siliceous diatoms and calcareous foraminif-era, coccolithophores and molluscan pteropods and cephalopods are impor-tant ballast organisms. Other forms of settling occur via faecal pellets oraggregates and gelatinous plankton. Exopolysaccharide aggregation canincrease sinking POC and PIC at a given overall density by decreasing thesurface area per unit volume (Engel et al., 2004) and terrigenous materialssuch as clay may also contribute (Klaas and Archer, 2002). It has even beensuggested that POC fluxes may drive mineral fluxes rather than vice versa(Passow, 2004). Although there is much data on the rate of organic carbonsinking in the Biological pump and its determinants, there is still uncertaintyas to the nature of a predictive model (Boyd and Trull, 2007; De La Rochaand Passow, 2007; Passow, 2004).

To predict future CO2 concentrations in the atmosphere there is a needfor a much improved understanding of the way that the Biological pumpvaries both geographically and temporally and the effects on the pump ofchanges in temperature, ocean circulation and ocean chemistry (e.g. acidi-fication due to increased CO2). It is not known, for example, if earlierspring blooms or higher Fe input into HNLC areas (e.g. the SouthernOcean) will affect carbon drawdown, or if CO2 drawdown will reduceduring prolonged periods of recycled production due to longer summers,nutrient limitation and expansion of the subtropics (e.g. Bopp et al., 2001).Recent studies, for example, van Hoof et al. (2008) indicate that naturaldecadal variability in atmospheric concentrations of CO2 as measured fromleaf stomata in the pre-industrial period from 1000 to 1500 AD were more


pronounced and faster than proposed in IPCC AR4. They suggest that thevariability is driven by oceanic perturbations in temperature and salinity.The extent to which the oceans may contribute to such ‘short-term’variability is not known.

4.2.3. Continental Shelf pumpContinental shelf seas comprise �7% of the surface ocean but provide adisproportionately large fraction (15–30%) of oceanic primary production(Bozec et al., 2005). Thus these regions have a strong impact on the globalcarbon cycle and provide a net flux to the deep ocean reservoir calculated at�1 Pg C year�1 by Tsunogai et al. (1999).

Cold, denser water with lower pCO2 is formed in many coastal shelfseawaters at temperate and sub-polar latitudes during the colder periods ofthe year. As a consequence these are regions of net uptake of atmosphericCO2 by solubilisation that may be enhanced by higher levels of phytoplank-ton production. Shelf seas may be totally mixed throughout the year or havea pycnocline/thermocline that separates stratified waters from the mixedwaters below that are isolated from the atmosphere. A range of complexprocesses transfer DIC through the pycnocline via the intermediaries POC,DOC and PIC. DIC is then transferred by isopycnal mixing (advection anddiffusion) off the shelf to the deep ocean. The transfer to the deep oceanmay continue even while the surface layer is isolated by stratification.Material may also be transferred to the deep ocean as POC, DOC andPIC via nepheloid layers and by transport of organic material as fluff alongthe bottom. In strongly mixed waters as in the southern North Sea (Bozecet al., 2005), the whole water column is in regular contact with theatmosphere and bacterial regeneration ensures that these regions are gener-ally net sources of CO2, especially if they are enriched with nutrients.

During stratified summer conditions, carbon export to the mixed watersbelow the pycnocline is probably reduced and so higher temperatures andthe resultant stronger stratification will likely feedback to a reduced exportof CO2. It is also estimated that higher nutrient input to these regions,especially in eutrophicated areas, will contribute to increased CO2 draw-down if more nutrients are available. Major works to improve water andsewage treatment in Europe, for example, will thus reduce CO2 drawdownby the Continental Shelf pump.

4.2.4. Carbonate Counter pumpThis pump operates in parallel with the (organic carbon) Biological pumpand covers the production and dissolution of marine organisms with bodyparts made up of inorganic CaCO3. The phytoplankton (coccolithophores)and zooplankton (foraminifera, pteropods, planktonic larval stages of ben-thic organisms) and some benthic algae plus many benthic animals,


including corals, produce body parts made of calcite, aragonite or Mgcarbonates. Production of carbonates leads to CO2 release (see Section 5).

4.3. Role of the four ocean carbon pumps

Some idea of the importance of these carbon pumps can be gauged from acomparison of the present estimated transfer of carbon by the Biologicalpump to the deep ocean (see IPCC AR4 WG 1, 2007, Fig. 7.3). A netreduction of only 10% (1.1 Pg year�1) would virtually counterbalance thecurrent estimated net input (1.4 Pg year�1) (Takahashi et al., 2009) ofatmospheric CO2 to the ocean. The relative contributions and importanceof the Solubility, Biological, Continental Shelf and Carbonate Counterpumps and their geographical and temporal variability is poorly constrainedand needs to be better defined to facilitate modelling efforts. In particular,the importance of mesoscale variability in the carbon pumps is poorlyunderstood at present.

4.4. Species biodiversity and functional groups

The diversity of species present in the plankton – from the viruses, bacteriaand archaea to the largest zooplankton and fish – is immense and withmodern genetic studies the true diversity is expected to be even larger. Inaddition to this genetic diversity there is also a diversity of function aspertains to the role a species or group of species plays in the ecosystem,including the contribution to carbon turnover by the biological pump.Over long time scales the relative dominance of functional groups isthought to have modulated carbon cycling between the ocean and atmo-sphere (Falkowski et al., 2003).

Plankton assemblages that characterise particular biogeochemical func-tions are important: in the production, turnover and release of radiativelyactive gases and their exchange with the atmosphere (e.g. CO2, DMS), inthe relative proportion of organic material that is respired near the surface oris sequestered to the deep ocean, and in the cycles of major elements such asnitrogen and silica (Boyd and Doney, 2002, Jin et al., 2006). The concept offunctional groups is particularly applied in models to simulate the presentand future role (in a changing environment) of biology and to estimate thecontribution of organisms to global-scale element cycles (Le Quere et al.,2005). Changes in the relative importance of different functional groups inthe plankton can strongly impact the Biological pump; for example, relativefluxes of diatoms versus calcareous plankton have been implicated as one ofthe causes for the changes in CO2 between glacial and interglacial periods.The changes are attributed to substantial differences between the periods innutrient inputs to the ocean from dust and rivers, sourced especially during


glacial times from loess and coastal erosion (Harrison, 2000; Treguer andPondaven, 2000).

4.4.1. Changes in the benthos and sea bottom sedimentBenthic organisms and bottom sediments also contribute to the oceaniccarbon cycle. Animals with carbonate skeletal systems live over a hugeshelf area. It has been estimated (Andersson et al., 2005) that coastal oceansurface water carbonate saturation state will decrease by 46% by 2100 due toacidification, leading to a decrease of 42% over the same period in thebiogenic production of CaCO3. Their modelling results also show thatthe carbonate saturation state of pore water in sediment will decrease inthe future due to a greater deposition of both land derived, recycled andlocally produced organic matter. This will lead to an increased dissolution ofcarbonate minerals in the sediments. The future reintroduction of carbonfrom sediments on the sea floor to seawater due to global warmingwill have aconsiderable impact on the atmosphere. Warming of shelf seas will changethe rates of microbial production and thus gas exchange and nutrient sup-ply—but potential impacts are largely unknown. Changes in the composi-tion, biomass and production of the benthos of both shelf seas and the deepoceans are also likely to be important—but again the impacts are unknown.

4.5. Global and regional information

For modelling evaluation, validation and other studies of the processesinvolved in the ocean carbon cycle comprehensive information is neededon the spatial and temporal coverage of key parameters over a long period(Boyd and Trull, 2007; Le Quere et al., 2005). Information is available formean fluxes of CO2 (Takahashi et al., 2002, 2009) and DMS (Kettle andAndreae, 2000; Kettle et al., 1999), but there is limited temporal informa-tion. Global-scale observations of chlorophyll did not begin until 1978 withthe operation of satellite measurements by the CZCS. SeaWiFS satelliteshave provided a global coverage of chlorophyll since 1997, although this isconstrained by cloud cover in many parts of the world so that the coverage ispiecemeal in places and at certain times of the year. New approaches toprocessing the multi-spectral characteristics of SeaWiFS data means thatsome individual plankton groups such as cyanobacteria and diatoms mayalso be estimated on a global scale (Raitsos et al., 2008). High reflectancefrom coccoliths released into the water after coccolithophore blooms sig-nifies that these phytoplankton can in part be determined on a global scalefrom satellites (Brown and Yoder, 1994; Iglesias-Rodriguez et al., 2008).Nonetheless, satellite information is inadequate to clarify how these post-bloom events relate to carbon export. Also, the most important calcifyingspecies are restricted to deeper water in the subtropics that cannot bedetected from satellites. In situ data to calibrate the satellite measurements


of phytoplankton are limited, and satellites provide no information onzooplankton. The Continuous Plankton Recorder surveys in the NorthAtlantic (Richardson et al., 2006) and Southern Oceans (Hosie et al., 2003)provide the only comprehensive coverage of selected phytoplankton classesand zooplankton diversity and abundance at monthly and regional, but notglobal scales.

Global information is available from more than 100 sediment trappingexperiments (Francois et al., 2002; Klaas and Archer, 2002, Boyd and Trull,2007) used to determine downward fluxes, regeneration and detrital com-position at single-site moorings throughout the ocean. Trap samplingmethodologies have not been standardised, so there are problems of inter-pretation. Furthermore, trap coverage is very restricted, especially on con-tinental shelves. A comparison between modelled estimates of export fluxbetween the last glacial maximum and the present, with superimposedmeasurements from satellites is shown in Fig. 1.17. This figure furtheremphasises the limited spatial information that is available from sedimenttraps for some regions of the world.

It is clear that global coverage of key parameters needed to understandthe ocean carbon cycle is limited and in most cases restricted to a short timeseries. This applies particularly to routine synoptic measurements at a specieslevel of plankton that are needed for validation of satellite measurements.Finally, the modelled results in some locations are at odds with othercalculations of palaeo-productivity, for example, estimated high productiv-ity in the central Pacific during the last glacial maximum (LGM) determined

80�N LGM > CTL LGM = CTL LGM < CTL LGM ? CTL

40�N

0�N

40�S

100�E 160�W 60�W 40�E

100908070605040302010

0−10−20−30−40−50−60−70−80−90

−100

Figure 1.17 Observed (superimposed circles) and modelled changes in export at theLGM compared to the late Holocene (Bopp et al., 2003). Model results are in percent.Observations are qualitative only and indicate a higher (red), lower (blue) or similar(white) export in the LGM compared to the present day. From Le Quere et al. (2005).


from barite measurements (Paytan et al., 1996) and from organic matterdeposition (Perks and Keeling, 1998).

4.6. Ocean fertilisation

Seeding the oceans with iron as a micro-nutrient, an essential nutrient forhealthy growth of most phytoplankton species, has been proposed as amitigation measure against rising levels of atmospheric CO2. General con-cerns exist that the science behind large-scale fertilisation of the oceans bynutrients (including iron) to increase the sequestration of atmospheric CO2

by the oceans is still poorly understood. These concerns have been debatedworldwide, for example, at the Woods Hole Oceanographic Institution inSeptember 2007 (http://www.whoi.edu/page.do?pid¼14617) and at the30th meeting of the London Dumping Convention and associated LondonProtocol in December 2007. The latter meeting endorsed the concernsexpressed by scientists, declared an intention to develop international reg-ulations to oversee such activities, and advised that large-scale fertilisationschemes are currently not justified. An example of the latest scientific viewis given in a press statement by the Scientific Committee on OceanicResearch (SCOR) and the Group of Experts on the Scientific Aspects ofMarine Environmental Protection (GESAMP), which can be foundhere: http://www.imo.org/includes/blastDataOnly.asp/data_id%3D21214/INF-2.pdf. However, given the urgency of potential climate change impacts,there is a need to continue smaller scale experiments. Such experimentsshould have similar controls to those outlined by the SCOR and GESAMPstatement to determine if manipulation of the oceans might be an effectivemeans of mitigation to help reduce the effects of rising atmospheric CO2.


� If the combined efficiency of the ocean carbon pumps showed a markeddecrease, there would be a strong positive feedback on atmospheric CO2.

� It is estimated that the Solubility pump may already have become lessefficient due to warmer temperatures.

� There is strong evidence to suggest that the Biological pump contributedimportantly to the marked variation in levels of atmospheric CO2 foundbetween Pleistocene glacial and interglacial periods.

� There is limited understanding of processes and spatial and temporalvariability in the Biological pump at the present day and how it maychange in the next century and impact climate change.

� Drawdown of CO2 by the Continental Shelf pump is likely to reduceover the next century due to warmer seas, compounded by improve-ments to urban waste water treatment.


http://www.whoi.edu/page.do?pid=14617



http://www.imo.org/includes/blastDataOnly.asp/data_id%3D21214/INF-2.pdf



� Changes in the relative importance of different functional groups in theplankton may impact the Biological pump.

� Changes in the composition, biomass and production of the benthos andin associated sediments of shelf seas and the ocean are likely to be impor-tant to climate change, but the impacts are difficult to assess due tolimited data.

� Small-scale, well controlled experiments in ocean fertilisation should becontinued as long as they adopt the controls outlined by SCOR andGESAMP.

� Global and regional coverage of many of the key biological measurementsneeded to determine fluxes to the deep ocean, including spatial andtemporal variability of plankton functional groups and sediment trappingis limited.

� Lack of inclusion of some ocean carbon feedbacks in climate changemodelling may lead to underestimates of the action required to stabiliseemissions at given targets.

5. Ocean Acidification and the Carbonate Pump

The important role that the oceans play in the carbon cycle and in theuptake of atmospheric CO2 is described in the previous section. As levels ofCO2 in the atmosphere increase due to anthropogenic emissions there is alarger uptake of CO2 by the oceans across the air/sea interface. This transferleads to higher levels of carbon in surface waters and by reaction, moreacidic seawater, which is reflected in a lower pH (pH is a measure ofacidity). This process is known as ‘ocean acidification’ (Denman et al.,2007; IPCC AR4 WG 1, 2007, Box 7.3; Raven et al., 2005) and is anindependent consequence of rising levels of anthropogenic CO2 separatefrom the Greenhouse Effect. Additional acidification in some coastal watersderived from anthropogenic nitrogen and sulphur deposition from fossil fuelcombustion and agriculture may also increase in the future to furtherexacerbate the problem (Doney et al., 2007). Levels of pH have declinedat an unprecedented rate in surface seawater over the last century and arepredicted to undergo a further substantial fall by the end of this century asanthropogenic inputs of CO2 continue to rise sharply (Caldeira andWickett, 2003). This is against a background where we know that emissionsare already going up even faster than the maximum modelled projections ofIPCC (Canadell et al., 2007). There is real concern over the impact thatsuch a large, rapid and unprecedented rise in acidification might have onmarine organisms (Guinotte and Fabry, 2008; Hall-Spencer et al., 2008;ICES, 2007), but little emphasis has so far been placed on the potentialfeedbacks from acidification to climate change. Acidification may cause


positive or negative feedbacks to climate change through alterations inbiogeochemical processes, nutrient speciation, trace metal availability andecosystem biodiversity (Milliman et al., 1999; Raven et al., 2005), changesthat may be accentuated in combination with rising temperatures.

5.1. The buffering of climate change by the oceans

The oceans have taken up�40% of the anthropogenic CO2 produced fromfossil fuel burning and cement manufacture since the industrial revolution(Sabine et al., 2004a). In doing so, the ocean is essentially buffering theeffects of climate change from the even more elevated atmospheric CO2

concentrations that it would be experiencing if it was not carrying out thisimportant role. The costs of uptake of anthropogenic CO2 by the surface ofthe world’s ocean are higher bicarbonate ions, lower carbonate ions, higherhydrogen ions and reduced pH (i.e. a more acidic surface ocean). It shouldbe noted that the oceans will not become truly acidic as their pHwill remainabove 7, even with the worst case scenario, due to the intrinsic bufferingcapacity of the oceans (this is the ability of a fluid to sustain a certain pH; inthis particular case while absorbing CO2).

Anthropogenic emissions cause an increase in the partial pressure of atmo-sphericCO2 (pCO2,atm). As pCO2,atm is typically larger than its equivalent overmost of the upper mixed layer of the ocean (pCO2,ocean), there is a net flow ofCO2 from the atmosphere to the ocean. Note, however, that there is consid-erable spatial variability in relative net fluxes (see Section 4 and Fig. 1.18).During the dissolution of atmospheric CO2 in seawater, most reacts rapidlywith the water (H2O) to produce carbonic acid at the same time as loweringpH. The reaction continues to produce bicarbonate ions and carbonate ions.This chainof reactions forms the carbonate buffer system that enables theoceanto take upmuchmoreCO2 thanwould be possible from solubility alone.Onlythe remaining unreacted carbon dioxide fraction of DIC in the seawater takespart in ocean–atmosphere interactions (Denman et al., 2007; Zeebe andWolf-Gladrow, 2001). In typical seawater, the products of the reactions (Fig. 1.18)occur in the approximate proportions and ratios:

Bicarbonate (HCO �3 ) �90%

Carbonate ions (CO 2�3 ) �10%

Remaining aqueous carbon dioxide (CO2) �1%Remaining carbonic acid (H2CO3) Negligible

The sum of these various breakdown products of former atmospheric CO2

are termed DIC:

DIC ¼ ½CO2� þ ½HCO �3 � þ ½CO 2�

3 � þ ½H2CO3�


A net result of the chain of chemical reactions is that carbonate ions(CO 2�

3 ) are neutralised and reduced as a proportion of the DIC. On aglobal scale, this process means that the overall buffering capacity is reducedas levels of atmospheric CO2 rise and more hydrogen ions (Hþ) remain insolution. This will increase acidity (reduce pH). A summary explanation ofthe terms pH, DIC, carbonate buffer, carbonate saturation horizon, and amore detailed outline of the various reactions is given in Appendix 1 ofRaven et al. (2005).

In equilibrium, the increase in dissolved CO2 in the surface ocean isproportional to the atmospheric pCO2, but the increase in DIC is notproportional to pCO2,atm. This is due to the carbonate buffering capacityof seawater, which results in a smaller pH change, and can be explained bythe Revelle factor (Zeebe and Wolf-Gladrow, 2001). The Revelle factor(or, previously buffering capacity factor) ranges between 8 and 15 units,depending on temperature and pCO2. Due to the buffering capacity, anincrease in DIC caused by acidification does not correlate with a 1:1 ratio to

800

600

400

200

00 200 400 600

[CO2]atm (ppm)

[CO

32−] (mm

ol k

g−1 )

800

CO2

CO2+ H2O => HCO3−+ H+

H++ CO32−=> HCO3

−

CaCO3=> Ca2++ CO32−

(coral)

Figure 1.18 Linkages between the build-up of atmospheric CO2 and the slowing ofcoral calcification due to ocean acidification. Approximately, 25% of the CO2 emittedby humans in the period 2000–2006 was taken up by the ocean where it combined withwater to produce carbonic acid, which releases a proton that combines with a carbonateion. This decreases the concentration of carbonate, making it unavailable to marinecalcifiers such as corals. Figure from Hoegh-Guldberg et al. (2007).


the increase of atmospheric CO2 but rather�1:10. Thus, the increase to thepresent day in atmospheric CO2 of �100 ppm from the pre-industrial280 ppm represents a rise of �36% whereas DIC has only increased by3.1% (Table 1.1), approximately a 10-fold difference.

5.2. Carbonate formation

A second major process within the carbon chemistry of the ocean that has acrucial long-term role (see later section) in modulating levels of atmosphericCO2 is the production of carbonates. Three types of minerals may beformed: calcite (CaCO3), aragonite (CaCO3) and magnesium (Mg) calcites,each with different solubility characteristics defined by their saturation state(symbolised by omega, O). Since calcium (Ca2þ) is extremely abundant inseawater and as a result its concentration difficult to alter, the saturation stateof seawater with respect to calcium carbonate (O ¼ ½CO2�

3 �½Ca2þ�=Ksp) isalmost always most strongly influenced by changes in the carbonate ionconcentration. The formation of the different forms of CaCO3 (see equa-tion below) requires the presence of water that is supersaturated withcarbonate ions, as is typically found at present in most of the upper mixedlayer of the ocean.

Ca2þ þ 2HCO �3 ! CaCO3 þ CO2 þH2O

In the reaction that produces carbonates, DIC is reduced, alkalinity con-sumed, CO2 released, acidification increased and pH lowered.

Table 1.1 Changes in surface ocean inorganic carbon chemistry assumingequilibrium with atmosphere

Pre-

industrial Present

Twice

pre-

industrial

Thrice

pre-

industrial

Atmospheric CO2a 280 380 560 840

Surface ocean CO2b 9 13 19 28

Surface ocean HCO �3

b 1766 1876 1976 2070

Surface ocean CO 2�3

b 225 185 141 103

Surface ocean total

dissolved inorganic Cb

2003 2065 2136 2201

Surface ocean pH 8.18 8.07 7.92 7.77

a mmol mol�1.b mmol kg�1.Total alkalinity 2324 mmol kg�1, 18 �C (modified from Table 1 in Raven et al., 2005).


The solubility of calcium carbonate increases with pressure (depth) andwith lower temperature. In consequence each of the three minerals has adifferent depth where O changes from saturation (>1) to undersaturation(<1). Below this depth, known as the saturation horizon, the minerals willdissolve unless they are protected by an organic membrane as part of aliving organism or detrital aggregate. The depth horizon at which CaCO3

starts to disappear from the sediments is known as the lysocline, and thedepth at which it (almost) completely disappears is known as the ‘com-pensation depth’ in sediments. The lysocline and compensation depth areshallower for Mg carbonate, aragonite and calcite in that order. As theseawater saturation state of the North Pacific is lower than the NorthAtlantic, the aragonite saturation horizon almost reaches the surface in theNorth Pacific while it is at approximately 3000 m in the North Atlantic(Fig. 1.19). For the calcite form of CaCO3 the saturation horizon variesbetween less than 1000 m in the North Pacific and more than 4500 m inthe North Atlantic.

While calcification by carbonate minerals may, in favourable condi-tions, occur by precipitation, the vast majority is secreted by pelagic andbenthic organisms to form complex tests and skeletal structures. Importantcalcifying groups include the microscopic protist foraminifera, algal coc-colithophores that utilise calcite, corals and bivalves (including the pelagicpteropods with aragonitic structures and coralline algae supported by Mgcalcite). Some of these organisms play a key role in the biological andcarbonate pumps and form extensive areas of calcareous ooze on thebottom of the ocean.

In polar regions, the lysocline comes much closer to the surface and, ascarbonates dissolve more readily in cold water, polar and sub-polar watersare particularly vulnerable to future changes in ocean carbonate chemistry.There is already evidence that the saturation horizons for aragonite andcalcite are shoaling (Orr et al., 2005) and organisms such as pteropods arethus especially under threat. This is an additional vulnerability for Antarcticand Arctic waters over the next century (Fig. 1.20) to those caused directlyby climate change (Andersson et al., 2008).

There have been observations to suggest that some pelagic and benthicmarine organisms may increase their calcification rates with increasingacidification (Iglesias-Rodriguez et al., 2008; Wood et al., 2008a). How-ever, the majority of experiments, models and field observations to dateshow a deleterious impact on calcifiers from acidification. It should be notedthat the ‘sudden’ changes in pH in these short-term experiments may not berepresentative of nature and that to some extent organisms may be able toadapt to the slower longer term projected changes. This is a key area forresearch as the implications either way are important.


5.3. Carbonate dissolution

As atmospheric CO2 increases in the long-term and penetrates deeper intothe ocean due to the THC and downwelling and via the solubility,Biological, Carbonate and, ultimately, the shelf sea pumps, the lysoclinesfor calcite, aragonite and Mg calcite will shoal (come closer to the surface).Previously sedimented carbonates will start to dissolve increasing dissolved

80�N

40�N

0�

40�S

80�S

50�E 150�E 110�W 10�WModel

Aragonite saturation depth Depth(m)

Depth(m)

A

B

3500

3250

3000

2750

2500

2250

2000

1750

1500

1250

1000

750

500

250

0

80�N

40�N

0�

40�S

80�S

50�E 150�E 110�W 10�WGLODAP

3500

3250

3000

2750

2500

2250

2000

1750

1500

1250

1000

750

500

250

0

Figure 1.19 Depth of aragonite saturation horizon: lower map from measurementsrecalculated from GLODAP after Key et al. (2004) and upper map modelled calcula-tions. Figure from Gangstø et al. (2008).


carbonate alkalinity. Total alkalinity, which in terms of ocean buffer capac-ity is more important, will also increase. Thus, when the water returns tothe surface over a timescale of several centuries, further CO2 can beremoved from the atmosphere and acidification of surface waters will bepartly reversed.

In a world of increasing CO2 the dissolution of calcium carbonate can beexpressed as

CO2 þ CaCO3ðsÞ þH2O ! 2HCO �3 þ Ca2þ

Dissolution of CaCO3minerals in the surface layers of the oceans acts as afurther buffer of pH and carbonate saturation state against acidification froman increasing ocean uptake of atmospheric CO2 (Andersson et al., 2006).However, ‘‘CaCO3 dissolution has a negligible impact on atmospheric

A

C

E F

D

B

4.5

Equatorial area

Global ocean

High latitudes

80�N

40�N

40�S

80�S

80�N

40�N

40�S

80�S

80�N

40�N

40�S

80�S

50�E 150�E 110�W 10�W

0�

80�N

40�N

40�S

80�S

0�

50�E 150�E 110�W 10�W

0�

0�

80�N

40�N

40�S

80�S

0�

3.5

2.5

1.5

0.51900 1950 2000 2050 2100

1861

50�E 150�E 110�W 10�W

2050

50�E 150�E 110�W 10�W

2100

2000

50�E 150�E 110�W 10�W

2075

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

Mean omega aragonite

Figure 1.20 Saturation state with respect to aragonite of surface waters (0–100 m): (A)time series of mean O for the global ocean, the equatorial area and for high latitudes,and maps in year (B) 1861, (C) 2000, (D) 2050, (E) 2075 and (F) 2100. Figure fromGangstø et al. (2008).


pCO2 or the atmospheric stabilisation of CO2 emissions’’ over the next fewcenturies (Archer et al., 1998). Even if dissolution of CaCO3was taking placeat a rate equivalent to the estimated total annual production of CaCO3 insurface waters, it would still only be partially buffered (estimated maximum6%). This is especially so as most CaCO3 production is pelagic and sinks todeeper depths (Andersson et al., 2006). Dissolution from bottom sedimentsas the lysocline shoals in response to the reduction in pH over the nextcentury and longer will enable the oceans to increase their CO2 sink.

5.4. Uptake of CO2 by the ocean

There is evidence that key ocean sinks for CO2 (the North Atlantic andSouthern Ocean) may already be reducing their rate of CO2 uptake (LeQuere et al., 2007, 2008; Schuster and Watson, 2007). However, thesemeasurements have not yet been taken over sufficiently long periods todistinguish whether this is from natural variation, changes in buffering orother causes. In the North Atlantic, for example, the reduced uptake hasbeen linked to a decline in mixing and ventilation between surface andsubsurface waters. This is due to increasing stratification associated withchanges in the NAO, exacerbated by the changing buffer capacity ofseawater as the carbon content of surface waters increased (Schuster andWatson, 2007). Sustained backbone observations such as carried out in thesestudies are important to continue but are under threat.

Over time periods of<10,000 years, the ocean is particularly sensitive toincreases in pCO2. On a longer term basis, the buffering capacity of theocean will become greater (as measured by the Revelle factor), as bufferingcaused by the dissolution of carbonate sediments moderates the effect of pHchange. On a 1000–100,000-year timescale, it is estimated that CaCO3

dissolution will absorb 60–70% and the oceanic water column 22–33% ofanthropogenic CO2 emissions (Denman et al., 2007). Thus, eventually, theoceans and their sediment CaCO3 will buffer or neutralise the CO2.However, the new concentration level of CO2 in the atmosphere willnever return to pre-industrial levels (Andersson et al., 2003, 2005; Archeret al., 1998).

High atmospheric CO2 does not automatically correlate with lower pH,because it can vary while pH remains constant if DIC changes. This fact isparticularly relevant to the interpretation of palaeo-evidence where acidifi-cation and calcification were thought to be high at the same time. Ifacidification takes place gradually, as appears to have occurred at times inthe geological record, then some of the potential change in pH may beabsorbed by dissolution of sediments. During the Palaeocene–Eocene ther-mal maximum (PETM), it is calculated that following the initial acidifica-tion there was a widespread dissolution of sea-floor carbonates, a pattern


that replicates modelled response to the anthropogenic rise in CO2 (Zachoset al., 2005). Changes in temperature may also alter pH, but any feedback toclimate is likely to be trivial. Any effect is likely to be in the other directionas warmer waters absorb less CO2. Warmer temperatures will increasestratification and thus reduce the volume of mixed water available forCO2 absorption from the atmosphere (Raven et al., 2005). And as a furtherconsequence the increased stability will lead to a reduction in the returnflow of carbon and nutrients from the deep ocean, reduced primary pro-duction and thus lower uptake of CO2.

5.5. Projected future levels of acidification

Recorded on a logarithmic scale, pH has reduced as a global average insurface seawater since the beginning of the industrial revolution by �0.1units (current mean level pH � 8.08, pre-industrial �8.18, last glacialmaximum�8.35). This is equivalent to a 30% increase in the concentrationof hydrogen ions (pH is a measure of the free positive hydrogen ionconcentration; measured in seawater as the total concentration; see Zeebeand Wolf-Gladrow, 2001). With continued ‘business-as-usual’ use of fossilfuels, pH is estimated to decrease by a further 0.4 by 2100 and 0.77 units by2300 (Caldeira and Wickett, 2003). The rate of change and degree ofchange are unprecedented for likely the last 20 million years (Raven et al.,2005; Fig. 1.21) and possibly since the PETM, 55 million years ago (Zachoset al., 2005). The most pronounced changes in acidification are seen in theNorth Atlantic extending down to 5000 m, a much deeper depth thanpreviously thought, due to the deep water formation that occurs there

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Figure 1.21 Changes in the level of seawater pH over more than the last 20 millionyears. Geological estimates (white diamonds) taken from Pearson and Palmer (2000)(method considered by some researchers to be unreliable when older than a fewmillionyears). Calculated mean oceanic pH levels for 1800 and 2000 shown on a vertical lineagainst dates with modelled future predictions for 2050 and 2100 based on IPCC meanscenarios (grey diamonds with dates). Figure from Turley et al. (2006).


(Tanhua et al., 2007). These changes reflect a high input of anthropogeniccarbon and possibly indicate that the oceans can take up more carbon thanpreviously thought over the next century.

5.6. Regional variation in acidification

Changes in acidity measured in the open ocean appear to be extending tosome shelf seas. For example, Feely et al. (2008) have shown a pronouncedshoaling and an increase in the extent of upwelled undersaturated water onthe western continental shelf of North America. This region of the North-east Pacific has one of the shallowest aragonite saturation horizons in theglobe and it appears to have shoaled by about 50 m as a response toacidification now allowing acidified waters to penetrate extensively ontothe shelf. The impact has been pronounced with deoxygenation and massmortality of benthic organisms. If a similar situation arose in the Arctic itmight further exacerbate the vulnerability of calcareous organisms in thisocean to acidification. Within the second half of the last century input ofbicarbonate (DIC) by the Mississippi river increased substantially, primarilyas a consequence of human agricultural changes. This marked change in oneof the major rivers of the world may have provided a localised bufferingsystem for ocean acidification in parts of the Gulf of Mexico (Raymondet al., 2008). It is not clear how such regional variability in acidificationmight feedback to climate change.

5.6.1. Carbonate biology: PlanktonLaboratory and field observations suggest that ocean acidification enhancesphotosynthetic carbon fixation in the major phytoplankton functionalgroups of the modern ocean namely cyanobacteria nitrogen fixers(Hutchins et al., 2007), diatoms (Tortell et al., 2000) and coccolithophores(Iglesias-Rodriguez et al., 2008; Riebesell et al., 2000, 2007). Unlike incorals, the effect of ocean acidification on calcium carbonate-producingphytoplankton is, however, unclear, and shows a non-uniform responseacross species in laboratory experiments (Iglesias-Rodriguez et al., 2008;Langer et al., 2006; Riebesell et al., 2000) although most experiments,including recent ones (Feng et al., 2008), have shown a decline in theratio of inorganic/organic carbon in coccolithophores at higher CO2.These laboratory experiments may, however, not reflect natural oceanicconditions. In the open ocean, the effect of ocean acidification on calcifica-tion remains an open question. It is the balance between calcification andphotosynthetic carbon fixation that controls whether calcifying phyto-plankton represent a sink or a source of CO2 to their surrounding environ-ment (see Frankignoulle et al., 1994), and this information is crucial toelucidate changes in the contribution of taxa to changes in the magnitudeand direction of CO2 fluxes. Assessing the variability of responses across taxa


is a challenge, particularly in the light of evidence of variability in othercalcifying groups within marine invertebrates (Ries et al., 2008;Wood et al.,2008b). Whether intraspecific physiological variability adds to the complex-ity of these responses or whether natural populations respond uniformly tochanges in carbonate chemistry is the next step in assessing the reciprocalinteractions between changing pCO2 and the carbon signature associatedwith biotic responses to ocean acidification. Higher ocean pCO2 will lead toincreased acidity, a lower pH and lower relative calcium carbonate satura-tion (omega). A temperature rise will, however, increase the relative cal-cium carbonate solubility, omega. Any effects from a combination of areduction in pH and rise in temperature will depend on the relative ratesof change of the two variables.

5.6.2. Carbonate biology: Coral reefsWhile only covering �2% of the area of continental shelves, corals throughtheir calcification account for �33–50% of the global production andaccumulation of inorganic CaCO3 (PIC) (Borges, 2005). There is now,however, considerable evidence that these levels of coral calcification willbe severely impacted by future projected ocean acidification (Tyrrell, 2008).A linear relation has been demonstrated between saturation state and calci-fication for coral reefs, but these experiments were performed in biospheresand tanks where the corals were stressed and growing at a slower rate.Recent research has shown, however, that in combination with risingtemperatures calcification rates have already declined (De’ath et al., 2009).It is estimated that lower rates of calcification will lead to a reduction in coralCaCO3 on a global scale of between 9% and 30% over the next 50–100years (Gattuso et al., 1999; Kleypas et al., 1999).

A range of experimental results show that coral calcification, structure andgrowth will be reduced by up to 40% for a doubling of pre-industrial atmo-spheric CO2 to 560 ppm (Hoegh-Guldberg et al., 2007; Wood et al., 2008b).These authors also showed, both experimentally and by comparison withpresent distributions, that aragonite formation ceases at saturation values of3.3. Acidification, however, is not the only process impacting coral reefs; otherphenomena such as extreme temperatures (coral bleaching), viral attacks,starfish predation, dust and precipitation as well as over fishing, pollutionand physical damage also need to be taken into account. The prognosis forreef corals is dire with serious consequences for the many millions of peoplewho depend on them for their homes and livelihoods, as biodiversity hot spots,for shore protection, local fisheries and tourism (Carpenter et al., 2008;Hoegh-Guldberg et al., 2007; Pandolfi et al., 2003). Because of shoaling ofthe aragonite lysocline, cold water corals are also seriously threatened byacidification. However, the ability of coral species to adapt to change, andespecially to the rapid rate of change in pH is not yet clear.


While corals only cover a small area of the global ocean, they areexpected to continue to be major players in the carbon cycle over thenext 100–1000 years because the formation and deposition of CaCO3

during their growth is so intense and because rather little of it dissolves.The breakdown of coral reefs in glacial periods due to lower sea-levels isconsidered. (Coral reef hypothesis of Berger (1982) as one of the possiblecauses of the alternation of CO2 levels between glacial and interglacial timesKleypas et al., 2006.)

5.6.3. Carbonate biology: BenthosIn attempting to identify the impact of ocean acidification on the marinebenthos, it would be unrealistic to focus excessively on the impacts oflowered pH on animals with calcareous body parts. The physiology of themarine biota is finely regulated and has evolved to function within relativelynarrow pH and CO2 ranges (Michaelidis et al., 2005). In a more acid ocean,animals operate under sub-optimal conditions and hence energy apportion-ment between respiration, repair, growth and reproduction will change.The latter two processes will suffer as more energy is consumed by repairand respiration. While there has been considerable concern about theimpacts of ocean acidification on animals with calcareous body parts,some species appear to be able to increase the rate of calcification at alower pH (Wood et al., 2008b) although this is at some metabolic costand may not be sustainable. There are therefore large uncertainties in theadaptation capabilities of marine species and functional groups and, inconsequence, any feedback effects to marine climate.

The scale of impacts on populations and assemblages resulting from adecline in growth and reproductive rates has yet to be quantified, but it isbelieved that coralline algae are particularly vulnerable as they utilise Mgcalcite. Experimental studies by Albright et al. (2008), Jokiel et al. (2008) andKuffner et al. (2008), for example, have shown a marked reduction in thegrowth and recruitment of both coralline algae and corals at elevated levelsof pCO2 comparable to those likely to be experienced near the end of thecentury. Hall-Spencer et al. (2008) have demonstrated the effects of acidifi-cation by studying shallow benthic ecosystems adjacent to volcanic CO2

vents along pH gradients. Rocky shore communities with abundant calcar-eous organisms showed significant reductions in sea urchins, coralline algaeand the absence of scleractinian corals at the extreme of the gradient withevidence of dissolution of gastropod shells.

5.7. Carbonate pump

This pump involves the production and dissolution of the three calciumcarbonate minerals (primarily calcite and aragonite), their transport to thedeep ocean by sedimentation and a contribution to increased levels of pCO2


in the surface ocean. Some of the pCO2 will escape out of the ocean tocontribute in a small way to increased levels of atmospheric CO2. Thispump is termed the CaCO3 counter pump in Denman et al. (2007).Sedimenting coccolithophores, calcareous resting cysts of dinoflagellates,foraminifera and pteropods form most of the settling material. The mineralcomponent may, because of its higher density, provide an important ballastthat ensures that detrital material from the dead organisms settles rapidlywithin aggregates, mucus nets and faecal pellets. Measurements from sedi-ment traps have shown that the net deposition rate in the carbonate pump iscomparable to the organic matter that is deposited by the biological pump.The highest production of carbonate minerals is in coastal upwelling areasand within subtropical gyres. Any reduction in calcification due to acidifi-cation of planktonic organisms could have a serious impact on the rates ofsettling out of both organic and calcareous material from the plankton withimportant feedback implications.

The subtropical gyres play a large role in carbonate production (Car-bonate pump) and are predicted to expand in area, but not in productivity,in a warming world (Behrenfeld et al., 2006). They are sensitive areas, butnot the focus for much research or monitoring. There is limited under-standing of the different regions where both the biological and carbonatepumps are most active, but some indication can be seen from bottomsediment distribution (Fig. 1.22).

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Figure 1.22 Global map of the distribution of different sediment types on the bottomof the ocean. Source: www.radiolaria.org.


http://www.radiolaria.org/index.htm?division=63

Based on the global carbonate budget calculated by Milliman et al.(1999), about 20% of the pelagic carbonate production accumulates indeep sea sediments (Fig. 1.23). These authors also estimate that 60–80% ofthe planktonic calcium carbonate formed is dissolved in the upper 500–1000 m of the ocean by reprocessing and packaging in the guts of zooplank-ton and settling aggregates. Previous to this study it was thought thatdissolution did not take place until particles settled below the carbonatelysocline. This dissolution buffers acidification and if it is within the pene-tration layer for anthropogenic CO2 would allow the oceans to take upmore CO2 (Milliman et al., 1999).

Shallow-water benthic production of carbonate minerals is also impor-tant both within and above the sediment, but little of this material will endup in the deep ocean. Potential dissolution of carbonate minerals on theshelves in the future as pH levels fall further may have important implica-tions for shelf ecosystems with unknown feedbacks to the carbon cycle.

The Biological pump is also likely to be seriously affected by acidifica-tion through change in plankton ecology and in the physiological processesinvolved in organic and carbonate production.

5.8. Nutrients

It is known that there are interactions between nutrients (including DIC),and photosynthetically active radiation (PAR) in the way that algae take upand assimilate DIC. Most algae, as well as corals and seagrasses, haveconcentrating mechanisms which can increase the rate of CO2 assimilation,especially at low DIC concentrations (Giordano et al., 2005). The discoveryof the widespread and abundant occurrence of PR genes in the oceans

0.5 Remineralization

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SedimentAccumulationUnits=Pg CaCO3 C yr −1

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Figure 1.23 Schematic CaCO3 budget. Figure from Sabine et al. (2004b).


opens up the possibility of ‘a previously unrecognised pathway of energycapture on Earth’ by heterotrophic bacteria (Karl, 2007); the consequencesfor biogeochemical cycles are as yet unknown. Changes in the availability ofammonium or nitrate as the nitrogen sources and of the supply of phospho-rus and iron can also affect uptake rate and growth. It is expected that theseeffects will modulate the way in which growth by photosyntheticallydifferent primary producers respond to increased CO2, but much moreresearch is needed before confident predictions can be made. In consideringthe effects of increased CO2 on growth above it was pointed out that CO2

assimilation continues to increase with rising CO2 even after growth (celldivision rate) has saturated. This will alter the food quality to the next, andperhaps higher, trophic levels. It is not clear if there are biologicallyimportant effects of the changes in ionisation state with decreasing pH of,for example, ammonium and phosphate. Finally, pronounced changes in N2

and CO2 fixation rates have been described from experiments on thecyanobacteria Trichodesmium at atmospheric levels of CO2 up to1500 ppm, implying potentially large impacts on the N and C cycles andon phosphate availability (Hutchins et al., 2007).

5.9. Palaeo-comparisons

By measuring CO2 in bubbles of air (Fig. 1.24) in layered ice cores fromboth Antarctica and Greenland, the cyclic alternation of CO2 and tempera-ture between Pleistocene glacial and interglacial periods has been docu-mented and recently extended back to 800,000 years before present (Luthiet al., 2008). From the last glacial maximum to prior to the industrial

WaterH2OH2

18OHDO

AirCO2CH4d15Nd40Ard18O...

ImpuritiesDust,sea salt,10Betrace elem.pollution,volcanism....

Figure 1.24 Bubbles of air in polar ice observed in a thin section under polarised light.Text redrawn fromRaynaud D. EPICA lecture (2008Ocean Sciences Meeting, Orlando,USA). Image: Copyright Michel Creseveur, CNRS/LGGE.


revolution CO2 levels in the atmosphere increased by 40%, likely repre-senting a release from the ocean reservoir. It should be noted, however, thatice core CO2 measurements are ‘smoothed’ by diffusion and dating pro-blems. Higher resolution data from oak leaf stomata reveal more ‘natural’variation (up to 34 ppmv) of CO2 in the millennium (van Hoof et al., 2008).The authors show that their stomata-based CO2 trends correlate withchanges in Atlantic SST trends and suggest that this may indicate thatchanges in oceanic sources/sinks may be the mechanism behind therecorded CO2 variability.

Prior to the Pleistocene, atmospheric concentrations of CO2 have to bedetermined from proxies or are calculated using geochemical models. Attimescales of millions of years during the Phanerozoic atmospheric CO2 wasdependent on the balance between volcanic sources (thereweremajor periodsof volcanic activity inEarthhistory) and consumptionofCO2byweatheringofsilicate minerals in terrestrial rocks (this process is rate dependent on tempera-ture) followed by deposition of carbonate sediments on the sea floor (Francoiset al., 2005) and by changes in photosynthesis. On timescales of tens ofthousands of years, weathering does not affect major ocean chemistry to anygreat degree; such changes take place in the longer term. Rates of organiccarbon deposition in rocks are also important. Both the latter rates andweathering are highly dependent on evolution, especially of the angiosperms,as well as extinction events and tectonic activity (Berner andKothavala, 2001).

The geological record provides evidence of major changes in oceanchemistry that are linked to levels of atmospheric CO2 such as fluidinclusion and other evidence that calcium concentrations approximatelyhalved and magnesium concentrations approximately doubled over the last100 million years (e.g. Tyrrell and Zeebe, 2004). Mackenzie and Pigott(1981) were the first to note that the carbonate oolites and cements incalcareous sediments oscillated between calcite/dolomite and aragonitethrough geological time (subsequently termed calcite–dolomite or arago-nite seas). Later work showed that biological skeletal precipitates show thesame alternation. These periods reflect changing environments and climateas well as Mg to Ca ratios in seawater, and atmospheric and seawater CO2

concentrations (Arvidson et al., 2006).Using the MAGic model of Arvidson et al. (2006) and a relatively small

number of calculated chemical parameters, Mackenzie et al. (2008) char-acterised the history of atmosphere and ocean composition during thePhanerozoic Eon (the last 545 million years). The two major oscillatorychemostatic modes (Fig. 1.25) are distinguished by differences in seawatercarbonate saturation state, major ion chemistry, especially SO4/Ca andMg/Ca ratios, degree of ocean acidification, and atmospheric CO2. Thecomputed trends agree with fluid inclusion data for Mg/Ca and SO4/Caratios through Phanerozoic time and the mineralogy of the dominant carbon-ate precipitates. During the earlier part of the Phanerozoic (the Palaeozoic),


seafloors were covered in carbonates and atmospheric levels of CO2 werevery high in contrast to the succeeding Mesozoic and Tertiary whenterrigenous silicilastic sediments predominated (Peters, 2008). In the Creta-ceous (Fig. 1.25) high levels of atmospheric CO2 coincided with high rates

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Figure 1.25 (A) Atmospheric levels of CO2 through the Phanerozoic calculated fromtwo different models with the periods of geological time distinguished from O (Ordo-vician) to T (Tertiary) on the bottom of the figure and alternations between calcite–dolomite and aragonite seas at the top. (B) Plots of pH, Omega CaCO3 and DIC plottedover the same period. From Mackenzie et al. (2008).


of CaCO3 formation, including the proliferation of coccolithophorids. Animportant element of the high CO2 world at that time was the higher sea-level, which meant that the area covered by shelf seas was much largerallowing the deposition of extensive layers of chalk. The modelling ofArvidson et al. (2006) suggests that pH was low and carbonate saturationstate higher in the Cretaceous. There is however, a contrasting view, thatthe Cretaceous ocean may not necessarily have been acidic and that themodelled saturation states proposed above would have made the calcitecompensation depth too deep.

Andersson et al. (2008) have proposed the hypothesis that the moremodern Earth system, in terms of the mineral composition of biogeniccalcifiers and carbonate sediments, and because of rapidly increasing levelsof atmospheric CO2 and ocean acidification, may currently be in process ofa transition from an aragonite sea to a condition that is more characteristic ofa calcite sea. If such an event occurs it will be without a change in theMg/Ca or SO4/Ca ratios of seawater. It is predicted however, that the Mgcontent of calcitic hard parts in marine organisms is likely to decrease, theproportion of stable carbonates formed (e.g. calcite) increase and the Mgcontent of carbonate sediments decrease. Such changes have occurred ingeological time and have been accompanied by profound alterations inmarine ecosystems and biogeochemical processes.


� The impact on climate change from ocean acidification is unclear.� The structure of marine ecosystems and the physiological responses ofmarine organisms are expected to be severely impacted by acidificationwith potential extinctions, primarily because of the speed of change that istaking place.

� Reduction in carbonate mineralisation due to acidification may have animportant impact on ballast in sedimenting particles, likely leading to morerecycling in the upper ocean and a lower uptake of atmospheric CO2.

� Changes in the relative location and intensity of the biological andcarbonate pumps may have important feedbacks to climate change.

� While corals cover only a small part of global shelf systems they are stillexpected to be major players in the carbon cycle over the next 100–1000years due to their intense growth and limited dissolution.

� Acidification is expected to have very serious consequences for thesurvival and growth of corals.

� Over a timeframe of thousands of years the oceans will be able tocontinue to take up much, but not all, anthropogenic CO2 due tocarbonate dissolution in the deep sea.


6. A Special Case: The Arctic and Seas Adjacent

to Greenland

6.1. Climate change in the Arctic Ocean and Subarctic seas

The Arctic Ocean (Fig. 1.26) has a central role in global climate. Its keyattributes are its high latitude, marked seasonality of insolation, uniqueenclosed nature and high reflectance of sunlight (albedo) from sea-ice,adjacent glaciers and snow cover. Enclosing the ocean is a terrestrial

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Figure 1.26 Map showing the geographical features and bathymetry of the ArcticOcean and adjacent seas. From Jakobsson et al. (2008).


environment that is dominated by the cryosphere, either seasonally on thesurface, or permanently just below the surface (i.e. permafrost). As a result ofa strong ice–ocean influence, small changes in temperature and salinity maytrigger large and sudden changes in regional climate with potential down-stream feedbacks to the climate of the rest of the world.

It is clear from the Arctic Climate Impact Assessment (ACIA, 2005), theIPCC AR4 and more recent publications that the Arctic region as a whole ischanging rapidly. While there are few long-term measurements, it isthought likely that Arctic air temperatures have been increasing since thebeginning of the last century and certainly since the 1950s, when moreobservations became available. During the twentieth century, it is estimatedthat the Arctic warmed at a rate that was 50% faster (0.09 �C compared to0.06 �C per decade) than the average for the whole of the NorthernHemisphere (ACIA, 2005; Fig. 1.27). However, Polyakov et al. (2002)consider that the Arctic long-term trend may not have been amplifiedwith respect to the global trend, and instead that the difference is a conse-quence of poor seasonal sampling coverage in the Arctic that is hidingpronounced interdecadal variability. New research by Kaufman et al. (2009)has shown that the Arctic cooled progressively over the last 2000 years until�1900 since when the trend reversed sharply to give from 1950 four of thewarmest decades in two millenia. Precipitation has also increased and,together with the temperature increase, has led to a chain of other rapidchanges within the last two decades including rising river flows, changes inocean salinity, thinning of permafrost, declining snow cover, melting ofglaciers and the Greenland ice sheet, rising sea-levels and most markedlyrapid retreat of summer sea-ice extent and a reduction in its thickness.

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Figure 1.27 Surface atmosphere air temperature trends (�C per year) averaged for theArctic (green) and Northern Hemisphere (red) (Jones et al., 1999) with 95% signifi-cance as dashed lines from Polyakov et al. (2002).


6.2. The circulation of the Arctic Ocean and sub-polar seas

Warm input to the Arctic Ocean comes from extensions of the Gulf Stream(Fig. 1.28). The North Atlantic Current and the European Slope currentreleasing heat and water to the atmosphere en route. These currents con-tinue north into the Arctic via the Norwegian Sea, as an outer meanderingand a topographically constrained current at the edge of the shelf. As thewarm saline Atlantic water moves into the Arctic Ocean and loses heat itbecomes denser and sinks beneath a cold halocline layer (�200 m) andcirculates throughout the Arctic Ocean. Mixing and diffusion spread bothheat and salt upward into the surface waters.

The counterbalancing deep outflow from the system is fresher andprimarily driven by temperature with sources from the Arctic shelf seasand deep convection sites in the Greenland and Labrador seas. This waterforms the southern out-flowing limb of the MOC in the North Atlantic.The exchange of water and heat is delicately balanced and highly dependenton the rate of sea-ice formation that in turn is governed by temperature andsalinity.

The upper surface of the cold and dense Arctic-sourced bottom water inthe Norwegian Sea has lowered markedly over the last two decades(Dickson et al., 1996). This suggests that dense water formation hasdeclined, and implies that the MOC might also have been reduced. Atpresent, however, there is no indication of a slowing of the MOC (seeSection 2), but some strong evidence for increased inflow of warm salineAtlantic water into the Barents Sea and Arctic that falls counter to thissuggestion.

The cold, dense water emanating from the Arctic has a further hurdle tocross before it becomes incorporated into the main circulation of the MOCin the North Atlantic. The relatively shallow sills that extend between

Lomonosovridge

Fram strait

Greenland gyre Icelandsea

Denmarkstrait Atlantic ocean

Surface water

Intermediate water

Deep water

Eurasian basinCanadian basin

Bering strait

Figure 1.28 Schematic of Arctic circulation (ACIA, 2005).


Greenland, Iceland the Faroes and Scotland with the two main overflowpoints through the Denmark Strait and the Faroe Shetland Channel meanthat there is no direct connection between the Arctic and the global ocean(Hansen et al., 2008). Understanding and measuring the variability ofoutflow and inflow at these two sites as part of the MOC has and willcontinue to be a major area of research into the future (Dickson, 2006;Dickson et al., 2008).

6.3. Runoff from Arctic rivers

Increased melting of permafrost and higher levels of precipitation in Russiaand Canada (ACIA, 2005) has led to a considerable increase in river runoffto the Arctic. This is in turn leading to changes in nutrients and circulation.Ice-free coastal waters are likely to be more turbid and less productive dueto light limitation, in addition to showing increased stratification due toriverine inflow. Basin wide, higher river flows will increase the intensity ofthe Arctic’s haline stratification. Both increased turbidity and enhancedstratification will reinforce the absorption of the Sun’s energy into thesecoastal waters and put more heat in contact with any remaining ice to hastenmelting and warm the region.

6.4. Ice formation in the Arctic

The development and seasonal sequence of sea-ice in the Arctic is verydifferent to the Antarctic, because of its enclosed nature. Due to its con-strained movement, ice that survives summer melt may continue to thickenfrom below year after year to form multi-year ice. The relative proportionsof young and multi-year ice, and the characteristic double halocline, have astrong influence on the role of the Arctic in climate.

The surface halocline layer in the Arctic is maintained by melting sea-ice. When this ice reforms at about �1.8 �C (due to the depressed freezingpoint of saltwater), seawater fractionates producing brine that sinks rapidlydownward, because of its density. This leaves both ice and fresher waterbehind at the surface, with additional freshening provided by the contribu-tions from Arctic rivers. This effect helps to explain why the Arctic is sodifferent from the Antarctic: a fresher ice-covered Arctic Ocean is insulatedfrom saltier warmer water below by the density differences (analogy of oiland vinegar). Cold, dense water that is formed seasonally on the shelves isalso contributed to the deep basins. These processes are important compo-nents of the MOC/THC. The multi-layered haline system is still a keyelement of the Arctic Ocean. As ice retreats and a more open water oceanstarts to develop, strong mixing will remove the haline stratification leadingto a step change in the whole Arctic system. Wind mixing will increase,biological production will be enhanced, a biological carbon pump will


develop and the solubility pump may become less important among otherchanges. However, even in an ice-free Arctic a surface freshwater layer willbe maintained in coastal zones due to the riverine input.

6.5. Observed changes in Arctic sea-ice cover

The most evident and rapid change that has taken place in the Arctic Oceanis the decline in summer Arctic sea-ice cover.

A marked decline has been measured, from both in situ and satelliteobservations, in summer Arctic sea-ice cover over the last three decades(Fig. 1.29). Since 1995 approximately, the decline has accelerated reachingthe lowest recorded area ever in September 2007 (�4.13 million km2;Fig. 1.30) (Stroeve et al., 2007). In September 2007 sea-ice extent wasnearly 50% lower than during the 1950s and 1960s and the 2008 sea-icearea was also significantly below the long-term average (Fig. 1.31), andsimilar to but not as low as 2007.

The thickness and volume changes were estimated to have been twice asfast as the changes in sea-ice extent (Maslowski et al., 2000). There is now

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Figure 1.29 Seasonal and annual mean sea-ice extent averaged for the whole ofthe Northern Hemisphere, January 1900–September 2007. Source: The CryosphereToday, University of Illinois, Polar Research Group, based on data from the U.S.National Center for Environmental Prediction/NOAA (http://arctic.atmos.uiuc.edu/cryosphere/).


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Figure 1.31 Extent of Arctic sea-ice (area of ocean with at least 15% sea-ice) in 2007,2008 and part of 2009 with the long-term average. Source: Nansen Environmentaland Remote Sensing Center, via the Arctic-ROOS web site (http://arctic-roos.org).

Figure 1.30 Sea-ice in September 2007. Total extent ¼ 4.1 million km2. The grey lineshows the average position of the ice edge (median). Source: U.S. National Snow and IceData Center, Boulder, CO (http://nsidc.org/news/press/2007_seaiceminimum/images/20071001_extent.png).


http://arctic-roos.org

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little of the thick, old ice left, which could make the region increasinglyvulnerable to further ice loss (Rigor and Wallace, 2004). In the winter of2008 measurements taken by Envisat showed that the thickness of wintersea-ice reduced by 0.26 m compared to the previous 6 years, averaged forthe whole circumpolar region (Giles et al., 2008). Thinning and less cover-age leads to a reduction in the overall volume of sea-ice, determining itsdisappearance in the future. Inflow of warm salty water from the Atlantichas likely contributed to the overall decline Polyakov et al. (2008) as well aschanges in atmospheric circulation (Maslanik et al., 2007) and cloud cover(Francis and Hunter, 2006) plus a marked increase in export of old ice viathe Fram Strait (Nghiem et al., 2007). While the major focus of reductionsince 1995 has been in the Eurasian Arctic, there has also been an importantcontribution to the melting from warm water originating from the Pacificand advection into the Chukchi Sea and adjoining deep basins (Shimadaet al., 2006). In 2008, the main melt occurred in the Beaufort, Laptev andGreenland Seas.

6.6. Trigger factors for initial sea-ice reductions

The North Atlantic Current, the west European shelf edge current and theirextension in the Norwegian Sea (the Norwegian Current) have warmedmarkedly over the last two decades (Holliday et al., 2008). This increasedinput of heat into the Arctic Ocean may have contributed to the trigger forthe start of the decline in ice extent. However, there is still considerabledebate on the relative role of oceanic versus atmospheric forcing of thechanges. The Atlantic inflow is mainly related to a strong increase in theArctic Oscillation (AO) and the North Atlantic Oscillation (NAO) at theend of the 1980s. However, even after 1996 when the NAO is average,temperatures, and possibly flow have increased, and there has been noreturn to the sea-ice state of pre-1988.

Warming in the North Pacific and Bering Strait in �1995 led to thefirst major reduction in the extent and thickness of ice in the westernbasin. Contrary to the North Atlantic side of the Arctic, which is insulatedby a deep halocline layer, the North Pacific surface water is close to theice, affecting it directly in the winter. This warming has been reinforcedsince �1998 by warmer temperatures in the West Greenland current.The coincidence of warmer conditions in the Canada Basin and in BaffinBay led in September 1998 to a complete retreat of ice from the north ofAlaska and Canada for the first time in recorded history.

6.7. Projected changes in Arctic sea-ice cover

Sea-ice loss is 30–50 years ahead of the modelling used in IPCC AR4(Stroeve et al., 2007). If the present rate of reduction in sea-ice continues,some models project an ice-free ocean in the Arctic summer by 2030


(Stroeve et al., 2007) or 2040 (Holland et al., 2006) compared to the moreconservative estimates of a loss of greater than 40% in the area covered bysea-ice by 2050 as suggested by the majority of IPCC AR4 models(Overland and Wang, 2007). A more recent modelling analysis of trendsin ice extent, thickness and volume (Maslowski et al., 2007); Whelan et al.(2007) estimated that the Arctic may be ice free in the summer as early as2013; however, more recent studies suggest a date of 2037 (Kerr, 2009).Such a rapid reduction will result in changes to many components of theArctic environment as well as to adjacent seas. This will include a change tothe ocean/atmosphere energy balance, affecting weather patterns, anincrease in the freshwater budget from melting ice, supplemented by anincrease in river runoff. Traditional patterns of salt and freshwater mixingwill change with a likely reduction in the strength of the MOC/THCbecause of reduced deep water convection. A reduction in deep convectionwill in turn lead to lower fluxes of CO2/DIC to the deep ocean. In thenear-term, further sea-ice loss and increases in marine phytoplanktongrowth rates are expected to increase the uptake of CO2 by Arctic surfacewaters (Bates et al., 2006), although mitigated somewhat by warming in theArctic (Bates and Mathis, 2009). Each of these changes has the potential tohave a global effect on climate and climate change.

6.7.1. Sea-ice retreat and feedbacksA positive feedback from the ice reduction already appears to be operating andleading to an acceleration of the retreat. Preconditioning of the sea wasidentified as a contributory factor to further sea-ice loss by Lindsay andZhang (2005). Historically, the high reflectivity (albedo) of ice has reflectedmuch of the sunlight during the longArctic summers back into space, but oncethe ice starts to break up, it exposes large areas of dark open water wheresunlight further heats the ocean. The scale of the effect from a change in albedois very marked. Perovich (2005), for example, has calculated that a 500%increase in solar heat anomaly, due to the extensive area of open water in thesummer of 2007, contributed to an increase in basal melting of ice in theBeaufort Sea and its accelerated retreat. The ponding of meltwater on thesurface of sea-ice further leads to reduced reflectance and increased absorptionof solar heat. The loss of sea-ice accelerates the warming of the dark oceanbelow, which distributes the heat to the surrounding water, deeper waters, seabed and atmosphere. Recent modelling has demonstrated that during rapidsea-ice loss episodes, warmth is released back to the air and can penetrate up to1500 km from the coast (Lawrence et al., 2008). This can destabilise permafrostand lead to the release of methane, thus accelerating climate change. Methanereleased from shallow shelf seas has recently been reported as reaching thesurface and off-gasing to the atmosphere (Westbrook et al., 2009) althoughmost methane released from sediment is converted to CO2 by microbialanaerobic oxygenation of methane (AOM) before it reaches the surface.


6.8. The Greenland ice sheet

Changes in the mass balance (snow accumulation–melting) of the Greenlandice sheet will be strongly impacted by adjacent Arctic and Subarctic seas. Therecent acceleration in ice reduction may in part be affected by the higher SSTfound in adjacent waters since �1998 (Holland et al., 2008). Changes in thecirculation of the sub-polar gyre (Hatun et al., 2005, 2009) are likely to havecontributed to the higher sea temperatures.Warmer temperatures are increas-ing the number of summer days when portions of the surface of the Greenlandice sheet melt. Along the margins of the ice sheet, up to 20 additional days ofmelting occurred in 2005 compared to the average since 1988 (Fig. 1.32).

Because of the high elevation of its central mass, the ice sheet has a majorimpact on Northern Hemisphere atmospheric circulation and storm tracklocation. Observed changes in the ice sheet as summarised in IPCC AR4(2007) are:

� Inland thickening over the higher elevations� Faster thinning around the coastal periphery� Recent accelerated shrinkage of the total mass� Northerly movement of the main ice zone from 66 to 70�N between2000 and 2005

Model simulations indicate that the Greenland ice sheet will decrease involume and area over the next few centuries, if a warmer climate continues.A threshold beyond which the ice sheet will continue to melt over manycenturies (3000 years, Ridley et al., 2005) is expected to be crossed if globalannual mean temperature exceeds 3.1 � 0.8 �C or the annual mean temper-ature for Greenland exceeds 4.5 � 0.9 �C (Gregory and Huybrechts, 2006;Lowe et al., 2006), or 3 �C (ACIA, 2005). Temperatures of this order are wellwithin the IPCC A1B Scenario estimates for 2100 (IPCC, 2007), and unlessglobal temperatures decline, the threshold for a complete melting of theGreenland ice sheet is likely to be crossed within this century. Once crossed,it is believed that the ice melt will be irreversible, resulting in sea-level rise ofseveral metres over the coming centuries. This is in addition to any contribu-tion from melting of the West Antarctica ice sheet. Lowe et al. (2006)suggested that complete or partial deglaciation of Greenland may be triggeredfor even quite modest CO2 stabilisation targets.

6.9. Methane and feedbacks to climate change

The importance of methane hydrates (methane gas trapped in an ice-likesolid) is becoming increasingly recognised. Methane is �25 times morepotent as a greenhouse gas than CO2, thus the release of this gas is poten-tially a large feedback to climate change. While elsewhere on Earth, meth-ane hydrates are maintained in place by the pressure of the overlying water,


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Figure 1.32 NASA map (by Robert Simmon and Marit Jentoft-Nilsen, based on datafrom Marco Tedesco, GSFC) indicating especially the increase in melt days in coastalregions (http://earthobservatory.nasa.gov/Features/Greenland/greenland3.php).


http://earthobservatory.nasa.gov/Features/Greenland/greenland3.php

http://earthobservatory.nasa.gov/Features/Greenland/greenland3.php

in the Arctic they are mainly stabilised by temperature (and occur atshallower depth). This fact makes them potentially vulnerable to climatechange, especially in a warming Arctic Ocean.

6.9.1. Methane hydratesIn the Arctic, and on continental shelves and intercontinental rises else-where, sediments entrap major deposits of this greenhouse gas. There isconsiderable variability and uncertainty over the size of reserves of methanewith estimates for methane stored in marine hydrates and sediment rangingfrom 10,000 Gt (GtC) (approximately twice all other carbon fossil fuels;Buffett and Archer, 2004) to 500 GtC and in permafrost from 450 to7.5 GtC (Brook et al., 2008). The impact of a sizeable release of thesereserves into the atmosphere would be large. It is estimated, for example,that a 10% release of global methane stores to the atmosphere over a fewyears would be equivalent to a factor of 10 increase in atmospheric CO2

(Archer, 2007). Fortunately, release of methane hydrates over the nextcentury is thought to be significant, but not catastrophic (Archer, 2007).

Methane hydrates are sensitive to temperature and geostatic/hydrostaticpressure changes, but will be partially stabilised by the increased pressurefrom a rise in sea-level. There are two main mechanisms that affect methanehydrates: The first is sensitivity to sea-level rise: if a shelf region is floodedwith warm water, a large thermal wave propagates into shallow sea bottomsediments and into the soils of flooded low-lying terrestrial regions. Manygigatonnes of methane hydrates are stored on the Arctic shelves of Alaska,Canada and Siberia, which could be reactivated by this type of warming.However, there are many uncertainties: including the level of temperatureincrease and timescales needed to melt permafrost. Advective inflow ofwarmer water from the Pacific or Atlantic would lead to a faster release ofgas and could be a positive feedback to climate change. It is worth noting,however, that AOM will have converted most methane to CO2 before itenters the atmosphere although this process will be slowed in the coldwaters of the Arctic. The anaerobic micro-organisms responsible substan-tially reduce oceanic emissions of methane and are a key component of thecarbon cycle (e.g. Pernthaler et al., 2008). Secondly, methane outcroppingat deeper depths can be affected by the temperature structure on the seafloor. If there is a feedback, it could come from a destabilisation of thehydrates in sediments; any loss could lead to a slope failure. If a turbidityflow was generated as a consequence, it might lead to a large pulse release ofhydrates that would float to the surface of the ocean and be released to theatmosphere. Such a process has been suggested as one of the possible triggermechanisms for the huge Støregga Slide on the shelf slope off Norway andits resulting tsunami circa 8000 BP (Beget and Addison, 2007).

For the Arctic, hydrate records show that they were released in previousglacial oscillations, but at least the present Canadian gas hydrate reserves


have probably been recharged since the last ice age. In off-shore regions ofthe Beaufort Sea, methane can be found bubbling from hydrates which havebeen destabilising for thousands of years—this is not a recent change, butcontributes to climate change. Post 2000, large volumes of methane havebeen observed bubbling from the sea bed of the Laptev and East SiberianShelf Seas and were measured in elevated concentrations above the seasurface (Shakhova et al., 2007, 2008) and attributed to warming conditions.Escape of methane has also been measured off Spitzbergen (Westbrooket al., 2009). It is not clear if these new findings are a response to ananthropogenic signal, and it is also unclear if hydrates have been involvedin previous changes of climate. For example, it is still unclear whether thePETM (55 million years ago) was brought on solely by a major methanehydrate release (Panchuk et al., 2008).

6.9.2. Permafrost methane releaseWarming of the Arctic, through direct warming and through heat releasedby the ocean, can degrade and melt permafrost and potentially lead to therelease of any methane stored within it. The rate of increase of this gas intothe atmosphere has slowed down over the last 20 years; a rate change that isnot well understood. In 2007, however, the concentrations of methane inthe air increased, particularly in the Arctic, suggesting a release from Arcticpermafrost among other sources (the NOAA annual greenhouse gas index,Hoffman, http://www.esrl.noaa.gov/gmd/aggi/).

6.10. Arctic ocean ecosystems

As surface sea-ice continues to be lost, there are likely to be further largechanges in the ecosystems and primary production of the Arctic (Carmack andWassmann, 2006). Temperature, sea-ice cover and light penetration in theenlarged ice-free zones are expected to change, but not the light season, sophytoplankton primary production will increase within the same growingmonths. Reductions of sea-ice cover in the last decade, particularly in thewestern Arctic Ocean, have resulted in a longer marine phytoplankton grow-ing season and an �30–60% increase in the rate of primary production (Pabiet al., 2008). Over the last several years, a similar �10–40% increase inphytoplankton primary production has been observed in the Beaufort andChukchi Seas (Arrigo et al., 2008). In the Bering Sea, reduced sea-ice cover isthought to favour a ‘phytoplankton–zooplankton’ dominated ecosystem overthe typical ‘sea-ice algae–marine benthos’ ecosystem (Piepenburg, 2005).

The life cycles of most Arctic species are highly adapted and intimatelylinked to the timing of sea-ice melt. At present, most phytoplanktonprimary production takes place as the sea-ice is melting and retreatingtowards the pole, with primary production rates typically lower in theolder open waters of the central basin. It is difficult to estimate what the


http://www.esrl.noaa.gov/gmd/aggi/

http://www.esrl.noaa.gov/gmd/aggi/

balance will be between planktonic production in a summer sea-ice-freeocean and sea-ice margin production. Indications are that a climate-inducedreduction of sea-ice cover duration on Arctic shelves will favour thepopulation growth of several key zooplankton species (e.g. Ringuetteet al., 2002), notably the predominant calanoid copepods, perhaps with atransition to a ‘phytoplankton–zooplankton’ dominated ecosystem ratherthan a ‘sea-ice algae–marine benthos’ ecosystem. In the Arctic’s marginalseas, ecosystem changes could be profound if changes in benthic–pelagiccoupling lead to increased pelagic production and a reduction of benthicproduction (e.g. Grebmeier et al., 2006; Wassmann, 2006). Regardless ofany changes in benthic–pelagic coupling, an enhanced seasonal penetrationof the generally smaller subarctic species is expected, although the degree towhich Arctic species may be displaced is uncertain. Such reorganisation inthe way the ecosystem operates will ultimately alter the pathways andmagnitude of energy that passes into upper trophic levels such as fish, seabirds and marine mammals, and impact the people dependent on thoseresources. Potential feedbacks from all these biological changes are unclear,as an integrated ocean-wide view on the structure and function of ArcticOcean food webs is not yet available (Carmack and Wassmann, 2006).

The large reduction in sea-ice cover to the north of Alaska and Canada(including the archipelago) for the first time on record in 1998, is likelylinked to evidence for an increased inflow to the Atlantic via this route seenin the first record of the Pacific diatom Neodenticula in the NorthwestAtlantic in the following year (Reid et al., 2007). Further incursions ofPacific water are likely to impact biological diversity and the carbon pumpin the northern North Atlantic.

6.11. Modelling

The current range of Arctic ice and climate models are too conservative anddo not adequately reproduce current changes taking place in the ArcticOcean (Stroeve et al., 2007). Some work suggests that a threshold (tippingpoint) has been passed in the loss of Arctic sea-ice (Lindsay and Zhang,2005). There are inadequacies in model forcing, parameterisation of sea andice processes and model structure. An Arctic model intercomparison projectis underway jointly between the EU DAMOCLES and US SEARCHprojects (Proshutinsky et al., 2008) for a wide range of global and regionalmodels that focus on different aspects of the Arctic environment. TheGlobal Green Ocean model (Le Quere et al., 2005) indicates that therewill be an increase in the Biological pump but this model does not consideracidification. The predicted ocean uptake of anthropogenic CO2 usingthe IPCC (Intergovernmental Panel on Climate Change) scenarios (e.g.Solomons et al., 2007) is expected to lower pH by 0.3–0.5 units over thenext century and beyond (Caldeira and Wickett, 2003, 2005), with the


Arctic Ocean impacted before other regions due to the relatively low pH ofpolar waters (Bates et al., 2009; Orr et al., 2005; Steinacher et al., 2009).Work within the International Polar Year is currently fostering improve-ments in many aspects of modelling within the region.


There are many feedback loops within the Arctic, some of which haveserious implications for global climate and climate change.

� Increasing heat flux of oceanic water to the Arctic as well as higheratmospheric temperatures is contributing to an accelerating retreat ofArctic sea-ice cover.

� The ice retreat removes the insulation between the ocean from theatmosphere enhancing ocean/atmosphere interaction and influencesatmospheric circulation.

� The ice-albedo effect is large and provides a strong positive feedback fromsea-ice loss.

� Increased warming of the wider Arctic oceanic region is likely to becontributing to Greenland ice sheet reduction.

� Methane is a potent greenhouse gas; warming of the Arctic Ocean andsurrounding tundra may lead to its destabilisation and release fromhydrates and permafrost with the capacity to accelerate global warming.

� Unless the trend in global temperature rise reduces, the temperaturethreshold for an eventual complete melting of the Greenland ice sheetmay be crossed this century. Melting of the Greenland ice sheet alonecould lead to 7 m of sea-level rise over the coming centuries.

� Model predictions for the disappearance of Arctic sea-ice during summersvary between 2013 and the end of the century.

� Most climate models underestimate the rate of ice loss over recent decades.� Some work suggests that a threshold (tipping point) has been passed in theloss of Arctic sea-ice and recent low ice conditions may persist for sometime.

� The impacts of climate change on Arctic biology and the carbon pump,and vice versa (any feedback to Climate Change) was not addressed byIPCC AR4. The scale and rate of any feedback to climate remain unclear.

� Deep water formation, the westward retraction of the sub-polar gyre(positive feedback to ice) and biological impacts were not adequatelycovered by IPCC AR4.

7. The Southern Ocean and Climate

This section focuses on the key role that the Southern Ocean(Fig. 1.33) plays in global climate, through its role in the MOC andinteraction with sea-ice, Antarctic ecosystems and carbon uptake. Major


changes that have taken place over recent decades in the forcing andresponse of the Southern Ocean are outlined, along with the impacts ofthese changes. As an example some of the rapid changes observed at theAntarctic Peninsula are described. Loss of ice shelves is addressed as well asevidence for net reductions of ice in western Antarctica. Finally, somerecent modelling prognoses are presented alongside some of the technolog-ical and observing challenges that need to be addressed to monitor such alarge and extreme environment. Changes in the cryosphere were compre-hensively addressed in the IPCC AR4 reports with less coverage of theSouthern Ocean. A detailed analysis of the state of the Antarctica andSouthern Ocean climate system has recently been completed for the Scien-tific Committee on Antarctic Research (SCAR; Mayewski et al., 2009).

7.1. Role of the Southern Ocean in climate

The Southern Ocean plays a critical role in driving, modifying and regulat-ing global climate change. This is partly due to its unique configuration: it isthe only ocean that circles the globe without being blocked by land. As aconsequence, it is home to the largest of the world’s ocean currents: theACC, which is driven by the strong westerly winds and buoyancy fluxes

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Figure 1.33 A map showing the regional geography of the Southern Ocean andAntarctica that includes the names of locations referred to in the text. Figure courtesy:Mike Meredith, British Antarctic Survey.


over the Southern Ocean. This current transports 150 times more wateraround Antarctica than the flow of all the world’s rivers combined.

The Southern Ocean controls climate in a number of ways. The flow ofthe ACC from west to east around Antarctica connects the Pacific, Indianand Atlantic Ocean basins (Fig. 1.34). The resulting global ocean circulationredistributes heat, salt, freshwater and other climatically and ecologicallyimportant properties. It has a global impact on patterns of temperature,rainfall and ecosystem functioning.

The Southern Ocean is a key region in the oceanic MOC/THC, whichtransports heat and salt around the world. Within the Southern Ocean, theproducts of deep convection in the North Atlantic are upwelled and mixedupwards into shallower layers, where they can be converted into shallow anddeep return flows that complete the overturning circulation (Fig. 1.34). Thisupwelling brings carbon and nutrient-rich waters to the surface, acting as asource of CO2 for the atmosphere and promoting biological production.

The lower limb of theMOC comprises the cold, dense AABW that formsin the Southern Ocean. Close to the coast, the cooling of the ocean and theformation of sea-ice during winter increases the density of the water, whichsinks from the sea surface, spills off the continental shelf and travels north-wards hugging the sea floor beneath other water masses (Fig. 1.34), travelling

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Figure 1.34 Schematic of the global ocean circulation, emphasising the central roleplayed by the Southern Ocean. Figure from Lumpkin and Speer (2003). See Fig. 1.35for an explanation of the acronyms.


as far as the North Atlantic and North Pacific. This cold water also absorbsatmospheric gases, including oxygen and carbon dioxide, which enables itboth to aerate the bed of the global ocean and to act as a temporary (hundredsof years) sink for natural and anthropogenically produced CO2.

The upper limb of the MOC is sourced towards the northern flank ofthe ACC. Here, the water that is upwelled within the ACC is convertedinto mode waters and nutrient-rich intermediate waters that permeatemuch of the global ocean basin south of the equator. Mode waters (likethe Subantarctic Mode Water, SAMW, Fig. 1.35) form at the surface inwinter via convective processes, and are relatively homogeneous watermasses of uniform density. They are undercut by intermediate waters(AAIW in Fig. 1.35) that are renewed by subduction near the PolarFront. The formation and subduction of the mode and intermediate watersis believed to be a critical process that removes anthropogenically producedCO2 from the atmosphere (Fig. 1.36).

Closer to the continent, ocean processes are strongly controlled by sea-ice,the formation of which is the largest single seasonal phenomenon on Earth.The freezing of the sea around the continent as sea-ice each year effectively

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Figure 1.35 Schematic of the overturning circulation in the Southern Ocean, wherebysouthward-flowing products of deep convection from the North Atlantic are convertedinto upper-layer (mode and intermediate) waters and deeper (bottom) waters andreturned northward. Marked are the positions of the main fronts (PF, Polar Front;SAF, Subantarctic Front; STF, Subtropical Front) and water masses (AABW, AntarcticBottom Water; LCDW and UCDW, Lower and Upper Circumpolar Deep Waters;NADW, North Atlantic Deep Water; AAIW, Antarctic Intermediate Water; SAMW,Subantarctic Mode Water). Note that as well as the north–south water movementshown in the figure water is also generally moving towards the observer (i.e. west toeast), except along the coast where coastal currents are moving water away from theobserver (east to west). Figure from Speer et al. (2000).


doubles the size of Antarctica and has a profound effect on climate. Because ofits high albedo (whiteness), it reflects the Sun’s heat back into space, coolingthe planet. However, the sea-ice also acts as a ‘patchy blanket’, limiting heatloss from the ocean to the atmosphere and restricting air–sea exchange ofclimatically important gases. The formation of sea-ice, as noted above, plays akey role in the production of AABW and its annual melt supplies a thin layerof freshwater to the surface ocean that stabilises the stratification and canpromote phytoplankton blooms. The sea-ice is also home to large algalpopulations, as well as sheltering the larvae of plankton such as krill.

Because of its upwelling nutrients, the Southern Ocean is highly biologi-cally productive, although it is not as productive as it could be. This is becausethe productivity is limited by the low availability of micro-nutrients such asiron, except in a few areas such as near the isolated islands that are scatteredwithin the ACC. Nevertheless, the Southern Ocean is a key region for theBiological pump with diatoms as ballast playing an important role in thesedimentation of organic material to the deep ocean (see Section 4).

7.2. Observed changes in the Southern Ocean region

The Southern Ocean has shown many marked changes in recent decades,highlighting its sensitivity to global processes and illustrating differentaspects of its control on regional and global change. The most conspicuous

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Figure 1.36 Water column inventories of anthropogenic CO2 in the ocean. Note inparticular the band of high levels flanking the northern side of the ACC, associated withmode and intermediate waters. Dissolved CO2 is lost to the atmosphere south of thePolar Front, where NADWwells up to the surface close to the coast (purplish colours)and gained from the atmosphere north of the Polar Front where mode waters andintermediate waters sink in the subduction process (green colours), making the South-ern Ocean both a source and a sink for atmospheric CO2. From Sabine et al. (2004a).


of these changes is probably the profound warming within the ACC (Gille,2002, 2008; Fig. 1.37). In this area, a strong, surface-intensified temperatureincrease has been noted that exceeds that of the global ocean as a whole. Theexact causes of this warming are not yet understood, though most theoriesseek to relate it to the intensification and southward shift of the band ofwesterly winds that overlie the circumpolar Southern Ocean. Potentialcandidate mechanisms include a latitudinal shift in the ACC, greater air–sea heat fluxes, an intensification of the circumpolar eddy field, and possiblyother processes also, almost certainly in some combination (Fyfe, 2006; Fyfeand Saenko, 2006; Gille, 2002, 2008; Hogg et al., 2008; Meredith andHogg, 2006). The large-scale circulation patterns of the Southern Hemi-sphere atmosphere over the past few decades reveal changes that arereflected in the leading mode of Southern Hemisphere climate variability,the SAM (Thompson andWallace, 2000). Interannual variability and trendsin the SAM have been shown to drive substantial variability in oceancirculation, upper-ocean biology, and the uptake and release of CO2 toand from the Southern Ocean (Lovenduski and Gruber, 2005; Lovenduskiet al., 2007, 2008). The intensification and movement of the wind field asexpressed in SAM changes is known to be at least partially due to anthro-pogenic processes (ozone depletion and greenhouse gas emissions; Marshall,2003; Thompson and Solomon, 2002). This suggests that the activities ofmankind are perturbing the ocean around Antarctica on a large scale.Noteworthy also is the observation that the current generation of climate

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Figure 1.37 Temperature differences in the Southern Ocean between the 1990s andearlier decades, at approximately 700–1100 m depth. Note in particular the markedwarming around the circumpolar band. Figure from Gille (2002).


models can produce a warming in the Southern Ocean comparable to thatobserved only if anthropogenic gases and sulphate and volcanic aerosols areincluded (Fyfe, 2006). If the role of volcanic aerosols is neglected, thesimulated warming is nearly double, implying that the potential humanimpact on Southern Ocean warming is only partially realised at present inour sequence of observations.

There are countless likely feedback mechanisms from this circumpolarwarming on regional and global climate, including impacts on sea-iceformation (and hence albedo; see below), solubility of carbon dioxideand other climatically important gases, and modulations to primary produc-tion and associated ‘biological pumping’ of carbon. Each of these are thesubject of ongoing investigation; however, it should be noted here that thecircumpolar winds are predicted to increase further over the next fewdecades, hence (if theories relating the warming to strengthening circum-polar winds are indeed correct) the effects are likely to be persistent ratherthan transient.

The strengthening circumpolar westerly winds have been highlighted asthe potential root cause of another important observed change in theSouthern Ocean region, namely a saturation of the Southern Ocean CO2

sink. Ocean inverse analyses (Gloor et al., 2003; Mikaloff Fletcher et al.,2007) indicate that the pre-industrial Southern Ocean (south of 44�S) was asource of natural CO2 to the atmosphere. But the rise in atmospheric CO2

from pre-industrial levels of about 280–380 ppm at present, has led to astrong perturbation of the air–sea CO2 balance, that is, it induced a flux ofanthropogenic CO2 that is directed into the ocean. This sink of anthropo-genic CO2 in the Southern Ocean takes up nearly 10% of the CO2 emis-sions to the atmosphere. However, based on atmosphere and oceanmeasurements, and the analysis of model output, Le Quere et al. (2007)argued that this sink has not increased since 1981, in spite of a >40%increase in CO2 emissions. A reduction in CO2 uptake would likely leadto an increase in the amount of CO2 in the atmosphere, with clear implica-tions for climate change. The theory proposed to explain this observationwas that upwelling in the Southern Ocean, which brings natural carbonfrom the deep ocean to the surface layers, has been accelerated by thestrengthening winds. This has increased surface concentrations of CO2,and precluded further absorption of anthropogenic CO2. Also noteworthyis that the increased upwelling of CO2 will increase the rate ofocean acidification, with consequences for the ecosystem. Although LeQuere’s conclusions have been supported by another modelling study(Lovenduski et al., 2008), it should be noted that Boning et al. (2008)have questioned this saturation of the Southern Ocean CO2 sink, arguingthat the effect of increased eddy formation could compensate for the extraenergy imparted to the ocean by the winds, with no significant change inthe overturning. Much remains to be done on this important subject,


including improved monitoring of CO2 and better understanding of thephysical processes that mediate the vertical motion in the ocean, and it isimperative that the research community tackles these subjects as a matter ofpriority.

On a regional level, the area in the Southern Hemisphere whose atmo-spheric climate has been changing most rapidly is that of the AntarcticPeninsula (e.g. Turner et al., 2005). On its western side, a wintertimeatmospheric warming of 5 �C since 1950 has been observed with a smaller(but still significant) warming seen in summer. This warming has beennoted to be strongly linked with the reduction of sea-ice extent andduration in the adjacent Bellingshausen Sea since the 1950s, and has alsobeen shown to be connected to a very strong summer warming of the upperocean (Meredith and King, 2005; Fig. 1.38). These authors used a largecompilation of in situ hydrographic profiles collected between the 1950s and1990s to demonstrate a surface-intensified warming (of >1 �C in theshallowest levels), and a coincident strong summer salinification. It isworth emphasising that these oceanographic changes constitute positivefeedbacks that act to sustain and enhance the atmospheric warming andfurther reductions in sea-ice formation—a clear example of ocean processesexerting a strong influence on regional climate, in an area of very rapid

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Figure 1.38 Trends in temperature during the second half of the twentieth century inthe vicinity of the Antarctic Peninsula. Four different depth levels are shown, namelythe surface, 20, 50 and 100 m. Note the strong, surface-intensified warming at thewestern side of the Peninsula. From Meredith and King (2005).


change. Meredith and King (2005) also noted that the rising temperatureshave played an important role in the accelerating retreat of the tidewaterglaciers on the Peninsula that have led to an increasing contribution ofglacial meltwater to the adjacent ocean. In accord with this, Cook et al.(2005) showed that the majority of glaciers on the western side of thePeninsula are retreating, and that retreat rates are accelerating.

Meredith and King (2005) also noted the profound consequences for theocean ecosystem in this sector, where benthic organisms are generally welladapted to cope with low temperatures, but poorly adapted to cope withchanges in temperature. Indeed, based on a study of temperature tolerances,Peck et al. (2004) asserted likely ‘population and species level losses’ of marineorganisms at the western Peninsula associated with a proposed 2 �C change inocean temperature. The observed change of >1 �C in 50 years illustrates thatsuch changes are very possible within the next few decades. It is also worthnoting that a key species in Southern Ocean food webs, namely Antarctic krill,has been undergoing a dramatic decline in numbers in the South Atlantic inrecent decades (Atkinson et al., 2004). This population is sourced at leastpartially from breeding and nursery grounds near the western Peninsula, and itwas argued that the loss of sea-ice and warming of the ocean may be the causeof their decline (Atkinson et al., 2004; Meredith and King, 2005). Krill are acritical component of the Southern Ocean marine food web (Hill et al., 2006;Knox, 2007) with most higher trophic levels depending on them and somesuch as the baleen whales feeding exclusively on these crustaceans. Krill arealso now targeted by commercial fishing and so are particularly vulnerable.Establishing the long-term impacts of their removal from regional ecosystemsand on climate is a high priority research area.

To the south of the retreating glaciers on the Peninsula referred to aboveand extending as far as the Trans-Antarctic Mountains is the West Antarcticice sheet. Much of this ice sheet rests on rock that is well below sea-level andparts of its margin are in direct contact with the ocean. Using satellite radarinterferometry and regional climate modelling, Rignot et al. (2008) haveestimated a widespread net loss of the ice sheet in western Antarcticaadjacent to the Bellingshausen and Amundsen seas; with the rate of lossincreasing by 59% in the decade to 2007. The current reduction in massfrom the Amundsen Sea embayment of the West Antarctic ice sheet isequivalent to that from the entire Greenland ice sheet (Lemke et al., 2007).The process believed responsible for this rapid and large change is a pro-gressive thinning of the fringing ice shelves seaward of the Amundsen Seaoutlet glaciers. The likely cause of this melting is a greater penetration ontothe shelf, typically at a few hundred metres depth and upwelling of ‘warm’Circumpolar Deep Water from the ACC. Why this warmer water is nowreaching the ice shelves more readily is still not fully understood, but it isbelieved to be caused by the increase in westerly winds. At a few keylocations these warmer waters flow towards the outlet glaciers along deep


glacially scoured submarine troughs carved by ice in past glacial periods.Once the ‘warmer’ water reaches the base of the floating ice shelves, itcauses extremely high melting rates of many tens of metres per year due tothe large temperature contrast between the seawater and ice. Ultimately,this sector could contribute 0.75 m to global sea-level if the area of ice lost islimited to that where the bed slopes downward towards the interior of WestAntarctica (e.g. Holt et al., 2006), so a contribution from this sector alone ofsome tens of centimetres to sea-level rise by the end of the twenty-firstcentury cannot be discounted.

On the eastern side of the Antarctic Peninsula the greatest warming isduring the summer months, and appears to be directly related to thestrengthening of the circumpolar westerly winds (Marshall et al., 2006).These have resulted in more relatively warm, maritime air masses crossingthe Peninsula from the west and reaching the low-lying ice shelves in theeast. The impacts of this change have included the break-up of large parts ofthe Larsen ice shelf, which has progressively disintegrated from north tosouth. The remaining part of this shelf (‘Larsen-C’) is being closely watched,and may well disintegrate within the next few years or decades. Again, withthe root cause of the change being the strengthening winds, there is a directconnection between anthropogenic processes (greenhouse gas emission andozone depletion) and a large response in the Antarctic.

In IPCC AR4 it was predicted that the Antarctic ice sheet as a wholewill increase in mass over the next century due to higher snowfall as aconsequence of a warmer climate (see also Krinner et al., 2007). Build-up ofsnowfall in the interior of Antarctica is balanced by wastage due to meltingand calving of ice along the coast and this balance is an important compo-nent of sea-level rise. Measurements made by satellite altimetry confirm agrowth in ice mass from snowfall in East Antarctica over an 11-year periodsince 1992 (Davis et al., 2005) and another study has shown a doubling insnowfall in the western Antarctic Peninsula since 1850 (Thomas et al.,2008). In contrast, the long records of Monaghan et al. (2006) and vanden Broeke et al. (2006) for the whole of Antarctica reveal large decadal tomulti-decadal variability in snowfall and yet no significant trend. Theabsence of an observed long-term change in snowfall, when averaged forthe whole continent, has taken place against a background where significantwarming is not just confined to the Antarctic Peninsula, but extends overmuch of western Antarctica and positive trends in temperature are recordedfor the whole of Antarctica since the 1950s (Steig et al., 2009). There istherefore no clear evidence that snowfall has changed in Antarctica as awhole in response to rising temperature, contrary to the predictions ofclimate models. The only exception is in the Peninsula, but there theincrease in mass has been small compared to the loss of mass fromthe glaciers, so that precipitation plays only a minor role in mitigating thecontribution to sea-level change from the Peninsula.


In terms of ice wastage, a rapid increase in glacier flow and retreat of icesheets has occurred in both the Antarctic Peninsula and West Antarctica; thespeed of the observed changes has demonstrated the important role that iceshelves play in controlling the mass balance of ice sheets (Rignot, 2006).In East Antarctica, glaciers grounded well below sea-level are also thinning(Rignot, 2006). The main driver for the glacier changes in the Antarctic is theocean. There is clear evidence that the Southern Ocean has warmed (Gille,2008) and it is likely that the ocean waters along some coastal sectors of theAntarctic are warmer than in the past, for example, the western Peninsula andAmundsen Sea, but unfortunately there are not enough measurements toshow the timing of these changes. These warmer waters condition the evolu-tion of ice shelves much more than air temperature; subsurface melting of iceby the ocean is orders of magnitude larger than what is happening on thesurface. Rignot (2006) concludes that the mass balance of ice in a warmerclimate will be more affected by the evolution of its ice streams and glaciersthan on changes in the precipitation of snow in the interior.

7.3. The future

The future climate evolution of Antarctica and the Southern Ocean isespecially hard to predict, since many of the coupled climate models thatare traditionally used for such predictions do not represent well some of thekey processes, and there is also a dearth of data with which to validate andchallenge the model-based results. Notwithstanding this, it is possible togenerate some understanding of likely future change using such models. Forexample, Bracegirdle et al. (2008) considered the output of the 20 coupledclimate models used in the IPCC Fourth Assessment Report, and produceda ‘scaled average’ of their predictions, with the scaling for each individualmodel being in accord with the skill shown by that model at reproducingprevious (observed) climate change. A ‘middle-of-the-road’ scenario forfossil fuel emissions was adopted for this.

Using this approach, the models predicted a continuing warming of thecircumpolar Southern Ocean in the next 100 years, but with markedlystronger warming in the sub-polar gyres (Weddell Sea and Ross Sea;Fig. 1.39). This stronger regional warming is associated with a 25% decreasein sea-ice extent. Given the locales, this will almost certainly impact onAABW production in these two key formation sites, with possible con-sequences for the lower limb of the ocean overturning circulation. Thecircumpolar westerly winds are also predicted to continue strengthening,with likely consequences in line with the discussions above.

In practice, the predicted ubiquitous warming over Antarctica and theSouthern Ocean is in line with changes predicted and beginning to beobserved in the Arctic. The equilibrium response of the two polar regions toplanetary-scale climate change is comparable; the differences observed so far


are concerned with the transient response. Accordingly, the rapid changesobserved in the Arctic and at the Antarctic Peninsula can be viewed aspotential harbingers of what is to come around Antarctica and the SouthernOcean as a whole.

The future evolution of the Southern Ocean CO2 sink is hard to predict.It depends on how the ocean circulation will change as forcing by theatmosphere evolves, in particular its overturning component. However,knowledge of the evolution of Southern Ocean overturning alone is notsufficient to predict the future of the oceanic CO2 sink because under veryhigh CO2 an increase in upwelling could favour more uptake of anthropo-genic CO2 and over-compensate the enhanced ventilation of natural carboncoming from the deep ocean. Furthermore, changes in circulation, tempera-ture and acidification will certainly impact the downward transport of organiccarbon by biological activity, but we do not know the direction, amplitude orthe rate of the potential changes. However, based on the behaviour of theSouthern Ocean carbon cycle during glaciations, it appears that its response toa warmer climate would be to permanently outgas some of its natural CO2 to

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Figure 1.39 Predicted trends in surface temperatures over the next 100 years from aweighted average of the 20 coupled models used in IPCC AR4. Note the ubiquitousSouthern Ocean surface warming, with ocean ‘hotspots’ in theWeddell and Ross Seas.From Bracegirdle et al. (2008).


the atmosphere while likely reducing the uptake of anthropogenic CO2,which will add to the challenge of stabilising atmospheric CO2.

Regarding the future of the Antarctic ice sheet, changes in the SouthernOcean, especially along the coast of Antarctica, are a major control on theevolution of Antarctic glaciers and on the mass balance of the ice sheet as awhole. This is something that glaciologists and modellers have known aboutfor some time, but it has not been included as a factor in the predictions ofthe future state of the Antarctic ice sheet. The oceans matter even more thananticipated, but it is a domain of study that is currently fundamentallylimited by a lack of basic observations, such as the shape of sub-ice-shelfcavities and oceanic conditions (temperature, salinity, currents, etc.) alongthe coast of Antarctica, near the glacier grounding lines. Only limitedprogress will be possible in the prediction of the evolution of Antarcticaover the next 100 years until an understanding has been developed of howthe Southern Ocean is changing now and into the future. This importantnew theme is emerging strongly from all recent ice studies and needs to beaddressed by the scientific community.


� The Southern Ocean, including the ACC, plays a critical role in driving,modifying and regulating global climate and climate change.

� An increase in westerly wind speeds due, at least partly, to humaninfluences (increases in greenhouse gases and ozone depletion) has beenobserved.

� A continuing warming of the Southern Ocean and strengthening of thewesterly winds is predicted.

� Rapid warming of the ocean west of the Antarctic Peninsula since the1950s has been measured and associated atmospheric and cryosphericchanges observed.

� Changes in the Southern Ocean are closely connected to the productionand melting of sea-ice, the formation of which is the largest seasonalphenomenon on Earth. Sea-ice has a major effect on the Earth’s energybudget and thus climate.

� A strong decrease in sea-ice extent over the next 100 years is predicted.� The evolution of the Southern Ocean along the coast of Antarctica is amajor control on the stability of Antarctic glaciers and on the mass balanceof the ice sheet as a whole.

� Deflation of the northern sector of the West Antarctic ice sheet inducedby a thinning of the fringing ice shelves is most likely associated withgreater subsurface penetration of Circumpolar Deep Water onto thecontinental shelf.

� Reduction of glaciers in the Peninsula and inWest Antarctica is predictedto accelerate.


� The Southern Ocean is an important sink for both natural and anthropo-genic carbon dioxide, a sink that has been reported as possibly saturating,and which urgently requires further investigation.

� Further modification to the CO2 sink is predicted.� Marked changes have occurred in Southern Ocean ecosystems includinga substantial decline in krill numbers.

� Acidification is predicted to increase with likely important modificationsto unique Antarctic ecosystems.

8. Climate Models

This section provides a brief review of the ‘state of the art’ in model-ling the feedbacks of the ocean on climate change. It notes existing limita-tions and offers some suggestions for important research priorities in modeldevelopment and associated observations.

8.1. Ocean–climate feedbacks

Figure 1.40 summarises the key ocean feedbacks that contribute to climate.This section attempts to identify and summarise the modelling issues andlimitations that exist for these feedbacks and in particular howwell the modelscurrently used for climate projections simulate the carbon cycle and sea-ice.The following key questions need to be considered against each of thefeedbacks: What are the consequences for future climate prognoses if thesefeedbacks are not adequately understood and how can they be prioritised?

8.2. Heat uptake

The oceans are the main heat reservoir for the world, particularly overlonger time periods, and strongly influence the rate of climate change asthey have a large capacity to absorb heat compared to land. As a conse-quence, the oceans warm up slowly down to depths of kilometres and act asa delay on anthropogenically forced global temperature rise. A corollary isthat ocean warming will continue for a long time into the future, even ifgreenhouse gas concentrations are stabilised in the atmosphere. Whiledamping the rate of surface climate change, this warming of the oceanalso leads to sea-level rise through the thermal expansion of seawater.

State-of-the-art coupled atmosphere–ocean global circulation models(AOGCMs) include the primary physics that controls ocean heat uptake,but there are still substantial differences in the results obtained by differentmodels. For example, the efficiency of ocean heat uptake varies by a factorof over 5 among the AOGCMs used in the IPCC AR4, although themajority of the models are more tightly clustered (Randall et al., 2007).Some models are able to reproduce the broad picture of increasing


heat content that is deduced from historical observations over the past 50years (e.g. Barnett et al., 2001). Models generally do not reproduce theapparent maximum in global heat content in the 1970s, apparently callinginto question whether the models have sufficient amplitude of internalclimate variability; however, recent analysis by Domingues et al. (2008)suggests that the heat content maximum in the observations may be partlyan artefact of instrumental errors, thus reducing the discrepancy betweenmodels and observations. Uncertainty in the observed heat content esti-mates also arises from the limited sampling, especially in the era before theArgo buoy network (Gregory et al., 2004). Assessment of modelled andobserved heat content changes remains an active research area.

Modelling of changes in the heat content of the North Atlantic by Banksand Gregory (2006) has shown that regional distributions of heat uptake arecrucially dependent on the changes in the large-scale circulation and mixing

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Figure 1.40 Factors involved in the interaction of the ocean with climate.


of the oceans and not just along lines of equal density as might be indicatedby tracers. In another study, Lozier et al. (2008) showed large regionaldifferences in the heat uptake of the North Atlantic, which has increasedon average at a rate equivalent to a surface heat flux of 0.4 � 0.05 W m�2

over the last 50 years. This basin-wide increase disguises a large contrastbetween the sub-polar gyre which experienced a net loss of heat betweenthe periods 1950–1970 and 1980–2000 against a large heat gain in thetropical and subtropical North Atlantic. The changes were attributed atleast in part to recent decadal variations of winds and heat flux linked withthe NAO. The present generation of climate models, in general, do notmodel recent NAO changes well, so that it can be concluded that there isstill considerable uncertainty in modelling heat uptake at this level of detail.

Recent analyses by Sriver and Huber (2007) have demonstrated that‘tropical cyclones are responsible for significant cooling and vertical mixingof the surface ocean in tropical regions’. They calculated that �15% of thetransport of heat by the ocean may be associated with this downwardmixing of heat. Furthermore, the strength of mixing is correlated withSST so that future increases in tropical temperatures may have importantconsequences for ocean heat transport and circulation. Since tropicalcyclones are poorly resolved in models that are in use at present, their effectsmust be represented in gross form (parameterised). The size of errors inmixing projections associated with possible future changes in tropicalcyclones has not been assessed.

8.2.1. Main limiters to heat uptake modelling progress

� The wide range in the present generation of model estimates of heatuptake efficiency.

� A greater understanding of the reasons for inter-model differences at theprocess level.

� An improvement in temporal and spatial coverage of observational dataneeded to evaluate models.

� Good estimates of historical water mass changes, including completeerror estimates.

� Shortness of time series (and limits to modelling of the main modes ofclimate variability) makes the distinction of Climate Change from naturalvariability difficult.

� Better sampling (from Argo) will over time improve global observationalcoverage.

� More sophisticated data assimilation (reanalysis) methods are needed toextract maximum information from limited historical data.

� Improved estimates of atmospheric aerosol forcing would have a knock-on impact by further constraining the calculation of the efficiency ofocean heat uptake.


8.3. Heat transport

The poleward transport of heat from the tropics, by extensions of the GulfStream and the North Atlantic Current and the southerly directed deepcounter currents as part of the MOC, has major implications for climate.Around 1015 W of heat is moved northwards in the North Atlantic and isdissipated to the atmosphere northwards of about 24�N to represent asubstantial heat source for Northern Hemisphere climate. It has beenpostulated that a slowing down or cessation of the MOC could lead to asudden and marked reduction in heat transport to the region, leading to acooling of Europe’s climate. However, total shutdown of the MOC isgenerally considered to be a high impact, low probability event, especiallyin the twenty-first century. The present generation of climate modelssuggests a slowdown ranging between 0% and 50% during the twenty-first century, under the IPCC A1B scenario, but none of the modelssuggests a shutdown (Meehl et al., 2007). In the models wherethe MOC weakens, warming will continue in Europe as any reductionin the MOC will be counterbalanced by warming due to increasinggreenhouse gases. At present it is not possible to give precise quantitativeadvice, especially on longer timescales, due to a large range of uncertaintyin the modelling.

Density contrasts caused by spatially differing air–sea heat exchange areone of the three driving forces behind the MOC; others are densitycontrasts due to spatially differing freshwater exchange (haline forcing)(Saenko et al., 2002) and surface flux of momentum (wind stress forcing)(Beena and von Storch, 2009; Chelton et al., 2001; Delworth andGreatbatch, 2000). Using models to help determine the relative impor-tance of these three driving forces is an important research area forClimate Change. Overall, models suggest that the response of the MOCto Climate Change is initially driven by changes in thermal forcing, withfresh water/salinity effects taking on an increasing role at longer time-scales. Freshwater supply from melting of the Greenland ice sheet is notproperly modelled in the current generation of climate models. Evidencefrom recent studies with improved ice sheet models (Fichefet et al., 2003;Ridley et al., 2005) is mixed as to whether this extra water source wouldhave a significant impact on the MOC, but still no model suggests anMOC shutdown during the twenty-first century. Since importantbranches of the MOC pass through narrow straits that are not fullyresolved in present climate models, the sensitivity of model projectionsto model resolution is an important open question.

Many changes have been observed in the North Atlantic recently, forexample, in salinity and in some elements of the MOC flow. The MOC atthe latitude (25�N) of maximum heat transport has been estimated only afew times from direct observations (Bryden et al., 2005) making it difficult


to know if there have been any long-term trends. However, a programmeof continuous monitoring has recently begun (Cunningham et al., 2007),which should considerably improve our knowledge of the MOC and itsvariability. Overall there is not yet a clear picture of how the North Atlantichas been changing in recent decades so that it is not yet possible to separateout the effects of climate change and natural climate variation. This remainsan active and important research area.

Because of the circumpolar surface circulation and the presence of majorsites of deep water formation, the Southern Ocean is also a key contributor tothe overturning of the world’s ocean. Its large surface area and potential forstrong mixing make it an important area for heat and carbon uptake. Theexisting generation of climate models tend to have some biases in theirsimulations of the Southern Ocean circulation, believed to be partly a conse-quence of errors in the simulated winds (Randall et al., 2007). Eddies andboundary current processes may also play an important role in the circulationand tracer transports, and it is anopenquestion as towhether their effects canbeadequately parameterised in coarse resolution models (e.g. Banks et al., 2007).Lackof available observations to test themodels in this remote part of theworldremains an important constraint, although the Argo float programme is nowhelping to fill data gaps. The tropics are another area where improved under-standing of modes of heat transport variability and links to ENSO requiresfurther development in global climate models (GCMs).

8.3.1. Main limiters to heat transport modelling progress

� Poor historical time series information on the MOC and its components.� Complex patterns of variability make the disentangling of natural andanthropogenic influences difficult.

� A wide range of responses to increasing greenhouse gases in models of theMOC. Detailed process-level understanding of the different responses isrequired.

� Important flows through narrow channels are poorly resolved in present-day models although the importance of this for the modelled response isunknown.

� Some common errors are found in model simulations of the SouthernOcean. In this region, poor resolution of eddies and boundary currentsmay be a particular modelling issue and observational gaps limitunderstanding.

� The limited observational evidence available does not suggest any radicalchange to the existing picture of the ocean’s role in the climate system.While there are deficiencies in climate models, there is no clear evidencethat the models on average would over- or underestimate large-scaleclimate change.


8.4. Water cycle

Many of the effects of climate change will be seen through the hydrologicalcycle. The hydrological cycle also feeds back on the ocean circulationthrough the impacts of fresh water on the THC (see Section 8.3). Inmodelling there is an increasing focus on the prediction of regional changesin precipitation. Overall, climate models predict a drying of the subtropicsand increased precipitation at high latitudes, but beyond these broad indica-tions there is considerable variation among model projections.

A key issue from a modelling perspective is a lack of available observa-tions of freshwater fluxes over the oceans. Substantial changes in salinityhave been seen, and these have been interpreted as indirect evidence ofchanges in the hydrological cycle (Bindoff et al., 2007). However, becauseof the ability of the ocean circulation to transport large amounts of freshwater, the interpretation of the salinity observations remains a matter ofdebate (e.g. Pardaens et al., 2008; Wu andWood, 2008). New datasets fromsatellites suggest a stronger response of the hydrological cycle to temperaturechanges than is seen in climate models (Wentz et al., 2007), but the datasetsare still new and require further scrutiny.

8.4.1. Main limiters to water cycle modelling progressLimited observations of precipitation and evaporation over the ocean, andnon-quantified error bars.

� Limitations to the use of historical salinity observations, and possibly largenatural variability, may restrict the use of salinity to quantify changes inthe hydrological cycle.

8.5. Sea-ice

In the Arctic, most climate models simulate slower losses of sea-ice in recentdecades than have been seen in measurements made from satellites. A fewmodels are able to simulate the observed long-term reducing trend (Stroeveet al., 2007), but it has been suggested that even these models are misrepre-senting key processes of ocean heat transport into the Arctic due to limitedresolution (Maslowski lecture 2008, http://www.ees.hokudai.ac.jp/coe21/dc2008/DC/report/Maslowski.pdf; see also Maslowski et al., 2007, 2008).Record low sea-ice extents were observed in summer 2007, but it isimportant not to read too much into an individual season, since year-to-year variability is large and not all observed trends are necessarily anthropo-genically forced.

In contrast, in the Antarctic a decrease in ice extent is simulated overrecent decades by some models, but other than the Antarctic Peninsula nosuch decrease has been observed. Clearly there is much research needed


http://www.ees.hokudai.ac.jp/coe21/dc2008/DC/report/Maslowski.pdf



to understand recent observed changes and to model them adequately.The sea-ice components of climate models have improved considerablyover the past decade, but the overall quality of sea-ice simulation dependsalso on the driving atmospheric and ocean simulations; and these may nowbe the limiting factors. Nonetheless a number of important thermodynamicand dynamic processes are still absent from most climate models, and thismay be playing a role in some of the model-observation discrepancies (seenext paragraph; Hegerl et al., 2007; Randall et al., 2007).

Pronounced changes take place in the albedo of the ice-covered Arcticand Southern Ocean when sea-ice melts or is covered with snow or water.The physics behind the changes is still not fully understood and in particularinteractions with the atmosphere, with surface melt water that can formponds on top of the ice, with varying thicknesses of surface snow and withthe freshwater surface layer on top of seawater once the ice has melted.Observations of these parameters are very limited, especially historically.In addition to the above difficulties, present-day modelling may not beadequately representing the dynamics of sea-ice, despite important devel-opments in recent years.

8.5.1. Main limiters to sea-ice modelling progress

� A lack of observations of sea-ice thickness.� Poor understanding of processes controlling sea-ice distribution, includ-ing important driving variables in the atmosphere and ocean.

� Potentially large year-to-year variability makes it difficult to distinguish aclimate change signal.

� A lack of understanding of a number of key sea-ice processes.

8.6. Gas exchange/carbon uptake (CO2, N2O, DMS)

Understanding the transfer of CO2 from the atmosphere to the oceans andthe carbon cycle is critical to the development of accurate future predic-tions. Eventually carbon from the atmosphere will end up in the oceans; theproblem is in determining the quantity, rates of transfer and location of thefluxes. There is a poor (but improving) knowledge of how the oceaniccarbon cycle works. This is a key issue in predicting climate change as theamount of carbon dioxide absorbed by the ocean will strongly affect theimpacts of particular atmospheric CO2 emission pathways on climate.Carbon cycle processes are not yet routinely included in climate generalcirculation models; hence feedbacks of climate change on carbon uptake arenot explicitly modelled. However, in recent years a number of modellinggroups have developed simple models of both the land and ocean carboncycles that have been coupled into GCMs to estimate these feedbacks(Friedlingstein et al., 2006).


Unlike physical processes, there is no convergence of scientific opinionon what are the key processes required to model the role of ocean biologyand microbial ecology in carbon uptake and the production of radiativelyactive gases. Part of this debate involves the complexity that is required toadequately model feedbacks between the biology and climate. Processes(and hence parameterisations) of gas exchange and sinking fluxes are poorlyunderstood (see the ‘Science Plan and Implementation Strategy’ of TheSurface Ocean—Lower Atmosphere Study: SOLAS, 2004; http://www.uea.ac.uk/env/solas), yet models are very sensitive to these parameters.Coastal processes, which are not explicitly included in global carbon mod-els, are likely to be highly dynamic in terms of gas exchange and carbon flux,although their overall importance for long-term carbon storage is uncertain.The debate extends to the physical part of the models: for example, eddiesmay play an important role in the carbon cycle through vertical transport ofnutrients, and it is not known whether such transports can be adequatelymodelled with the existing resolution that is feasible in climate models.

In summary, process-level understanding is poor so that predictiveoutput differs greatly between models. However, most existing modelssuggest that the fraction of CO2 emissions absorbed by the ocean willdecrease as climate warms (Denman et al., 2007). This is likely partly dueto increased stratification and lower solubility of CO2 as the ocean surfacewarms. Recent observations have suggested reductions in carbon uptake inboth the Southern Ocean and the North Atlantic; however, it is not clearwhether these changes are global in extent or can be related to climatechange (Le Quere et al., 2005; Schuster and Watson, 2007). It thereforeremains an open question whether such analyses of recent carbon uptakechanges provide a useful constraint on future model predictions.

8.6.1. Main limiters to gas exchange modelling progress

� A lack of quantitative and global understanding of driving biogeochemi-cal processes.

� There is poor understanding of how to incorporate into models thecomplex biodiversity and functioning of microbial systems and theirimpact on biogeochemical cycles.

� Uncertainty over what level of complexity is required to adequatelymodel the global effects of the ocean ecosystem.

� A potential high sensitivity of model results (especially vertical tracerfluxes) to resolution.

8.7. Retro-modelling of past climate change

While palaeoclimate scenarios have been only marginally covered in thischapter, they provide some analogies to the rapid increases in temperatureand pCO2 that are currently taking place due to anthropogenic forcing.


http://www.uea.ac.uk/env/solas



Possibly the closest analogues to the present situation are the changes thattook place prior to and during the PETM, �56 million years ago. In thisevent, global temperatures increased by 5 �C within 1000 years and>2000 GtC as CO2 was injected into the atmosphere with profoundimpacts on, and feedbacks from, the oceans (Nunes and Norris, 2006;Sluijs et al., 2007; Zachos et al., 2008). The source of the CO2 remainscontroversial, but the most likely candidates are methane hydrates, volcanicemissions and oxidation of sedimentary organic carbon (Sluijs et al., 2007).It should be noted that even this event, considered ‘rapid’ in geologicalterms, was a significantly slower change than is projected over the twenty-first century as a result of anthropogenic greenhouse gas emissions. Retro-modelling of the PETM has failed as the models show a strong gradientbetween the equator and poles, whereas palaeodata convincingly indicate aweak gradient with subtropical conditions in the Arctic (Moran et al., 2006;Sluijs et al., 2006). This implies that some key processes/phenomena thatwere operating in the PETM are not being taken account of in the currentgeneration of models. The PETM provides us with information on thefeedbacks that operate in the Earth system on longer (multi-century) time-scales. It is not clear how important these feedbacks are for the more rapidtwenty-first century response to anthropogenic forcing. A greater useshould also be made of palaeodata not only to test models but also toinvestigate the coupling of carbon cycling and climate, and the role offeedbacks and the sensitivity of climate to extreme changes in greenhousegases (see Zachos et al., 2008).

8.8. Final comments

� There is a need for an improved understanding of the sensitivity of modelresults to resolution. This will require the development of higher resolu-tion models and/or improved parameterisations of unresolved processes(e.g. vertical mixing, sill through-flows, boundary currents, eddies).Developments of this nature will be highly dependent on the availabilityof appropriate computer power.

� An integrated global ocean observing programme needs to be implemen-ted to include continuous time series of key ocean–climate variables.Such time series need to be maintained for a sufficient length of time toenable a climate change signal to be distinguished from internal variability(e.g. Argo, Altimetry, RAPID MOC array, Continuous PlanktonRecorder, CPR).

� Development of improved and integrated observational datasets of sea-icethickness is needed.

� A better observational structure is required to measure the large-scalehydrological cycle that includes error estimates.


� Observational constraints on large-scale ocean carbon uptake need to beresolved with an improvement in the understanding of key processescontrolling the ocean carbon cycle (leading to development of modelsat the appropriate level of detail).

� Model development is a painstaking, lengthy and continuous process.Long-term investment commitments for both model development andobservational time series must be maintained if current demands for anincreasing level of detail and reliability in climate predictions are to bemet.

� A greater use should be made of palaeodata not only to test models butalso to investigate the coupling of carbon cycling and climate, and the roleof feedbacks and the sensitivity of climate to extreme changes in green-house gases.

9. Conclusions and Recommendations

The Earth is a blue planet, with two-thirds of its surface covered byoceans. It is home to many hundreds of thousands of organisms rangingfrom the important microbial viruses, bacteria and Archaea to the micro-scopic and beautiful siliceous, frustuled diatoms to magnificent whales.Some indication of this diversity and beauty has been captured by theCensus of Marine Life.3 This chapter has been produced to draw attentionto the key role that the oceans play in regulating climate as the main heatengine, water reservoir and carbon sink of the planet. It is worth noting aswell that the oceans are greatly impacted in turn by climate change withconsiderable consequences for coastal communities and urban centres fromsea-level rise and storms to fisheries and marine transport.

The oceans have been buffering (neutralising) climate change over thepast two centuries by absorbing carbon dioxide and heat from the atmo-sphere generated by both natural variability and man’s contribution viaincreased levels of greenhouse gases in the atmosphere. This key role inclimate has helped substantially reduce the rate of climate change. There hasnot, however, been any reduction in the independent and parallel effects ofocean acidification due to increasing concentrations of CO2. In recentdecades changes have occurred that could alter and possibly underminethe buffering role of the oceans via negative and positive feedbacks. There isa need for a better understanding of these feedbacks, not all of which arefully included in modelling. Some studies indicate that incomplete account-ing of land and ocean carbon cycle feedbacks may already have led to anunderestimate of the measures needed to mitigate climate change.4 The

3 http://www.coml.org4 IPCC, SPM, WGIII Legend to Table.


http://www.coml.org

http://www.coml.org

wide range and rates of changes now underway in the seas and the potentialfor abrupt changes to occur that may be triggered by feedbacks from theoceans, raises concern. It should be noted, however, that it is still impossi-ble, due to a lack of appropriate long-term measurements, to establish theextent to which some of these changes are due to natural variability ordirectly a consequence of man-made climate change.

9.1. A decade ago

In 1998 in a seminal paper in Science, Falkowski et al. noted that theirintention was ‘‘not to make quantitative predictions of the feedbacks, butto call attention to the sensitivity of marine ecosystems, on all time scales, toclimatic and geophysical processes external to the ocean, and the rolemarine ecosystems have played in regulating the chemistry of the Earth.Our predictive capabilities will improve only when the need for an inter-national network of coordinated long-term (multidecadal) observations ofoceanic biology is addressed, and our ability to incorporate the biologicalprocesses and feedbacks in coupled ocean–atmosphere models is dramati-cally improved’’. These words are as true today as they were then. A decadehas passed, climate change has become a much more urgent issue, and yetthe resources to develop an understanding and to measure, through ocean-scale observing programmes, these key feedbacks for climate change havenot been made available. Progress has been made, but not at the scale andrate that is needed.

9.2. Warming waters

The main role that the ocean plays in climate variability and change is its hugecapacity for the transport and storage of heat that reaches the surface of theplanet from the Sun. Some of the heat is transferred to the deep ocean bymixing and some is released back to the air-driving weather systems andwarming adjacent coasts (Bindoff et al., 2007). Over recent decades the oceanshave warmed rapidly at the surface (�0.64 �C over the last 50 years) and inthe whole water column in terms of heat storage. Some idea of the scale of thechange is clear when it is realised that warming of the global oceans accountedfor more than 90% of the increase in the Earth’s heat content between 1961and 2003. Surface warming has been most pronounced in the Arctic andaround the western Antarctic Peninsula where winter temperatures haveincreased by 5 �C in winter months since the 1950s. Globally, most of theincrease in ocean heat content has very likely been caused by increasinggreenhouse gases. Heat is the main driver of change within the oceans andleads to the biggest feedbacks to climate change. It has pronounced effects onglobal ocean circulation, sea-level rise, the concentrations of a major green-house gas, water vapour in the air (through increased evaporation), the


occurrence of tropical storms, and the melting of polar sea-ice. Increasedtemperatures and storms could also alter the sea-to-air transfer of sea saltparticles and gases that contribute to climate-cooling aerosols and clouds.Warming also affects the water’s ability to absorb carbon dioxide and theamount of this greenhouse gas removed from the atmosphere. Finally, there isevidence for increases in the intensity of upwelling at the major upwellingsites around the world leading to large increases in phytoplankton production,anoxia and release of greenhouse gases.

9.3. Freshening waters

Salinity, the second factor that changes the density of seawater besidestemperature has shown a remarkable freshening in many regions of theworld, including in deep water surrounding Antarctica. The pattern ofchange is consistent with an enhanced hydrological cycle, a response thathas been predicted by climate modellers as a consequence of a warmingocean. In the case of the deep waters around Antarctica the reducedsalinities almost certainly reflect the measured deflation of the West Antarc-tic ice sheet, retreat of glaciers in the Antarctic Peninsula and enhanced basalmelt of sea glaciers.

9.4. Changing ocean circulation and sea-level

Warmer water is less dense; as it heats up, a warmer upper layer is establishedand ‘floats’ above cooler, denser water. This ‘stratification’ of seawater isincreasing globally, isolating the surface warmer layer from the nutrient-richdeeper waters. As a consequence, the large central tropical/subtropical areasdeficient in nutrients are expanding in most oceans. Associated with thischange is an expansion of the OMZs in the tropical oceans that has apronounced effect on the carbon and nitrogen cycles and impacts on marineecosystems. Combined, all these factors can limit the production of plank-ton and reduce the amount of carbon dioxide that is removed from the air.Intensified stratification and oxygen depletion may also lead to betterpreservation of carbon in bottom sediments, thus acting as a sink for carbondioxide. The net global balance between these opposing processes is likelyto leave more carbon dioxide in the air and contribute to increasing rates ofglobal heating.

As rainfall patterns change and ice melts, the freshwater inputs into manyseas have increased. The saltiness of the sea has declined markedly in deeperwaters of the Southern Ocean and in waters at all depths flowing from theArctic into the Atlantic. Global circulation in the oceans, the ‘conveyorbelt’, relies upon the formation of cold and salty water sinking in high-latitude seas, and ultimately drives the transfer of heat, nutrients and dis-solved gases around the world’s oceans. Warmer and less saline polar seas are


less effective at driving this process, thereby affecting the way heat istransported around the world. Current models predict a reduction in theintensity of this global overturning circulation of up to 50% by 2100, but noabrupt shutdown,5 as has been occasionally suggested in the media.

Both the expansion of water due to heating and the melting of glaciersand ice caps cause sea-level to rise. Sea-level is currently tracking the rise inglobal SST. There are major concerns over the likely contribution that theGreenland, and possibly the West Antarctic, ice sheets might make to sea-level over the next few centuries. The processes involved in ice sheetdestabilisation are not well understood and have not been adequatelytaken into account in current ice sheet models. Historical evidence addscredibility to the possibility of rises at the upper end of and beyond theIPCC AR4 projections by 2100 and a rise of several metres within severalhundred to thousands of years. Sea-level rise will affect humans in manyways, including the potential displacement of millions of people. Displace-ment of populations and loss of coastal lands will likely lead to changes inland and resource use that have the potential to further increase climatechange.

9.5. The MOC and cooling of NW Europe

Combined together, changes in salinity and temperature alter density distri-bution, stratification and the Meridional overturning circulation with largepotential feedbacks to climate. However, there is no evidence as yet that theTHC/MOC has been changed by the observed salinity and temperaturechanges. Modelling projections predict that the MOC will reduce bybetween 0% and 50% by the end of the century, but that this will not leadto a cooling of Northwest Europe, but a slowing down of the warmingassociated with a rise in global mean temperature.

9.6. Tropical storms

The intensity of tropical storms (hurricanes, cyclones, typhoons) hasincreased by 75% in the North Atlantic and western North Pacific and aglobal increase in their destructiveness has been documented. With risingsea temperature and enhanced precipitation the area for seeding tropicalstorms may expand. These storms may feedback to climate as they have amajor impact on the mixing of the ocean. There is, however, at present, noscientific consensus on whether tropical storms will continue to increase inintensity and possibly frequency with rising global temperatures.

5 IPCC AR4 WG 1, Chapter 10.


9.7. Primary production, biodiversity and non-native species

Production of atmospheric oxygen and fixation of carbon during photo-synthesis by phytoplankton enables the Earth to support a rich diversity ofmarine life and has strongly influenced changes in climate through geologi-cal time. The many tens of thousands of planktonic species in the oceansplay a key role in ecological and biogeochemical processes that are impor-tant in the carbon cycle and climate. Within the last decade major advanceshave been made in understanding oceanic microbial diversity and ecology,but the extent to which these newly discovered microbial systems willchange and impact biogeochemical cycles and climate in a warming worldis poorly understood. Changes in the composition of different functionalgroups in the plankton can strongly impact the biological pump thatremoves carbon from the upper ocean and have been implicated as one ofthe causes of the large changes in carbon dioxide between glacial andinterglacial periods. There is limited knowledge of the spatial and temporalvariability of plankton composition and production versus recycling andexport rates in most oceanic geographical provinces. Improved understand-ing of the interactions between different types of plankton food webstructure and the export efficiency of carbon is urgently needed.

Increased inflow of warmer water from both the North Atlantic andNorth Pacific into the Arctic Ocean has contributed to reductions in sea-ice. In 1998/1999, retreat of the ice from the north of Alaska and Canadaallowed the first trans-Arctic migration of a Pacific organism (the phyto-plankton Neodenticula seminae) into the North Atlantic, for more than800,000 years. Further introductions of invasive species are expected fol-lowing the ice reduction in the summer of 2007. Such non-native speciescould have a large impact on the plankton communities, biodiversity andecosystems of the North Atlantic and the biological pump—with implica-tions for the amount of CO2 which is absorbed by the ocean from theatmosphere. Warming seawater is also allowing non-native species toextend their distributions polewards.

9.8. Oxygen

One of the most critical variables in the world’s ocean is the distribution ofdissolved oxygen (O2) which is fundamental for all aerobic life. Significantreductions in the O2 supply to the ocean interior and expansion of lowoxygen areas may result from continued anthropogenic global warming,although there may be regional increases in O2 levels. Models suggest thatdetectible changes in O2 content due to global warming may already haveoccurred. Expansion of the regions of the ocean interior that are devoid ofO2 (anoxic) will adversely affect fish and other species.


9.9. Nutrients

A range of nutrients and micro-nutrients such as iron are essential forphytoplankton growth and production. Strong regional changes in nutrientsare expected in the future dependent on variability in wet precipitation,wave storminess, expanding OMZs, increased nitrogen fixation by cyano-bacteria in tropical/subtropical waters, mixing and the depth of stratifica-tion. It is not possible at present to predict future trends in nutrients becauseof the localisation of the changes or how these regional responses will add upto a global mean and influence climate change.

9.10. Ocean uptake of carbon dioxide

The ocean carbon pumps together are possibly the second most importantfeedback to climate after rising temperatures. The ocean takes up carbondioxide (CO2) from the air through three major processes that bufferclimate change. Each of these processes has the potential to become lesseffective as global warming impacts the oceans, leaving more carbondioxide in the atmosphere, and further increasing climate change.

9.10.1. The Solubility pumpThe gas CO2 is soluble in water and enters the ocean by air–sea exchange.The solubility pump removes large quantities of CO2 from the atmosphereeach year, and stores them in the deep ocean where they cannot immedi-ately contribute to the greenhouse effect. Over �1000 years, these deepwaters are mixed back to the surface, allowing some gas to return to theatmosphere. At high latitudes, dense waters sink, transferring carbon to thedeep ocean. Warming of the ocean surface inhibits the sinking and soreduces the efficiency of this pump. Furthermore, as waters warm, thesolubility of CO2 in seawater declines, so less gas can be held in the seawaterand taken up from the atmosphere.

9.10.2. The Biological pumpCO2 is used by phytoplankton to grow. While most organic material isrecycled within the food chain, a small proportion of the plankton sinks, andcarries with it carbon from the ocean’s surface to the deep sea. In the verylong term, much of this carbon is stored in sediments and rocks, eventuallyforming oil and gas deposits. Changes in temperature, acidification, nutrientavailability, circulation, and mixing all have the potential to change theplankton productivity of our seas, and are expected to reduce the drawdownof CO2 via the Biological pump.


9.10.3. The Continental Shelf pumpWater and particles containing carbon are transferred from shallow shelf seas tothe deep ocean by this pump. Projected warmer water and higher rainfall(causing reduced salinity) will together lead to increased layering of shelf sea-waters and are expected to contribute to a decline in the efficiency of this pump.

9.10.4. The Carbonate Counter pumpThis pump provides a relatively small offset to the above effects. Manymarine animals and plants, such as some plankton and corals, use carbon tomake calcium carbonate, a building block of their protective walls andshells. By this process, carbon is ‘fossilised’, but the net growth of theseorganisms typically does not draw down CO2, but releases back a smallproportion to the water and potentially to the atmosphere, in this wayacting as a reverse pump. Acidification (see Section 9.11) in combinationwith rising temperatures is expected to have a pronounced effect on theefficiency of this pump and through dissolution of carbonate will allow theoceans, over several centuries, to take up slightly more CO2.

For CO2 to be transferred from the air to the sea, the level in air must behigher than in the surface water. There is mounting evidence that concen-trations in surface seawater have increased faster than in the air in someregions. If this trend became global in extent and continued into the future,the efficiency of oceanic carbon uptake could be expected to reduce.

Given their importance, there is an urgent need to improve understand-ing of these carbon pumps and better include them in climate modelpredictions. IPCC AR4, for example, noted that ‘‘There are no globalobservations on changes in export production or respiration’’. Of greatconcern is evidence from observations and models that the uptake of carbondioxide by the oceanic sink may be declining, and that the terrestrial sinkmay not be keeping pace with increasing emissions.

9.11. Acidification

As well as causing climate change through the ‘greenhouse effect’, carbondioxide is having a profound effect on the ocean by making seawater moreacidic (lower alkalinity). As this gas dissolves into the ocean, it reacts,forming carbonic acid and reduces the pH of seawater. The changes inacidity measured in the open ocean also appear to be extending to someshelf seas. Due to the rapid rate of acidification, the ocean is predicted to beless alkaline, within 50 years, than at any time in the past 20 million yearsand possibly since the PETM, 55 million years ago. There is concern thatocean organisms will not be able to adapt to the speed and scale of changenow underway. Among organisms expected to be most affected are someplankton (e.g. small snail-like pteropods; Fig. 1.41) and corals. These


organisms may be vital to the whole food chain, but also to the way theoceans take carbon dioxide out of the atmosphere and store it in the oceans,thus affecting the Biological pump.

9.12. A special case: The Arctic

Covered by ice for much of the year, the Arctic Ocean is strongly influ-enced by relatively small changes in sea and air temperature. Warming maychange Arctic winds, the thickness and extent of sea-ice, and the water’ssalinity by melting ice and driving higher precipitation. Alterations in eachof these may trigger large changes in regional climate within decades, withdownstream consequences for the rest of the world.

The Arctic has lost around 30% of its summer sea-ice in recent decades,with the most extreme reductions observed during the last decade. Sea-iceextent in 2007 was at a record low that was 40% below the recent long-termaverage. Despite being a cooler year than most in the past decade, the sea-ice extent in 2008 was also well below the long-term average, although itwas not as low as the 2007 record. Sea-ice in 2008 was notable in that thereis now little of the thick, old ice left, which could make the regionincreasingly vulnerable to further ice loss. The Arctic has been losing itssea-ice rapidly and it has been suggested that this may lead to a step changein the whole system due to a loss of the capping layer of fresh water in theArctic Ocean. Ice is highly reflective and returns much of the solar radiationback to space; as it melts and exposes the dark ocean surface, the waterrapidly absorbs and accumulates the incoming radiation over the long Arcticsummer. This creates a feedback that tends to accelerate ice loss and warm-ing of both sea and air, triggering further ice loss and regional warming.

Figure 1.41 A pteropod. Image from http://pubs.usgs.gov/of/2000/of00-304/htmldocs/chap11/images/pelag10l.jpg (U.S. Geological Survey).


http://pubs.usgs.gov/of/2000/of00-304/htmldocs/chap11/images/pelag10l.jpg



Model predictions for the disappearance of Arctic sea-ice during summersvary between 2013 and the end of the century. However, most climatemodels underestimate the rate of ice loss over recent decades, and eventhose that simulate recent trends suffer from deficiencies in resolution thatmay lead to an underestimate of future change. Some model results suggestthat a threshold (tipping point) has been passed in the loss of Arctic sea-ice,meaning that recent low ice conditions may persist for some time.

9.13. Methane

A warmer Arctic Ocean releases warmth back to the air, which can pene-trate into adjacent coastal areas as far as 1500 km. This can melt permafrost,and potentially lead to the release of methane stored within it. Methane is25 times more potent as a greenhouse gas than CO2, thus the release ofmethane is potentially a large feedback to climate change. The rate of releaseof this gas into the atmosphere has slowed down over the last 20 years; a ratechange that is not well understood. In 2007 the concentrations of methanein the air increased, particularly in the Arctic, suggesting a release fromArctic permafrost among other sources.

Extensive deposits of methane hydrate (methane gas trapped in an ice-like solid) are found beneath coastal Arctic seas, and within permafrost onthe adjacent land. A large release of methane from warming of marinehydrates is thought to be unlikely, unless warming causes landslides onsteep continental slopes which hold hydrates or inflow of warmer waterfrom adjacent oceans intensifies. Recently, large volumes of methane havebeen observed bubbling from the sea bed of the Laptev and East Siberianshelf seas and off Spitzbergen. It is not clear, however, if these new findingsare a response to an anthropogenic warming signal.

9.14. Greenland ice sheet

A recent accelerating reduction in the mass balance of the Greenland ice sheetmay in part be due to higher temperatures in the adjacent ocean. While theprecise threshold is not known, unless the trend in global temperature risereduces, the temperature threshold for an eventual complete melting of theGreenland ice sheet may be crossed this century.Melting of the Greenland icesheet alone could lead to 7 m of sea-level rise over thousands of years withimplications for all coastal regions around the world.

9.15. The Southern Ocean

The Southern Ocean, including the ACC, plays a critical role in driving,modifying and regulating global climate and climate change. An increase inwesterly wind speeds due, at least partly, to human influences (increases ingreenhouse gases and ozone depletion) has been observed, and a continuing


warming of the Southern Ocean and strengthening of the westerly winds ispredicted. The ocean west of the Antarctic Peninsula has warmed rapidlysince the 1950s in parallel with changes in atmospheric climate and thecryosphere. Changes in the Southern Ocean are closely connected to theproduction and melting of sea-ice, the formation of which is the largestseasonal phenomenon on Earth. Sea-ice has a major affect on the energybudget of the Earth and thus climate. A 25% decrease in sea-ice extent overthe next 100 years is predicted. The evolution of the Southern Oceanalong the coast of Antarctica is a major control on the stability of Antarcticglaciers and on the mass balance of the ice sheet as a whole. A reduction in themass balance of the northern sector of theWest Antarctic ice sheet induced bya thinning of the fringing ice shelves is most likely associated with greatersubsurface penetration of Circumpolar Deep Water onto the continentalshelf. The rates of retreat of glaciers in the Peninsula and in West Antarcticaare predicted to accelerate. The Southern Ocean is an important sink forcarbon dioxide, a sink that has been reported as possibly weakening andapproaching saturation, and which urgently requires further investigation.In the future, it is estimated that the CO2 sink in the Southern Ocean willundergo further modification. Marked changes have occurred in SouthernOcean ecosystems including a substantial decline in krill numbers. Thechanges in biodiversity, combined with the effects of acidification and risingtemperature are likely to lead to important modifications to unique Antarcticecosystems with associated feedbacks to the carbon cycle and climate.

9.16. Modelling

Pronounced changes in ocean processes are now being recorded, some ofwhich through complex feedbacksmay accelerate global warming.Models arean essential tool to help investigate these feedbacks and their role in futureclimate change. Global Climate Change models have proved to be especiallyreliable in predicting future changes in global temperature.Modelling of oceanprocesses is less advanced, however, and there are a number of generallimitations to progress in modelling feedbacks including poor data, a lack ofunderstanding of key processes and inadequate representation of the processesin models (parameterisation). Data are needed for input to and validation ofmodels; a lack of historical measurements and time series of key variables andprocesses is a major restriction onmodelling progress. To address this problemthere is an urgent need to implement an integrated global ocean observingprogramme that includes continuous time series of key ocean–climate vari-ables. Such time series need to be maintained for a sufficient length of timeto enable a climate change signal to be distinguished from internal naturalvariability (e.g. Argo, Altimetry, RAPID MOC array, ADCP arrays, CPR).

In a number of cases, models representing key ocean feedbacks thatcontribute to climate have failed to represent observations or capture


regional variation between different ocean basins, for example, the heatuptake, models used in IPCC AR4 and sea-ice models in the Arctic. Poorunderstanding of processes, inadequate representation of ocean/atmospheredrivers, a lack of inclusion of some important processes in models, scalingfactors and spatial resolution as well as a lack of measurements are likelycontributors to the failures. Some important ocean feedbacks such as thedifferent ocean carbon pumps are not well represented in GCMs to date.Some studies of mitigation options omit feedbacks from the carbon pumpsaltogether. This omission could lead to an underestimate of the rate offuture climate change, the stabilisation targets necessary to limit warmingand, thus, the measures needed to achieve mitigation.

There is no clear scientific agreement on the key processes required tomodel the role of ocean biology and microbial ecology on carbon uptake andthe production of radiatively active gases. The processes involved ingas exchange and sinking fluxes, and their parameterisation are especiallypoorly understood and yet models are very sensitive to these parameters.In particular, it is not yet clear how the complex biodiversity and functioningof microbial systems and their impact on biogeochemical cycles should beincorporated into models. In the case of acidification, open ocean modelswork well, but the models are less effective in upwelling, coastal and shelf searegions, which could be especially vulnerable to increased acidification.

Observed changes in ocean feedbacks have occurred with a globalaverage (land and sea) temperature rise of less than 1 �C. Further warmingmay increase the impacts of the oceans on climate change, and amplifyfeedbacks. Despite considerable progress in the development of ocean/climate models the above limitations mean that their output and prognosesneed to be viewed with caution. It should be stressed, however, that whilethe models are not perfect, this does not reflect on their usefulness as theyare an essential tool to look into the future.

9.17. Final concluding comments

This chapter demonstrates that the oceans are vital in regulating our climate.There is an urgent need to improve understanding of the interactionbetween the oceans and climate change and better include this in climatemodel predictions. Greater use should also be made of palaeodata to test andinform climate models.

The oceans have buffered climate change substantially since the beginningof the industrial revolution, acting as a sponge to carbon dioxide and heat fromglobal warming. While it was assumed this would continue, this chapter givesa warning—changes underway in our ocean may accelerate warming or itsconsequences to organisms, and have the potential to increase climate changeitself. In some examples, such as sea-ice loss, this process may already beunderway. In this sense, and to quote a reviewer: ‘‘The ocean strikes back’’.


Appendix: Workshop Participants

Name Organisation

Russel Arthurton LOICZ, UKUlrich Bathmann Alfred Wegener Institute, GermanyGregory Beaugrand University of Lille, FranceDiogo De Gusamao Hadley Centre, MetOffice, UKStephen Dye Marine Climate Change Impacts Partnership, UKMartin Edwards Sir Alister Hardy Foundation for Ocean

Science, UKAstrid Fischer Sir Alister Hardy Foundation for Ocean

Science, UKJacqueline Fluckiger Swiss Federal Institute of Technology,

SwitzerlandTore Furevik University of Bergen, NorwayJean Claude Gascard AOSB, iAOOS, DAMOCLES, FranceDebora Iglesias-Rodriguez

National Oceanography Centre,Southampton, UK

Sabine Kasten Alfred Wegener Institute, GermanyMike Kendall Plymouth Marine Laboratory, UKReto Knutti Swiss Federal Institute of Technology,

SwitzerlandEmily Lewis-Brown World Wide Fund for Nature, UKCecilie Mauritzen CliC, NorwayGill Malin University of East Anglia, UKCharlie Paull Monterey Bay Aquarium Research Institute, USARobin Pingree Marine Biological Association, Plymouth/PML/

SAHFOS, UKPhilip C. Reid Sir Alister Hardy Foundation for Ocean Science,

UK and University of PlymouthMike Sparrow SCAR, UKPaul Treguer University of Brest, FranceAlexander Tudhope University of Edinburgh, UKCarol Turley Plymouth Marine Laboratory, UKMeike Vogt University of East Anglia, UKCraig Wallace RAPID, UKZhaomin Wang British Antarctic Survey, UKRichardWashington

University of Oxford, UK

Richard Wood Hadley Centre, MetOffice, UK


ACKNOWLEDGEMENTS

Philip C. Reid wishes to thank especially John Raven, John Church and Wolf Berger fortheir helpful advice and encouragement throughout the production of the chapter. We arealso indebted to Richard Wood and Diogo de Gusmao for their contribution and advice onthe modelling chapter. Especial thanks are given to attendees at the workshop, who are noton the authorship or mentioned above, for their advice and discussions, Russel Arthurton,Jean Claude Gascard, Catia Domingues, Jacqueline Fluckiger, Debora Iglesias-Rodriguez,Reto Knutti, Robin Pingree, Paul Treguer, Alexander Tudhope and Carol Turley and wewish to acknowledge helpful discussions/correspondence with Nathan Bindoff, Philip Boyd,Howard Cattle, Jean-Claude Duplessy, Nick Hardman-Mountford, Graham Hosie, PatrickHyder, Richard Kirby, Doug Martinson, Steve Rintoul, Daniela Schmidt, Toby Tyrrell,Martin Visbeck, the sources of the figures, and many other unnamed colleagues. We alsowish to thank Sylvette Peplowski, Sally Bailey and Deborah Chapman from WWF whoacted as rapporteurs at the workshop.

The project to produce this chapter was started at the beginning of 2008 and formallyinitiated in March 2008 by a workshop in London funded by WWF. P. C. R. and A. F.gratefully acknowledge funding support from WWF, SAHFOS, The University of Ply-mouth and the Marine Biological Association of the United Kingdom and wish especially toacknowledge the backing and encouragement of Peter Burkill, Director of SAHFOS andassistance from Darren Stevens, SAHFOS on computing issues. P. C. R. thanks CharlesPearson, Regional Manager, NIWA Christchurch, New Zealand, for provision of facilitiesand Josh Bean, NIWA for computing support. The document was improved by the adviceand comments of Jan de Leeuw.

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C H A P T E R T W O

Vulnerability of Marine Turtles

to Climate Change

Elvira S. Poloczanska,* Colin J. Limpus,† and Graeme C. Hays‡

Contents

1. Introduction 152

2. Marine Turtle Biology and Life History 154

3. Observed and Projected Changes in Oceans and Atmosphere 159

3.1. Air and ocean temperature 159

3.2. Rainfall, storms and cyclones 160

3.3. Sea level 161

3.4. Winds and ocean currents 161

3.5. Large-scale ocean–atmosphere patterns 162

3.6. Ocean acidification 162

4. Climate Change Impacts on Marine Turtles 163

4.1. Embryos and hatchlings on nesting beaches 164

4.2. Reproductive turtles on inshore breeding grounds 169

4.3. Juveniles and adults foraging in oceanic waters 176

4.4. Juveniles and adults on inshore foraging grounds 180

4.5. Oceanic migrations 184

5. Responses to Past Climate Change 185

6. Adaptation and Resilience 187

7. Global Trends 189

8. Recommendations 189


References 191

Abstract

Marine turtles are generally viewed as vulnerable to climate change because of

the role that temperature plays in the sex determination of embryos, their long

life history, long age-to-maturity and their highly migratory nature. Extant species



* Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Cleveland,Queensland 4163, Australia

{ Environmental Sciences, Environmental Protection Agency, Brisbane, Queensland 4002, Australia{ Institute of Environmental Sustainability, Swansea University, Swansea SA2 8PP, United Kingdom

151

of marine turtles probably arose during the mid–late Jurassic period

(180–150 Mya) so have survived past shifts in climate, including glacial periods

and warm events and therefore have some capacity for adaptation. The present-

day rates of increase of atmospheric greenhouse gas concentrations, and asso-

ciated temperature changes, are very rapid; the capacity of marine turtles to

adapt to this rapid change may be compromised by their relatively long genera-

tion times. We consider the evidence and likely consequences of present-day

trends of climate change on marine turtles. Impacts are likely to be complex and

may be positive as well as negative. For example, rising sea levels and increased

storm intensity will negatively impact turtle nesting beaches; however, extreme

storms can also lead to coastal accretion. Alteration of wind patterns and ocean

currents will have implications for juveniles and adults in the open ocean. Warm-

ing temperatures are likely to impact directly all turtle life stages, such as the sex

determination of embryos in the nest and growth rates. Warming of 2 �C could

potentially result in a large shift in sex ratios towards females at many rookeries,

although some populations may be resilient to warming if female biases remain

within levels where population success is not impaired. Indirectly, climate change

is likely to impact turtles through changes in food availability. The highly migra-

tory nature of turtles and their ability to move considerable distances in short

periods of time should increase their resilience to climate change. However, any

such resilience of marine turtles to climate change is likely to be severely

compromised by other anthropogenic influences. Development of coastlines

may threaten nesting beaches and reproductive success, and pollution and

eutrophication is threatening important coastal foraging habitats for turtles

worldwide. Exploitation and bycatch in other fisheries has seriously reduced

marine turtle populations. The synergistic effects of other human-induced stres-

sors may seriously reduce the capacity of some turtle populations to adapt to the

current rates of climate change.

Conservation recommendations to increase the capacity of marine turtle popu-

lations to adapt to climate change include increasing population resilience, for

example by the use of turtle exclusion devices in fisheries, protection of nesting

beaches from the viewpoints of both conservation and coastal management, and

increased international conservation efforts to protect turtles in regions where

there is high unregulated or illegal fisheries (including turtle harvesting). Increas-

ing research efforts on the critical knowledge gaps of processes influencing

population numbers, such as identifying ocean foraging hotspots or the pro-

cesses that underlie the initiation of nesting migrations and selection of breeding

areas, will inform adaptive management in a changing climate.

1. Introduction

Climate change is one of the major threats facing our world over thecoming century and impacts on biodiversity are already being recorded(Parmesan, 2006; Rosenzweig et al., 2007; Walther et al., 2002). The IUCN

152 Elvira S. Poloczanska et al.

(International Union for Conservation of Nature) Marine Turtle SpecialistGroup through its Burning Issues assessment (http://www.iucn-mtsg.org/hazards/) recently identified global warming as one of the top five majorhazards to marine turtles globally; the other threats being fisheries impacts,direct harvesting of adults and eggs, coastal development, and pollution andpathogens. Life-history characteristics of marine turtles such as temperature-dependent sex determination, long age-to-maturity and a highly migratorynature may make marine turtles vulnerable to climate change. In this chapter,we consider the evidence and likely consequences of the potential impacts ofclimate change on marine turtles. Impacts are likely to be complex and therewill be positive as well as negative impacts; however, adverse impacts arelikely to be exacerbated by other anthropogenic-induced stressors such ascapture by fisheries and coastal pollution.

A long history of capture of adult turtles and harvesting of turtle eggs hasreduced many populations worldwide to precarious levels. Marine turtlesare iconic animals, especially given increases in eco-tourism and overseastravel, which acts to raise conservation awareness. Recent conservationefforts have resulted in a trend of increasing nesting numbers for severalpopulations (e.g. Broderick et al., 2006; Chaloupka et al., 2008a; Hays,2004; Seminoff and Shanker, 2008), but there are still a number of pressingconservation matters including climate change. For example, increasingtemperatures and rising sea levels linked to large-scale climate changes areof particular concern for future nesting success. Shifts towards greaterproportion of female hatchlings have been recorded on warming beaches(Chu et al., 2008; Glen and Mrosovsky, 2004; Hays et al., 2003a). However,earlier nesting has also been recorded at loggerhead, Caretta caretta, coloniesin Florida and the Mediterranean, which may alleviate the impact of risingtemperatures, to some degree, on hatchling sex ratios (Mazaris et al., 2008;Pike, 2009a; Weishampel et al., 2004).

Extant turtle species probably arose during the middle–late Jurassicperiod (180–150 million years ago) when the world was warmer andmore humid (Sellwood and Valdes, 2008). They have survived past shiftsin climate, including glacial periods and warm events, by probably alteringmigratory routes, redistributing breeding and foraging sites and adjustingphysiological parameters. Evidence of these can be found in contemporarypopulations. For example, in northern Australia, where temperatures areextremely high during the austral summer, flatback turtle Natator depressuspopulations breed during the winter. While on the Australian east and westcoasts, at higher latitudes and hence cooler temperatures, N. depressuspopulations from adjacent genetic stocks nest during the summer months(Limpus, 1971). The timing of peak nesting at each location thus coincideswith beach temperatures (25–32 �C) compatible with high incubationsuccess and suitable male/female hatchling ratios. The time period over

Marine Turtles and Climate Change 153

http://www.iucn-mtsg.org/hazards/



which reproductive phenology shifted is unknown, but is likely to havebeen over a time scale of thousands of years.

The question is can marine turtles adapt to future climate change giventhe rapid projected rates of global warming in the coming century? Rapidclimate change coupled with high anthropogenic impacts on turtle popula-tions, particularly pollution and high mortality through directed harvest andbycatch in fisheries, may seriously comprise the ability of turtle populationsto adapt to our changing climate. On the other hand, climate change maybenefit marine turtle populations through expansion of potential nestingand foraging areas and increased food supplies for various life stages. Impactson trophic resources and key habitats such as open-ocean gelatinouszooplankton, seagrass beds and coral reefs may be critical for marine turtles.

In this chapter, we review climate variability and change impacts on thelife stages of marine turtles in five different habitats: embryos and hatchlingson nesting beaches, reproductive turtles on inshore breeding grounds,juveniles and adults foraging in oceanic waters, juveniles and adults oninshore foraging grounds, and during oceanic migrations. We also discussthe responses of marine turtle populations to past climatic change and thepotential for adaptation to projected climate change by marine turtle popu-lations. Long-term climate-related trends in marine turtle populations aregenerally obscured by heavy exploitation historically, in addition to theeffects of current conservation efforts which are leading to recent increasesin targeted populations (Broderick et al., 2006; Chaloupka et al., 2008a;Seminoff and Shanker, 2008). We conclude our chapter by discussing thecurrent status and trends of marine turtle stocks worldwide and with somerecommendations for conservation and research.

2. Marine Turtle Biology and Life History

There are seven living species of marine turtle: flatback Natator depres-sus, green Chelonia mydas, loggerhead Caretta caretta, olive ridley Lepidochelysolivacea, Kemp’s ridley Lepidochelys kempii, hawksbill Eretmochelys imbricataand leatherback Dermochelys coriacea (Fig. 2.1). They are classified into twotaxonomic families: the Dermochelyidae, which contains only the leather-back turtle, and the Cheloniidae, which contains the other six species. All ofthese, with the exception of the flatback N. depressus, are classified as‘vulnerable’, ‘endangered’ or ‘critically endangered’ in the InternationalUnion for the Conservation of Nature (IUCN) Red List (IUCN, 2009;Seminoff and Shanker, 2008). The flatback, N. depressus, which occurs onlyin Indo-Pacific waters, is currently ‘data deficient’ for IUCN Red Listassessment purposes but is considered ‘vulnerable’ in Australian waters


(Environment Protection and Biodiversity Conservation Act, AustralianGovernment 1999) where all known nesting occurs.

Cheloniid turtles are distributed throughout the world’s tropical andsub-tropical waters, but may appear seasonally in cooler waters of the north-western Atlantic (Hawkes et al., 2007a; Morreale and Standora, 2005)or sporadically year round in cool waters of the south-western Pacific(C.J. Limpus, unpublished data). Marine turtles are generally consideredectothermic with their thermoregulatory capacity varying among speciesand with body size (Hochscheid et al., 2002; Spotila and Standora, 1985;Standora et al., 1982; Still et al., 2005). The largest turtles, adult leatherbacks,

Figure 2.1 Marine turtles: (A) loggerhead (Caretta caretta), (B) hawksbill (Eretmochelysimbricata), (C) flatback (Natator depressus), (D) green (Chelonia mydas), (E) olive ridley(Lepidochelys olivacea), and (F) leatherback (Dermochelys coriacea).


D. coriacea, display the greatest degree of endothermy (Bostrom and Jones,2007; Eckert, 2002; Frair et al., 1972; Goff and Lien, 1988; James et al.,2005a, 2007; Mrosovsky and Pritchard, 1971; Southwood et al., 2005;Spotila and Standora, 1985; Wallace and Jones, 2008; Witt et al., 2007a).Mechanisms for heat retention such as counter-current heat exchangers intheir flippers, thick body insulation and large body size enable adult leather-backs (D. coriacea) to penetrate cold, high-latitude waters (Paladino et al.,1990; Wallace and Jones, 2008).

Flatbacks, N. depressus, and Kemp’s ridleys, L. kempii, have the mostrestricted distributions with N. depressus only found in the continental shelfwaters of northern Australia, eastern Indonesia and southern Papua NewGuinea, while Kemp’s ridleys (L. kempii) occur mainly in the Gulf ofMexico and the eastern seaboard of the USA.

Marine turtle species display common life-history traits which includelong-distance migrations, natal homing, no parental care of eggs and young,and temperature-dependent sex determination in the nest (Carr et al., 1978;Meylan andMeylan, 1999). Marine turtles are long-lived and may not reachsexual maturity for many decades (e.g. Casale et al., 2003; Chaloupka et al.,2004; Limpus, 1992; Limpus and Chaloupka, 1997; Zug et al., 1997). Theyshow strong fidelity to natal and foraging areas and undertake long breedingmigrations between these regions, generally at intervals greater than 1 year(Avens et al., 2003; Bowen et al., 2004; Limpus and Limpus, 2003; Limpuset al., 1992; Luschi et al., 2003).

During nesting, females come ashore and lay eggs in nests dug above thehigh water line on sandy beaches in the tropics and sub-tropics (Fig. 2.2).Typically, a female will make repeated visits to lay multiple clutches withinone breeding season (Carr et al., 1978; Hays et al., 2002a; Limpus and Reed,1985a; Limpus et al., 1983a, 1984, 2001). Sex of the hatchlings is deter-mined by the nest temperature during the middle third of the incubationperiod, with higher temperatures producing females (see Fig. 2.3;Hewavisenthi and Parmenter, 2002; Merchant Larios et al., 1997; Millerand Limpus, 1981; Yntema and Mrosovsky, 1982). The ‘pivotal’ tempera-ture, at which a 50:50 sex ratio is produced, is around 29 �C for most marineturtle populations (Binckley et al., 1998; Broderick et al., 2002; Godfrey andMrosovsky, 2006; Hewavisenthi and Parmenter, 2000; Limpus et al., 1985;Mrosovsky, 1988; Mrosovsky et al., 1992, 2002; Yntema and Mrosovsky,1982).

Hatchlings (Fig. 2.2) disperse to open-ocean foraging areas where asjuveniles they may spend many years foraging in oceanic waters on gelati-nous and other plankton, often at ocean fronts and eddies (Bolton et al., 1998;Bowen et al., 1995; Carr, 1987; Casale et al., 2007; Parker et al., 2005; Polovinaet al., 2001; Salmon et al., 2004). The exception to this general pattern beingthe flatback (N. depressus), which remains in the continental shelf waters offnorthernAustralia (Limpus, 2008;Walker and Parmenter, 1990). The juvenile


Figure 2.2 (A) Green turtle (Chelonia mydas) laying eggs, Mon Repos, Queensland,Australia. (B) Monitoring green turtle (Chelonia mydas) nesting, Mon Repos.(C) Loggerhead (Caretta caretta) hatchlings heading to the ocean. (D) Flatback (Natatordepressus) hatchlings. (E) Tourists watch a nesting green (Chelonia mydas) turtle.


pelagic period has been termed ‘the lost years’ (Carr et al., 1978) as, untilrelatively recently, little was known of the distribution and ecology of theyoung turtles during these years. For some populations, particularly of leather-backs (D. coriacea), olive ridleys (L. olivacea) and Kemp’s ridleys (L. kempii), thisis still the case.

Different species, populations and age classes display a wide range offoraging modes. Foraging grounds of adults and large juveniles of hawksbillsE. imbricata, loggerheads (C. caretta), Kemp’s ridleys (L. kempii), flatbacks(N. depressus) and green turtles (C. mydas) tend to be in coastal waters,and the larger immature and adult turtles spend most of their time inthese foraging habitats. Hawksbills, E. imbricata, are omnivorous andforage around coral reefs and rocky outcrops, eating benthic invertebratessuch as sponges and algae, and occasionally jellyfish (Blumenthal et al.,2009; Houghton et al., 2003; Leon and Bjorndal, 2002; Meylan, 1988).Loggerheads (C. caretta) and Kemp’s ridleys (L. kempii) are generally carnivo-rous, taking invertebrates such as crustaceans and molluscs (Godley et al.,1997; Limpus et al., 2001; Plotkin et al., 1993; Seney and Musick, 2007;

Mal

e (%

)

TRT

50

29 °C Temperature

100

0

Present

Future

Pivotal temperature

Figure 2.3 Generalised scheme of temperature-dependent sex determination in seaturtles and the effect of warming temperatures. A 1:1 sex ratio is produced at the pivotaltemperature (around 29 �C); cooler temperatures produce a male bias and warmertemperatures produce a female bias. TRT is the transitional range of temperatures overwhich sex ratios shift from 100% male to 100% female. The blue shading markedPRESENT corresponds to the range of temperatures currently experienced by hypo-thetical turtle nests at a rookery over the breeding season; red shading markedFUTURE indicates nest temperatures following climate warming—the sex ratio hasshifted from male biased to female biased.


Wallace et al., 2009). Leatherbacks (D. coriacea) and eastern Pacific oliveridleys (L. olivacea) tend to forage in oceanic environments as sub-adults andadults, exploiting gelatinous plankton and planktonic crustaceans (Bensonet al., 2007; Houghton et al., 2006; James and Herman, 2001; Salmon et al.,2004; Wallace et al., 2006). In the Australasian region, olive ridleys(L. olivacea) are benthic, foraging on crustaceans and molluscs (Whitinget al., 2007). Flatbacks (N. depressus) also are carnivorous, feeding on softbodied invertebrates (Limpus, 2008). In contrast, green turtles (C. mydas)are primarily herbivorous feeding on mostly seagrass and algae (Andreet al., 2005; Brand-Gardner et al., 1999; Fuentes et al., 2006; Garnett et al.,1985; Lopez-Mendilaharsu et al., 2005; Mortimer, 1981). However,recent studies reveal C. mydas may continue to consume of gelatinouszooplankton even as adults during foraging periods along benthic coastalhabitats (Arthur et al., 2007).

3. Observed and Projected Changes in Oceans

and Atmosphere

Climate varies over spatial and temporal scales from seasonal changes todecadal or even millennial variations. The geological record reveals a positiverelationship between atmospheric CO2 concentrations and global tempera-tures (Doney and Schimel, 2007). Present-day atmospheric CO2 concentra-tions were last reached, at a minimum, 650,000 years ago (Denman et al.,2007). The Earth may now be within approximately 1 �C of maximumtemperatures of the past million years (Hansen et al., 2006). While manypatterns are evident in the global climate, what is now, unequivocal, is thatglobal climate has warmed over the past century due to anthropogenicgreenhouse gas emissions (IPCC, 2007). Owing to the inertia of theatmosphere–ocean system, temperatures will continue to rise over the nextfew decades, if not longer, regardless of any attempts at mitigation of green-house gas emissions (IPCC, 2007; Matthews and Caldeira, 2008).

Evidence for climate change manifests not only through observedwarming temperatures but also through associated changes in the ocean–atmosphere system, such as alternation of rainfall and storm patterns, risingsea level and changes in ocean salinity, all of which will impact the variouslife stages of marine turtles.

3.1. Air and ocean temperature

Average global surface temperatures have risen by 0.74 �C over the hundredyears since 1906, with warming in recent decades being the most rapid(Trenberth et al., 2007). Eleven of the twelve warmest years since records


began in 1850 (to 2006) occurred from 1995 onwards (Trenberth et al.,2007). Warm days and nights have become more frequent over most landareas over the past few decades and are projected to continue to increase infrequency while the frequencies of cold extremes are declining (IPCC,2007; Shiogama et al., 2007). The Northern Hemisphere is warmingmuch faster than the Southern Hemisphere and surface air temperaturesare rising faster over land than over the ocean (Hansen et al., 2006; IPCC,2007). Warming air temperatures may impact the hatching success andhatchling sex ratios of marine turtles globally.

Ocean temperatures have also been rising, albeit at a slower rate than airtemperatures given the large thermal capacity of the oceans. Over the last50 years, ocean temperature has risen by 0.1 �C to depths of 700 m. Oceanwarming is projected to evolve with the upper ocean warming first, thenpenetration of warming to the deep ocean by the end of the twenty-firstcentury, and particularly so in mid-latitude regions (IPCC, 2007).

3.2. Rainfall, storms and cyclones

Rainfall is highly variable both temporally and spatially, but long-termobserved trends during the past several decades are evident over manyregions linked to rising atmospheric CO2 levels (IPCC, 2007; Zhanget al., 2007). The trends show a drying of Northern Hemisphere tropicsand sub-tropics and a moistening of Southern Hemisphere tropics (Zhanget al., 2007). Tropical wet seasons are projected to get wetter, particularlyover the tropical Pacific, while dry seasons may get dryer or remainunchanged (Chou et al., 2007). As the frequency of intense rainfall increasesover many land areas, including tropical areas, so will the risk of flood events(Meehl et al., 2007). There may also be a tendency for more intense mid-latitude storms over this century and an associated increase in wave height(Meehl et al., 2007).

The intensity of cyclones has increased in some regions such as thetropical North Atlantic, the Indian Ocean and Southwest Pacific Oceans(IPCC, 2007; Saunders and Lea, 2008). A 0.5 �C rise in August–Septembersea surface temperature (SST) over the period 1965–2005 resulted in anapproximately 40% increase in cyclone activity during the storm season(August–October) in the tropical Atlantic (Saunders and Lea, 2008).Climate model projections suggest that the strength of intense storms islikely to further increase over the coming century (Bengtsson et al., 2007;Meehl et al., 2007). For example, simulations of a regional climate model forthe Cairns coastline, northeast Australia, showed that projected increases incyclone intensity can result in a storm surge event with a return period of100 years, becoming a 55-year event by 2050 and a 40-year event whensea-level rise is also considered (McInnes et al., 2003).


The global areas affected by tropical storms may widen polewards,particularly in the Southern Hemisphere (IPCC, 2007). There is evidenceto indicate a polewards shift in storm tracks has already occurred over thesecond half of the twentieth century (IPCC, 2007; Seidel et al., 2007). Thedestructive effects of cyclones, such as flooding, may, therefore, impact athigher latitudes as global temperatures warm (Isaac and Turton, 2009).

3.3. Sea level

Sea level has risen by an estimated 1.7 mm/year during the twentieth centurydue to thermal expansion of the oceans andwidespread melting in glaciers andice caps (IPCC, 2007). Sea-level rise is projected to continue but at a greaterrate than over the last several decades. The rates of sea-level rise vary betweenregions with some areas rising much faster than the global mean rise, while inother areas sea level appears to be falling. Sea levels in the western Pacific andeastern IndianOceans, where a myriad of tropical islands are found, andmanyof which contain turtle nesting beaches, are rising in accordance with theaverage global sea-level rise (Church et al., 2006). The differences in sea-levelrise among regions depend largely on regional hydrodynamics and geology.Low-lying, small islands, such as coral atolls, are considered ‘especially vulner-able’ to sea-level rise and extreme events, particularly in the Pacific, althoughstudies have indicated some islands may bemorphologically resistant (Mimuraet al., 2007). Generally, coral atoll islands are low-lying with the majority ofland lying less than 2m abovemean sea level, and are thus vulnerable to stormswhich can redistribute large quantities of sand and rubble so eroding orbuilding shorelines (Woodroffe, 2008). Islands which have lithified sedimentsand contain high vegetative cover may be more resilient than unconsolidatedor unvegetated islands (Woodroffe, 2008).

Large storm surges and tidal surges can be extremely destructive to low-lying coastlines and magnify effects of sea-level rise (Zhang et al., 2004).Sandy beaches are dynamic systems, undergoing continual processes oferosion and accretion (Short, 2006; Zhang et al., 2004) as sea levels andocean climate alter. As long as beaches can evolve naturally, there should bea continuum of nesting beaches of marine turtles on regional scales. How-ever, beaches that are trapped in a ‘coastal squeeze’ between human devel-opments and climate change will be least resilient, especially considering thepresent-day recessional nature of the majority sandy beaches globally (Fishet al., 2005; Jones et al., 2007; Schlacher et al., 2007; Zhang et al., 2004).

3.4. Winds and ocean currents

Rising temperatures will affect atmosphere and ocean circulation. Nosignificant global trends in marine wind speeds have been identified butregional trends are apparent in the tropics and extratropics (regions between


30� and 60� latitude from the equator) (IPCC, 2007). A polewards shift andstrengthening of the westerly wind belts, driven by rising atmospheric CO2

concentration, has resulted in a strengthening of the East Australian Current(EAC), which carries tropical water from the Coral Sea, and an enhance-ment of warming rates in the Tasman Sea, impacting marine fauna in thisregion (Cai, 2006; Cai et al., 2005; Hill et al., 2008; Poloczanska et al., 2007).The Kuroshio Extension current in the western North Pacific, an importantforaging hotspot for juvenile turtles (Polovina et al., 2004b, 2006) hasincreased and moved southwards after 1976, this shift being linked tospin-up by the sub-tropical wind in the North Pacific influencing thewind-driven sub-tropical ocean gyre (IPCC, 2007; Sakamoto et al., 2005).There is no evidence to date for a trend in the strength of the Gulf Stream inthe North Atlantic, a subject of much public deliberation (IPCC, 2007).

3.5. Large-scale ocean–atmosphere patterns

The El Nino-Southern Oscillation (ENSO), a large-scale ocean–atmospherephenomenon, has profound influence inter-annually on regional seas butwith teleconnections to global climatology. Described simply, ENSO eventsfluctuate irregularly between two phases: El Nino and La Nina although eachENSO event evolves slightly differently. There are well-documented impactsof ENSO on atmospheric and ocean climates and ecosystems. For example,during El Nino years seasonal rainfall increases over the central and eastern-central Pacific Ocean, and decreases in the Western Pacific and Indian Oceanwith a weakening of monsoons in Asia. The ENSO signal has been found inmarine ecosystems at all trophic levels from phytoplankton and algae (Turket al., 2001); to tropical corals (Baker et al., 2008; Grottoli and Eakin, 2007),marine turtles (Limpus and Nicholls, 1988; Saba et al., 2007) and predatoryfish (Lehodey et al., 1997).

Historically, El Nino events occur every 3–7 years but El Nino eventsappear to have become dominant since the 1976–1977 ‘climate shift’ whenglobal temperatures started to rise rapidly due to anthropogenic forcing bygreenhouse gas emissions (IPCC, 2007; Power and Smith, 2007). Whileclimate models project a weak shift towards ‘El-Nino-like’ conditions infuture climate there is no consistent indication of changes in amplitude andintensity (IPCC, 2007).

3.6. Ocean acidification

Ocean acidification is not a direct effect of climate change but is a conse-quence of fossil fuel CO2 emissions, which are the main driver of recentclimate change (see Denman et al., 2007). The oceans are a major buffer ofanthropogenic CO2 emissions absorbing over 40–50% in the past 200 years(Raven et al., 2005). Open-ocean surface waters are slightly alkaline with an


average pH of around 8.2 (Raven et al., 2005). The average pH of theoceans has lowered by about 0.1 units, representing a 30% increase inhydrogen ion concentration, since 1750 (around the advent of the IndustrialRevolution) when anthropogenic emissions of CO2 into the atmospherestarted to increase substantially. The ocean surface is projected to acidify byup to 0.5 units over the twenty-first century (Caldeira and Wickett, 2003,2005). The pH decrease over the coming centuries may be greater than anychanges over the past 300 million years as inferred from the geologicalrecord (Caldeira and Wickett, 2003). Acidification leads to a decrease in thesaturation state of calcium carbonate and a reduction in the depth belowwhich calcium carbonate dissolves, thus impacting biological calcificationrates (Orr et al., 2005; Riebesell, 2004).

In waters under-saturated with respect to calcium carbonate, biologicalcalcification rates decrease. For example, calcifying plankton shows dissolu-tion, deformation and/or reduced calcification of shells and liths in under-saturated marine waters (Engel et al., 2005; Moy et al., 2009; Riebesell et al.,2000). Reduced calcification with increased acidity has also been shown inmolluscs (Gazeau et al., 2007), coralline algae ( Jokiel et al., 2008; Martin andGattuso, 2009), echinoderms (Clark et al., 2009; Dupont et al., 2008) andreef-building corals ( Jokiel et al., 2008; Silverman et al., 2009). Muchconcern has been raised over the severity of the threat of ocean acidificationto the survival of coral reefs; by the end of this century all coral reef systemsglobally may display net dissolution of carbonate with deleterious conse-quences for coral ecosystems and coastal protection (Hoegh-Guldberg et al.,2007; Silverman et al., 2009).

Ocean acidification may have far reaching impacts on ocean biodiversitybeyond reduced biological calcification rates, depressing metabolisms andimpacting physiologies of species ranging from invertebrates (Clark et al.,2009; Ellis et al., 2009; Kurihara, 2008) to fish (Munday et al., 2009).Increased dissolution of CO2 will increase physiological stress on organismssuch as dissolved oxygen levels decrease and metabolic rates and physiologi-cal pathways are affected (Ishimatsu et al., 2005; Portner et al., 2005; Ravenet al., 2005; Wilson et al., 2009). There is potential for the widespreaddisruption of marine food chains and ecosystems (Fabry et al., 2008).

4. Climate Change Impacts on Marine Turtles

Climate change manifests in biological systems as changes in thedistributions and abundance of species, alteration of phenology such asearlier occurrence of spring and other events, and the lengthening ofvegetative growing seasons. Polewards distribution shifts consistent withrecent warming have been recorded in many marine species ranging from


plankton to fish (Beaugrand et al., 2002; Edwards, 2004; Mieszkowska et al.,2005; Perry et al., 2005) and phenological shifts are also evident in marinesystems (Chambers, 2004; Edwards and Richardson, 2004; Mackas et al.,1998). Climate change will impact all life stages of marine turtles(Table 2.1).

4.1. Embryos and hatchlings on nesting beaches

4.1.1. Air temperatureA major concern for marine turtles with respect to the effects of globalwarming is the impact on hatchling sex ratios, size and quality, and thereforeon population dynamics (e.g. Booth and Astill, 2001a; Burgess et al., 2006;Glen et al., 2003; Godley et al., 2002a,b; Hewavisenthi and Parmenter,2001; Mazaris et al., 2008). The temperature range over which sex ratiosshift from 100% male to 100% female varies between marine turtle speciesand populations, but in general the range lies between 1 and 4 �C (Wibbels,2003). Small changes in temperature close to the pivotal temperature(�29 �C) can result in large changes in the sex ratio of hatchlings(see Fig. 2.3; Glen and Mrosovsky, 2004; Janzen, 1994; Limpus et al., 1985;Yntema and Mrosovsky, 1982). This suggests that warming of a couple ofdegrees centigrade, well within the warming expected over the comingcentury, can potentially result in a large shift in sex ratios. Air temperaturesat many turtle nesting beaches worldwide have already warmed to, or areclose to, all female-producing temperatures (e.g. Antigua, Caribbean: Glenand Mrosovsky, 2004; Ascension Island, South Atlantic: Hays et al., 2003a;Australasia, Western Pacific: Chu et al., 2008). As global temperatures rise, theambient surface air temperatures at many turtle nesting sites globally willwarm (Fig. 2.4) thus reducing or eliminating the likelihood of males.

There is evidence to indicate, however, that turtles may not be asvulnerable to warming temperatures as first anticipated. Some nestingbeaches have persisted with strong female biases over a few decades oreven longer (Broderick et al., 2000; Godfrey et al., 1999; Hays et al.,2003a; Marcovaldi et al., 1997; Reed, 1980). There is no evidence to datethat a low production of male hatchlings has resulted in a low reproductivesuccess within populations (e.g. Broderick et al., 2000; Glen andMrosovsky, 2004), although it is possible that the long-term populationdeclines due to exploitation and other factors may mask such effects.Population units may also span many rookeries, so although individualnesting beaches may be female-producing, other beaches within the regionmay produce the necessary males and conservation of these beaches maybecome increasingly important as temperatures warm (Hawkes et al., 2007b;Hays et al., 2003a). Furthermore, temperatures will fluctuate during thenesting seasons so may be below pivotal temperatures for at least some of theseason (Godfrey et al., 1996; Mrosovsky and Provancha, 1992; Reed, 1980).


Table 2.1 Summary of marine turtle life stages, habitat and potential major climate change impacts on the different life stages

Turtle life

stage

Habitat (and

distribution)

Warming air

and ocean

temperatures

Alteration

of rainfall,

storms and

cyclones

Rising

sea

level

Alteration

of winds

and ocean

currents

Alteration of

large-scale

ocean–

atmosphere

patterns

Ocean

acidification

Incubation

and

hatching

Sandy beaches in the

tropics and sub-

tropics

pAir

p p p

Breeding

and

nesting

Coastal waters and

sandy beaches in

the tropics and

sub-tropics

pOcean

p p p

Oceanic

juvenile

and

adults

Open ocean, tropics

to cool-temperate

latitudes

pOcean

p p p

Neritic

juveniles

and

adults

Coastal and shelf

waters, tropics to

temperate

latitudes

pOcean

p p p p

Migrations Shelf seas and open

ocean, hundreds

of kilometres to

across ocean

basins

pOcean

p p

The propensity for female biases and likelihood of declining maleproduction for some populations raises theoretical questions about theevolutionary significance of temperature-dependent sex determination(Godfrey et al., 1999; Hulin and Guillon, 2007; Hulin et al., 2009;Mrosovsky and Provancha, 1992; Reece et al., 2002; Wibbels, 2003), andas well as the importance for population dynamics of polyandry (multiplepaternity) observed in some species to date (Lee and Hays, 2004;Theissinger et al., 2009; Zbinden et al., 2007). However, data series forhatchling production tend to be short or patchy and sample sizes small.Some of the longest data are for marine turtles nesting in the south-westernPacific over the last quarter century. These reveal long-term, highly skewedsex ratios towards females [hawksbill turtles (E. imbricata): Limpus andMiller, 2008; green turtles (C. mydas): Limpus, 2009] or towards males[loggerhead turtles (C. caretta): Limpus and Limpus, 2003]. Resolving suchtheoretical challenges may become increasingly important as global

30

35

30

25

20

15

10

5

35

30

25

20

15

10

5

350300250200150100500

350300250200150100500

−40

−30

−20

−10

0

10

20

30

40

A

B

−40

−30

−20

−10

0

10

20

30

40

20

20

25

25

25

3030

30

25

202020

25

30

30

25

20

25

20

20

20

20

30

3030

20

20

20

25

25

25

25

25

25

Figure 2.4 Mean annual surface air temperature projections for (A) 2001–2010 and(B) 2091–2100 from CSIRO Mk 3.5 General Circulation Model (GCM) under green-house gas emission scenario SRES A2. The 20�, 25� and 30� contours drawn. GCMprojections downloaded from the IPCC data hosted by PCMDI and processed atCSIRO marine research. Locations of major nesting sites for loggerheads (Carettacaretta), hawksbills (Eretmochelys imbricata) and leatherbacks (Dermochelys coriacea)(white dots) taken from maps printed by SWoT (2005, 2006, 2007). Full citations foreach data point are given in SWoT (2005, 2006, 2007).


temperatures warm. We suggest concerns should be raised if sex ratios forregional stocks, that is, the sex ratio across all nesting beaches for a particularstock, approach 1:4 (male to female). Urgent work is also needed toestablish the breeding periodicity of male and female turtles. There hasbeen the suggestion that males may return to breed (the remigrationinterval) more frequently than females which generally only breedevery 2–5 years depending on the population. Shorter remigration ratesby males might help balance the sex ratios on the breeding groundscompared to hatchling sex ratios. To date, there has been little targetedwork on males.

The likelihood of males being produced is also determined by variationsin localised factors such as sand albedo, sand grain size and vegetative coverwhich produce small-scale differences in thermal properties of nesting areas(Booth and Astill, 2001b; Hays et al., 2001a, 2003a; Hewavisenthi andParmenter, 2002; Loop et al., 1995; Speakman et al., 1998), in addition toenvironmental factors such as rainfall (see below). For example, Mon Reposbeach on the mainland in south Queensland has brown sand producespredominantly female loggerhead (C. caretta) hatchlings while the whitesands of nearby (�150 km) coral cay islands, such as Heron Island, producemostly male hatchlings (see Fig. 2.5A and B; Limpus et al., 1983b). OnHeron Island itself, the northern beach is warmer at nest depth than themore shaded southern beach and hence green turtle (C. mydas) hatchlingshave a female bias from the northern beach and a male bias from thesouthern beach (Booth and Freeman, 2006; Limpus et al., 1983b). It willtake temperature shifts of several degrees to change these male-producingbeaches into beaches producing 100% female hatchlings. Beaches of con-trasting sand colour within a population nesting regions are also found inother areas such as on Ascension Island (see Fig. 2.5C; Hays et al., 2001a).

4.1.2. Rainfall, storms and cyclonesTurtles tend to nest just above the high water mark but cyclones, stormsurges and heavy rainfall can inundate nests or erode sand dunes resulting insignificant nest and egg loss (Edminston et al., 2008; Foley et al., 2006; Pikeand Stiner, 2007a; Ragotzkie, 1959; Whiting et al., 2007; Xavier et al.,2006). Populations of marine turtles with nesting seasons that overlap withstorm seasons will be most vulnerable to projected increases in stormintensity (Pike and Stiner, 2007a,b). The expected polewards expansion oftropical storm regions (Seidel et al., 2007) will increase impacts on popula-tions nesting at higher latitudes. Rising sea levels, increases in wave heights,coastal erosion and increased storm intensities may all act to increase the riskof tidal inundation of nests at higher beach levels.

Heavy rainfalls, such as those caused by storms and cyclones, may act tore-dress the balance in sex ratios through a cooling effect on sand tempera-ture (Reed, 1980). Rainfall is accompanied by a drop in sand temperatures


and it has been shown that protracted rainfall can have a marked, althoughshort-term, cooling effect on nests (Booth and Freeman, 2006; Gyuris,1993; Houghton et al., 2007; Loop et al., 1995), skewing sex ratios towardsmales if coinciding with critical periods for sex differentiation (Godfreyet al., 1996; Houghton et al., 2007; Reed, 1980). For example, a significantnegative relationship between monthly rainfall and sex ratios has beenshown for leatherbacks, D. coriacea, and green turtles, C. mydas, nesting inSuriname (Godfrey et al., 1996). In general, a reduction in tropical rainfallglobally is projected over the coming century which coupled with risingtemperatures may exacerbate female biases in hatchling sex ratios. Regionalincreases, such as that projected for summer rainfall in north-westernAustralia (Nicholls, 2006), or short-term extreme increases in rainfall duringstorm events, may act to cool nests, if nesting coincides with rainfall andhence increase male production from otherwise female-producing beaches(Reed, 1980).

Figure 2.5 Contrasting sand colours of beaches within nesting regions of marineturtles in (A, B) the southern Great Barrier Reef and (C) Ascension Island. (A) MonRepos beach, mainland southern Queensland, Australia. (B) Heron Island, southernQueensland, Australia. (C) Sand from Long Beach, Ascension Island (left) and NorthEast Bay beach, Ascension Island (right).


4.1.3. Sea levelCoupled with increases in storm intensity, rising sea levels may resultsin increased risk of tidal inundation or destruction of turtle nests on low-profile beaches, thereby reducing population reproductive success(see above). Nesting beaches backed by coastal developments or salt marshesand lagoons that hindered beach evolution may be at most risk from risingsea levels (Fish et al., 2005, 2008). Where the area of beach available fornesting is substantially reduced, turtles may be forced to dig nests in beachzones that are sub-optimal for hatching success, for example in low regionswith high salt-water inundation risk. Nesting area reduction may also resulton subsequent increases in nesting density, thus increasing the risk of nestdestruction during digging of neighbouring nests and the risk of predation(Mazaris et al., 2009). If nest density increases the likelihood of a disturbanceimpacting a larger proportion of nests on the beach may increase.

4.1.4. Large-scale ocean–atmosphere patternsThe large-scale atmospheric patterns such as El Nino influence local andregional climatology, such as the tropical monsoon season in the northernIndian Ocean. Any alteration in the pattern and intensity of El Nino eventswill impact turtle nests through changes in rainfall, temperature and stormregimes.

4.2. Reproductive turtles on inshore breeding grounds

4.2.1. Air and ocean temperatureAir temperatures directly affect nest incubation temperatures and thereforehatchling sex ratios (see above) and hatchling production. Nest tempera-tures are modified by factors such as the presence of vegetation and nestdepth, so the nesting choices of females will influence hatchling sex ratios(e.g. Booth and Astill, 2001b; Foley et al., 2006; Hays et al., 2001a; Kameland Mrosovsky, 2006; Speakman et al., 1998).

Within a breeding year, successive nests may be clustered on the beach,but there is little evidence this represents fidelity to a specific beach area(Hays et al., 1995; Kamel and Mrosovsky, 2004; Limpus et al., 1984;Nordmoe et al., 2004; Xavier et al., 2006). Fidelity to beach zones such asdune areas or forest edges rather than specific beach regions has been shownfor some populations but not for others, and it is unknown if such choicesare genetically determined (Garmestani et al., 2000; Kamel and Mrosovsky,2006; Nordmoe et al., 2004; Pfaller et al., 2009). Hawksbills, E. imbricata,have been shown to consistently select the same beach area for eachsuccessive nesting (Mrosovsky, 2006) but there is a lack of evidence tosuggest some individuals in the population are genetically programmed toconsistently nest in ‘poor’ areas (Pike, 2008a). Turtles are likely to use


multiple environmental cues during the multiple phases of the nestingprocess which includes emergence, beach crawls and nest site selection(Mazaris et al., 2006). There is little evidence that females will shift nestinglocations on beaches in response to the local environment; for exampleselecting heavily vegetated sites in warmer years (Hays et al., 1995; Loopet al., 1995; Mazaris et al., 2006; Tiwari et al., 2005; Weishampel et al., 2006)although loggerhead (C. caretta) females with nesting experience have beenshown to select a higher proportion of successful nest sites on a beach thanunexperienced females (Pfaller et al., 2009).

Alteration of nesting dates may mitigate effects of warming temperatureson embryos (Kamel and Mrosovsky, 2004; Mazaris et al., 2008; Morjan,2003). Shifts in nesting dates and other spring/early summer events havebeen extensively recorded in Northern Hemisphere birds, butterflies,amphibians and fish (Parmesan, 2007; Root et al., 2003; Rosenzweiget al., 2007). Correlations between peak nesting date and spring (April andMay) SSTs were found in populations of loggerheads, C. caretta, nesting attwo beaches in Florida, USA (Pike et al., 2006; Weishampel et al., 2004) andat a beach in North Carolina (Hawkes et al., 2007a). Median nesting date onthe beaches in Florida has advanced by around 8–10 days over 15 years andappears correlated with warming May SSTs, although these warming trendswere apparently not significant (Pike et al., 2006; Weishampel et al., 2004).Earlier nesting with significant increasing SST has been shown in logger-heads,C. caretta, in theMediterranean, with first nesting emergence advanc-ing by 17 days over 19 years (Mazaris et al., 2008). Egg production may beresource limited in C. caretta (Broderick et al., 2003) which may account forthe shorter nesting seasons recorded for this species in warmer years whenfirst laying commences earlier (Pike et al., 2006).

Turtles aggregate on breeding grounds before nesting commences for anumber of weeks or longer (Fossette et al., 2007; Hays et al., 2002b; Myersand Hays, 2006). Feeding while in these breeding aggregations and duringthe subsequent inter-nesting phase is at least minimal andmay even be absent(Limpus et al., 2001; Tucker andRead, 2001).Nevertheless, temperatures onbreeding grounds can directly affect female physiology, for example byincreasing metabolic rates (Hamann et al., 2003; Kwan, 1994; Sato et al.,1998). The shorter inter-nesting intervals observed during warmer years aresuggestive of increased metabolic rates and may result in shorter nestingseasons for some populations with highly seasonal nesting (Hays et al.,2002a; Mrosovsky et al., 1984; Pike et al., 2006; Sato et al., 1998).

However, nesting phenologies are most probably influenced by thegeographic position of nesting beaches. At present, turtle nesting sitesappear to be constrained by an annual mean surface air temperature ofaround 25 �C in the Southern Hemisphere and around 20 �C in theNorthern Hemisphere (Fig. 2.4). Nesting in the cooler Northern Hemi-sphere regions, such as the Mediterranean and Japan, is highly seasonal


taking place during the summer when seasonal mean surface air tempera-tures are greater than 25 �C and air temperatures are likely to be above thepivotal temperature for balanced sex ratios (�29 �C) for at least some of thisperiod. For example, in Sarawak, Malaysia (latitude� 3 �N) where monthlyaverage maximum air temperatures are above 29 �C all year, green turtles,C. mydas, nest year round with a peak in July–September. In Cyprus(latitude� 35 �N)C. mydas nesting is concentrated largely within 4 months(May–August) when monthly average maximum air temperatures reach24–34 �C so even at these cooler, higher latitudes, sex ratios can befemale-biased. Data loggers deployed in turtle nests on Cypriot beacheshave recorded temperatures that range from 25 to 33 �C depending on sandalbedo and date of egg-laying with a prevalence at higher temperatures(Godley et al., 2001; Hays et al., 2001a). Populations of turtles breeding atnorthern hemisphere, higher latitude regions have thus adapted to thestrong seasonality in temperatures.

Adaptation to strongly seasonal temperature regimes is evident on otherlife-history stages (discussed further below) of turtles in northern hemi-sphere waters, with feeding migrations to higher latitudes during warmermonths and dormancy as a response to low temperatures recorded for turtlesin the Atlantic and Mediterranean.

Warming temperatures may lengthen nesting seasons, even if nestingseasons of individuals are shortened due to increased metabolic rates,provided other environmental conditions, such as rainfall intensity, remainfavourable. Warming temperatures may also expand availability of favour-able breeding habitat for marine turtles (see Fig. 2.4), as beaches outsidepresent-day high-latitude nesting boundaries warm (provided suitable nest-ing habitat is available). Although turtles show natal fidelity this tends to beto wider regions rather individual beaches within the region. Once a femaleselects an area during first breeding, she will show strong fidelity to that area,though not necessarily to individual beaches within the area. Turtles nestingon highly dynamic coastlines where beaches and sandbars accrete and erodeover short time times (years to decades), such as Suriname, French Guianaand deltas in Myanmar, may regularly shift nesting following natural beachmodification or colonise newly formed nesting habitat (Fossette et al., 2008;Kelle et al., 2009; Thorbjarnarson et al., 2000). Further, turtle nesting issporadically reported, in very low numbers, from beaches where nesting haspreviously been unrecorded (e.g. Alava et al., 2007; Lima et al., 2003; Tomaset al., 2008) although in some cases this may be due to poor reporting ratherthan colonisations (Petro et al., 2007). Loggerheads (C. caretta), green turtles(C. mydas) and leatherbacks (D. coriacea), in particular, nest sporadically onbeaches at higher latitudes outside major rookeries (e.g. Soto et al., 1997).For example, loggerheads (C. caretta) are recorded nesting regularly in lowdensities on beaches in southern Queensland and northern New South


Wales, Australia that have been too cool to have produced females withinthe last 100 years (C.J. Limpus, unpublished data).

So how will turtle nesting populations shift with warming temperatures?Two mechanisms may come into play (Fig. 2.6): First, a gradual warming oftemperatures may result in the warmest areas becoming all female producing(if not already), with an increased probability of females on previously coolbeaches. High temperatures could also increase hatchling mortality (so aslow population decline may occur at the warmest beaches). However,given many turtle populations already operate with female-biased sex ratios,populations may persist in these regions and a gradual expansion of breedingsuccess may occur at cooler distributional edges of the nesting range.Secondly, inter-annual variability in warming temperatures may also pro-duce ‘pulses’ of females on cooler beaches during ‘hot’ years or vice versa.

Tim

e

Warm year

Present

TropicsSub-tropicsWarm temperate

Figure 2.6 Potential changes in turtle nesting populations with warming temperaturesover generational time at three latitudes: tropics, sub-tropics and warm temperate,showing trends in nesting females (large turtles) and hatchlings (small turtles). Theproportion of male hatchlings (blue) declines as temperatures warm. At the lowerlatitude (warm-temperate) rookeries, pulses of females (in box) are produced duringextreme warm years (shown) while cool years will produce pulses of males (notshown).


4.2.2. Rainfall, storms and cyclonesMarine turtles nest on tropical beaches where intense rainfall can occurduring summer months, particularly in monsoonal regions, and nesting atmany colonies overlaps with tropical storm and cyclone seasons. Timing ofnesting is probably determined by climatic pattern of the nesting location,for example whether rainfall is seasonal and predictable or seasonal butunpredictable and heavy (monsoonal rainfall in the wet–dry tropics; seeShine and Brown, 2008) coupled with temperature regimes and otherenvironmental cues. Prolonged rainfall can lower nest temperatures(Houghton et al., 2007) but may also submerge or destroy nests (Foleyet al., 2006) and can affect sand stability. At Ascension Island, where the sandtends to be very dry and unstable, therefore unsuitable for digging, nestingoccurs during the wettest months (Mortimer and Carr, 1987). In addition,turtle eggs require certain levels of moisture in the sand, depending onspecies, to avoid desiccation (Bustard and Greenham, 1968; Limpus et al.,2001; Mortimer, 1990). Interestingly, the hydric environment appears tohave little influence on the hatching success of flatback, N. depressus, eggswhich nests on the generally arid, tropical Australian coastline (Hewavisenthiand Parmenter, 2000, 2001).

At immediate timescales, rainfall may directly influence female nestingbehaviour. Heavy rainfall may render nest sites unsuitable for digging or eggincubation or may mask cues that trigger female emergence. During intenserainfall events, coastal waters are often turbid and salinity is reduced. Somepopulations of olive ridley turtles, L. olivacea, display mass nesting eventsknown as ‘arribadas’ when females emerge synchronously to lay eggs.L. olivacea arribadas in Costa Rica have been found to postpone mass nestingduring periods of heavy rainfall (Plotkin et al., 1997). In contrast, loggerheadturtles (C. caretta) nesting in Florida, USA, were shown to increase nestingactivity during periods of heavy rainfall (Pike, 2008b). The actual benefitsoccurred by nesting during rainfall periods are unclear and it is likely thatthere are a number of environmental cues that drive nesting emergence.

The destructive effects of storms, cyclones and heavy rainfall are mostlylikely to be directly on the nests and eggs (see above) and on beach nestinghabitat. Storms and cyclones can be highly destructive causing rapid erosionof beaches and dune systems behind the foreshore and loss of aquaticvegetation or coral reef destruction (Edminston et al., 2008; Thom andHall, 1991; Woodroffe, 2008). New beach can also be formed during theseevents (Woodroffe, 2008). Projected increases in severe storms and cyclonesand increases in significant wave height are expected to impact sandybeaches globally, particularly when coupled with other anthropogenic influ-ences (Nicholls et al., 2007). For example, coastal development, such as seawalls and dune destruction, can reduce the natural resilience of beach systemsto disturbance events (Brown and McLachlan, 2002; Jones et al., 2007;


Nicholls et al., 2007; Schlacher et al., 2007). Turtle nests on beaches withhigh coastal development and burgeoning human populations (e.g. CentralAmerica: Tomillo et al., 2008; India: Mohanty et al., 2008; Indo-Asia:Hamann et al., 2006) are likely to be most at risk. Remote nesting beaches,such as many of the mainland nesting sites throughout Northern Australiaor on south Pacific islands, are likely to be more resilient assuming theintegrity of associated ecosystems such as coral reefs and seagrass beds are notimpaired.

4.2.3. Sea levelSea-level rise may also be a major threat for turtle breeding beaches,particularly on beaches where coastal development acts as a barrier con-straining landward movement of beaches or hindering natural accretion ofbeach material and the evolution of beach morphology (Fish et al., 2005,2008; Jones et al., 2007; Nicholls et al., 2007). It is suggested that thedynamics of shoreline systems means the horizontal recession of sandybeaches can be much more rapid (50–100 times) than vertical sea-levelrise, although evidence is generally lacking in this area (see Jones et al., 2007;Nicholls et al., 2007). However, there may be little change to beaches,especially those with an extensive dune system, other than a landwardmigration ( Jones et al., 2007).

Sandy beaches are highly dynamic systems undergoing periods of accre-tion and erosion; however, themajority of theworld’s beaches have retreatedover the past century (Nicholls et al., 2007). Sea-level rise may not be theprimary driver of these retreats as alteration of wind patterns, river inflow andoffshore bathymetric changes can cause beach erosion (Nicholls et al., 2007).Turtle nesting beaches in regions with high costal development, whether forindustry, coastal defence, habitation or tourism, may be most stronglyimpacted. For example, a 0.5-m rise in sea level could lead to the loss of32% of total beach area in the Netherlands Antilles, Caribbean, and 26% ofbeach area in Barbados with the most vulnerable beaches being those thatback onto salt lakes and coastal developments (Fish et al., 2005, 2008).Prohibiting construction within 30–50 m of beaches in Barbados couldsubstantially reduce loss of Hawksbill (E. imbricata) nesting beach areaalthough losses on some beaches may still be severe (Fish et al., 2008).

Sea-level rise may result in a reduction or loss of small islands, particu-larly in the Pacific (Mimura et al., 2007). Interactions with adjoiningecosystems may be particularly important in maintaining resilience ofthese islands to rising sea levels. For example, the integrity of the surround-ing coral reefs is important for the shoreline protection of low-lying islandson coral atolls as the reefs dissipate wave energy, thus helping reduce coastalerosion (Sheppard et al., 2005). Declines in reef health through pollution,eutrophication, over-exploitation and fishing, warming temperatures (coralbleaching) and increasing cyclone intensity, may accelerate coastal erosion


of small tropical islands (Mimura et al., 2007), thereby impacting turtlebreeding beaches.

4.2.4. Large-scale ocean–atmosphere patternsThe number of nesting turtles can vary considerably year to year with thelargest inter-annual variations generally found in the herbivorous greenturtle (C. mydas) populations (Broderick et al., 2001; Limpus et al., 2001).There is evidence of large-scale environmental forcing on numbers ofnesting turtles at widely separated rookeries. These may be a reflection ofwide-scale ocean–atmosphere forcing such as the ENSO, although theexact mechanisms remain to be determined (Balazs and Chaloupka, 2004;Chaloupka, 2001; Chaloupka and Limpus, 2001; Limpus and Nicholls,1988; Saba et al., 2007; Solow et al., 2002). An example illustrating thisidea is that the numbers of nesting green turtles,C. mydas, at rookeries in thewestern Pacific have been correlated with ENSO with an 18–24 month lag,with the highest numbers following El Nino events (Chaloupka, 2001;Limpus and Nicholls, 1988).

The numbers of turtles breeding each year are likely to be drivenby environmental conditions on foraging grounds. Turtles are capitalbreeders—they deposit fat reserves that can be mobilised later for reproduc-tion (Hamann et al., 2003; Kwan, 1994). Vitellogenesis, the process bywhich egg yolks are formed, commences at least 8–10 months before thebreeding season and can partly explain the lag between environmentalsignals and breeding numbers (Hamann et al., 2003). The cues to initiatevitellogenesis are unknown but could be environmental such as thresholdtemperatures or genetic factors such as an energy ‘threshold’ where breedingis initiated only when the turtle has acquired a large enough energy store tosustain itself over the breeding period and breeding migration (Hamannet al., 2003; Hatase and Tsukamoto, 2008). ENSO affects temperature,rainfall and storm patterns over wide Pacific regions but there can beconsiderable variation in these environmental signals within a region.Further, other large-scale climate modes, such as Indian Ocean Dipole, maydominate signals in some regions. These low frequency climate signals cansynchronise breeding of turtles across widely distributed foraging grounds.

Females in a nesting area may have migrated from widely spaced forag-ing areas, which raises questions as to which cues are operating to triggerbreeding and how are females responding to these cues (Hamann et al.,2003). Certainly, there is some evidence of differing initiation dates formigration for females from different foraging areas that utilise the samenesting region (Miller and Limpus, 1981).

Peak nesting of leatherback, D. coriacea, turtles in Costa Rica has beenshown to have a strong ENSO signal suggesting oceanographic conditionson offshore foraging grounds are influencing female nesting (Saba et al.,2007, 2008). Peak nestings were associated with the high surface


productivity of oceanic, foraging regions that develops during La Ninaevents and following termination of El Nino events. It has been suggestedthat recent increases in green turtle, C. mydas, nesting populations in thesouthern Great Barrier Reef may be attributable to concurrent increases inthe frequency of ENSO anomalies (Chaloupka and Limpus, 2001). Thebreeding season of austral summer 1998/1999 was one of the largest onrecord (Dethmers et al., 2006; Limpus et al., 2003). This record breedingfollowed the 1997–1998 ‘super El Nino’, which led to 1998 being thewarmest year (between 1856 and 2005) for SSTs (Trenberth et al., 2007).Other biological impacts of this super El Nino included the mostsevere global episode of mass coral bleaching that has occurred to date(Hoegh-Guldberg, 1999).

4.3. Juveniles and adults foraging in oceanic waters

4.3.1. Ocean temperatureAdult turtle distribution throughout the global ocean is generally limited byminimum temperatures around 15–20 �C (Coles and Musick, 2000;Davenport, 1997; McMahon and Hays, 2006). Optimal temperature rangescan vary between species, age classes and seasonally. For example, juvenileloggerheads, C. caretta, generally occupy waters ranging from 15 to 25 �Cwhile juvenile olive ridleys, L. olivacea, are found in much warmer tempera-tures of 23–28 �C (Polovina et al., 2004b). Large leatherbacks, D. coriacea,show the greatest adaptations for metabolic heat production and retention(Davenport et al., 1990; Frair et al., 1972; Paladino et al., 1990; Wallace andJones, 2008), and canmake seasonal transitory forays intowaters below 10 �C(Eckert, 2002; James et al., 2006; McMahon and Hays, 2006).

Warming ocean temperatures are likely to extend the potential globalpelagic habitat of marine turtles further polewards (McMahon and Hays,2006). For example, satellite tracking of leatherback turtles, D. coriacea, inthe North Atlantic suggests that the 15 �C SST isotherm may encapsulatethe northern boundary of distributions, although they are routinelyreported from colder waters (McMahon and Hays, 2006). The meanmonthly 15 �C SST isotherm has moved 330 km north in the last17 years (McMahon and Hays, 2006). However, this warming is withinvariability over the past 150 years, and as such may not be due to globalwarming per se, but such events are occurring with increasing frequency(Hobson et al., 2008). Warming projected over the coming century isexpected to move this contour further northwards thus increasing leather-back, D. coriacea, foraging areas, particularly in the northeast Pacific andnortheast Atlantic (Fig. 2.7). It is likely that these isotherms integrateoceanographic and trophic processes, such as the availability of gelatinouszooplankton, that influence movements of D. coriacea (Houghton et al.,2006; Witt et al., 2007b).


Dense jellyfish aggregations are a natural feature in oceanic ecosystems,but severe blooms are being reported with increasing frequency in recentdecades (Richardson et al., 2009). Will climate change therefore be goodnews for foraging turtles in oceanic waters? The factors driving long-termchanges in prey fields, such as gelatinous zooplankton, remain too poorlyresolved to address this question. Overfishing (fish are major competitorsand predators of jellyfish), eutrophication, habitat modification and climatechange may all be regulating jellyfish density (Purcell, 2005; Richardsonet al., 2009). For example, there have been reported increases in the abun-dance of jellyfish in the Benguela upwelling system (Lynam et al., 2006)

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Figure 2.7 Mean sea surface temperature projections for 2001–2010 summers in theNorthern hemisphere ( June–August) and in the Southern hemisphere (December–February) from CSIRO Mk 3.5 General Circulation Model (GCM). The position ofthe 15 �C isotherm (black solid line) is indicated, which may effectively encompass thedistribution of foraging leatherback, Dermochelys coriacea, turtles. The position of themean 15 �C isotherm (black dotted line) for boreal and austral summers, projected for2091–2100 under greenhouse gas emission scenario SRES A2, is also shown. Blackarrows indicate the general pattern of dispersal away from nesting beaches measuredwith satellite tags in the North Atlantic, Pacific and Southern Africa and inferred fromrecaptures of flipper tagged for D. coriacea (indicated by black dots) nesting in WestAfrica. The movement of D. coriacea nesting in the Andaman Islands (Indian Ocean) isnot known. GCM projections downloaded from the IPCC data hosted by PCMDI andprocessed at CSIRO marine research.


that have been attributed to eutrophication and overfishing although thedetails of mechanisms remain enigmatic. However, in the North Sea, long-term changes in the abundance of various species of jellyfish have been linkedto climatic signals (Lynam et al., 2004).

Overall, we are left with the impression that prey abundance is closelylinked to the fitness of sea turtles inhabiting oceanic waters and the preyabundance is likely to be heavily shaped by climate change although thespecific causes remain obscure (Hays et al., 2004). Strong associationsbetween ocean productivity and associated plankton landscapes and turtledistributions have been suggested (Houghton et al., 2006; Polovina et al.,2001; Witt et al., 2007b). Future alterations of open-ocean prey abundancemay be a critical issue for marine turtles, but one that has as yet received verylittle attention.

Warming of the sea surface can enhance stratification of the watercolumn, leading to nutrient-poor waters (potentially favouring jellyfish)and a reduction in productivity (Polovina et al., 2008; Richardson et al.,2009). Over the last half century in the western Pacific, a negative correla-tion between the slowly increasing mean annual SSTs in the core, foragingareas for loggerhead turtles, C. caretta, and the trend in the size of annualnesting populations during the following respective summers in Japan andeastern Australia has been identified (Chaloupka et al., 2008b). The authorssuggested a relationship between warming ocean temperatures and reducedocean productivity, with the resultant reduction in food supply potentiallyinfluencing the annual breeding numbers of Pacific loggerheads, C. caretta,unless they adapted by shifting their foraging habitat to cooler regions. Thegradual warming of the Pacific Ocean appears to be a major risk factor forthese populations.

In the western Atlantic, reported sightings of leatherbacks, D. coriacea, inCanadian waters were found to increase by 12.5% for each degree rise inmean weekly SST, although it was acknowledged that turtles may beresponding to seasonal availability of gelatinous zooplankton in these watersrather than directly to temperature ( James et al., 2006). Temperature anddeclines in prey abundance may also play a role in triggering departuresfrom these grounds, but it is also possible that other factors such as areduction in feeding efficiency or a threshold for body fat deposition mayinteract to trigger migrations (Sherrill-Mix et al., 2008).

In the North Atlantic, water temperatures play a role in the seasonalmovements of turtles to high-latitude foraging grounds (Hawkes et al.,2007a; James et al., 2006; Morreale and Standora, 2005; Morreale et al.,1992; Renaud and Williams, 2005). Warming temperatures may thereforeresult in increased frequency of leatherbacks, D. coriacea, reported fromhigh-latitude North Atlantic waters and a longer seasonal residence inthese waters. For example, most sightings of marine turtles in UK waters,taken from records over the past century, have been recorded in the past


40 years and sightings are increasing, which is suggestive of a possible shift orexpansion in distributions (Robinson et al., 2005). A competing explanationis the hypothesis that increases in turtle populations globally have resulted ina proportional increase in the number of young ‘strays’ (Carr, 1987) andsummer migrants carried to British waters by the North Atlantic drift (Wittet al., 2007a). However, increased contemporary sightings of turtles in UKwaters may also be an artefact of better reporting and improved publiceducation in recent decades (Robinson et al., 2005; Witt et al., 2007a).

4.3.2. Wind and currentsCurrents play a number of roles in the distribution of juvenile turtles at sea.They may influence turtle movements through advection, offer a thermalrefuge from colder waters and will influence to a large degree the availabilityof planktonic prey. Ocean circulation patterns may thus help define turtledistributions and deflect turtle movements, particularly those of juvenileturtles (Bowen et al., 2007; Polovina et al., 2006; Revelles et al., 2007a). Forexample, circulation patterns into and within the Mediterranean Sea arethought to retain immature loggerheads, C. caretta, hatched on Mediterra-nean beaches until they attain sufficient size and strength to swim againstcurrents and are able to exit into the Atlantic (Revelles et al., 2007a,b).A proportion of green turtles, C. mydas, on foraging grounds in the easternCaribbean have been shown to originate from Ascension Island rookeriesand are probably transported there by the North Atlantic gyre (Luke et al.,2004).

Evidence for the influence of ocean circulation patterns on juveniledispersal and possible fidelity to particular water masses has been shownthrough genetic and tagging studies (Bass et al., 2006; Carreras et al., 2006;Casale et al., 2007; Luke et al., 2004; Naro-Maciel et al., 2007). Clearly then,straying outside ocean gyre and currents systems can be fatal for youngturtles if the temperature difference is large (Carr, 1986, 1987; Lohmannand Lohmann, 1996). Loggerheads (C. caretta) in the North Atlantic havebeen shown to use the warm waters at the edge of the Gulf Stream as athermal refuge (Hawkes et al., 2007a). At temperate latitudes, the tempera-ture difference within such currents, which originate in tropical latitudes,and surrounding waters may be large. For example, in southeast Australianwaters, the temperature difference between the warm-water East AustralianCurrent (EAC) and surrounding waters may be over 5 �C (see Zann, 2000).Juvenile and adult marine turtles seasonally appear in New Zealand waters(34–38 �S) and off southeast Australia, either carried or assisted by thepoleward extension of the EAC (Gill, 1997; Limpus and McLachlan,1979; Scott and Mollison, 1956). The numbers of records of turtle mortalityin this region have increased in recent decades, with high influx yearscoinciding with a recent strengthening of the EAC as well as rising oceantemperatures (Cai, 2006; Gill, 1997). The EAC has strengthened driven by


changes in the circumpolar westerly wind belt due to warming tempera-tures; the EAC is projected to strengthen by 20% by the 2070s (Cai et al.,2005). This has resulted in a warming of waters off Tasmania, southeastAustralia, of 2.28 �C in 60 years (Hill et al., 2008). With the strengthening ofthe EAC, observations of juveniles in New Zealand waters are expected toincrease.

4.3.3. Large-scale ocean–atmosphere patternsThe large-scale atmospheric patterns such as El Nino influence regionaloceanography and productivity. Fluctuations in the abundance of gelatinouszooplankton in regions of the world’s oceans are related to large-scaleclimate indices such as El Nino and the North Pacific Decadal Oscillation(Anderson and Piatt, 1999; Attrill et al., 2007; Dawson et al., 2001; Purcell,2005; Raskoff, 2001). How these evolve, as global climate changes, willhave repercussions for marine turtle populations globally.

4.3.4. Ocean acidificationOcean acidification will affect the acid–base cellular regulation of marineorganisms but as air breathers, marine turtle physiology will be less suscep-tible to changes in ocean chemistry. The indirect effects of ocean acidifica-tion on primary and secondary production may have consequences formarine turtles, particularly if coral reefs decline (see above) or ocean pro-ductivity decreases.

4.4. Juveniles and adults on inshore foraging grounds

4.4.1. Ocean temperatureWater temperatures in coastal waters tend to be more variable than in open-ocean waters and strongly seasonal. Foraging turtles are frequently reportedfrom high-latitude, coastal and shelf waters during the summer months(Goff and Lien, 1988; James et al., 2006). Cold stunning of turtles at higherlatitudes is a frequent occurrence and, if exposures to low temperatures areprolonged, morbidity and death may occur (Morreale et al., 1992; Still et al.,2005). In partially enclosed seas, such as the Mediterranean (�40 �N), greenturtles, C. mydas, can show periods of ‘dormancy’ rather than migration totropical waters. During dormancy individuals rest in mid-water or on thebottom (although some level of activity is retained) during periods of lowwater temperatures (Godley et al., 2002c; Hochscheid et al., 2007). Thisbehaviour appears to be an adaptation of the Mediterranean populationssince green turtles, C. mydas, in southeast Australia (�30–35 �S) do notshow dormancy at temperatures similar to the low Mediterranean tempera-tures. The observed trend to warmer temperatures in the Mediterranean(Bindoff et al., 2007) should reduce the occurrence of dormancy in resident


turtle populations, thus potentially increasing foraging times and improvingresultant body condition.

Increased temperatures may also expand the availability of potentialturtle coastal foraging habitat polewards and influence food resources.However, turtles show some fidelity to foraging areas, depending on speciesand population, which may constrain invasion of higher latitude areas astemperatures warm although if foraging regions can no longer support turtlepopulations then turtles will be driven to locate alternative grounds.

4.4.2. Rainfall, storms and cyclonesThe increase in tropical, cyclone intensities projected with global warmingwill impact most heavily on turtles that nest during the storm season or onturtles that forage in shallow coastal habitats such as green turtles. Turtlescan survive severe storms and cyclones by reducing time spent at the surfaceand moving to deeper water (Storch et al., 2006). However, cyclones andlarge storm surges will cause damage, stress, starvation and death of turtles ifforaging grounds are in very shallow areas (Carr, 1987; Limpus and Reed,1985b). For example, Cyclone Kathy which crossed the Gulf of Carpen-taria, Northern Australia in 1984, led to large-scale stranding of 500–1000adult green turtles, C. mydas, on one section of coastline with a largeproportion of these subsequently dying (Limpus and Reed, 1985b).

Large storm events can have long-lasting impacts on turtle populations.A 1200 km2 of seagrass beds were destroyed off southern Queensland,Australia in 1992 following two cyclones in quick succession and a majorriver flood event (Preen et al., 1995). The seagrass die-off was followedsome 5 months later with a record number of strandings of dead dugongs,Dugong dugon (large marine herbivores) on the adjacent coastal areas (Preenand Marsh, 1995). During the same period there was an increased numberof strandings of dead green turtles, C. mydas, on the adjacent Hervey Baycoast (EPA Marine Wildlife Stranding and Mortality Database, Brisbane,Australia). In western Shoalwater Bay, Australia, following Cyclone Joy inearly 1990 which caused similar regional loss of seagrass, it was found theproportion of foraging green turtle (C. mydas) adults that prepared forbreeding migrations for the 1991 breeding season was severely depletedand remained below average until 1996 (Limpus et al., 2005). Growth ratesof immature C. mydas foraging in the same area were depressed during thesame period (Chaloupka et al., 2004).

Understanding the impact of climate change in marine turtles in coastalareas will require a more detailed examination of storm and rainfall patternstogether with local bathymetry and topography. However, the degree ofdestruction of coastal marine systems by a cyclone will depend on manyfactors including cyclone track, topography and coastal hydrodynamics.A severe cyclone may not necessarily be a destructive one for coastal marinesystems, particularly for submerged fauna and flora. Seagrass beds appear


remarkably resilient to storm disturbance as long as the plants are notuprooted or heavily smothered (Carruthers et al., 2002; Cruz-Palacios andvan Tussenbroek, 2005; Tilman et al., 1994). For example, Hurricanes Ivan(in 2004) and Katrina (in 2005) were found to have resulted in little loss ofseagrass beds in Alabama despite extensive damage on land (Byron andHeck, 2006). However, if damage or destruction does occur, thenre-vegetation can take 10 years or more and will have implications formarine herbivores.

Storms, cyclones and heavy rainfall events can increase turbidity incoastal waters and can cause rapid drops in salinity affecting the stability ofcoastal waters. They also wash nutrients from the land which can often leadto harmful algal blooms in coastal waters, particularly in waters which areoligotrophic. For example, higher than average rainfall, coupled withwarmer temperatures, may have contributed to a toxic cyanobacteriumbloom on an important green turtle, C. mydas, foraging ground in Queens-land, Australia (Arthur et al., 2007). The turtles were found to be ingestingthe cyanobacterium with potential long-term detrimental effects to theirhealth. Red tides, which are also toxic algal blooms, can develop in coastaland shelf waters following heavy intense rainfall (Lee, 2006; Vargo, 2009).Mass mortalities of marine flora and fauna, including turtles, are oftenreported from the red tides (e.g. Florida, USA: Gannon et al., 2009;Landsberg et al., 2009; Simon and Dauer, 1972; South Africa: Stephenand Hockey, 2007; Korea: Lee et al., 2007a; Japan: Koizumi et al., 1996).The potential consequences of climate change for harmful algal bloomproduction and severity are unknown, but it must be assumed the risingCO2 levels and temperatures coupled with alteration of rainfall patterns andexpanding human populations (hence increasing likelihood of coastal eutro-phication) may lead to more frequent or severe outbreaks of toxic algae.

4.4.3. Sea levelNearshore foraging habitats of marine turtles, such as seagrass beds and coralreefs, may be vulnerable to rising sea levels (Duarte, 2002; Short andNeckles, 1999). Although sea levels are presently rising at 1–2 mm a year,the rise is slow compared to the rates of coral growth (20 cm/year; Done,2003) and hence is not a major challenge to healthy coral populations.However, additional stressors such as warming temperatures, ocean acidifi-cation and pollution may slow coral growth considerably (Hoegh-Guldberget al., 2007). Benthic marine plants and algae may be more at risk. It isestimated a 50-cm rise in sea level will result in a 30–40% reduction in thegrowth of the widespread Northern Hemisphere seagrass Zostera marina(Short and Neckles, 1999), which is likely to reduce the area of green turtle,C. mydas, foraging grounds.


4.4.4. Large-scale ocean–atmosphere patternsEvidence of ENSO influences on green turtle, C. mydas, populations onforaging grounds can be seen in the numbers nesting every year (see above).Increase in ‘El Nino-like’ conditions may enhance seagrass and algal growth inthe tropics and sub-tropics with positive consequences for feeding C. mydas.

4.4.5. Ocean acidificationOcean acidification is like to impact two key, coastal, turtle-foraging habi-tats: coral reefs and seagrasses. The threat of ocean acidification is a majorconcern for coral reefs globally (Hoegh-Guldberg, 2007; Kleypas et al.,2001). Coral reefs are restricted to high-latitude warm waters which haverelatively high aragonite saturation states compared to colder lower latitudewaters (Hoegh-Guldberg, 2007; Kleypas et al., 2001). Not only may climatechange lead to a net dissolution of coral reefs, but also the potential forpoleward expansion of coral reefs with rising temperatures may be restrictedto a few hundred kilometres at the most by the lower carbonate saturationlevels of seawater at higher latitudes (Kleypas et al., 2001). Furthermore,recent warming of the oceans has led to repeated coral bleaching events, notseen anywhere globally before 1979 (Hoegh-Guldberg, 1999). In Australia,for example, temperature thresholds for coral reef bleaching may beexceeded every year by the middle of this century (Hoegh-Guldberg,1999). The additional stressor of ocean acidification coupled with warmingtemperatures may lead to a decline in coral density and diversity globally,associated losses of coral-associated fish and invertebrates and an increase inmacroalgal cover (Hoegh-Guldberg et al., 2007).

Coral reefs form major coastal foraging grounds for turtles, in particularhawksbills, E. imbricata, and these would be vulnerable if reef systemsdeteriorated, even though the abundance of hawksbill, E. imbricata, turtlesforaging on the rocky reefs of sub-tropical Queensland and northern NewSouth Wales suggests that they are not necessarily limited by coral reefdistribution (Speirs, 2002). However, a long-term decline in coral reefhabitat will have severe repercussions for many tropical marine ecosystems(Hoegh-Guldberg et al., 2007) including the long-term persistence ofhawksbill (E. imbricata) populations.

Seagrasses primarily rely on dissolved CO2 and so are photosyntheticallyinefficient in seawater (Invers et al., 1997; Short and Neckles, 1999).Increased CO2 levels could potentially increase seagrass biomass, providingthat optimal temperature regimes exist (Invers et al., 2002; Zimmermanet al., 1997); this response may therefore benefit the herbivorous greenturtles, C. mydas. However, seagrass beds are declining globally as a resultof other anthropogenic stressors, such as reductions in water quality, whichmay cancel the climate change benefits to seagrasses (Ferwerda et al., 2007;Waycott et al., 2009).


4.5. Oceanic migrations

Turtles can make long migrations between breeding and foraging areas,depending on species and population (Hays et al., 2002c; James et al.,2005b; Limpus et al., 1983c). The actual strategies used by turtles to navigateduring these journeys have been subject of much research and debate.Whilethere is some evidence turtles may use the Earth’s magnetic field to orientateand possibly to navigate (Lohmann, 2007; Lohmann and Lohmann, 1996),and may use currents opportunistically (Luschi et al., 2003), it is still largelyunknown how they home precisely to natal and foraging regions (Lohmannet al., 2008). While the mechanisms used during migration remain enig-matic, the return migratory abilities of sea turtles are now fairly well estab-lished. For example, both tagging and genetic studies have revealed theability of turtles to return to breed within natal areas (e.g. Lee et al.,2007b). Furthermore, tracking studies have shown that turtles may under-take long-distance movements during the breeding season, sometimes ofseveral hundred kilometres, and yet return directly to nesting regions (e.g.Georges et al., 2007; Fig. 2.8). These tracking results imply turtles have somegeospatial knowledge of their environment. Yet turtles artificially displacedtens or hundreds of kilometres from nesting sites often show searchingbehaviour and are unable to return directly to their starting point (Luschiet al., 2001). This finding illustrates that active searching may be an integralcomponent of turtle migrations, especially across finer spatial scales, andsuggests that even with some climate-induced alterations of homing clues,an active search strategy may still help turtles to find nesting sites (Sims et al.,2008). Set against this backdrop it is particularly difficult to make specificpredictions about how climate change might impact migrations.

Figure 2.8 Loggerhead (Caretta caretta) turtle with GPS tag.


4.5.1. Wind and currentsThere has been considerable debate on the role that the major oceancurrents play in turtle migrations: do turtles use currents opportunistically,do currents represent migration corridors for marine turtles, or arecurrents a challenge to be overcome by swimming turtles if migrating ina different direction to current flow? The answer may be all of these,depending on species and population. Certainly, the major current systemsplay a role in linking foraging and nesting areas in turtle populations (Basset al., 2006).

Juveniles and adults may use current flows to facilitate transport, for exam-ple, juvenile loggerheads,C. caretta, originating from Japanese populations havebeen identified from feeding grounds off Baja California, representing a jour-ney that crosses the entire PacificOcean,most likely aided by theNorth PacificCurrent (Bowen et al., 1995). Adult loggerheads, C. caretta, have also beentracked using satellite tagging, crossing the Indian Ocean (Luschi et al., 2003)and the Pacific Ocean (Nicols et al., 2000) in the direction of prevailing oceancurrents. The increasing use of satellite tagging has revealed turtles domake useocean currents during their long-distance migrations (Bentivegna et al., 2007;Hays et al., 1999, 2001b, 2002c; Luschi et al., 2003).

Long-distance migrations may not rely solely on the directions of thesecurrents. Turtles have also been tracked swimming against prevailingcurrents suggesting the use of currents may be opportunistic or, at least,not obligate (Bentivegna et al., 2007; Cardona et al., 2005; Luschi et al.,2003; Miller et al., 1998; Polovina et al., 2004a, 2006). Migrations acrosslarge expanses of oceans are often direct until coastal waters are reached(Hays et al., 2002c; James et al., 2005b), although currents have been foundto deflect turtle migratory paths (Gaspar et al., 2006; Girard et al., 2006).There is evidence of persistent migration corridors for adult turtles that donot necessarily coincide with current flow or other oceanographic features(Hays et al., 2001b; Morreale et al., 1995; Shillinger et al., 2008; Troenget al., 2005). Disruption or displacement of major ocean currentsystems could therefore have repercussions for turtle stocks by influencingturtle movements and the impacts may be greatest on juveniles. It is morelikely that impacts will manifest through associated changes in oceanproductivity.

5. Responses to Past Climate Change

The first turtles appear in the fossil record at least 200 million years agoand the turtle lineage (Testudines) probably diverged around this time(Hedges and Poling, 1999; Rieppel and Reisz, 1999). Extant turtles mayhave arisen some 50–100 million years ago. The most recent period with a


climate warmer than the present-day climate (2–3 �C above pre-industrialtemperatures), particularly at mid- and high latitudes, was the middlePliocene (�3 million years ago). Tropical sea surface temperatures and airtemperatures were probably little different to present day or slightly warmer(1–4 �C) and wetter, whereas high latitudes were significantly warmer(Haywood et al., 2000; Jansen et al., 2007). Sea levels were around15–25 m higher than present day. Since then, climate has cooled, under-going a cycle of glacial and interglacial periods with the last glacial maxima(LGM) being �21,000 years ago and a mid-Holocene warm period 6000years ago. During the last glacial maximum, global temperatures werecooler (�5 �C) particularly at higher latitudes with extensive ice coverand sea levels were up to 120 m lower. Genetic analysis has revealed thatover the past 100 million years the tropics acted as a refuge during glacialcycles for many nesting turtles with sub-division and isolation of populationsas sea levels and temperatures altered (Formia et al., 2006; Reece et al., 2005).Nesting turtles were likely to have been continually displaced by coolingperiods and changes in sea level, particularly loggerheads, C. caretta, whichgenerally nest at higher latitudes on the sub-tropical and warm-temperatebeaches (Bowen and Karl, 2007).

Sea levels have been rising since the Last Glacial Maximum (LGM),substantially altering coastal areas and displacing turtle nesting sites. A casestudy for northern Australia green turtles, C. mydas, provides evidence ofpast adaptation to climate change by marine turtles (Dethmers et al., 2006).Much of the shelf area off northern Australia would have been exposed21,000 years ago. Most of the present-day nesting beaches were inaccessible,being far inland (Dethmers et al., 2006; Limpus, 2008), The Gulf ofCarpentaria would have been an inland lake until it was flooded when sealevels began to rise 6000–10,000 years ago. A land bridge between Australiaand Papua New Guinea would have existed until around 10,000 years ago(�450 turtle generations) effectively separating turtle stocks breeding ineastern Australia from those breeding in northern and western Australia, asshown by genetic analysis of green turtles C. mydas (Dethmers et al., 2006).Green turtles, C. mydas, nesting in the Gulf of Carpentaria appear to haveinvaded from western populations, but have since altered the timing ofbreeding (from austral summer to the austral winter) to adapt to localtemperature regimes. Migration routes have also changed as some greenturtle populations in the Gulf of Carpentaria, Northern Australia, migratebetween nesting and foraging areas contained entirely within the Gulfrepresenting migratory routes in the order of hundreds of kilometres ratherthan the thousands of kilometres found in other green turtle (C. mydas)populations (Kennett et al., 2004).

Evidence of similar phenological shifts and/or colonisation events arealso found in other turtle populations. For example, genetic analysis ofgreen, C. mydas, turtles nesting in the Indian Ocean suggests the turtle


population nesting at rookeries in the South Mozambique Channel (south-west Indian Ocean) have recently colonised from the Atlantic Oceanaround the tip of South Africa (Bourjea et al., 2007). Suitable green turtle-foraging habitat occurs close to the tip of South Africa due to warm waterflows in this region but no analogous habitat is found along cold-upwellingsystem that dominates the west coast. The cold South African waters areconsidered a major geographical barrier for C. mydas dispersal and, prior tothe discovery of Atlantic haplotypes in the southern Mozambique Channelpopulations, no evidence has been found of gene flow between the Indianand Atlantic Oceans over the last 1.5 million years. Further, it is unlikelythis colonisation is an ongoing process and the genetic differentiation ofthe southern Mozambique Channel populations is maintained by theoceanographic currents in this region (Bourjea et al., 2007).

6. Adaptation and Resilience

Marine turtles are considered vulnerable to climate change given thestrong role temperature plays in all life stages (Davenport, 1997). Muchdiscussion with regard to marine turtles and climate change is centred on thetemperature-dependent sex determination of embryos in the nest. Warmingexpected over the coming century may result in shifts to neat to 100%female-producing beaches for some populations. However, the differencesin breeding seasons observed at rookeries within the same genetic stock andrecent evidence of some relationships between peak nesting and tempera-ture (Pike et al., 2006; Weishampel et al., 2004) suggests some capacity foradaptation to altered climate by breeding marine turtles. Such responses maynot occur at a fast enough rate to keep pace with projected rapid warmingover the next 100 years.

Loss of suitable nesting sites may be countered by colonisation of newsites as has happened over past, much greater, shifts in sea level and climaticalteration. Fidelity to breeding beaches by turtles may not be as strong asgenerally supposed. A study of 2891 nesting green turtles, C. mydas, alongthe Australian east coast, all of which have nested in previous years, revealed6% changed rookeries (nesting beaches) between nesting seasons, with 1.6%having changed rookeries within a nesting season (Dethmers et al., 2006).Turtles may track changing coastal environments by moving to nearbybeaches, as may have happened when the Gulf of Carpentaria flooded(Dethmers et al., 2006). Or events may be long-distance, as in a recent(on an evolutionary scale) colonisation of green turtles, C. mydas, from theAtlantic Ocean into the Indian Ocean via the Cape of Good Hope (Bourjeaet al., 2007).


Many turtle populations have operated with a strong female bias overmany decades, if not longer. Thus, some populations may be resilient towarming if female biases remain within or at levels where population successis not impaired. At present, there is little information about the biases thatpopulations can sustain (Hamann et al., 2007). Given the projected warmingat turtle rookeries globally, it must be assumed that some populations will beunder threat.

Resilience of marine turtles to climate change is likely to be compromisedby other anthropogenic influences. Development of coastlines may threatennesting beaches and reproductive success and reduce the availability ofalternative breeding areas if current regions become unsuitable. Pollutionand eutrophication, in addition to coastal development, is threatening impor-tant coastal foraging habitats for turtles worldwide. Around 29% of seagrassbeds have disappeared in the last 130 years and rates of decline have acceler-ated since 1990 (Waycott et al., 2009). Losses are attributed to a loss of waterquality from changes in land use and eutrophication, coastal development,invasive species and climate change (Abal and Dennison, 1996; Kirkman,1997; Ruiz and Romero, 2003; Walker et al., 1999; Waycott et al., 2009).The world has also lost 19% of the original area of coral reefs with a further20% under serious threat over the next 20–40 years from anthropogenic-induced degradation including climate change (Wilkinson, 2008). Majorlosses of coral reefs are reported from the occurred in the Caribbean and inthe heavily populated regions of Asia.

Exploitation and bycatch in other fisheries has seriously reduced marineturtle populations; marine turtles may once have been extremely commonin coastal ecosystems until hunting associated with the rise of seafaringreduced numbers relatively rapidly ( Jackson, 1997). Turtles themselveshave been the target of major fisheries in the past which have drasticallyreduced turtle numbers; many populations are still reduced from exploita-tion over a century ago (Aitken et al., 2001; Daley et al., 2008; Jackson,1997; Tripathy and Choudbury, 2007) and in some areas, particularly Indo-China, are still exploited. Turtles are also exploited, often illegally, for theireggs and their shells (e.g. Barnett et al., 2004; Hope, 2002; Lagueux andCampbell, 2005). Large numbers of turtles die as the result of being caughtas bycatch in pelagic longline and trawl fisheries every year (Ferraroli et al.,2004; Hays et al., 2003b; James et al., 2005a; Kaplan, 2005; Kotas et al., 2004;Lewison and Crowder, 2007).

The cumulative effects of other human-induced stressors may seriouslyreduce the capacity of some turtle populations to cope with the additionalstressor of climate change. The widespread and global nature of many of theanthropogenic-induced stressors means that many turtle populations may bethreatened at every life stage. Conservation efforts targeting critical lifestages or highly threaten populations should increase resilience.


7. Global Trends

The IUCN Red List in 2009 included marine turtles as vulnerable,endangered or critically endangered, with the exception of the flatback,N. depressus, which is data deficient (IUCN, 2009; Seminoff and Shanker,2008). Many marine turtle populations globally are increasing (although stillseverely depleted) as the result of conservation efforts resulting in the IUCNlistings being contested as misleading (Broderick et al., 2006; Hays, 2004;Seminoff and Shanker, 2008). For example, green turtles, C. mydas, nestingat Ascension Island have increased by an estimated 285% since the 1970s(Broderick et al., 2006). Increases are also reported for C. mydas populationselsewhere (Australia: Chaloupka and Limpus, 2001; Hawaii: Balazs andChaloupka, 2004; Costa Rica: Bjorndal et al., 1999; Troeng and Rankin,2005). Similar increases have been recorded for other species. For example, a10-fold increase in 11 years in nesting activity of olive ridley turtles, L. olivacea,in Brazil has been reported (da Silva et al., 2007). Observations from the USVirgin Islands suggest leatherback populations, D. coriacea, nesting there havebeen increasing at a rate of around 13% per annum since the 1990s (Duttonet al., 2005), while an recent upward trend has been found in hawksbill,E. imbricata, nesting numbers in Antigua (Richardson et al., 2006).

8. Recommendations

Management of marine turtle populations in the face of a rapidlychanging climate will require a concerted effort globally, both to reducethe direct impacts of climate change and to increase resilience of turtlepopulations. Clearly, a beneficial approach to many animal species includingturtles would be an international effort to mitigate greenhouse gas emis-sions. However, while that is being achieved, reducing other stressorsshould be seen as a priority for helping to increase the resilience of turtlepopulations.

Conservation efforts to date have tended to focus on nesting beaches asthese are the most accessible of the turtle habitats and therefore the most costeffective to manage. On a local scale, strategies such as increasing shading tocool nest temperatures, for example, by increasing shoreline vegetative orrelocation of eggs, has been used as a management tool, although the costsof large-scale programmes may be prohibitive (Dutton et al., 2005; Hamannet al., 2007; Pfaller et al., 2009; Pike, 2008a). It has been argued that survivalto reproductive age of individual hatchlings is extremely low so the likeli-hood of hatchlings from ‘saved’ nests contributing to the future populationsare minimal (Pike, 2008c). This also raises questions about whether such


strategies interfere with the natural ability of populations to respond toclimate variability (Mrosovsky, 2006). Concerns have been raised that eggrelocation will distort gene pools by imposing artificial selection on ‘poor’nesters, if individual females consistently select unfavourable sites and if suchtraits are heritable (Mrosovsky, 2006; Pike, 2008c). Egg relocation would bea viable conservation strategy for populations with low repeatability inindividual selection of nest sites (Pfaller et al., 2009). In this case the‘doomed nests’ may result from a large percentage of the population sowould not distort gene pools.

Other strategies have involved ‘head-starting’ turtles where juveniles areraised in hatcheries and released in the wild; however, generally suchapproaches have not been successful. Options for beach re-nourishmentand restoration of low-lying beaches to counteract sand loss due to rising sealevels or storm erosion could also be explored. The success of beachnourishment is currently under discussion with both increases and declinesin reproductive output reported (Brock et al., 2009; Fuentes and Hamann,2009; Pike, 2008c, 2009b). Protection of nesting beaches and protection ofnests from land-based predators will increase reproductive successes, whileprotection of cooler (hence male-producing) beaches, may become criticalas temperatures warm. In this context, minor, high-latitude rookeries maybecome increasingly important.

In the open ocean, longline fisheries have received attention as a highsource of turtle mortality (Ferraroli et al., 2004; Hays et al., 2003b; Jameset al., 2005a; Kaplan, 2005; Kotas et al., 2004; Lewison and Crowder, 2007)and efforts to reduce turtle catch in these fisheries should improve the healthof turtles stocks globally. The introduction of turtle exclusion devices intrawl fisheries, such as the Northern Prawn Fishery in the Gulf of Carpen-taria, Australia or prawn fisheries in the Gulf of Mexico, has greatly reducedturtle bycatch (Brewer et al., 2006; Lewison et al., 2003).

Many turtle nesting beaches and foraging grounds are in regions of theworld where regulated and unregulated fishing and harvesting are high,both of turtles and of turtle eggs. Conservation programmes within theseregions will play an important role in conserving turtle stocks. Strongrecoveries of seriously depleted green turtle, C. mydas, populations werefound in only a few decades following increases in protection of nestingpopulations (Chaloupka et al., 2008a).

There are many knowledge gaps to be filled before a deeper understand-ing of turtle population dynamics and life histories will be possible.Advances in genetic approaches are revealing phylogeography of turtlepopulations worldwide and informing on responses to past climate changewhich, in turn, will inform us about some of the potential responses ofmarine turtles to future climate change. Advances in satellite tagging aresupplying much needed information on key turtle-foraging regions in theopen ocean and turtle migrations, but there is still much to be learnt (Hays,


2008). Long-term monitoring studies, both at major rookeries and atperipheral nesting beaches, as well as modelling studies, are required tounderstand how sex ratios respond to a fluctuating environment and howthese affect long-term turtle population dynamics.

Reproductive studies have tended, for obvious reasons, to concentrateon turtle nesting beaches, but channelling efforts solely on the present-dayrookeries ignores the processes driving variability in turtle nesting behaviourand distributions. As research on marine turtles expands, so does our insightinto the processes that underlie the initiation of nesting migrations andselection of breeding areas. The paradigm that turtles return to their natalbeach to nest has been replaced by a view that turtles return to a natal regionas evidence arises of variability in beach selection between years andbetween individuals in the same breeding stock. This view may alter furtheras our marine turtle data sets lengthen to encompass multi-generationalobservations. We recommend that investigation of knowledge gaps of theprocesses driving breeding site selection is critical for adaptive managementdecisions in the face of a changing climate.

ACKNOWLEDGEMENTS

We would like to thank David Sims and an anonymous referee whose comments havehelped to improve this manuscript.

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C H A P T E R T H R E E

Effects of Climate Change and

Commercial Fishing on Atlantic

Cod Gadus morhua

Nova Mieszkowska,* Martin J. Genner,*,† Stephen J. Hawkins,*,‡

and David W. Sims*,§

Contents

1. Introduction 214

1.1. Basic biology and global distribution 215

1.2. Genetic population structure 216

1.3. Traits in different stocks 218

1.4. Movement and activity 219

2. Impacts of Climate Change 222

2.1. Biogeographic changes 224

2.2. Physiology 226

2.3. Metabolic scope for activity 229

2.4. Maturation and spawning 230

2.5. Early life stages 231

2.6. Recruitment 233

2.7. Growth 237

3. Impacts of Fishing 238

3.1. Northwest Atlantic stocks 238

3.2. Northeast Atlantic stocks 239

3.3. The fishing versus climate change debate 244

4. Population-Level Impacts of Fishing and Climate Change 245

4.1. Stock assessment 245

4.2. Stock evaluation—An example from the North Sea 246

4.3. Allee effects and management plans 247

5. Monitoring Status and Recovery of North Sea Cod: A Case Study 249



* Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB,United Kingdom

{ School of Biological Sciences, University of Bristol, Bristol BS8 1UG, United Kingdom{ College of Natural Sciences, Memorial Building, Bangor University, Gwynedd LL57 2UW,United Kingdom

} Marine Biology and Ecology Research Centre, School of Biological Sciences, University of Plymouth,Drake Circus, Plymouth PL4 8AA, United Kingdom

213



References 252

Abstract

During the course of the last century, populations of Atlantic cod Gadus

morhua L. have undergone dramatic declines in abundance across their biogeo-

graphic range, leading to debate about the relative roles of climatic warming

and overfishing in driving these changes. In this chapter, we describe the

geographic distributions of this important predator of North Atlantic ecosys-

tems and document extensive evidence for limitations of spatial movement and

local adaptation from population genetic markers and electronic tagging. Taken

together, this evidence demonstrates that knowledge of spatial population

ecology is critical for evaluating the effects of climate change and commercial

harvesting. To explore the possible effects of climate change on cod, we first

describe thermal influences on individual physiology, growth, activity and

maturation. We then evaluate evidence that temperature has influenced popu-

lation-level processes including direct effects on recruitment through enhanced

growth and activity, and indirect effects through changes to larval food

resources. Although thermal regimes clearly define the biogeographic range of

the species, and strongly influencemany aspects of cod biology, the evidence that

population declines across the North Atlantic are strongly linked to fishing activity

is now overwhelming. Although there is considerable concern about low spawning

stock biomasses, high levels of fishing activity continues in many areas. Even with

reduced fishing effort, the potential for recovery from low abundance may be

compromised by unfavourable climate and Allee effects. Current stock assess-

ment and management approaches are reviewed, alongside newly advocated

methods for monitoring stock status and recovery. However, it remains uncertain

whether the rebuilding of cod to historic population sizes and demographic

structures will be possible in a warmer North Atlantic.

1. Introduction

Atlantic cod Gadus morhua Linnaeus, 1758 is one of the most widelystudied marine fishes (Fig. 3.1). The species is a major predator in NorthAtlantic ecosystems as well as being a prey item for larger fishes and piscivo-rous marine mammals. It has been exploited as a human food resource forover 1000 years and forms a key component of major fisheries throughout theNorth Atlantic. Its pivotal ecological role, together with its economic impor-tance, has made it a model system for study among marine fishes. Studiesrange from individual physiology, to population ecology, community inter-actions and responses to environmental change, including climate change andfishing. Here, we review these studies and discuss how key aspects of cod

214 Nova Mieszkowska et al.

biology are likely to be influenced by changing environments, such as thoseassociated with changes in fishing pressure and climate. We examine theimpacts of these drivers on the current status and potential for future recoveryof stocks, with a focus on the North Sea and evaluate potential managementstrategies to reverse the current global decline in Atlantic cod.

1.1. Basic biology and global distribution

Atlantic cod is an apex predator of North Atlantic continental shelf waters.It feeds mainly on invertebrates and fish. It grows to a maximum of 2 m intotal length, weighs up to 96 kg, matures at between 2 and 4 years of age(O’Brien et al., 1993) and can live for up to 25 years. Females are typicallyhighly fecund, producing an average of 1 million eggs per individual(Cohen et al., 1990). Spawning takes place between December andJune depending on geographic location, and eggs hatch 2–3 weeks later.The pelagic larvae feed on zooplankton for approximately 2 months beforesettling on demersal nursery grounds.

The biogeographic range of cod, like many marine fish species, isprimarily governed by temperature (Coutant, 1987; Sundby, 2000). In theNorth Atlantic Ocean, it is found between 40 and 80 �N over a tempera-ture gradient of �1 to 20 �C. Northern limits occur in Canada and Iceland,and southern limits are reached around New England in the westernAtlantic, and in the Celtic Sea–English Channel in the eastern Atlantic(Fig. 3.2). Key areas of population abundance are Labrador, Newfoundland,southern Greenland, Iceland, the North Sea, the Baltic Sea and the BarentsSea (Bigg et al., 2008; Sundby, 2000). Its depth range extends from shallowwaters to 200 m, although it has been recorded at depths of over 500 m(Cohen et al., 1990).

Figure 3.1 Atlantic cod, Gadus morhua Linnaeus 1758. Photograph courtesy of theMarine Biological Association of the UK.

Climate and Fishing Effects on Cod 215

1.2. Genetic population structure

Cod live in a diverse and complex marine landscape with contrasting watertemperatures, depths, salinities, substrates and prey availability. In manymarine species, habitat discontinuities can act as barriers to gene flow byrestrictingmovement of adults or larvae (Hauser andCarvalho, 2008).Geneticdifferences between populations can be further promoted by behaviouraltraits, such as adult philopatry, population-specific migratory behaviour orkin aggregation (Pardini et al., 2001). The formation of genetic substructurewill, however, be counteracted to some extent by the capability that adultfishes have to range over long stretches of coastline and open water, and thepelagic dispersal of eggs and larvae (Hauser and Carvalho, 2008).

Identification of geographic and behavioural barriers to gene flow iscritical for stock identification and management. Cod are very patchilydistributed across their range (�7300 km), and molecular markers havehelped to reveal the extent of migration among populations. Several studieshave revealed a broad spatial trend of isolation-by-distance across the NorthAtlantic. In mitochondrial DNA, despite an apparent lack of nucleotidediversity (Arnason and Palsson, 1996), there are large differences in thefrequency of common haplotypes (Arnason, 2004; Carr and Crutcher,1998). Similar patterns have been revealed using restriction fragments ofnuclear genes (Pogson et al., 1995, 2001), and nuclear microsatellite markers(Hutchinson et al., 2001; O’Leary et al., 2007; Pampoulie et al., 2008;Skarstein et al., 2007). The extent of population differences in microsatelliteallele frequencies are such that cod can be reliably assigned to the Baltic Sea,North Sea and the Northeastern Arctic Ocean on the basis of theirgenotypes alone (Nielsen et al., 2001).

90�W 60�W 30�W

90�W

60�N

40�N

60�N

40�N

60�W 30�W 0�

0�

Figure 3.2 The distribution of Atlantic cod in the North Atlantic Ocean (greyshaded area).


1.2.1. Cod population persistenceNearly all studies making temporal comparisons of cod population structureusing archived genetic material have found remarkable stability (Imslandet al., 2004; Jonsdottir et al., 1999, 2001; Lage et al., 2004; Nielsen et al.,2001; Pampoulie et al., 2008). A major change in genetic diversity was,however, found in the heavily fished Flamborough Head population in theNorth Sea between 1954 and 1970. After the decline observed over thisperiod, diversity subsequently increased, and this has been linked to theincursion of new genotypes as new colonists had proportionally greaterreproductive success (Hutchinson et al., 2003). The general natural stabilityof cod populations, however, implies that the present distribution of geneticdiversity has changed little over recent time. Bigg et al. (2008) concludedthe present distribution of cod dates back more than 100,000 years, but bycontrast, using more rapidly evolving microsatellite markers, Pampoulieet al. (2008) calculated the time scale of divergence dates more closely tothat of the Last Glacial Maximum, approximately 20,000 years ago.Although the accuracy of these time scales will depend on methods usedto calibrate evolutionary rates, together these results suggest that the largerscale distribution of genetic diversity pre-dates the last northern hemisphereglacial cycle.

1.2.2. Regional patterns of genetic diversityUsing microsatellite DNA markers, patterns of isolation-by-distance havebeen revealed over spatial scales of approximately 1000–2000 km (Beachamet al., 2002; O’Leary et al., 2007). At smaller scales (<1000 km), however,the extent of stock structure appears closely linked to environmental para-meters and behavioural differences. For example, genetic structure withinthe Northwest Atlantic has been linked to habitat discontinuities, such aschannels and trenches. Lage et al. (2004) found cod on the southernNantucket shoals to be genetically distinct from those on the neighbouringmore northerly offshore Browns Bank and Georges Bank, but there wereno genetic differences apparent between Browns Bank and Georges Bank,despite these being separated by a stretch of deep water that likely acts as abarrier to movement of adult cod (Lage et al., 2004). Here, it is likely that agyre system leads to retention of eggs and larvae on the two offshore banks,but those spawned on the Nantucket shoals do not enter this gyre and areeither retained locally, or are transported southwest. This evidence iscompatible with both larval dispersal and adult habitat fidelity-determiningspatial patterns of genetic diversity (Ruzzante et al., 1998, 1999).

There are several other examples where substantial genetic differenceshave been identified within regions. Populations in the Canadian Arcticsaltwater lakes at the extreme northwest of the species range are stronglygenetically differentiated from Atlantic populations, and show much lower


genetic diversity (Hardie et al., 2006). This evidence is consistent with along period of genetic isolation linked to a habitat barrier. Similarly, strongpatterns of genetic differences have been found between populations in theNorth Sea and the Baltic Sea (Nielsen et al., 2003). In this case, a zone ofadmixture is flanked at each side by non-admixed populations (Nielsenet al., 2003, 2006); this pattern is associated with local adaptation fordiffering salinity regimes. Such extreme population structuring is not alwayscommon within regions, and weak genetic structuring, or genetic homo-geneity, are more typical results of studies employing neutral markers atspatial scales around 1000–2000 km (e.g. Beacham et al., 2002). In somecases, genetic differences between populations have been recovered, butthey are not always directly correlated with known environmental condi-tions or geographic distances. On the northern coast of Norway, forexample, coastal cod have clear spatial genetic structure, but no evidenceof isolation-by-distance ( Jorde et al., 2007). In this case, it would appearthat gradual adult or larval dispersal is unlikely, and instead spatial structurehas formed through sporadic colonization waves of genetically similarindividuals.

The existence of co-occurring populations that are geneticallysegregated has also become apparent. In Norway, there are differencesin otolith shapes between the Arctic offshore cod that overwinter inthe warmer, deeper waters, and the coastal inshore cod that overwinter inthe cooler, shallower water, and early genetic work found that theseoffshore and inshore cod possessed adaptive differences in their haemoglo-bin HBI allele frequency (M�ller, 1966). In the North Sea–Skagerrak areathere is also evidence that the migratory-offshore North Sea stock and thenon-migratory-coastal Skagerrak stock are genetically different, but simi-larly co-occur within inshore waters (Case et al., 2005). Genetically differ-ent offshore migratory and inshore overwintering cod are also present inNewfoundland (Ruzzante et al., 1996a,b), and have been found to differ intheir blood ‘antifreeze’ protein levels, with the inshore cod that experiencethe cooler winter temperatures possessing higher antifreeze protein concen-trations. These genetic differences appear to exhibit interannual stability(Ruzzante et al., 1997, 2000).

1.3. Traits in different stocks

There is an increasing body of evidence suggesting that genetically differentcod stocks differ in adaptive life history traits. In the Skagerrak, wherepopulation structure is apparent at a scale of less than 100 km, there isapparent spatial variability in traits, such as juvenile growth rate that corre-sponds with observed genetic variation (Olsen et al., 2008). In support of anevolutionary explanation for the observed pattern, a range of molecular andbreeding studies have revealed evidence for selection on functional genes.


Several genes show variation at the stock level (Hutchinson, 2008), perhapsthe most studied gene in this context is pantophysin (PanI) (Pogson et al.,2001), formerly synaptophysin (Syp I) (Fevolden and Pogson, 1997). Par-ticular life history traits have been associated with this gene, for example,differences in mean weight, length and growth rates have been shown to bedependent on the PanI genotype around Iceland ( Jonsdottir et al., 2002,2003), and temperature and salinity have been shown to influence the PanIgenotype frequency in the Northeast Atlantic (Case et al., 2005). These fieldresults have been supported by ‘common garden’ experiments showingPanI-dependent differences in growth rate and condition factor of indivi-duals reared to 10 weeks. Although these results may be due to genes linkedto the PanI (Case et al., 2006), the pattern nevertheless suggests that stronglocal adaptation of stocks is present in the natural environment.

1.4. Movement and activity

The movement and activity patterns of predatory fish such as Atlantic codcan be considered a major driver of the spatio-temporal dynamics ofpopulations and communities within ecosystems. Movements such asmigration, dispersal and regional philopatry, when played out over longertemporal scales, not only contribute to observed patterns of populationsub-structuring and connectivity, but will also determine how populationdistribution responds to drivers of climatic change or fishing pressure. Moni-toring movements of cod in relation to environment is therefore relevant tounderstanding the effects of these drivers on cod population re-distributions,with a significant role in future adaptive management regimes.

1.4.1. Adult movementsEarly mark-recapture studies, fishery surveys and fishing reports informed ageneral picture of mature cod annual movements, with migration to spawninggrounds followed by spent cod returning to their feeding grounds afterspawning (Harden Jones, 1968). Although this general model is broadlyapplicable to cod, the emerging paradigm is that their movements bygeographic location and by season are complex, with marked differencesin behaviour even within a region such as the North Sea, for example(Hobson et al., 2007). The recent advances in remote telemetry technologyfor tracking fish, particularly the miniaturization of data-loggers, has enabledthese insights (Arnold and Dewar 2001; Sims, 2008) with adult cod move-ments and activity being recorded over long time periods (>1 year) innearly all the main regions within its geographic range (Clark and Green,1990; Cote et al., 2003; Metcalfe, 2006; Neat and Righton, 2006; Neatet al., 2006; Rillahan et al., 2009; Robichaud and Rose, 2001, 2002, 2003,2004; Steinhausen et al., 2006; Wright et al., 2006). Data-logging storagetags have been attached to cod and used to obtain regionally explicit,


individual-based data on horizontal and vertical movements and thermalhabitat. These studies support the contention that there is not a singleparadigm of extended movement between spawning and foraging areas, asgenerally supposed previously (e.g. Harden Jones, 1968), but rather thatsuch movements vary from individual to individual and from sub-stock tosub-stock (Hobson et al., 2009). Behavioural plasticity is evident for cod inthe extent and timing of migration, in the persistence of spawning orfeeding site fidelity (philopatry), and also in relation to the types of beha-viour displayed on feeding grounds and where and when they occur in thewater column compared with remaining close to the seabed (Hobson et al.,2007, 2009; Neat et al., 2006; Palsson and Thorsteinsson, 2003; Rightonet al., 2001).

Residence and homing behaviour have been shown to be importantfeatures of Atlantic cod behaviour (Hobson et al., 2009). Cod are known toaggregate seasonally to spawn and to feed at particular geographic locations(Metcalfe, 2006). For example, spawning area fidelity shown by aggrega-tions representing more or less distinct groups of fish is a behavioural traitsupported by at least some evidence from genetic and mark-recapturestudies (Metcalfe, 2006). However, the degree to which residence andhoming applies to different populations and to sub-stocks has been foundto vary greatly depending on geographic location. Robichaud and Rose(2004) proposed four categories of populations of Atlantic cod based on thedegree of migration and philopatry. The latter authors identified ‘sedentaryresidents’ that exhibit site fidelity year round, ‘accurate homers’ that returnto spawn in a specific area, ‘inaccurate homers’ that home to a much broaderarea around the original tagging location in the following years, and‘dispersers’ that move and spawn in a more irregular pattern within largegeographical areas (Metcalfe, 2006). It seems coastal areas support residentpopulations more commonly, such as those in the Norwegian fjords, theIcelandic coast and the Canadian east coast (Metcalfe, 2006), whereas theNortheast Atlantic has large subpopulations that home with accuracy com-pared with the Northwest Atlantic that has more inaccurate homers anddispersers (Metcalfe, 2006; Robichaud and Rose, 2004). Nested within thislarger scale complexity, are the variations in individual patterns observedwithin a region and which exemplify the problem with broad categorisationof cod behaviour.

Comprehensive studies of cod movements in the Northeast Atlantichave deployed over 3000 electronic tags in the Barents Sea, the North Sea,the Baltic Sea and on the Icelandic and Faroe Plateau between 2002 and2005, with over 850 tags returned by fishermen, giving more than 130,000days of data (www.codyssey.co.uk). In the North Sea, for example, it ispossible to link horizontal with vertical movement patterns. For individualtracks ranging in duration from 40 to 468 days, cod showed horizontalmovements up to 455 km, however, individuals did not always show signs


http://www.codyssey.co.uk

of migration during winter months, even displaying continuous localisedresidence for up to 360 days (Hobson et al., 2009). This indicates that cod donot always migrate between feeding and spawning grounds. Vertical move-ments showed even greater flexibility, with a variety of movement patternsseen within both periods of residence and directed horizontal movement.Close association with the seabed was seen during both directed horizontalmovements and residency, while midwater oscillations in swimming depthwere also evident during both horizontal movement types. Therefore,vertical patterns in activity alone could not be used to reliably define periodsof migration or localised residence (Hobson et al., 2009). Taken together,the results from studies that have tracked large numbers of individual cod forlong periods suggest that Atlantic cod behaviour is mediated by complexinteractions between biological and ecological factors that result in diversemovements and activities in relation to changing environment (Hobsonet al., 2009; Righton et al., 2001).

1.4.2. Cod thermal habitsElectronic tagging data show that cod occupy depths from 10 to 860 m, andwater temperatures of�1.5 �C in polar fronts off Iceland and in the BarentsSea, to 21 �C when resting on the seabed in the southern North Sea.In terms of cod distributional responses to thermal habitat, such studiesreport, for example, that northern North Sea populations above 57 �Ndo not intermix with southern populations below 56 �N (Neat andRighton, 2007), thus concurring with previous mark-recapture pro-grammes (Righton et al., 2007; Robichaud and Rose, 2004; Wright et al.,2006) and genetic studies (Hutchinson et al., 2001). Within the northernNorth Sea, west Shetland is the warmest and least variable region (<3 �Cvariation) and no cod movement from here to cooler waters has beenrecorded. By contrast, cod released back into the east Shetland and VikingBank populations moved rapidly into cold fronts and prolonged occupancyof cooler waters was recorded (Neat and Righton, 2007). Within thesouthern sector of the North Sea, the German Bight population experiencesa highly variable thermal environment, with intra-annual variation of�14 �C. The greatest acute fluctuations recorded comprised a 7 �C decreaseover 3 days, and a 7 �C increase over a 2-day period. Individuals from thisregion, and the neighbouring eastern English Channel mostly migrated onlyshort distances, or remained resident, despite experiencing water tempera-tures up to 19 �C during late summer and autumn (Neat et al., 2006;Righton et al., 2001). Notably, adult cod only commenced vertical migra-tion in October–November once surface temperatures began to decline(Righton et al., 2001), and during this period some mature individuals havebeen recorded migrating to spawning grounds in the eastern English Channeland Southern Bight (Daan, 1978).


Given the complex behaviour of cod, and in relation to thermal changesand other biological and physical factors operating across the broad range oftemperatures in which it is found, predicting how individual cod willrespond to climate-driven changes in sea temperature, for example, remainschallenging.

1.4.3. Larval dispersalGenetic evidence for reproductively isolated stocks that co-occur on groundsduring non-breeding periods, but that often segregate during spawningseasons, demonstrates the importance of knowledge of spawning and nurseryhabitats for appropriate management. Tests of population genetic differencesusing adult individuals have informed us about the general patterns of spatialand temporal stock structure, but such studies convey little about the relativeimportance of spawning grounds within spatial management units. Tradi-tionally, ichthyoplankton surveys and visual identification of larval speciesidentity have been used for identification of spawning grounds. Indeed, thisapproach has allowed broad-scale mapping across its range of cod spawningareas and the general pattern of egg and larval transport (Brander, 1997).Eggs and larvae, however, can be difficult to separate visually from thoseco-occurring gadoids such as whiting (Merlangius merlangus) and haddock(Melanogrammus aeglefinus) (Fox et al., 2005). Recent developments in molec-ular genetic techniques have enabled reliable identification of cod eggs,revealing, for example, considerable overestimation of cod abundance inthe Irish Sea (Fox et al., 2005; Taylor et al., 2002). This approach has alsoallowed the identification of active spawning grounds in the North Sea(Fox et al., 2008). Importantly, these locations, including the Dogger Bank,German Bight and Moray Firth show close corroboration with spawningareas inferred from historical survey data, implying cod have well-defined,active spawning grounds that have been used by multiple generations.However, to date there is very little available information on the extent oflarval dispersal or retention in relation to these spawning grounds, or the cuesemployed for location and settlement on nursery grounds. Hydrodynamicmodels coupled with in situ ichthyoplankton surveys for model verificationoffer considerable promise for revealing mechanisms of larval dispersal orretention over large spatial scales (van der Molen et al., 2007).

2. Impacts of Climate Change

Global climate has warmed to temperatures unprecedented over thelast 1300 years. Anthropogenic inputs into the atmosphere are now recog-nised as the primary driver (IPCC, 2007). The latest model predictionsindicate that global mean surface temperature will increase by a further


1.1–2.9 �C (low emissions B1 scenario), or 2.4–6.4 �C (high emissions A1FIscenario) (IPCC, 2007). Climatic warming has been observed in marineenvironments across the North Atlantic, and appears to be of a greatermagnitude and duration than any periods in recent history (Fig. 3.3)(IPCC, 2001, 2007; Southward, 1963; Southward and Boalch, 1994;Southward et al., 1988). Marine ecosystems are already responding tothese changes in sea temperature, through polewards shifts in biogeographicranges (Beaugrand et al., 2002; Berge et al., 2005; Griffiths, 2003; Hellberget al., 2001; Mieszkowska et al., 2006, 2007; Zacherl et al., 2003), pheno-logical changes (Genner et al., 2009a; Sims et al., 2001, 2004), and throughalterations in the relative abundance of ectothermic species and the struc-turing of the communities they comprise (Barry et al., 1995; Berge et al.,2005; Genner et al., 2004, 2009b; Hellberg et al., 2001; Mieszkowska et al.,2006; Sagarin et al., 1999; Southward, 1995; Southward et al., 1988).Furthermore, there is burgeoning evidence for climate-driven effects onmarine fishes (Graham and Harrod, 2009). In this section, we explore therole of climate drivers on the biology and ecology of Atlantic cod and, inaddition to description and discussion of the known or potential biologicalimpacts, we identify knowledge gaps where new studies will progress ourunderstanding towards prediction of cod responses to changing environments.

Year

Mea

n an

nual

Nor

th A

tlant

ic S

ST

(�C

)

20.2

20.4

20.6

20.8

21

21.2

21.4

1870 1890 1910 1930 1950 1970 1990 2010

Figure 3.3 Mean annual sea surface temperatures of the North Atlantic (weightedaverage 5��5� grid squares from 0 to 70 �N). Data derived from the National Oceanicand Atmospheric Administration Kaplan SST data set, and are available at http://www.cdc.noaa.gov/data/timeseries/AMO/.


http://www.cdc.noaa.gov/data/timeseries/AMO/



2.1. Biogeographic changes

Distributional limits of marine fish species are governed to a large extent byregional thermal regimes. The observed thermal occupancy or ‘climateenvelope’ of species is the basis for many models that attempt to predictfuture abundance and distributions (Pearson and Dawson, 2003; Waltheret al., 2002, 2005). Where environmental conditions change to fall withinthe physiological tolerance limits of a species, range extensions are predictedas fish are able to colonize new areas of suitable habitat. In practice,however, the range edge may lie some distance inside this fundamentalniche envelope. This is because population distributions are often influ-enced by additional environmental parameters and biological interactionssuch as competition, predation and prey availability, parasitism and otherfactors such as habitat availability and dispersal ability (Brett and Groves,1979; Davis et al., 1997; Kelsch and Neill, 1990). There is still no generalmodel to describe how thermal physiology of ectotherms and climateinteract to determine biogeography (Chown and Gaston, 1999; Clarke,2003). Clearly, development of such models is a significant challenge forunderstanding and predicting the macroecological responses of fish species.

Data from commercial fishing and research vessel surveys have been usedto explore how the biogeography of cod has changed (Blanchard et al.,2005; Daan, 1994). However, use of abundance data from trawl surveys canbe insensitive to short-term individual variations in distribution (Neat andRighton, 2006) which can make range assessments for spatially structuredstocks problematic (Hutchinson et al., 2001; Metcalfe, 2006; Wright et al.,2006). Both migratory behaviour and density-dependent effects linked toprey abundance can affect geographic distributions (Beaugrand et al., 2003;Blanchard et al., 2003; Moyle and Cech, 2004; Roessig et al., 2004; Swain,1999; Swain et al., 2003). Moreover, other environmental variables such assalinity, storminess, cloud cover and precipitation can strongly influence thedistribution and productivity of marine ecosystems (Bakun, 1996; Stensethet al., 2004) and the phenology of production cycles (Edwards andRichardson, 2004). The stochastic nature of these parameters is reflectedin the annual fluctuations in abundance of cod across its range.

Despite the large diversity of factors that can influence distributions,there is compelling evidence that populations have shown responses toclimate-related thermal changes during the twentieth century. The NorthAtlantic warmed at the basin-scale during the 1920s and 1930s, and duringthis warm period the distributional limits of cod were observed to extendsome 1200 km further north from southern Greenland to Disko Island(northwest Greenland), while the Barents Sea population apparently shiftedeastwards (Hansen, 1949; Jensen and Hansen, 1931). Similarly, Icelandiccod were restricted to spawning on southern shelf regions until the1920s, but afterwards spread to the northern shelf (Sæmundsson, 1934;


Vilhjalmsson, 1997). During a cool period during the 1960 and 1970s, thesechanges were seen to reverse. Cod evidently retracted further south in thecolder conditions and disappeared entirely from coastal waters around DiskoIsland (Buch and Hansen, 1988). Furthermore, the population spawning onthe northern Icelandic shelf declined to minimal levels during this period,presumably due to a shift in abundance centred further south. During thelate 1980s and early 1990s, cooler waters were also present in the NorthwestAtlantic from the Labrador Shelf to the Grand Banks, leading to a suddendecline in cod abundance (Atkinson et al., 1997; de Young and Rose, 1993;Drinkwater, 2002; Rose et al., 1994, 2000; Taggart et al., 1993).Whilst fishing activity may also have played a role in establishing this pattern(Hutchings, 1996; Hutchings and Myers, 1994b; Myers et al., 1996),analyses of blood chemistry (Rose et al., 2000) and genetics (Ruzzanteet al., 2001) also support a biogeographic shift of Northwest Atlantic stocksto lower latitudes at this time.

Apparent northward shifts of both the centre of distribution andthe southern range limit of cod in the southern North Sea in recent yearsare possibly a direct response of individuals to increased seawater tempera-ture over the last decade (Hedger et al., 2004; Perry et al., 2005; Rindorf andLewy, 2006). However, there is no direct evidence to suggest that fish haveactively moved to avoid increasing temperatures (Rindorf and Lewy, 2006).Studies supporting a northward shift in cod have based analyses on theassumption that there is single population in the North Sea that is mostabundant at the range centre, and has decreasing numbers of individualstowards range limits. For species that are more or less in a steady state, andare not changing in abundance or distribution rapidly, this pattern can bebroadly accepted. By contrast, where a single dimension of the nichechanges rapidly, and where there is evidence of population subdivisionand local adaptation, responses may not be straightforward. This may bethe case in the North Sea given some evidence that several discrete stocksare present (Hutchinson et al., 2001; Metcalfe, 2006; Wright et al., 2006),and which appear to have distinct habitat preferences during different lifehistory stages (Righton et al., 2007; Robichaud and Rose, 2004; Wrightet al., 2006). An additional consideration is that individual cod can movelarge distances or remain resident, and behaviour shows great flexibilityacross multiple spatio-temporal scales, resulting in complex spatial dynamics(see Section 1.4.1). Thus, there may not necessarily be a long-term locationfor occupation of the most suitable environmental conditions where thehighest abundance of fish can be found. The case of the North Sea is furthercomplicated by a seasonal inversion of the latitudinal temperature gradient,with the southern North Sea being colder in the winter but warmer in thesummer than the northern North Sea. Furthermore, analysis of North Searesearch survey data suggests that cod have responded to a winter bottomtemperature increase of 1.6 �C over 25 years by moving into deeper water at


an average rate of about 7 m per decade (Dulvy et al., 2008). Together, thisevidence suggests that climate-driven changes to cod distributions may bemore complex than predicted using straightforward ‘climate envelope’approaches.

Observed northward shifts of the southern range limits could also beattributed to local population abundance changes due to fishing pressure,variation in migration between populations (Hedger et al., 2004) or spatialdifferences in the thermal tolerance limits of adult cod leading to localdepletion of stocks (Neat and Righton, 2006; Portner et al., 2008). Thelack of concordant responses to thermal regimes shown by individual cod isconsistent with temperature being only one of the factors determininghabitat choice (Neat and Righton, 2006). Occupancy of space by cod inhistorical habitats has declined from 90% to lower than 50% over the last30 years, and spatial distributions have become increasingly characterized byaggregations in areas of optimal thermal habitat (Blanchard et al., 2005;Horwood et al., 2006; Marshall and Frank, 1994; Myers and Stokes, 1989;Rose and Kulka, 1999). These studies support earlier observations ofdensity-dependent habitat selection in cod (Myers and Stokes, 1989;Swain and Sinclair, 1994), and strongly suggest changing distributionsmay additionally be linked to aggregation behaviour.

2.2. Physiology

Most fish are ectotherms with limited capacity for internal heat regulation(Clarke, 1993). To predict how changes in global climate will affect fishdistributions, it is important to know how physiological functions areinfluenced by temperature variation, and to quantify thermal tolerancethresholds (Guderley, 1990; Portner, 2001, 2002; Portner and Knust,2007; Portner et al., 2001). This individual-level physiological responseextrapolates to population, community and ecosystem-level responses(Roessig et al., 2004). Although temperature is recognised as an importantcontrolling factor for biotic processes, from cellular to ecological levels oforganisation (Fry, 1971), defining thermal optima is a complex process dueto differential effects of temperature on various physiological processes, andon different life history stages. For example, larval fish drifting passivelywithin the plankton may be more vulnerable than juvenile or adult fish thatcan actively move away from unfavourable conditions. Moreover, differentstocks have also been observed to show local adaptation to differing thermalranges (Coutant, 1977, 1987; Daan, 1994; Scott, 1982).

2.2.1. Tolerance limits and thermal preferencesBoth adult and larval cod can tolerate salinities from almost 0% to 35%, butexhibit some preference for 30–35%. They also have a wide thermaltolerance, and have been recorded in waters ranging from �1.5 to 21 �C,


although their temperature range is typically between 0 and 12 �C (Trembleand Sinclair, 1985; Wise, 1961). Despite this apparent broad tolerance, theyare highly sensitive to even slight water temperature variation of �0.3 �C,and individuals seemingly alter their position in the water column tomaintain themselves near their temperature for optimal performance, Topt

(Fig. 3.4) (Herbert and Steffensen, 2005; Rose et al., 1994). Body temperaturehas a significant effect on fitness of cod (Fry, 1947; Huey and Berrigan, 2001),so Topt is expected to correspond to the temperature of maximum fitness,Trmax (Beamish, 1978; Schurmann and Steffensen, 1997). Temperature-fitness curves are asymmetric, however, and therefore body temperaturesgreater than Tmax can lead to stress and rapid fitness decline (Martin andHuey, 2008). The proximity of stressful temperatures to Trmax can result inTopt being lower than Trmax in natural, thermally variable environments. Thismay have important implications for predicting physiological fitness inresponse to future climate warming scenarios.

2.2.2. Sublethal physiological thresholdsIt may not always be possible for a fish to occupy a thermal environmentmatching the temperature of optimal performance, and thermal stress mayresult from exposure to unfavourable temperatures. The first symptoms ofthermal stress are caused by the limited capacity of respiratory systems toprovide sufficient oxygen to body tissue above the pejus temperature Tp

(pejus, meaning getting worse, deleterious) (Frederich and Portner, 2000;Portner, 2001; Portner et al., 2001). This is the threshold beyond which thecardiorespiratory system cannot increase aerobic metabolism and body

0Adult heart rate curve

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Figure 3.4 A schematic diagram of the thermal physiological thresholds of Atlanticcod. See Sections 2.2.1, 2.2.2 and 2.5 for explanations of terms and concepts.


fluids start to become hypoxic. This has been determined experimentally tobe between 13 and 16 �C in adult cod (Fig. 3.4) (Sartoris et al., 2003), andbeyond this range cardiac arrhythmia, if present, can cause a reduction inblood circulation capacity. As a consequence, this results in lower venousoxygen concentrations, onset of anaerobic mitochondrial metabolism, alter-ation of enzymatic rates (Clarke, 1993; Coutant, 1987; Fry, 1971) and asudden decrease in intracellular pH (Van Dijk et al., 1997). This in turn isaccompanied by energetic collapse in white muscle (Foster et al., 1993;Sartoris et al., 2003), reduced scope for whole organism aerobic activity and,ultimately, death at the critical temperature threshold, Tcrit (Lannig et al.,2004; Portner, 2001; Sartoris et al., 2003). Experimental data suggest thatTcrit ranges between 16.0 and 22.2 �C in adult cod populations (Gollocket al., 2006; Lannig et al., 2004; McKenzie, 1938; Portner et al., 2008;Sartoris et al., 2003) and is lower at 15.5–18.0 �C in juveniles (Perez-Casanova et al., 2008; Yin and Blaxter, 1987), although survival uponacute exposure to 20 �C has been demonstrated in controlled laboratoryconditions (Perez-Casanova et al., 2008). This variation in response may bedue to different experimental methodologies, but it could also reflect stock-specific adaptation of cod (Portner et al., 2008).

The highest partial pressure of venous oxygen in southern North Seacod held in laboratory conditions occurs at approximately 5 �C (Lanniget al., 2004), which relates closely to Topt for adult growth. The frequency ofhaemoglobin genotypes in the population can be affected by environmentaltemperature experienced by parental fish, and underlies thermal preferencesin cod (Andersen et al., 2009). Warmer water preferences are associatedwith the Hb-1 genotype (Petersen and Steffensen, 2003), with highestfrequencies of the Hb-1–1 allele found in the southern North Sea(Husebo et al., 2004; Sick, 1965), a region of some of the warmest bottomtemperatures within the cod biogeographic range (Vaz et al., 2007).Although Topt of all haemoglobin genotypes appears to be centred around14 �C ( Jordan et al., 2006), optimal oxygen extraction rates occur below12 �C (Colosimo et al., 2003), which may explain why many cod popula-tions occur in waters below this temperature.

Thermal adaptation generally optimises whole animal aerobic scope towithin a thermal range or window (Portner, 2001, 2002). However, short-term thermal acclimatisation may also allow occupation of specific thermalregimes, such as the 2–3 �C sea surface isotherm characterising the seasonalmigration highway used by cod in the Northwest Atlantic (Rose, 2004b).Evidence for seasonal acclimatisation in cod is not widespread, but hasbeen provided by laboratory trials demonstrating that the thermal limitbeyond which heart rates begin to decline can be elevated by acclimatisationto warmer temperatures (Lannig et al., 2004). This suggests that cod maybe able to buffer the effects of climate-linked sea temperature warmingsufficiently well in the short term, however, as sea temperatures continue


to rise in the region occupied, shifts in distribution may eventually takeplace that prevent exposure to temperatures beyond the pejus temperature.

2.3. Metabolic scope for activity

Metabolic rate is temperature -dependent (Claireaux et al., 2000; Lanniget al., 2004) and cod inhabiting temperate seas need to acclimatize metabol-ically to seasonal fluctuations in sea temperature. The costs of routinemetabolic activity are lower for individuals experimentally exposed tocolder water. In homogeneous water conditions, voluntary activity, meta-bolic rate and oxygen consumption all increase in response to a 2.5 �C risein temperature, leading to a subsequent decrease in scope for activity(Claireaux et al., 1995). When presented with a thermally stratifiedenvironment, however, behavioural changes are exhibited by cod, withindividuals swimming away from thermally stressful locations (Claireauxet al., 2000).

It appears that both swimming speed (Claireaux et al., 1995) and foragingrate (Peck et al., 2003) are also determined by thermal conditions. BetweenJune and August in the southern North Sea, decreased activity and predom-inantly benthic habitation were recorded from electronically tagged adultcod. When sea temperatures cooled, first nocturnal activity, then almostcontinuous activity took place during the following months (Righton et al.,2001). This pattern corresponds with expectations about energy conserva-tion (Arnold and Walker, 1992). When higher temperatures are encoun-tered it would be expected that they would either be avoided (O’Brienet al., 2000), and/or activity reduced, since occupation of higher tempera-tures will increase standard metabolic rate and reduce scope for aerobicactivity (Soofani and Hawkins, 1982; Soofiani and Priede, 1985). Growthalso decreases under such conditions, with individuals apparently switchingto a ‘translucent’ phase where an opaque band is formed during otolithgrowth (Pilling et al., 2007), indicating exposure to unfavourable tempera-tures (Hussy et al., 2004). Earlier onset and increased duration of thetranslucent zone of growth in recent decades has been attributed toincreased spring/summer water temperatures (Beckman and Wilson,1995), indicating that climate warming may be extending the period ofmetabolic stress (Pilling et al., 2007).

Sea surface temperatures have exceeded Topt for short periods duringrecent summers in the southern North Sea, for example. The subsequentdecrease in aerobic and locomotory performance will theoretically havebeen sufficient to impair activity such as to prevent optimal feeding in adultindividuals (Lannig et al., 2004; Portner, 2001; Portner et al., 2001). Thismay explain the seasonal absence of cod in the southern North Sea regiondespite apparent prey availability (Lannig et al., 2004). From these results ithas been suggested that if the climate continues to warm, seasonal


disappearance of cod from some areas may increase in frequency andduration. However, these conclusions assume that Topt does not shift as aresult of acclimation to regional temperature regimes, which may not be thecase of course. Differences in compensatory capacity to specific temperaturechallenges are generally expected for populations inhabiting different watermasses or latitudes as a result of acclimation to local thermal regimes (Clarke,1993), so it is unlikely that specific thermal thresholds will be the same for allcod populations across the biogeographic range.

2.4. Maturation and spawning

Significant correlations between mean annual sea temperatures and age atmaturity have been found for many cod stocks ( Jorgensen, 1990, 1992;O’Brien, 1999; Yoneda and Wright, 2004). Together these results indicatea 1-year reduction in maturation age linked to a 2 �C increase in tempera-ture (Drinkwater, 2002). Hence, closer to the southern range edge of thespecies, maturation is predicted to be at a younger age. This pattern hasimplications for future stock success in warmer climates because smaller,younger fish are less fecund and spawn for shorter periods (Kjesbu et al.,1996), and warmer spring seasons may promote earlier maturation.

Climate-linked sea temperature changes may have direct and indirecteffects on cod energy provisioning and maturation processes that precedespawning. Cod build up energy reserves during summer and autumn, andmature during the winter months. Mature female fish in better conditionprior to spawning tend to be more fecund (Kjesbu et al., 1991), and expendless energy and lose less somatic mass during the spawning season (Lambertand Dutil, 2000; Lloret and Ratz, 2000; Ratz and Lloret, 2003). Hence,these fish are at less risk of subsequent natural mortality (Krivobok andTokareva, 1972; Love, 1958). When energy reserves are low, investment inreproduction by females may be maintained, but at a somatic cost, andreproduction may also be reduced or delayed in extreme conditions to limitsomatic loss. Changes in environmental conditions and subsequent ecolog-ical processes that negatively affect food intake will influence the energybudget and ultimately reduce productivity of the stock (Lambert and Dutil,1997). If fishing pressure and climate change act synergistically to reducethe age and condition of the spawning stock, population fecundity maydecline (Ottersen et al., 2006). Faster development of early life stages andsubsequent higher survival under warmer climatic regimes may, however,counteract any such decline in fecundity.

Peak spawning dates have been found to vary among different Norwe-gian coastal cod populations kept in identical environmental conditions(Ottera et al., 2006). This indicates that spawning time is under geneticcontrol, and could be an adaptation related to environmental conditions intheir source location. Consistent with this evidence, survey data show cod


do not rapidly alter spawning time to match the timing of life history eventsin zooplankton prey species (Beaugrand et al., 2003). This suggests thatstock adaptation may result in a limited capacity for the stock to respondrapidly to climate-driven changes in peak abundance of prey. Thus, it canbe hypothesised that weak year classes following high larval mortality maybecome more common with warming sea temperatures.

Contrary to the assumed random mating strategy of many broadcastspawners, there is evidence for male lekking behaviour in cod (Robichaudand Rose, 2004;Windle and Rose, 2007), and for direct female mate choice(Engen and Folstad, 1999; Rowe and Hutchings, 2003; Rowe et al., 2004;Rudolfsen et al., 2005). In laboratory trials, both males and females displayedhigher reproductive success when mating occurred between larger indivi-duals (Rowe et al., 2007). The observed reduction in the size spectra of wildfish is thus likely to be affecting total reproductive output (Bekkevold, 2006;Bekkevold et al., 2002). Although climate will influence fecundity throughtemperature-related effects on maturation and reproductive success, size-targeted fishing mortality (of the largest fish) is one of the most likelydominant factors negatively affecting subsequent year class strength andrecovery of spawning stock biomass (SSB).

2.5. Early life stages

Cod eggs and larvae suffer high mortality (up to 99.9%) via predation(Campana, 1996; Cushing and Horwood, 1994; Houde, 1989; Leggettand Deblois, 1994; Shepherd and Cushing, 1980). The growth-predationhypothesis predicts a direct relationship between mortality rate and growthrate of early life stages of fishes (Anderson, 1988; Hare and Cowen, 1997),with more rapid egg and larval development promoting metamorphosis atan earlier age, thereby decreasing the duration of pre-juvenile stages(Drinkwater, 2005). Support for this theory has come from both experi-mental and simulation studies on early life stages of cod, and togetherthese show how small changes in early growth rates due to increases intemperature can lead to large increases in numbers surviving to recruitment(Chambers and Leggett, 1987; Houde, 1989; Meekan and Fortier, 1996;Miller et al., 1988; Pepin and Myers, 1991).

Cod eggs are found over a wide range of temperatures, from �1.5 �C inthe Northwest Atlantic, to 9 �C in the Celtic Sea (Geffen et al., 2006), andthere is evidence of local adaptation in development rates (Houde, 1989).Cod eggs from North Sea stocks cannot develop at temperatures less than1.5 �C, while larvae from the Baltic Sea can survive exposure to 1 �C, andeggs from the most northern populations will develop below 0 �C (Geffenet al., 2006; Valerio et al., 1992; Wieland and Jarre-Teichmann, 1997). Eggincubation periods can also vary significantly with temperature (Pauly andPullin, 1988; Pepin et al., 1997). Much of the observed seasonal variance in


egg and larval development times (Pauly and Pullin, 1988) and hatching size(Miller et al., 1988) can also be attributed to thermal conditions, with sizedecreasing as temperature increases. Thermal tolerance experiments,together with knowledge of spawning locations, indicate that it is unlikelythat wild eggs become exposed to lethally high water temperatures imme-diately after release. Egg mortality is probably caused by other processesincluding predation and disease, but egg mortality due to sublethal effects ofincreasing energetic costs at high temperatures may also take place (Nissling,2004).

Optimal temperature for growth (Toptg) undergoes a clear ontogeneticshift in cod (Fig. 3.4) (McCauley, 1977; Reynolds, 1977). Yolk sac larvaehave the lowest Toptg ( Jobling, 1988) while the highest Toptg is for freeswimming larvae and juveniles ( Jobling, 1994; McCauley and Huggins,1979). This ontogenetic difference in Toptg can range from 2 to 11 �Cdepending on the local thermal regime inhabited by the source population(Brander, 1994, 2005; Buckley et al., 2004; Bunn and Fox, 2004; Nissling,2004), but is centred around 7 �C (Buckley et al., 2004). Larval growth ratesincrease as temperature increases between 4 and 14 �C (Caldarone et al.,2003; Laurence, 1978; Otterlei et al., 1999; Steinarsson and Bjornsson,1999) with time to metamorphosis decreasing from 56 days at 4 �C, to23 days at 14 �C (Otterlei et al., 1999). Laboratory estimates of growth ratesmay, however, be dictated in part by indirect thermal effects on foodlimitation, as was observed for Georges Bank cod larvae during an anoma-lously warm period of 1992–1994 (Buckley et al., 2004).

The slowest growing cod larvae are found both in the cold waters of theNortheast Arctic (Otterlei et al., 1999), and in warm water towards thesouthern end of the range (Buckley et al., 2004) including the southernNorth Sea (Pilling et al., 2007). Survival of larvae has been recorded attemperatures as high as 12 �C in the Irish Sea (Geffen et al., 2006). Earlyjuvenile cod from the Irish Sea (Geffen et al., 2006) and those from theNorwegian coastal population exhibit higher Toptg and are heavier at thesame life stage than individuals inhabiting colder waters of the NortheastArctic (G�do and Moksness, 1987; Otterlei et al., 1999). This indicates thatupper pejus (deleterious) temperatures have not been reached, and thattemperature-driven growth relationships seem to be population specific.

Investigations to date indicate that slight warming of the marine climateis likely to enhance egg and larval survival by decreasing the time taken toreach metamorphosis that in turn limits the temporal window of greatestpredation risk. Even stocks close to southern range limits in the centralNorth Sea are likely to show increased survival of early larval stages due towarming of between 1.5 and 4 �C during the twenty-first century (Hulmeet al., 2002). If predator–prey relationships remain unchanged it is possiblethat the survival of young fish may therefore increase. The lagged responsesof cod to climate warming may thus be driven by conditions affecting


survival, growth and food availability during early life stages (O’Brien et al.,2000; Planque and Fredou, 1999; Platt et al., 2003).

2.6. Recruitment

Recruitment success of fish can be dictated by extrinsic stochastic eventssuch as changes in temperature, winds, currents, food availability, preda-tion/parasitism, and intrinsic factors such as variation in adult condition,stock reproductive effort and age structure (Cushing, 1996; Heath andGallego, 1997; Houde, 1989). These factors subsequently affect cod pro-duction, egg viability and survival of the early life stages (Kjesbu et al., 1996;Marshall et al., 1998; Nissling et al., 1998), as well as primary and secondaryproduction of the whole ecosystem (Hooper et al., 2005).

Recent studies indicate that the dominant pattern of recruitment varia-tion may be related to an effect of climate-driven sea temperature changes(Brunel and Boucher, 2007). Such climate-related changes in recruitmentsuccess may occur through one or more of several potential mechanisms,including higher production or survival of pelagic eggs or larvae (Rijnsdorpet al., 2009). Temperature plays a key role in the variation of cod recruit-ment success through a combination of direct and indirect effects (Cushing,1996; Hermann et al., 1965; Ottersen and Loeng, 2000; Sætersdal andLoeng, 1987). Fecundity is lower in mature individuals from northerncod stocks inhabiting colder waters, but given there is no evidence forcompensation through an increase in egg size (Brander, 1994), it appearsthat the cold-induced shift in the energy budget is unfavourable for repro-ductive output (Portner et al., 2001). This is supported by observations ofstrong year classes during warmer years in northern cod stocks (de Youngand Rose, 1993; Drinkwater, 2005; Malmberg and Blindheim, 1994;O’Brien et al., 2000; Ottersen, 1996; Ottersen and Sundby, 1995;Ottersen et al., 1994; Sundby, 2000).

Interannual variation in recruitment success is strongly dependent onseasonal temperatures (Wieland et al., 2000). Temperatures between Februaryand June have most impact on recruitment and subsequent year classstrength in the North Sea. A rise of 0.25 �C has been linked to a 30%reduction in recruitment (Clark et al., 2003). Simulations using the UKHadley Centre HadCM3 climate model reveal an inverse relationshipbetween change in abundance of 1-year-old cod and sea surface tempera-tures the previous spring, implying that climate effects on life stage is key tolater population recruitment success (O’Brien et al., 2000; Planque andFredou, 1999). A broad relationship between temperature regimes andstock success has been proposed by Drinkwater (2005), who suggestedthat recruitment increases as bottom sea temperatures increase until 5 �C,with little subsequent change until 8.5 �C, before a continual decline athigher temperatures. Based on these conclusions, a 2 �C increase in sea


temperature could result in significant declines in cod abundance in theNorth Sea from recent levels, with local extinctions being more likelybeyond a rise of 3 �C (Drinkwater, 2005). This model assumes that theslope of the temperature–recruitment relationship does not vary betweenstocks, does not account for seasonal variation in temperature and does nottake into account fishing mortality, or water column profile and occupancy.Indeed, such factors may explain why temperature–recruitment relation-ships are often weak (Brander, 2000). O’Brien et al. (2000) found nostatistically significant link between environmental temperature and recruit-ment in Northwest Atlantic stocks during the 1980s and 1990s, and re-analyses of recruitment data sets tend to confirm this result (Frank, 1997;Myers, 1998; Myers and Cadigan, 1995a,b; Myers et al., 1995a). In contrast,predictions of climate change impacts on recruitment and SSB in the NorthSea have been constructed using a model that includes fishing mortality,temperature-dependent growth rates, and a temperature-dependent Rickerstock–recruitment function (Clark et al., 2003). This model indicates thatsea temperature affects population dynamics via recruitment rather thanadult growth. Moreover, the model supports the hypothesis that Februaryto June sea surface temperatures most strongly influence recruitment(Dickson et al., 1974; O’Brien et al., 2000; Planque and Fredou, 1999).Under an unchanging climate scenario, the Clark et al. (2003) modelsuggests that both SSB and recruitment should increase over the next50 years if fishing mortality remains constant. However, even under asmall forcing of the climate by þ0.05 �C per decade, which is much lessthan the 1 �Cwarming that has already occurred in UK coastal seas since themid-1980s (Hawkins et al., 2003), SSB and recruitment are predicted todecrease. Under the A1F high emissions scenario (IPCC, 2001) of þ0.26 �Cper decade, North Sea stocks are predicted to virtually disappear if fishingmortality is not reduced (Clark et al., 2003). However, the model has caveats.It is based on linear models that do not fully capture the relationship betweenrecruitment and temperature, and it also does not account for potential rate-limited recruitment at higher temperatures. There is also a lack of spatialrepresentation of adult distributions, including potential for changes inspawning locations over time (Brander, 1994, 1997; Daan, 1978).

Cod recruitment patterns may also reflect temperature-driven variabilityin availability of food resources at lower trophic levels (Rothschild, 1994).It has been demonstrated that peak spawning date in low biomass codpopulations shows strong associations with temperature (Kjesbu et al.,1994; Wieland et al., 2000). In the Northwest Atlantic, higher temperaturesappear to result in earlier annual spawning dates in stocks occupying higherlatitudes, due to accelerated gonad development (Hutchings and Myers,1994a,b). The most northern stock in the Barents Sea also shows a positiverelationship between recruitment and temperature. The opposite relation-ship was observed in stocks located at lower latitudes towards the southern


limits in the North Sea (Daan, 1994; Dickson et al., 1974; Myers, 1998).These relationships were subsequently re-tested and shown not to hold,emphasizing that studies of recruitment may need to step beyond searchingfor straightforward spawner–recruit and temperature–recruitment relation-ships (Myers, 1998).

In the North Sea, changes in the plankton community have been a keydriver of interannual fluctuations in cod dynamics. Long-term changes inrecruitment co-vary with changes in the abundance and body size of zoo-plankton prey with a 1-year time lag, and show a tighter relationship than thatobserved between cod recruitment and sea surface temperature (Beaugrandet al., 2003; Horwood et al., 2006). The relationship holds for both anoma-lously cool and warm periods, such as the gadoid outburst between the mid1960s and 1980s when cool temperatures were associated with high abun-dances of the boreal copepod Calanus finmarchicus. This copepod is a majordietary component of the cod early life stage, and these high abundancesoccurred in parallel with 12 years of high cod recruitment (Fig. 3.5).Conversely, during the warm period of the late 1990s and early 2000s,anomalously low cod recruitment reflected low biomass of C. finmarchicus.Warmer waters appear to have resulted in unfavourable conditions for theoverwintering stage of this copepod (Greene et al., 2003; Heath et al., 1999)and forced a distributional shift to higher latitudes in the North Sea(Beaugrand and Ibanez, 2004). Higher confidence can be placed on theassumptions of these shifts in biogeographic distribution due to the extensivespatial and temporal coverage of the data, and the use of direct observationaldata rather than extrapolations based on putative centres of distribution.

Direct effects of thermal regimes on physiology of larval fish, andindirect effects on their prey availability, are both likely to be importantdrivers of recruitment strength. However, the exact nature of the

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Figure 3.5 Parallel long-term changes in zooplankton fluctuations (with 1-year lag)and cod recruitment in the North Sea. Adapted from Beaugrand et al. (2003).


relationships remains unclear. The abundance and size structure of a popula-tion will depend on a range of factors, including the extent of immigrationand emigration from populations with different thermal tolerances (Simset al., 2001, 2004). In the absence of gene flow, adaptation or local acclima-tization may lead to a contraction of the spawning period and spawning area,causing fish such as cod to become more sensitive to changes in environmen-tal conditions (Ottersen et al., 1994). Heavily exploited populations of codmay therefore display amplified responses to climate change (Planque andFredou, 1999). These complications may lead to difficulties when predictingshort-term outcomes of environmental change on populations (Planque et al.,2003; Rothschild, 1994, 1998).

Biological responses may show strong relationships with large-scaleclimate indices such as the North Atlantic oscillation (NAO) (Broitmanet al., 2008; Drinkwater et al., 2003; Fromentin and Planque, 1996;Ottersen et al., 2001; Stenseth et al., 2002; Walther et al., 2002). Suchclimate indices often incorporate multiple variables and the interactionsbetween them, and thus can capture a complex interplay of weather andclimate-induced variations in the natural environment. As a consequence,they can provide useful assessments of climate fluctuations with which toexplore ecosystem change (Namias and Cayan, 1981; Stenseth et al., 2003).The NAO is the main index of winter atmospheric circulation over theNorth Atlantic. During positive NAO years, warmer winters occur andseawater temperatures are warmer around Northwest Europe. When theNAO switches to a negative phase, winter temperatures are colder in theregion (Hurrell and Van Loon, 1997; Van Loon and Rogers, 1978). Overthe last 25 years, the frequency and magnitude of NAO positive-indexevents have increased and winter sea surface temperatures have becomemilder in British coastal waters. The NAO is predicted to remain in a largelypositive phase in the coming decades.

Relationships between the NAO index, the physical environment of theNortheast Atlantic and biological responses within it have been well estab-lished (Broitman et al., 2008; Hurrell and Van Loon, 1997; Reid et al., 2001;Sims et al., 2001, 2004). Importantly, the NAO index has been linked tochanges in recruitment success of most cod stocks in this region (Ottersenet al., 2001), mainly via the direct effects of environmental temperature onsub-adult growth and survival (Attrill and Power, 2002; Dippner, 1997;Ottersen et al., 1994). When all Northeast Atlantic cod stocks are combinedwithin a single recruitment model, a significant geographic relationshipbetween the strength of the NAO and recruitment emerges, with stock-specific trends also apparent (Stige et al., 2006). Environmental conditionsduring a positive NAO index have been shown to have a negative influencefor southern stocks on both seaboards of the Atlantic, but a positive influ-ence on more northerly stocks (Brander and Mohn, 2004).


2.7. Growth

Experimental studies and analyses of catch statistics show that changes inseawater temperature exert a major influence on growth (Bjornsson andSteinarsson, 2002; Bjornsson et al., 2001; Brander, 1995, 2000; Campana,1996; Campana and Hurley, 1989; Jobling, 1988; Solberg and Tilseth, 1987;Steinarsson and Bjornsson, 1999; Taylor, 1958). As such, temperature isconsidered to be a major determinant of production in cod stocks (Dutiland Brander, 2003). Benthic water temperatures have been shown to accountfor 90% of observed variation in growth rates between cod stocks (Brander,1994, 1995) and to drive annual growth fluctuations within them (Brander,1995; Brander et al., 2003; Campana et al., 1994; Clark et al., 2003; deCardenas, 1996; Drinkwater, 2005). This temperature-dependent variabilityin growth rates is mediated by immediate physiological requirements, andtrade offs between growth and reproduction (Portner et al., 2001).

Free swimming cod tend to select temperatures in which growth rate ismaximised (Claireaux et al., 1995; Magnuson et al., 1979), but it is not alwayspossible for individual fish to maintain themselves within thermally optimalhabitats. Low temperatures result in slower growth rates and a reduction in thephysical condition via direct impacts on rate of food assimilation, and indirecteffects on food supply (Otterlei et al., 1999). The resultant physiological andecological impacts are manifested as a small size-at-age, reduced cohort size, adecline in stock biomass, and surplus energy redirected into reproductiveeffort (Brander, 1995; Campana, 1996; Krohn et al., 1996; May et al., 1965;Taylor, 1958). Meta-analyses of cod populations show that body conditionexhibits a significant increase with warmer mean sea bottom temperatures(Drinkwater, 2005; Ratz and Lloret, 2003). The temperature for optimalgrowth, however, decreases with size and age, and ranges between 14.3 and17.0 �C for newly hatched juveniles, to between 5.9 and 10.0 �C for adults(Bjornsson and Steinarsson, 2002; Bjornsson et al., 2001; Brander et al., 2003;Buckley et al., 2004; Portner et al., 2001). Thus, decreasing growth perfor-mance in adult cod is observed with increasing latitude (Brander, 2004;Portner et al., 2001). Genetic differences between stocks are also likely to beat least partly responsible for the observed spatial differences, as populationdifferences in growth rates have been seen under controlled experimentalconditions (Portner et al., 2001). Such population variation in growth rates andbody size may also be a consequence of fishing, as sustained removal of largerindividuals has resulted in evolutionary selection for individuals maturing atearlier ages and sizes (Gadil and Bossert, 1970; Olsen et al., 2004).

Although studies indicate that as seawater temperatures rise, cod inwarmer climates may experience increased growth rates, such increasesmay be counteracted by food availability, which can explain up to 97%of the variance in growth in wild cod (Chabot and Dutil, 1999). Food-dependent growth rates may become particularly apparent because


exposure to warmer water increases standard metabolic rates. Such negativeeffects on growth may be intensified in conditions of low prey density, asthe temperature of optimal performance can become lowered (Brett andGroves, 1979; Buckley et al., 2004). Since growth and survival of larval fishare implicit to many recruitment hypotheses (Anderson, 1988; Cushing,1990; Ware, 1975), and are affected by climate-driven sea temperaturechanges (Rijnsdorp et al., 2009), predictions of growth rates under futureclimates will clearly require data on prey abundance, and information onprey distribution and sub-adult feeding behaviour (Buckley et al., 2004;Dower et al., 1998; Fiksen and MacKenzie, 2002).

3. Impacts of Fishing

Marine fishing activity in the North Atlantic can be traced back over atleast 1000 years (Barrett et al., 2004, 2008), and there is compelling evidencethat this has severely depleted demersal fish stocks in the region, reflectingglobal trends. Biomass of commercially valuable demersal fish populations isnow estimated to be at only 10% of pre-industrial levels (Worm and Myers,2003), and there has been a concomitant decrease in mean trophic level oflanded fish (Pauly et al., 1998). Atlantic cod abundance in particular hasdeclined dramatically since the onset of commercial fishing. Using historicalrecords of New England cod abundance derived from mid-nineteenthcentury fishing logs, it was estimated that current population biomass nowstands at less than 5% of that in 1852 (Rosenberg et al., 2005). Reconstruc-tions using historical records or proxies have also revealed high levels offisheries exploitation affecting key biological parameters of cod. For exam-ple, by studying cod vertebrae preserved in middens in New England, largedeclines in population body size distributions have been revealed ( Jacksonet al., 2001), changes that have links to the biological effects of commercialfishing (Olsen et al., 2004).

In this section, we describe the impacts of fishing on cod populations ineach of the main regions across its biogeographic range, and bring togetherthese findings with those on climate impacts to evaluate the relative contri-bution of each set of drivers to observed trends.

3.1. Northwest Atlantic stocks

All cod stocks are now generally considered to be either fished at unsustainablelevels, are subject to moratoria following dramatic stock collapses, or haverecovery plans that do not meet ‘precautionary approaches’ advised by theInternational Council for the Exploration of the Seas (ICES) (CEC, 2001;FAO, 2002; Hutchings and Myers, 1994a,b; ICES, 2005, 2006, 2008;


Kuikka et al., 1999;Myers et al., 1997). Arguably themost dramatic collapse ofcod was that seen in the Northwest Atlantic. During 1986 and 1987 recruit-ment was very strong in all cod stocks in this region. As a consequence, fishingmortality (F) increased from 0.5 to>1.0 between 1989 and 1992 for all stocks,except that of the southern Grand Banks (Bishop et al., 1993; Myers et al.,1996). Landings initially increased as SSB was decreasing, a pattern thought tohave been caused by fish at lower population biomass tending to aggregate,perhaps making them easier to capture (Hutchings, 1996; Morgan et al., 1997;Rose and Kulka, 1999). Whatever the mechanism, catches were soon domi-nated by young and small cod (Hutchings and Myers, 1994a,b; Myers et al.,1996). It has been argued that the main factors responsible for the collapseacross many of the cod stocks by 1993 were the ignorance of the relationshipbetween fishing mortality and stock biomass, due to consistent underestima-tion of the proportion of fish harvested annually (Myers et al., 1996), and anunwillingness to cut fishing effort due to the perceived short-term economicconsequences (Rivard and Maguire, 1993; Schiermeier, 2002). Evidenceindicates that incorrect calculations of fishing mortality resulted fromoverestimation of biomass (Steele et al., 1992; Walters and Maguire, 1996),an underestimation of reductions in productivity (Rice and Evans, 1988),overweighting of abundance indices to provide the most optimistic estimatesof SSB (Myers et al., 1996, 1997) and an increase in efficiency of the fishingfleet (Hilborn and Walters, 1992; Walters and Maguire, 1996). No evidencewas found to link abundance of age classes or distributions with water temper-ature, and thus climate change was rejected as a primary driver for the collapseof these cod stocks (Hutchings and Myers, 1994a,b). A decade after themoratorium on cod fishing was introduced in 1992, populations were still athistorically low abundance (Lilly et al., 2003), and even in 2007 the SSBcontinued to have weak representation from all year classes (STECF, 2007).

3.2. Northeast Atlantic stocks

Atlantic cod have a broad distribution on the European continental shelf. Inthis section, however, rather than review stocks in all areas, we focus onthree areas with contrasting habitats and different fates of stocks. First, wedescribe how fishing has impacted cod in the North Sea, a region wheresome of the largest declines have occurred, we then compare this to changesin the Celtic Sea stock, where, in general, cod are found at relatively lowabundance. Finally, we discuss the status of cod in Icelandic waters, wheremanagement structures are different with respect to these other areas.

3.2.1. North SeaThe entire North Sea has been commercially fished since the mid-eigh-teenth century (Cushing, 1988; Smith, 1994), with periods of cessationduring the two World Wars (Beverton and Holt, 1957; Borley, 1923;


Hardy, 1959; Margetts and Holt, 1948). Catchability of cod was high duringthe late 1940s and 1950s, but began to decline in the 1960s as increasedlevels of exploitation caused dense aggregations to be fished out (Gulland,1964). During the ‘gadoid outburst’ of the 1970s, high recruitment led tomassive increases in juvenile cod abundance, with estimated stock sizes of250,000 tonnes (Brander, 1995; Cushing, 1984; Hislop, 1996; Horwoodet al., 2006). This period was associated with cooler waters and increases inthe abundance of the cold water copepod C. finmarchicus, a primary foodsource for pelagic larval cod (Beaugrand et al., 2003). Landings rose until theearly 1990s, then declined before levelling out at record low levels after2003 (Holden, 1978; ICES, 2007; Jennings et al., 1999; Olsen et al., 2004;Rijnsdorp and van Leeuwen, 1996; Rijnsdorp et al., 1996; Fig. 3.6). Theyear class of 1996 was anomalously strong, but it was removed by fishingbefore reaching maturity (Bannister, 2004), indicating that fishing impactson stock dynamics were far outweighing those of climatic variability. Size ofindividual adults also declined across the twentieth century in response toincreased fishing mortality of larger, older cod (Fig. 3.7).

North Sea cod has been managed under joint management agreementsinvolving annual assessments by the European Council of Ministers and theNorwegian government since 1974 (Reeves and Pastoors, 2007). The definedlimits of theNorth Sea include the Skaggerak and easternEnglishChannel, andall cod are treated as one stock for ease of management despite some geneticevidence for multiple populations within the region (Blanchard et al., 2005;

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Figure 3.6 Total estimated catch (in thousands of tonnes) of cod from the North Seasince 1985 including landings and discards. Data: ICES (2008).


Hutchinson, 2008; Hutchinson et al., 2001; STECF, 2007). The assessmentand total allowable catch (TAC) advice process is conducted under anICES umbrella, and primarily reflects the needs of the main customer, theCommission of the European Communities (Holden, 1994).

TACs have been restricted for the last two decades to allow an estimated30% increase in spawning biomass, but also whilst falling within 15% of theprevious year’s TAC. Data from both research vessel surveys and fisherieslandings data suggest that TACs have been ineffective. By 1992, only 4% ofNorth Sea cod were surviving to maturity at 4 years old due to intensiveharvesting across the year classes (Cook et al., 1997), and the most com-monly caught age classes over the last two decades were immature 1 and2 year olds (Myers et al., 1996; O’Brien et al., 2000). By 2000, SSB hadfallen to around 40,000 tonnes (ICES, 2000), well below the ICES mini-mum biomass limit of 70,000 tonnes, at which stock production wasconsidered as being severely impaired (Horwood et al., 2006). Conclusionsfrom cod recovery scenarios suggested that even a reduction in fishingmortality to a precautionary F ¼ 0.65 per year provided a low probabilitythat stocks would recover to a precautionary biomass level within a decade(STECF, 2007). Moreover, these models did not take into account climatechange in the projections. A narrow window between ‘potential’ and ‘no’recovery was highlighted (Horwood et al., 2006), which may explain whyreductions in fishing effort close to precautionary levels have failed toincrease stock biomass. Repeated recommendations from ICES of eithertotal closure or reductions in fishing mortality of up to 70% duringthe 2000s have resulted in annual re-calculations of TACs and reductions

Figure 3.7 High numbers of large cod being landed on the fish market at Aberdeen,Scotland. Photograph ca. 1920.


in the number of days at sea for gill-netting vessels and beam trawlers in the70–99mmand>100mmmesh sectors (ICES, 2003, 2004, 2006, 2007, 2008).

A recovery plan involving TACs to allow a 30% increase in biomass wasfinalized in 2004 for the North Sea, Kattegat, West Scotland and Irish Seastocks. A year later, ICES announced that the recovery plan for cod was notprecautionary (ICES, 2004) and by 2006 the North Sea and NorthwestRegional Advisory Committees had found little evidence of recovery, withstocks still at or close to historically low levels (NSRAC, 2006). Althoughthere have been some indications of improved recruitment with a relativelystrong year class in 2005, no increase in SSB has been observed to date.ICES altered their recommendations from ‘lowest possible catch’ in 2002 to‘zero catch’ from 2004 to 2008 (ICES, 2003, 2004, 2006, 2007, 2008).Interestingly, North Sea cod were listed as being ‘harvested sustainably’ byICES in 2008, but these stocks in 2009 have been categorized as ‘overf-ished’, with fishing mortality ‘above target’ and a recommendation of ‘zerocatch’ (ICES, 2008).

3.2.2. Celtic SeaCod have also been targeted by both single- and mixed-species fisheries inthe Celtic Sea for several centuries (Kurlansky, 1997), but intensive com-mercial fishing began relatively recently in comparison with other NorthAtlantic regions (Pinnegar et al., 2002). Recent assessments have valuedlandings made by the combined international fleet to be approximately£10.5 million per year, with maximum landings occurring during wintermonths (Fisheries Science Services, 2008; ICES, 2006).

Dwindling numbers of pelagic and demersal fish, including cod, in thecoastal Celtic Sea and elsewhere around the UK were of concern as early asthe mid-nineteenth century (Sims and Southward, 2006). During theperiod of modern data collection and assessments, fishing mortality in theCeltic Sea has remained at very high levels since the mid-1980s (FisheriesScience Services, 2008; Worm and Myers, 2003) albeit with a slightdecrease in recent years due to a reduction in the section of the fleettargeting cod since 1999 (ICES, 2006). The stock has been well belowsafe minimum limits since 2004, and even with the recent reduction infishing effort, biomass is continually declining (ICES, 2006, 2008). Despitedeclining stock size and low projected recruitment if present fishing effort ismaintained, a successful management strategy has yet to be put into practicein the Celtic Sea region.

The Celtic Sea cod stock is located close to the southern biogeographiclimit of the species in the Northeast Atlantic. The fish have relatively fastgrowth rates and mature at 2–3 years of age (Armstrong et al., 2001; ICES,2003). Recent poor recruitment rates have been purported to be driven inpart by warming seas, but there is little evidence for climate-driven changesin the biogeographic range or abundance of this stock, and thus fishing is


still recognized as a primary factor determining SSB. In addition to species-level impacts, it is notable that significant declines in the mean trophic levelof catches overall have been observed from the region, consistent withfishing-induced changes to the structure of the whole fish community(Pinnegar et al., 2002).

3.2.3. IcelandThe Icelandic cod stock is one of the largest in the North Atlantic, with amaximum sustainable yield (MSY) of 330,000 tonnes providing annualrevenue in excess of £400 million. The stock is managed as a single unit,although there are discrete regional spawning components (Begg andMarteinsdottir, 2000). Stock size declined throughout the twentiethcentury from a peak of 3.3 million tonnes in 1928 to 600,000 tonnes by1993 (Schopka, 1994), accompanied by a decline in SSB to 120,000 tonnes(Marine Research Institute, 2008). A low stock size was recorded in 2007 ascatches have continued to exceed advised levels, although SSB has shown anincrease in recent years to approximately 230,000 tonnes (Marine ResearchInstitute, 2008). Mean weight at age has decreased significantly to an all-time low in 2007 and 2008, attributed to the lack of capelin as a food sourcein recent years. This weight-at-age trend, in combination with recent poorrecruitment, has led to very low productivity of the current stock (MarineResearch Institute, 2008).

Three so-called ‘cod wars’ have taken place in the waters off Icelandduring the latter half of the twentieth century, in 1958, 1972 and 1975.These hostilities arose as a result of extensions in the offshore spatial extentof the Icelandic fishery exclusion zone and a lack of recognition of thisexpanding zone by vessels from European countries already fishing in thesewaters. The first conflict resulted in an extension of Iceland’s territorialwaters to 12 nautical miles from the coast. Further extensions of theIcelandic fishing zone to 50 nautical miles in 1972 and 200 nautical milesin 1975 resulted in more severe international conflicts. The final confronta-tion was resolved when intervention by the North Atlantic Treaty Organi-zation (NATO) succeeded in brokering an agreement that reduced access toBritish vessels within the 200 nautical mile limit, including closure of fourconservation areas to British fishing activities. Various Icelandic govern-ment acts have since been introduced in an attempt to reverse the trend ofdeclining fish stocks within the 200 nautical mile limit, including TheFisheries Act of 1976 (amended in 1983), Individual Effort Restrictions in1977, The Fisheries Management Act 1990, the Harvest Control Rule in1995 and the current system of TACs. Despite these measures, stock size hasshown no signs of recovery to sustainable levels.

In the early decades of the twentieth century, stock size was stronglycorrelated with environmental changes in the Iceland–Greenland region.The coastal current and Atlantic inflow are thought to exert a strong


influence on annual success of each spawning component via alterations inthe strength of water flow from the main spawning grounds off the north-west coast of Iceland to the main nursery grounds off the north coast (Beggand Marteinsdottir, 2002). Pelagic juveniles are larger and more abundantduring years of stronger current flow and Atlantic inflow, due to bothincreased dispersal and increased abundances of the main prey species ofzooplankton, C. finmarchicus that is brought into the region by the Atlanticinflow (Sundby, 2000). As fishing mortality has steadily increased from 0.16to approximately 1.0 between the 1930s and 2000s, it has exerted anincreasingly dominant influence on the annual stock size of Icelandic cod.Stock models that incorporate both environmental and fishing componentsindicate that substantial reductions in fishing effort are required to permitstock recovery (Baldursson et al., 1996).

3.3. The fishing versus climate change debate

Historically high abundances of North Sea cod during the early 1900s(Eckman, 1953), 1960s and 1970s (Cushing, 1984) have been linked tocooler marine climates, while the recent period of rapid climate warminghas been suggested to have contributed to the observed declines in SSB(Blanchard et al., 2005; Clark et al., 2003; O’Brien et al., 2000; Ottersenet al., 2006; Schiermeier, 2004). During recent decades it is possible thatclimate signals have been overridden by fishing impacts, and recent warmerclimates have exerted additional pressures on already stressed stocks(Graham and Harrod, 2009). However, separating the interactions betweenthe two drivers has proved difficult. Thus, quantifying strengths of compo-nent effects will be challenging, especially between regions that differ incommunity compositions, thermal regimes and habitat structure, and also incod abundance, distributions and behaviour (Neat and Righton 2006;Righton et al., 2001). Despite this, there is a need to more fully understandthe contributive effects of climate change on cod stocks that are already athistorical low abundance due to overexploitation.

Biological responses to environmental changes such as fishing andclimate, for example, can be divided into two categories. Firstly, proximateecological responses that depend upon relationships between physicalfactors and organismal-level processes, population dynamics and commu-nity structure (Harley et al., 2006). Secondly, direct impacts on individualperformance during various life stages through changes in physiology,morphology and behaviour (Mieszkowska et al., 2006, 2007). Theseimpacts lead to population-level responses, which can be additionallyaffected by climate-driven changes in hydrographic processes that affectdispersal of the pelagic larval life stages and recruitment. All of these arelikely to lead to alterations in cod distributions, biodiversity, productivityand micro-evolutionary processes.


4. Population-Level Impacts of Fishing

and Climate Change

Shifts in survival, maturity, fecundity, reproduction, recruitment suc-cess and growth all scale up to the population level. If sufficient numbers ofindividuals display the same response to an external driver, such as climate,then population dynamics are likely to be altered. Such effects of climate arelikely to be observed first within populations located close to the distribu-tional limits, where environmental conditions are most likely to be alreadyapproaching stressful levels (Lewis, 1986, 1996; Orton, 1920; Southward,1995). By contrast, effects of fishing mortality may well affect populationsacross much of their range.

4.1. Stock assessment

SSB is the parameter used to define the size of exploited fish stocks. Bothshort- and long-term variability in SSB may be driven by natural age-structured interactions, including competition between year classes, canni-balism and natural mortality (Bjornstad et al., 1999). The SSB–recruitmentrelationship may be contextualized with respect to underlying environmental,ecological and biological processes that control growth, reproduction andmortality. Supporting this idea, inclusion of age structure data can help toimprove SSB–recruitment models (Marteinsdottir and Thorarinson, 1998).Different age classes may contribute unequally to reproductive output and aspawning stock with a more diverse age structure may exhibit protraction ofthe spawning period due to size or age-dependent factors (Hutchings andMyers, 1994a,b; Marteinsdottir and Petursdottir, 1995). The most commonmethod of determining the spawner–recruitment relationship is the applica-tion of a model such as the Ricker or Beverton–Holt model to a single stock(Myers et al., 2001). Unfortunately, the stock–recruitment curve that isgenerated can be simplistic, and the effects of biological and environmentalfactors can strongly affect this relationship leading to large variations inrecruitment (God�, 2003; Marshall et al., 1998, 2000).

The existence of a relationship between abundance of spawners andnumber of recruits is implicit to SSB calculations (Hilborn and Walters,1992; Myers and Barrowman, 1996), but within-stocks data provide a poorfit to models (Myers and Cadigan, 1995a,b; Myers et al., 1995a,b; Shepherdand Cushing, 1980). Potential reasons for this are pre-recruit mortality(Cushing, 1988; Goodyear and Christensen, 1984; Walters and Collie,1988), model skew caused by outliers (Chen and Paloheimo, 1995) and/orerrors in variablemeasurement (Walters and Ludwig, 1981). There is also thepossibility of high variance in reproductive output among individuals, that


may in turn result in large disparities between effective and observed popu-lation sizes (Hedgecock, 1994), and even large populations may have fewindividuals that effectively contribute to spawning (Hauser and Carvalho,2008). In theory, a minority of individuals that spawn in favourable oceano-graphic conditions can disproportionately contribute to the next generation(Hedgecock, 1994). Finally, migrations affecting stock connectivity are alsonot typically considered when assessing these relationships (Myers et al.,2001).

4.2. Stock evaluation—An example from the North Sea

The ICES Stock Assessment Working Group uses data from commercialcatches, research vessel surveys and time series to evaluate the status of theNorth Sea stock relative to previous years and defined reference points.Information on catch per unit effort, catch-at-age and natural mortality arecompared to an average between 1980 and 1982, and used to calculate SSB(Beare et al., 2005; Sparre, 1991). These parameters are assumed to remainconstant between years. Forecasts of stock status for the forthcoming yearare made for a range of exploitation rates, and presented as a catch-optiontable of resultant SSB from specific fishing mortalities (Reeves and Pastoors,2007). These projections are then peer-reviewed by the ICES AdvisoryCommittee for Fisheries Management before management decisions aremade at the political level.

The use of stock–recruitment methods in fisheries management has beencriticized due to a lack of concordance between the projected model out-puts of stock assessments, and the observed annual variation in reproductivepotential of stocks. The disparity is likely to be due to interannual stochasticfluctuations, which in turn are likely to be largely driven by natural envi-ronmental changes. This highlights the need for stock assessment analyses toinclude survey-based indices of stock abundance (Marshall et al., 1998).In theory, changes in SSB should be able to provide a clear indication ofwhether fishing mortality or climate change is the dominant factor causingthe continual decline observed during the last two decades. If climate-driven effects are the primary cause of the decrease in population abun-dance, years with high observed SSB would be expected to be preceded byhigh survivorship and recruitment of sub-adults (Myers et al., 1996). How-ever, this is not generally observed. In the North Sea, for example, adultstock biomass has declined from the 1960s until recently (2006–2008),despite numbers of recruits-per-spawner being relatively high, indicatingthat the loss of individuals from populations is occurring from the older ageclasses. By contrast, if fishing is the driving force, proportional mortality dueto harvesting would continue to increase during the decline of the stock(Myers et al., 1996). Figures indicate that such fishing mortality hascontinued to increase, despite severe reductions in the TACs issued


(ICES, 2003, 2004, 2006, 2007, 2008). Taken together, this evidencestrongly indicates that overexploitation is the dominant factor causing thecontinuing decline in cod SSB in the North Sea.

4.3. Allee effects and management plans

When population size falls below a critical point, individual fitness may bereduced, causing a decline in population growth rate known as ‘growthdepensation’, with an increase in extinction vulnerability of the populationas a whole (Drake and Lodge, 2006; Myers and Cadigan, 1995a,b; Postet al., 2002). More generally, the correlation between population size andpopulation growth rate is known as the Allee effect (Allee, 1931), and theAllee threshold is reached when the population size either increases ordeclines to an unstable density equilibrium, where the birth rate equalsthe death rate (Berec et al., 2007) (Fig. 3.8). This threshold is unstable, andfor cod, any variation in recruitment or SSB can cause a population that issubject to strong Allee effects to expand, stabilize or collapse (Rose, 2004a,b;Shelton andHealey, 1999; van Kooten et al., 2005). Allee effects can be drivenby numerous causes. In some species, they may be induced by a decreasedprobability of finding a mate, failure of schooling behaviour to preventpredation or decreased foraging efficiency in social foragers at lower popula-tion densities (Courchamp et al., 1999; Stephens and Sutherland, 1999).Fisheries exploitation can induce an Allee effect if fish population-size reduc-tions lead to aggregation, enabling fishers to more efficiently locate andharvest the remaining fish.

Cod may experience Allee effects from low fertilization success andreduced juvenile survival at low population densities (Rowe et al., 2004).As a top predator, Allee effects may also occur if cod feed specifically onsmall individuals of a size-structured prey population, and this leads to adecline in the prey abundance, enhanced intraspecific competition and

Population density

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Figure 3.8 A schematic diagram of theoretical Allee effects on a population. SeeSection 4.3 for explanations of terms and the concept.


ultimately a decline in the adult cod population (de Roos and Persson,2002; de Roos et al., 2003). Equally, Allee effects may act on cod through a‘predator-pit’ scenario. If predators are able to continually maintain codbiomass at low levels, then populations may be unable to produce sufficientrecruits to allow population expansion. Harp seals (Phoca groenlandica) haveconsumed an estimated 88,000 tonnes of cod per annum in the NorthwestAtlantic throughout the second half of the 1990s, many of which are pre-recruits (Stenson et al., 1997). The grey seal (Halichoerus grypus) is alsoreported to be responsible for heavy predation on two Northwest Atlanticstocks (Chouinard et al., 2005; Fu et al., 2001; Trzcinski et al., 2006). NorthSea cod are pre-dated upon by grey seals, but estimated consumption of codonly amounts to approximately 3.7% of the total stock biomass (Hammondand Grellier, 2005). Harbour porpoises (Phocoena phocoena) also feed oncod, and are four times as abundant as harbour seals in the North Sea.Cod populations are therefore exposed to both natural and fisheries-induced depensation.

The debate continues over the existence of fishing-induced Allee effectsin cod. It has been argued that the species does not exhibit any of themechanisms usually associated with the Allee effect (Myers et al., 1995a,b;van Kooten et al., 2005). Instead, it has been suggested that fishing mortalitymay actually enhance juvenile survival due to low spawner densities (Myerset al., 1995a,b). Exclusion of depensation in stock assessment predictions forNorthwest Atlantic stocks gave rise to predictions of an annual growth rateof 19% with zero F and a threefold increase in stock size after 7 years fromthe moratorium in 1993 (Myers et al., 1997). Over a decade on, however,only four stocks have showed any signs of increased abundance, with onlyone experiencing substantial recovery (Shelton et al., 2006).

The potential presence of Allee effects operating on cod populationssuggests that if insufficient information on the life history of the targetspecies is included in management models, the effects of climate changeon fisheries could be vastly underestimated. For populations such as theNorth Sea cod, for example, which have been reduced to levels far belowthe carrying capacity of the system, it is vital that this does not occur. Thecombination of Allee effects and incorrect management could reduce thestock size to a critical level where the population will suddenly crash.Fisheries assessment models generally assume a spawner stock–recruit func-tion whereby recruitment increases with spawner biomass until it reacheseither an asymptote (Beverton–Holt model) or declines (Ricker model).Thus, these models assume that individual reproductive output will actuallyincrease at low fish densities. The inclusion of potential Allee effects intomanagement plans could help to optimise risk management strategies, eventhough Allee thresholds cannot currently be accurately established (Berecet al., 2007). Protection of areas where high densities of cod are presentcould help to prevent Allee effects from occurring.


5. Monitoring Status and Recovery of

North Sea Cod: A Case Study

Monitoring North Sea cod stocks for signs of recovery has provendifficult, not least because catches and bycatches often go unreportedmaking assessment of recovery difficult (ICES, 2004, 2005). The regioncurrently falls within a single ICES management unit, but the existence ofmultiple distinct stocks within the North Sea may obscure the dispropor-tionate decline of some more vulnerable stocks for which separate manage-ment plans may be required (Hutchinson, 2008). Landings may need to besplit into relative contributions from different stocks to allow appropriatemanagement strategies, as recommended by the North Sea Regional Advi-sory Council (NSRAC, 2008). In addition, a range of values of fishingmortality are obtained using multiple research vessel surveys, introducinguncertainty into stock estimations (Blanchard et al., 2005).

Prior to 1988, assessment and forecasting techniques showed largeinterannual variation in performance as the methodology developed, andbetween 1988 and 1995 relatively high performances were obtained. How-ever, since then, there has been a systematic underestimation of fish mortalityand overestimation of the contribution of incoming year classes (Reeves andPastoors, 2007). Similar problems have been encountered in other codstocks (Pastoors, 2005). Under-reporting of landings and the absence ofdiscard data creates uncertainties in catch estimation, although errors in theassessment preceded the problems arising from limited catch data and do notappear to explain the change in model performance. Instead, this may beattributable to the reliance on parameters estimated from earlier timeperiods where the ecosystem may have been in a different state, and/orthat may also have been potentially, at least in part, a consequence of theimpacts of climate change (Beaugrand et al., 2003; Blanchard et al., 2005;O’Brien et al., 2000).

The international aspect and mixed species nature of the North Seafishery have been highlighted as the main factors contributing to the recentpoor state of the North Sea stock (Bannister, 2004), despite efforts to reducefishing mortality at the European scale. A wider ecosystem-based approachis being developed to attempt to account for the mixed species nature ofNorth Sea demersal fisheries (Vinther et al., 2004). However, the process ofdetermining suitable parameters that distinguish relative impacts of fishing,climate change and natural variance is continuing (Blanchard et al., 2005;Rice, 1995, 2000; Rice and Evans, 1988; Rice and Rochet, 2005; Rochetand Trenkel, 2003; Trenkel and Rochet, 2003). Among these approaches issize spectra analysis, a technique that has proven useful for detecting effectsof exploitation on fish stocks, as temporal changes in the index are consistent


with fishery-mediated changes in community structure (Bianchi et al., 2000;Gislason and Rice, 1998; Jennings and Greenstreet, 1999; Murawski andIdoine, 1992; Rice and Gislason, 1996; Shin et al., 2005; Zwanenburg,2000). Even this approach has difficulties, however, as warmer watersexpected due to climate warming may lead to enhanced recruitment ofsmall species, and concomitant shifts in the size spectra. If such issues can beovercome by allowances for discrimination between forcing factors, thensize-based metrics may become useful management tools (Blanchard et al.,2005; Genner et al., 2009b).

There has been little research into the application and utility of closedareas for fishing, and it appears most closures have been designated withoutclear objectives (SGMOS, 2003). At the geographical scale of the ICESrectangle, the lack of high densities of cod suggest that movement of fishingeffort would save few fish (Blanchard et al., 2005). A 10-week closure ofpart of the North Sea in 2001 was deemed ineffective, and data were ofinsufficient resolution to separate any closure effects from additional factors(Council Regulation (EC) No. 259/2001). It has since been concluded thattemporal closures must be used with other management approaches to havea role in the future maintenance of North Sea cod biomass, and would berequired over several years and across larger spatial scales (Horwood et al.,2006; STECF, 2007).

Emerging management ideas include the introduction of OptimumRestorable Biomass to replace MSY as a target reference point (Ainsworthand Pitcher, 2008). This has been suggested as a suitable cost/benefitapproach to restoration of severely depleted fish stocks (Pitcher, 2008) anduses ‘Back To the Future’ simulation models to establish a restorationtrajectory from the present depleted system to a target of an historical systemafter establishing sustainable fishing (Ainsworth and Pitcher, 2008; Pitcher,2008; Pitcher and Forrest, 2004). Several optimal trajectories can besimulated based on restoration targets and economic profit scenarios. Thismultidisciplinary approach to restorative ecology suggests that rebuildingstocks to defined targets is the main goal for fisheries management (Paulyet al., 1998). In contrast, however, the North Sea Regional AdvisoryCouncil has recently issued advice to the European Commission that thecod recovery plan should be reviewed and targets changed from recoverybased on biomass to that based on fishing mortality (NSRAC, 2008).

6. Concluding Remarks

Most recovery plans for fish stocks are less than two decades old, andquantifying potential recovery is still proving difficult (Caddy and Agnew,2004; Caddy and Surette, 2005). Pelagic stocks appear to be responding


more positively than demersal stocks, and comparatively few stocks havebeen restored. The World Summit of Sustainable Development set a targetdate of 2015 for the management of all fish stocks at the level of MSY.No indication was given, however, as to how multi-species fisheries shouldbe managed to attain such a standard, and it is questionable whetherproposed targets are realistic in rapidly changing environments. Addition-ally, there is debate as to whether the focus of management should besustainability within an already depleted system, or the complete restorationand rebuilding of fish stocks to historic levels (Pitcher and Pauly, 1998).Moreover, reconstruction of past ecosystems may be an impossible policygoal if the past ecosystems existed under different climatic regimes (Pitcherand Forrest, 2004).

It is vitally important that the relative contributions of both fishingmortality and climate change on stock biomass, population structure andabundance changes are quantitatively understood to provide accurate andtimely advice for effective fisheries management (Horwood et al., 2006;Rose, 2004a,b). Predicting the effects of climate change on fish productiv-ity, as discussed in earlier sections of this chapter, is difficult due to incom-plete knowledge of the physiological and ecological mechanisms by whichfishes respond to changes in local and regional environmental conditions.Regime shifts also make predictions of future assemblage states problematicas the drivers force the assemblage into a new stable state which may differgreatly from the previous one (Cury et al., 2008; DeYoung et al., 2004;Mantua, 2004). Time series provide a basis for understanding the effects ofenvironmentally driven fluctuations in abundance and production of stocks,and provide the opportunity for deeper insights of the effects of highexploitation pressure (God�, 2003). However, investigations into themacroecological responses of wide ranging fishes such as Atlantic cod areproblematic due to the lack of uniformity in spatial data collection fromcommercial fisheries. In recent years, the availability of research vessel trawldata and standardized fisheries statistics has gone some way to address thisproblem. It is imperative that these data are now combined with detailedphysiological knowledge of the various life history stages, and an under-standing of interactions between cod and their environment, to allow moreaccurate predictions of future stock structure and abundance. Only then wewill be able to determine to what degree observed changes in cod popula-tions have been due to fishing and warming seas, and have the ability tointroduce effective management plans for mitigation of climate change andfisheries impacts.

The review of the European Common Fisheries Policy (CFP) in 2008acknowledges these factors and a Green Paper on the CFP reform sets out avision for European fisheries by 2020, which includes integration with thenew Integrated Maritime Policy and the Marine Strategy FrameworkDirective (CEC, 2009). The urgent need to review fisheries management


as part of the wider maritime environment and associated activities isrecognized (Greenstreet and Rogers, 2006), as are the additional impactsof climate change on exploited marine stocks. Fleet over-capacity is stillidentified as the fundamental problem that needs to be addressed. Moreactive stewardship, including appropriate use of the increasing scientificknowledge base, combined with emergent European and internationalmaritime directives is required if we are to redress the decline in Atlanticcod whilst stocks remain to be conserved.

In a rapidly changing world a precautionary approach is required.Climate change interacts with overfishing to increase the risk of decliningstocks, especially for species of boreal biogeographic origin such as Atlanticcod. Occasional large recruitment events can enable a single annual-breed-ing boreal species, which is dependent on the spring/summer temperatureregime, to persist in the face of climatic change. If longevity and size ofspawning fish are reduced, then persistence becomes less likely as theprobability of a major recruitment event during the lifespan of an individualis much reduced. As we describe in this chapter, it seems clear that climatecan act to exacerbate the deleterious effects of overfishing on marineecosystems; however, in this context, climate change effects should notexcuse overfishing. Moreover, given the mosaic structure of cod popula-tions with complex stochastic responses to climate change, the revolution ofmanagement measures must match the scale of these ecological processes.Management strategies with one size and approach, such as the CFP, willnot sufficiently well accommodate the complexities of cod interactions withchanging environments.

ACKNOWLEDGEMENTS

We thank G. Beaugrand for providing Fig. 3.5 and S. Cotterell for providing critical com-ments on an earlier version of this Chapter.We gratefully acknowledge funding support fromthe UK Department for Environment, Food and Rural Affairs (DEFRA), the UK NaturalEnvironment Research Council (NERC) Oceans 2025 Strategic Research Programmethrough Themes 6 (Science for Sustainable Marine Resources) and 10 (Integrating sustainedobservations for marine environmental monitoring) and The Worshipful Company ofFishmongers. MJG was supported by a Great Western Research Fellowship and DWS byan MBA Senior Research Fellowship.

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C H A P T E R F O U R

Susceptibility of Sharks, Rays and

Chimaeras to Global Extinction

Iain C. Field,*,†,1 Mark G. Meekan,†,2 Rik C. Buckworth,‡

and Corey J. A. Bradshaw§,}

Contents

1. Introduction 277

1.1. Aims 280

2. Chondrichthyan Life History 281

2.1. Niche breadth 281

2.2. Age and growth 282

2.3. Reproduction and survival 283

3. Past and Present Threats 284

3.1. Fishing 284

3.2. Beach meshing 305

3.3. Habitat loss 306

3.4. Pollution and non-indigenous species 306

4. Chondrichthyan Extinction Risk 308

4.1. Drivers of threat risk in chondrichthyans and teleosts 309

4.2. Global distribution of threatened chondrichthyan taxa 310

4.3. Ecological, life history and human-relationship attributes 313

4.4. Threat risk analysis 317

4.5. Modelling results 320

4.6. Relative threat risk of chondrichthyans and teleosts 326

5. Implications of Chondrichthyan Species Loss on Ecosystem

Structure, Function and Stability 328

5.1. Ecosystem roles of predators 328


ISSN 0065-2881, DOI: 10.1016/S0065-2881(09)56004-X All rights reserved.

* School for Environmental Research, Institute of Advanced Studies, Charles Darwin University, Darwin,Northern Territory 0909, Australia

{ Australian Institute of Marine Science, Casuarina MC, Northern Territory 0811, Australia{ Fisheries, Northern Territory Department of Primary Industries, Fisheries and Mines, Darwin, NorthernTerritory 0801, Australia

} The Environment Institute and School of Earth and Environmental Sciences, University of Adelaide,Adelaide, South Australia 5005, Australia

} South Australian Research and Development Institute, Henley Beach, South Australia 5022, Australia1 Present address: Graduate School of the Environment, Macquarie University, Sydney, New South Wales2109, Australia

2 Present address: Australian Institute of Marine Science, University of Western Australia Ocean SciencesInstitute (MO96), Crawley, Western Australia 6009, Australia

275

5.2. Predator loss in the marine realm 331

5.3. Ecosystem roles of chondrichthyans 333

6. Synthesis and Knowledge Gaps 335

6.1. Role of fisheries in future chondrichthyan extinctions 335

6.2. Climate change 337

6.3. Extinction synergies 339

6.4. Research needs 340



References 343

Abstract

Marine biodiversity worldwide is under increasing threat, primarily as a result of

over-harvesting, pollution and climate change. Chondrichthyan fishes (sharks,

rays and chimaeras) have a perceived higher intrinsic risk of extinction com-

pared to other fish. Direct fishing mortality has driven many declines, even

though some smaller fisheries persist without associated declines. Mixed-

species fisheries are of particular concern, as is illegal, unreported and unreg-

ulated (IUU) fishing. The lack of specific management and reporting mechan-

isms for the latter means that many chondrichthyans might already be

susceptible to extinction from stochastic processes entirely unrelated to fishing

pressure itself. Chondrichthyans might also suffer relatively more than other

marine taxa from the effects of fishing and habitat loss and degradation given

coastal habitat use for specific life stages. The effects of invasive species and

pollution are as yet too poorly understood to predict their long-term role in

affecting chondrichthyan population sizes. The spatial distribution of

threatened chondrichthyan species under World Conservation Union (IUCN)

Red List criteria are clustered mainly in (1) south-eastern South America;

(2) western Europe and the Mediterranean; (3) western Africa; (4) South China

Sea and Southeast Asia and (5) south-eastern Australia. To determine which

ecological and life history traits predispose chondrichthyans to being IUCN

Red-Listed, and to examine the role of particular human activities in exacerbating

threat risk, we correlated extant marine species’ Red List categorisation with

available ecological (habitat type, temperature preference), life history (body

length, range size) and human-relationship (whether commercially or game-

fished, considered dangerous to humans) variables. Threat risk correlations

were constructed using generalised linear mixed-effect models to account for

phylogenetic relatedness. We also contrasted results for chondrichthyans to

marine teleosts to test explicitly whether the former group is intrinsically more

susceptible to extinction than fishes in general. Around 52% of chondrichthyans

have been Red-Listed compared to only 8% of all marine teleosts; however,

listed teleosts were in general placed more frequently into the higher-risk

categories relative to chondrichthyans. IUCN threat risk in both taxa was

276 Iain C. Field et al.

positively correlated with body size and negatively correlated albeit weakly, with

geographic range size. Even after accounting for the positive influence of size,

Red-Listed teleosts were still more likely than chondrichthyans to be classified

as threatened. We suggest that while sharks might not have necessarily experi-

enced the same magnitude of deterministic decline as Red-Listed teleosts, their

larger size and lower fecundity (not included in the analysis) predispose chon-

drichthyans to a higher risk of extinction overall. Removal of these large pre-

dators can elicit trophic cascades and destabilise the relative abundance of

smaller species. Predator depletions can lead to permanent shifts in marine

communities and alternate equilibrium states. Climate change might influence

the phenology and physiology of some species, with themost probable response

being changes in the timing of migrations and shifts in distribution. The syner-

gistic effects among harvesting, habitat changes and climate-induced forcings

are greatest for coastal chondrichthyans with specific habitat requirements

and these are currently themost likely candidates for extinction. Management

of shark populations must take into account the rate at which drivers of

decline affect specific species. Only through the detailed collection of data

describing demographic rates, habitat affinities, trophic linkages and geo-

graphic ranges, and how environmental stressors modify these, can extinc-

tion risk be more precisely estimated and reduced. The estimation of

minimum viable population sizes, below which rapid extinction is more likely

due to stochastic processes, is an important component of this endeavour and

should accompany many of the current approaches used in shark manage-

ment worldwide.

1. Introduction

Humans have depended on marine resources since prehistory (Walkerand Deniro, 1986), with the commonly held belief until even recent timesthat it was beyond human capability to cause the extinction ofmarine species.This is summarised by two of the foremost thinkers of the eighteenth andnineteenth centuries, Jean Baptiste de Lamarck and Thomas Huxley, whoreflected a widespread belief that the high fecundity andwide distributions ofmarine fishes made the seas an inexhaustible source of food and wealth, andthat people could use but a small fraction of the total resources available usingfishing methods employed at the time (Garibaldi and Caddy, 2004; Sims andSouthward, 2006). Even only a decade ago, a survey of marine scientistsrevealed that nearly one-third believe marine extinctions are currently not aserious problem (Roberts and Hawkins, 1999).

In the past decade, it has become clear that marine biodiversity world-wide is under increasing threat, primarily as a result of over-harvesting,

Susceptibility of Sharks, Rays and Chimaeras to Global Extinction 277

pollution and the direct and indirect impacts of climate change (Gardneret al., 2003; Harley et al., 2006; Harvell et al., 2002, 2004; Hutchings andReynolds, 2004; Jackson et al., 2001; Jones et al., 2004; Lotze et al., 2006;Pauly et al., 2002; Roberts, 2002). At present, around 40% of the world’shuman population lives within 100 km of the coast (Martinez et al., 2007)and this proportion is increasing. With the median global human populationpredicted to increase to over 9 billion by 2050 (McMichael, 2001) and morepeople choosing to live along the coastal fringes, marine habitats are likely tosuffer increasing degradation and over-exploitation (Worm et al., 2006).As a corollary, anthropogenic stresses and climatic changes have reduced theresilience of ecosystems in many locations around the globe by slowlydegrading habitats and directly harvesting species, causing many ecosystemsto switch unexpectedly into alternate states (Folke et al., 2004; Hughes et al.,2003; Nystrom et al., 2000; Scheffer et al., 2001; Worm et al., 2006).Stressors can operate singly or synergistically at multiple scales (Brooket al., 2008), resulting at times in large shifts in species composition. Familiarexamples include regime or phase shifts on coral reefs (Aronson et al., 2004;Bellwood et al., 2004; Hawkins and Roberts, 2004; McManus andPolsenberg, 2004), in kelp forests following declines in canopy-formingspecies (Steneck et al., 2002, 2004), and the abandonment of many coastaland oceanic fisheries (Dulvy et al., 2004b, 2006; Jennings and Kaiser, 1998;Pauly et al., 2002; Roberts, 2002, 2003; Worm et al., 2006). Indeed, despitehaving sometimes wide geographic distributions and unique regional his-tories, many marine systems have experienced long periods of slow degra-dation followed by rapid acceleration in collapse of the biologicalcommunities they support (Lotze et al., 2006). This has been largely attrib-uted to the global colonisation by European nations and then thesubsequent increase in industrial fishing efficiency (Christensen et al.,2003; Mullon et al., 2005; Roberts, 2003). These rapid changes since the1950s have been scrutinised intensely over the past decade (Essington et al.,2006; Hilborn et al., 2003; Hutchings, 2000; Hutchings and Reynolds,2004; Jackson et al., 2001; Jennings and Kaiser, 1998; Myers and Worm,2003, 2005) to the extent that the sustainability of current and futurefisheries is now seriously called into question (Pauly et al., 1998, 2002;Roberts, 2002).

The total world catch from wild marine stocks has increased from19.3 million tonnes in 1950, peaking in 2000 at 86.4 million tonnes andthen slightly declining to 84.5 million tonnes in 2004 (Food and AgricultureOrganization of the United Nations, 2005). The majority of the world’s fishstocks have been as intensively fished as deemed possible, even to the extentthat target populations have been severely reduced and many fisheries havebeen abandoned (Hilborn et al., 2003). One of the most infamous examplesof such depletions is that of Atlantic cod (Gadus morhua) (Hutchings, 1996;Myers et al., 1997); and examples of fisheries abandonment include those


targeting whales (Baker and Clapham, 2004) and herring (Engelhard andHeino, 2004). These have most often been associated with decline inabundance across entire species’ ranges, or a decreased reproductive capacitythrough the excessive removal of large, mature females (McIntyre andHutchings, 2003; Scott et al., 1999) or immature stages (Hutchings andMyers, 1994; Myers et al., 1997).

Population declines have also had a number of ripple effects includingchanges to ecosystems and shifts in fishing to other economically lucrativetarget species. For example, once cod stocks declined around Newfound-land, the shellfish (shrimp, lobster and crab) populations increased substan-tially due to a reduction of predators (Bundy, 2001; Worm and Myers,2003). For mixed-species fisheries, it has commonly been seen through timeseries of harvesting that population reductions occur selectively for largerindividuals first, causing a decline in the size of individuals caught (Jacksonet al., 2001; Pitcher, 2001) before leading to an overall decline in catches.This results in smaller species being caught, with the fishery remainingeconomically viable only because there is a shifting focus towards specieslower down the food web (Jennings et al., 1999; Pauly and Palomares, 2005;Pauly et al., 2001). Fisheries harvests are linked to the majority of recordedmarine extinctions; around 55% of 133 extinctions have been attributedprincipally to direct and indirect harvesting by industrial fisheries (Hilton-Taylor, 2000; Lotze et al., 2006; Roberts, 2002). Of course, a large propor-tion has been initiated by subsistence, artisanal and recreational fishing, butthese have generally been responsible for local and regional, rather thanrange-wide extinctions (Dulvy et al., 2003).

Physical changes that largely degrade fish habitats can result from eithernatural sources (e.g. severe storms—Cheal et al., 2004; Kaufman, 1983;earthquakes—Noerenberg, 1971; freshwater inputs and disease—Dulvyet al., 2003) or anthropogenic sources (e.g. land reclamation, coastal devel-opment, alteration of freshwater flow and other habitat destruction). Suchnatural changes can compound the severity of population declines arisingfrom fisheries exploitation. The effects of habitat change will usually alterthe abundance and distribution of affected species, and can act differently ondifferent age or developmental groups. These effects can also be location-and species-specific, typically affecting critical habitat requirements(e.g. nursery areas), meaning that attributing observed declines to particularsources can be difficult. Furthermore, the amount of habitat change ismostly related to proximity to land and to human population pressures.Therefore, freshwater and estuarine species are predicted to receive thegreatest threats (Musick et al., 2000b). The effects of pollution are closelyrelated to, and often found in association with, other habitat changes.Common pollutants include sewage effluent, organic and inorganic com-pounds, heavy metals and nutrients that potentially affect all trophic levels.Other biological threats include introduced species, parasites and disease.


Introduced organisms can outcompete or eat native prey, or they can act asvectors for the transmission of diseases and parasites, thus increasing extinc-tion risk (Dulvy et al., 2003). This risk is further heightened as climate changeand other habitat degradation provide more suitable habitats for invadingnon-indigenous species (Harvell et al., 1999; Ruiz et al., 2000).

One taxonomic group of marine fishes that has come under increasingscrutiny in terms of extinction risk from these processes is Chondrichthyes(sharks, rays and chimaeras). These species are typically large predators in allmajor marine systems and have life history strategies that are likely to predis-pose them to extinction under rapid environmental change.Chondrichthyanfishes are subject to the range of human-derived threats, from targeted andindirect fishing pressure to other impacts (e.g. habitat change and pollution)across their entire range (Cadet et al., 2003; Cheung et al., 2007; Dulvy et al.,2008; Ferriti et al., 2008; Garcıa et al., 2008; Stevens et al., 2000, 2005;Walker, 1998). But are chondrichthyans any more or less susceptible torapid environmental change than other marine biota? We explore thiscomplex question by describing the life history strategies adopted by chon-drichthyans in relation to the different threats they face today.

1.1. Aims

The overall aim of this chapter is to review the available evidence for andagainst the posited higher susceptibility of marine shark populations tothreatening processes, relate this to other fish taxa that are conservation-listed, and identify areas (regional and topical) requiring more knowledge inthis regard. We also tackle the question of whether chondrichthyans shouldbe treated as a specific case in fisheries research and management, orwhether they respond in much the same way as all other marine taxachallenged with the additional pressure imposed by human activities. It isnot our intention to provide an exhaustive review of all chondrichthyanfisheries (target, by-catch or otherwise) (for some reviews, see Camhi et al.,1998; Fowler et al., 2005; Garcia and de Leiva Moreno, 2003; Hilborn et al.,2003; Kroese and Sauer, 1998; Mullon et al., 2005; Rose, 1996; Sims, 2008;Stevens et al., 2000; Walker, 1998); rather, we contextualise the currentextinction risk within this taxon with respect to one of its principal sourcesof mortality by highlighting specific fishery examples. Nor is our goal toprovide a complete overview of chondrichthyan life history (see Caillietet al., 2005; Compagno, 1990; Cortes, 2000; Dodd, 1983; Frisk et al., 2001;Smith et al., 1998; Wourms, 1977 for more comprehensive compilationsand reviews); our coverage of ecological, life history and human-relation-ship traits is undertaken to examine the relative susceptibility of this taxon toparticular extinction drivers. Specifically, our review encompasses fivemain, inter-related topics: (1) a description and discussion of chondrichth-yan life history traits that are thought to predispose species within this taxon


to population declines and possible extinction; (2) a broadly comprehensivereview of the past and present threats faced by sharks and rays; (3) aquantification of threat risks faced by chondrichthyan and teleost speciesbased on correlations of World Conservation Union (IUCN) Red Listcategories (www.iucnredlist.org) and a series of life history, ecological andhuman-relationship attributes; (4) an overview of the ecosystem role ofchondrichthyans as predators and implications of their loss to marinebiological communities and (5) an appraisal of the future of chondrichthyanspecies richness and abundance, with emphasis on research priorities.

2. Chondrichthyan Life History

Chondrichthyes are cartilaginous fish that include sharks and rays (ClassElasmobranchii) and chimaeras (Class Holocephalii) (for a detailed review ofcurrent classification, see Compagno et al., 2005). Modern chondrichthyansare derived from over 400 million years of evolution (Compagno, 1990), andthere are presently thought to be over 1100 species (Compagno et al., 2005).However, not all species have been described, and there are new species beingdescribed regularly. For examples of recent new descriptions, see Last et al.(2008). The taxonhas survived and re-radiated after twomajormass extinctionperiods: the Permian–Triassic and Cretaceous–Tertiary transitions (Carroll,1988). Although chondrichthyans are generally large in size compared to theaverage teleost (Compagno, 1981), their historically low economic value tofisheries (see Section 3.1) has stymied the impetus to collect informationdescribing their biology, ecology and role in ecosystem dynamics (Caillietet al., 2005). At present there is a paucity of essential biological parametersrequired for both conservation and resource management, with the informa-tion currently available derived largely from commercially important or by-catch species (Cailliet et al., 2005; Walker, 1998; Wood et al., 2007).

2.1. Niche breadth

Chondrichthyans are found throughout all of the world’s oceans(Compagno, 1990), although they essentially adopt a single trophicmode—predation—and have radiated to fill a range of habitat types. Around50%of extant species live in coastal and shelf waters (to around 200m),�35%in deeper water (200–2000 m), and the rest are either oceanic (�5%), live infreshwater (�5%) or occur within several of these habitats (�5%)(Compagno, 1990; Compagno et al., 2005). Although some are obligatefreshwater species (�35 species), we focus on marine species that liveeither partially or totally in the marine environment. Within these habitats,some have wide distributions, while others are endemic to specific habitats.



They also have a range of foraging niches including benthic or pelagicspecialisation such as whitetip reef sharks Triaenodon obesus (Stevens, 1984)and salmon sharks Lamna ditropis (Kubodera et al., 2007), respectively. Someare opportunistic predators (e.g. tiger sharks Galeocerdo cuvier—Simpfendorfer et al., 2001), and other are the ocean’s largest filter feeders(e.g. basking sharks Cetorhinus maximus—Sims, 2008).

During their evolution, chondrichthyans have adopted alternative lifehistories from that of most other marine fishes (Compagno, 1990; Holden,1974). The general category into which these life histories fall has beensummarised as ‘K-selected’ (Cortes, 2002; Fowler et al., 2005) whereindividuals are long-lived, slow-growing and late-maturing, and have lowproduction and low mortality rates (Cailliet et al., 2005; Musick et al.,2000a; Stevens et al., 2000), although there are a few exceptions, such asspot-tail Carcharhinus sorrah and sharpnose Rhizoprionodon taylori sharks(Simpfendorfer, 1999; Stevens and Wiley, 1986). There is now a generalconsensus in the literature that these traits, in combination with their mainrole as predators (Camhi et al., 1998), make chondrichthyan populationshighly susceptible to over-exploitation (Cortes, 2002; Fowler et al., 2005).

2.2. Age and growth

The measurement of growth, survival and reproductive potential can provideimportant information on rates of population change (Hilborn and Walters,2001; Sinclair et al., 2006; Walters and Martell, 2004), and ultimately risk ofextinction (Dulvy and Reynolds, 2002; Hutchings, 2002; Reynolds et al.,2005; Smith et al., 1998). Various methods have been used to calculate orestimate age in chondrichthyans, including measurement of growth bands invertebrae or other hard structures, bomb carbon dating, tag recapture andcaptive growth experiments (Cailliet and Goldman, 2004). Some species live>50 years (Beamish and McFarlane, 1987; Bradshaw et al., 2007; Pauly,2002; Wintner, 2000). Age and growth patterns have been validated foraround 120 species (Cailliet and Goldman, 2004; Haddon, 2001) and showa wide range of growth coefficients from ‘slow-growing’ species such asLeucoraja ocella [K ¼ 0.06 (von Bertalanffy growth constant); Sulikowskiet al., 2003] to relatively rapid-growing species like C. sorrah (K ¼ 1.17;Davenport and Stevens, 1988). Chondrichthyans also vary widely in age atmaturity (Cailliet and Goldman, 2004), from 1 year in the brown smooth-hound shark (Mustelus henlei) that can live up to 13 years (Yudin and Cailliet,1990), to bull sharks (Carcharhinus leucas) that can live for >32 years and notreach sexual maturity until 13 years (Wintner et al., 2002). The distribution ofthe age at maturity among species appears bimodal, with one peak at5–6 years and second at 15–25 years (Cailliet and Goldman, 2004). Growthrates also vary extensively within species depending on local water tempera-ture and productivity (Barker et al., 2005; Francis, 1997).


2.3. Reproduction and survival

Chondrichthyan reproduction has evolved to be specialised and highlyefficient (Carrier et al., 2004). It generally involves considerable parentalinvestment to produce relatively few large, well-developed young that havea high natural probability of survival (Hamlett and Koob, 1999; Holden,1974). This is in contrast to teleost fishes that typically produce thousands totens of millions of tiny eggs annually, although only a few young survive tomaturity. This is primarily due to density feedback mechanisms that permitincreasing fertility and juvenile survival to compensate for adult populationdecline (Hilborn and Walters, 2001).

Chondrichthyan reproductive parameters are still relatively unquantifiedfor most species although there have been a number of detailed reviews(Budker, 1958; Carrier et al., 2004; Dodd, 1983; Wourms, 1977). Chon-drichthyan reproductive strategies tend to proceed along a single path, withall species having internal fertilisation. However, there is still a large diver-sity among chondrichthyans in terms of egg production, ovulation cycle,gestation period and mating systems (Carrier et al., 2004). Once fertilisationhas occurred females retain the eggs during the most vulnerable stagesof development. Although energy-expensive, the production of well-developed embryos with access to energy reserves allows for highly efficientenergy transfer from mother to offspring. Depending on how long embryosare retained, chondrichthyan species are divided into oviparous (egg-laying)and viviparous (live-bearing) forms (Carrier et al., 2004). Oviparous speciesretain their eggs for a short time and then deposit or attach the eggs tobenthic structures. The embryos continue to develop by consuming a yolksac within the egg case and then hatch fully developed. Viviparous specieswill retain their embryos internally in one of the five uteri. There are variousforms of vivipary employed. These include placental vivipary where theembryo is attached by a placenta, ovovivipary where the development ofunattached embryos within the uterus is sustained by food supplied by largeegg yolks; oophagy where embryos ingest infertile eggs; embryophagywhere embryos consume smaller embryos; and hysteritrophy where fluidssecreted by the uterus sustain the embryo.

Depending on the species, females can bear from one or two young insand tiger sharks Carcharias taurus and manta raysManta birostris (Robins andRay, 1986; Springer, 1948), to 300 young in whale sharks Rhincodon typus( Joung et al., 1996). Gestation rates are unknown for most species, butmeasured times range from around 3 months for Dasyatis sp. rays (Hamlettand Koob, 1999) to more than 22 months for the ovoviviparous spinydogfish which has the longest gestation period known for any living marinevertebrate (Pratt and Casey, 1990). Breeding does not always occur annuallyin females and some species have one or more ‘resting’ years betweenpregnancies.


Following their high initial investment in pup production, many sharksand rays subsequently give birth in sheltered coastal or estuarine nurseryareas where predation risk to pups (primarily from other sharks) is presum-ably reduced (Branstetter, 1990). Other species deposit eggs in locationswhere they are most likely to survive undamaged until the pups emerge.There is no known post-birth parental care. Nevertheless, it is thought thatmost chondrichthyans have relatively low natural mortality compared toteleosts (e.g. Bradshaw et al., 2007; Cortes and Parsons, 1996; Grant et al.,1979; Gruber et al., 2001; Heupel and Simpfendorfer, 2002; Walker andHislop, 1998; Waring, 1984).

Recently, there has been an increase in the development and use ofdemographic and population models to describe and predict the status ofchondrichthyan populations (Cortes, 2007). Modelling approaches rangefrom empirically derived age-based demographic models to recruitmentmodels used to estimate survival and productivity, or to characterisevulnerability to exploitation (e.g. Au and Smith, 1997; Cortes, 1995,2002; Frisk et al., 2001, 2005; Gruber et al., 2001; McAuley et al., 2007;Punt and Walker, 1998; Simpfendorfer, 1999; Sminkey and Musick, 1996;Smith et al., 1998; Walker, 1992; Xiao and Walker, 2000).

3. Past and Present Threats

Harvest of shark and ray populations has been proposed as the currentgreatest threat to their diversity and abundance, with risk from commercialand industrial fisheries far out-weighing that of artisanal and subsistenceharvests (Baum et al., 2003; Dulvy, 2006; Dulvy and Reynolds, 2002;Dulvy et al., 2008; Garcıa et al., 2008; Robbins et al., 2006; Stevens et al.,2005; Worm et al., 2005). In comparison, the effects of habitat change anddegradation, pollution and invasive species on this taxon are poorly under-stood (Stevens et al., 2000). In this section, we provide an overview ofcurrent and past fishing effects on shark populations by industrial fishing,within single and mixed-species fisheries, by targeted or indirect harvesting,as by-catch in fisheries directed to other species and other threats includingbeach meshing, habitat loss and pollution.

3.1. Fishing

Chondrichthyans are a diverse taxonomic group that have radiated intospecialised and opportunistic top predators. Whether chondrichthyan fish-eries are sustainable has been debated and reviewed extensively over the lastthree decades (Holden, 1973; Stevens et al., 2000; Walker, 1998). Over thelast decade or so in particular, there has been much controversy regarding


the causes of collapsing fisheries (Hutchings and Reynolds, 2004; Myers andWorm, 2005; Reynolds et al., 2005) and the global state of shark popula-tions (Baum et al., 2005; Burgess et al., 2005a; Dulvy et al., 2008; Ferritiet al., 2008; Robbins et al., 2006; Stevens et al., 2000; Walker, 1998). Therehas also been much discussion and supposition regarding the impact of sharkand ray removal on the marine ecosystems that support them (Coll et al.,2006; Jackson et al., 2001; Stevens et al., 2000; Ward and Myers, 2005;Worm et al., 2006). Some have gone so far as to suggest that many of theworld’s shark populations are teetering on the brink of extinction, withcatastrophic ecosystem change predicted as the logical corollary (Baumet al., 2003; Myers and Worm, 2003; Worm et al., 2006). Although thereis some support for this contention (Aires-da-Silva et al., 2008;Simpfendorfer et al., 2002) others strongly disagree with this outlook, andidentify problems in data quality and interpretation (Burgess et al., 2005a,b;Hampton et al., 2005; Hilborn, 2007; Polacheck, 2006; Walters, 2003), andthe use of other data sources (Sibert et al., 2006) (see also Section 3.1.3.2).The debate thus far has been confined mainly to large pelagic fisheries, butthere is increasing concern for deepwater species living in presumablyrelatively stable environments that have already become subject to newand increasing exploitation as pelagic and coastal fisheries fail to meet theeconomic demand for fish products (Camhi et al., 1998; Garcıa et al., 2008;Roberts, 2002). Furthermore, local fishing has also been suggested asthe main driver for population reductions in and around conservationareas (Robbins et al., 2006), which highlights a number of managementdifficulties associated with the design and implementation of marineprotected areas.

The global catch of chondrichthyans (including sharks, rays andchimaeras—Fig. 4.1) has increased from approximately 270,000 tonnes inthe 1950s to around 810,000 tonnes in 2004, with a peak catch of 881,000tonnes in 2003 (Food and Agriculture Organization of the United Nations,2005). This accounts for approximately 1% of the current total landings ofall marine fish (Food and Agriculture Organization of the United Nations,2005). The greatest period of increase during that time was between the1960s and 1970s when catches rose by 40%. More recently, from 1996 to2004, the annual catch has exceeded 800,000 tonnes. FAO fishery statisticsshow that in 2004, 20 countries shared over 75% of the total catch, withIndonesia (15%), India (7.5%), Spain (6.5%), Taiwan (5.5%) and Mexico(4%) sharing approximately 40% of the total catch (Food and AgricultureOrganization of the United Nations, 2005) (Fig. 4.2). The current status ofregional fisheries harvesting chondrichthyans are reviewed in greater detailby Fowler and Cavanagh (2005). However, recent research has indicatedlarge potential errors in FAO reporting based on market estimates of sharkfins (Clarke et al., 2006), from which global fin trade is estimated to be up tofour times higher.


Figure 4.1 Examples of legal and illegal harvest of sharks. (A) Blue sharks (Prionaceglauca) being landed at a port in Portugal (photo credit: N. Queiroz, CIBIO, Portugal,and the Marine Biological Association of the UK). (B) Dried shark fins (unidentifiedspecies) confiscated by the Australian Customs Service from an illegal fishing boatfound within the Australian Fishing Zone in the Arafura Sea (photo credit: M. G.Meekan, Australian Institute of Marine Science). (C) Whole shark carcasses (mainlysilky sharks Carcharhinus falciformis, blue sharks and dusky sharks Carcharhinus obscurus)(photo credit: W.White, Commonwealth Scientific and Industrial Research Organisa-tion, Australia).


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Figure 4.2 Global distribution of the relative shark catch for the top 20 countries listed by the Food and Agriculture Organization of theUnited Nations (FAO) in 2004. These 20 countries shared over 75% of the total catch in 2004, with Indonesia (15%), India (7.5%), Spain(6.5%), Taiwan (5.5%) and Mexico (4%) sharing approximately 40% of the total catch (www.fao.org).

http://www.fao.org

These catches deliver products to a global and growing market for theirmeat, fins, cartilage, skin (leather), oil, teeth, gill rakers and jaws (Rose,1996). Unfortunately, records of how and in what quantities these resourcesare used are poor, and for most catches they are entirely unquantified. Freshshark meat is consumed locally near landing ports, but due to the need forexpedient processing and cold storage it has little export value relative tomost teleost fisheries (Camhi et al., 1998). On the other hand, dried sharkmeat and fins are easily processed and supply distant markets (Fig. 4.1). Thishas led to a large demand that has continued to grow since the mid-1980s,especially for dried fin that is the main ingredient in popular Asian soups(Clarke et al., 2006; Marshall and Barnett, 1997; Rose, 1996).

The biological and social effects of fishing exploitation are welldocumented (Dulvy et al., 2000, 2004b; Hawkins and Roberts, 2004;Hutchings and Reynolds, 2004; Jackson et al., 2001; Jennings and Kaiser,1998; Jennings et al., 1999; Kitchell et al., 2002; Pauly and Palomares, 2005;Robbins et al., 2006; Stevens et al., 2000; Worm et al., 2006). In addition tothe obvious reduction in abundance brought about by unsustainable har-vesting, chondrichthyan species might also experience changes to their lifehistory traits (e.g. age at maturity and size distribution) and demographyfollowing harvest (Frisk et al., 2005; Stevens and Davenport, 1991).

Currently, it is thought that sustainable and economically viable shark andray fisheries can be maintained if carefully managed, especially for specieswith relatively high productivity rates (Walker, 1998) such as gummy (Mus-telus antarcticus) and blue sharks (Prionace glauca) (Fig. 4.1). Presently, bothindustrial and small-scale commercial operations frequently raise concernregarding their sustainability, and with an increased demand for shark finproducts it has been suggested that shark and ray catches are in reality threeto four times higher than those reported (Clarke et al., 2006). This highlightsthe potential threats from illegal, unreported and unmanaged (IUU) fishing(see Section 3.1.4). It is worth noting that most industrial shark fisheriesare unmanaged with the exception of those from a few countries such asAustralia, New Zealand, Canada and USA (Fowler et al., 2005).

3.1.1. DefinitionsFrom the perspective of providing objective insight into the global status ofharvested chondrichthyans and to place this deterministic driver of popula-tion reduction into the context of extinction biology, we must be clearabout what we mean by ‘extinction’. In his classic paper, Caughley (1994)differentiated the two main paradigms in conservation biology that are stillrelevant today: (1) the declining population paradigm, which refers tofactors that depress the demographic rates of a species and cause its popula-tion to decline, and (2) the small-population paradigm, which refers to smallpopulations that have already declined due to some (deterministic) pertur-bation and are thus more susceptible than large populations to extinction via


chance events. This distinction is important because semantic labelling of afishery’s status, with similar terms used with different meanings, does notnecessarily indicate heightened extinction risk.

A large number of individuals are typically required to ensure that aspecies will persist with high certainty, given the substantial evidencedemonstrating that small and isolated populations are most vulnerable toextinction (Berger, 1990; Brook et al., 2002; Spielman et al., 2004). Smallpopulations have a relatively higher extinction risk than large populationsfor three main reasons. Firstly, due to demographic fluctuations resultingfrom random variation in survival and fertility. Secondly, through environ-mental variation in resource or habitat availability and quality, competitiveinteractions or predation, and catastrophic mortality events (e.g. diseaseepidemics, severe storms). Finally, with decreasing genetic heterozygosity,inbreeding depression and genetic drift (Gilpin and Soule, 1986; Shaffer,1981), the eventual fate of all closed, finite populations is extinction throughgenetic erosion (Frankham et al., 2004).

As populations decline they become more susceptible to demographicvariance in vital rates, stochastic variation in environmental conditions,Allee effects, inbreeding depression and loss of genetic diversity(Caughley, 1994; Frankham, 1995; Melbourne and Hastings, 2008; Traillet al., 2009). A minimum viable population (MVP) size is defined as thesmallest abundance required for an isolated population to persist at a defined‘high’ probability (usually set at >95%) for some (mostly arbitrary) setperiod into the future (Shaffer, 1981; typically 100 years or 40 genera-tions—Traill et al., 2007). Population-specific MVP sizes can be estimatedempirically using population viability analyses (PVA) that calculate theprobability of an initial population persisting in spite of demographic,environmental and genetic stochasticity and natural catastrophes (Shaffer,1981). PVA models can be constructed by empirical simulation, experi-ments or long-term monitoring (Traill et al., 2009); however, such modelsgenerally require good demographic and/or census data to provide reliableestimates (Traill et al., 2007). Other MVP methods use genetic data toestimate the minimum population size that will maintain evolutionarypotential—the population size required at equilibrium to balance the lossof quantitative genetic variation with the gain from mutation (Franklin andFrankham, 1998). Once a fishery (or some other deterministic driver)reduces a population to below its MVP size (Shaffer, 1981), then thereduced population becomes subject to a host of population-specific threats,most of which are stochastic (Traill et al., 2007).

This important concept appears to have had little adoption or tractabilityin fisheries science, perhaps mainly because so few chondrichthyans haveassociated good census or demographic data. As an example, the spinydogfish (Squalus acanthias) has declined by >78% in the north-easternAtlantic in about three generations, which is sufficient to warrant Endangered


status under the IUCN’s Category A. Yet the entire population ofS. acanthias numbers in the millions (Reynolds et al., 2005), which exceedsall cross-taxonomic estimates of MVP size (Traill et al., 2007, 2009).Therefore, this species, and perhaps many other chondrichthyans thathave declined due to fishing harvest (Reynolds et al., 2005) still have arelatively low risk of extinction.

Instead, the fisheries literature is replete with subjective terms that areused to refer to a fished population’s status, with little differentiationbetween local, global, biological and economic ‘extinction’. Terms suchas ‘over-exploited’, ‘over-harvested’, ‘depleted’ and ‘collapsed’ are oftenonly arbitrarily or not explicitly defined, so confusion is common (Hilborn,2007; Jennings, 2007). For example, a fishery has been labelled ‘collapsed’when its catch in any year falls below 10% of the highest recorded catch(Worm et al., 2006), yet this definition is uncoupled from the concept ofdistance to a population’s MVP. Likewise, terms adopted by the FAO like‘depleted’ are reserved to describe the point at which harvest rate exceedsthe maximum biological productivity (or maximum sustainable yield, MSY;Fig. 4.3), but this relationship depends on the underlying model chosen torepresent the relationship between population rate of change and density(Fig. 4.4), which can vary considerably and is rarely evaluated specifically(Bradshaw, 2008; Brook and Bradshaw, 2006). The term ‘collapse’ has beendefined loosely as when high catches continue for some time after ‘depletion’has occurred, usually followed by low catch rates and abandonment of theparticular fishery (Cooke, 1984), with some definitions based again onarbitrarily set magnitudes of decline (e.g. >90% relative to baseline abun-dance; Worm et al., 2006). This is a result of socio-economic factors relatedto profitability (Hilborn et al., 2003; Musick, 2005).

Even the word ‘extinction’ can have different meanings. ‘Local’ or‘population’ extinction is often referred to as ‘extirpation’. This differsfrom ‘global’ extinction in that only a proportion of the total number ofindividuals of that species is removed, usually, a sub-population that isgeographically or genetically distinct from others (Sodhi et al., 2007). Thisis further complicated because it is nearly impossible to observe localextinctions directly, especially in the marine environment where mostspecies’ behaviours go unnoticed. Thus extinctions can only be trulydetermined from successive surveys that fail to identify a species’ presence(Fagan and Holmes, 2006; Sodhi et al., 2007). There are also a number ofalternative methods can be used to infer extinction including correlativeapproaches based on life history and ecological information, time-series toestimate changes in abundance; or demographic analyses based on age- orstage-structured models of vital rates (Dulvy et al., 2004a). These approachesall focus on individual species.

Extirpations can change the local biological community (see Section 5),or lead to trophic replacements ( Jackson et al., 2001). Local extinctions can


also lead to increased fragmentation and genetic isolation, which are knownto increase extinction risk especially for weakly dispersing and specialistspecies (Brook et al., 2008; Purvis et al., 2000b). Another concern for range-restricted species is density depensation, or Allee effects, that cause a reduc-tion in the growth rate of small populations as they decline via reducedsurvival or reproductive success (Courchamp et al., 2008; Mullon et al.,2005). We want to avoid potentially subjective terms ( Jennings, 2007) andfocus instead on how deterministic decline due to harvesting can changechondrichthyan susceptibility to extinction. In the following sections, wedocument several chondrichthyan fisheries with the view to assess thedegree of population decline that could lead to higher extinction risk.

3.1.2. Targeted fisheriesCommercial fisheries targeting sharks started as early as the late eighteenthcentury, with basking sharks (C. maximus) being the earliest-known targetspecies (McNally, 1976). Although this fishery started from artisanal opera-tions, it grew quickly in response to increasing consumer demand(McNally, 1976). From the 1920s, commercial fisheries targeting sharksgrew steadily (Bonfil, 1994; Gauld, 1989), with overall shark landings

Yie

ld

F

MeMb(MSY)

Figure 4.3 The classic trade-off between recruitment and fishing rate (F) showing thefishing rate where maximum biological productivity (Mb) occurs, also known asmaximum sustainable yield (MSY). Also shown is the fishing rate where economicbenefit (Me) is maximised, which is inferior toMb because it takes into consideration thelong-term sustainability of the fishery (i.e. sustained fishing at Mb will tend to result inlong-term declines in catch rates) (Hilborn and Walters, 2001).


increasing by 2% each year since 1985 (Food and Agriculture Organizationof the United Nations, 2005).

More recently, directed shark fisheries have clearly reduced target pop-ulation sizes. These fisheries usually focus on one or two primary species andare often managed using conventional single-species modelling approaches.It has been suggested that shark populations can withstand only modestlevels of fishing without large reductions in population size (Camhi et al.,1998; Cortes, 2000; Musick, 1999b; Musick et al., 2000a). Brief periods ofhigh harvest rates are usually followed by severe declines in catch rates infished shark populations (Camhi et al., 1998), usually associated with afishery’s closure and a long, slow period of recovery, or continued lowcatches at a fraction of those obtained during the initial period (Gauld, 1989;Hurley, 1998; Schindler et al., 2002; Sminkey and Musick, 1996). Due tothis predominant historical pattern, intensive and careful management isrecommended at the inception of any shark fishery (Musick et al., 2000a).However, the majority of shark fisheries (e.g. see Kroese and Sauer, 1998)are unmanaged (Walker, 1998). These are likely to cause rapid population

Carry capacity of population

Populationdecline

Populationgrowth

F

0r

log (N) or CPUE

Figure 4.4 A simple linear relationship between the rate of population change(r ¼ loge(Ntþ1/Nt)), and measure of abundance (logeN or catch-per-unit-effort,CPUE) and fishing rate (F). This particular population dynamical model represents theclassic logistic rise to an environmentally determined (temporally averaged) carryingcapacity and has formed the basis for fisheries models for the past 50 years (e.g. Bevertonand Holt 1957, 1993; Fox, 1970); however, many non-linear forms of the relationshipbetween r and N exist and should also be considered when the true relationship isunknown (Bradshaw, 2008; Brook and Bradshaw, 2006; Turchin, 2003).


declines (Bonfil, 1994), with slow or little recovery, or fishery abandonmentdue to economic or market constraints (Musick, 2005).

Although many shark species and their fisheries have traditionally beenof low economic value compared to dedicated teleost fisheries, the eco-nomic impact of population reductions can be similar because recovery timeand associated economic downturns usually last much longer (Musick andBonfil, 2005). Often-cited examples of reduced or abandoned shark fish-eries are the various basking shark fisheries (Anonymous, 2002; Kunzlik,1988; Parker and Stott, 1965), the porbeagle shark (Lamna nasus) fishery inthe Northeast Atlantic (Department of Fisheries and Oceans, 2001; Gauld,1989), the tope or ‘soupfin’ shark (Galeorhinus galeus) fisheries off Californiaand Australia (Olsen, 1959, 1984; Ripley, 1946; Walker et al., 1995) andthe spiny dogfish (S. acanthias) fisheries in the North Sea and off BritishColumbia, Canada (Anderson, 1990) (Fig. 4.5). Although the history andstatus of targeted shark fisheries are reviewed in detail elsewhere (Camhi et al.,1998; Fowler et al., 2005), we have provided a brief overview of examples ofboth abandoned and apparently sustainable shark fisheries below.

3.1.2.1. Basking shark C. maximus Dedicated fishing for basking sharkshas been noted across northern Europe since the mid-1700s (InternationalCouncil for the Exploration of the Sea, 2007), with the oldest confirmedfishery records available from west Ireland in the late eighteenth century.This was most likely an artisanal net fishery spanning several decades andbecoming a commercial enterprise with rising demand for shark liver oil.This led to notably large declines by 1830 and fishery abandonment in thesecond half of the nineteenth century. Basking sharks were not targetedagain until 1947, at which point a new localised fishery started near AchillIsland (Ireland), where 900–1800 sharks were taken each year from 1950 to1956 (Fig. 4.5). Catches started to decline after 1955, from 1067 per yearbetween 1949 and 1958, to 119 per year between 1959 and 1968, and thento 40 per year for the remaining 7 years of the fishery that ended in 1975.Toward the end of the fishery, even increasing shark oil prices and capitalinvestment did not reverse the steady decline in catches. A total of 12,360individual fish were caught over the life of the fishery, with 75% caught inthe first 6 years (McNally, 1976). Today, basking sharks are often sightedaround shelf fronts, although total population sizes are unknown (Sims,2008; Sims and Quayle, 1998; Sims et al., 2005). Over the same period asthe Irish fishery and beyond its end, a Norwegian fleet was also fishing forbasking sharks over a large area of the northeast Atlantic. Catches were high(>1000 sharks per year, and>4000 in some years) between 1959 and 1980.Since 1981, landings have declined and not exceeded 1000 sharks per year(Kunzlik, 1988). This decline has been attributed to an ageing fleet, adecline in value of basking shark liver oil (Kunzlik, 1988), or possibly achange in the species’ distribution to areas of higher productivity (Sims and


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Figure 4.5 Location of fisheries and target chondrichthyan species mentioned in the text (coverage is not intended to be inclusive of all sharkfisheries). (1) Blue shark Prionace glauca high-seas fisheries; (2) tope, school or ‘soupfin’ sharkGaleorhinus galeus fisheries off California, south-eastern Australia and New Zealand; (3, 4) Gulf of Mexico and south-eastern USA coastal and pelagic shark fisheries (including duskyCarcharhinus obscurus, sandtiger Odontaspis taurus, oceanic whitetip Carcharhinus longimanus, sandbar Carcharhinus plumbeus, silky Carcharhinusfalciformis, great white Carcharodon carcharias, hammerhead Sphyrna lewini, S. mokarran and S. zygaena, thresher Alopias vulpinus and A. super-ciliousus, short-fin mako Isurus oxyrinchus, and tiger sharksGaleocerdo cuvieri); (5) barndoor skateDipturus laevis off New England and Canada inthe western Atlantic ground fishery; (6) basking shark Cetorhinus maximus fisheries in the north-eastern Atlantic; (7) Irish Sea common skateDipturus batis fishery; (8) porbeagle Lamna nasus fishery in the North Atlantic; (9) angel shark Squatina squatina in United Kingdomwaters; (10)blacktipCarcharinus tilstoni andC. limbatus and spot-tailC. sorrah shark fishery in the Arafura-Timor Seas, northern Australia; (11) gummy sharkMustelus antarcticus catches increasing to offset declines in school shark catches in south-eastern Australia; (12) grey nurse sharkCarcharias taurusrapid decline in eastern Australia due to spear-fishing, recreational fishing by-catch, commercial by-catch and beach meshing. Bold numbersand zone demarcations refer to Food and Agriculture Organization of the United Nations (FAO) Fishing Areas (www.fao.org).

http://www.fao.org

Reid, 2002). Overall in the north-eastern Atlantic between 1946 and 1997,including the target fishery in Scottish waters, records indicate 105,730basking sharks were captured and traded (Sims, 2008). However, due to alarge fishing area and location uncertainty, it has been difficult to detect andevaluate temporal trends in the catch data. Since 1978, management ofbasking shark fishing in European Community waters (UK and Ireland) hasbeen by a total allowable catch quota system initially set at 400 tonnes, butnow the quota has been reduced to zero (Sims et al., 2005). There stillappears to be incentive to continue the fishery due to the high prices paidfor large basking shark fins in Singapore (Camhi et al., 1998) and other Asianmarkets.

3.1.2.2. Tope, school or soupfin shark G. galeus Although there arenumerous fisheries for tope (‘school’ or ‘soupfin’ shark) around the world,the most infamous fishery occurred off the Californian coast in the early tomid-1900s (Holden, 1974; Ripley, 1946; Fig. 4.5). The fishery only lasted8 years and was abandoned in the mid-1940s (Ripley, 1946). It is stilluncertain whether populations have recovered more than 50 years later(Camhi et al., 1998). Shark landings from 1930 to 1936, of which topecomprised a high proportion (around 80%), were relatively low and stable ataround 270 tonnes per year. The fishery then expanded enormously fol-lowing the establishment of a new market for liver oil in 1937, with catchespeaking at 4185 tonnes in 1939. This new market demand also pushedprices from some US $50 per tonne in 1937 to US $2000 per tonne in1941. Tope landings were declared independently of the general take from1941, with annual declines from 2172 tonnes in 1941 to 287 tonnes in 1944.Catch-per-unit-effort (CPUE) in one region declined from 34.4 fish/1000m of gillnet fished for 20 h in 1942, to 4.8 fish/1000 m/20 h in 1945(Roedel and Ripley, 1950).

Not all targetedG. galeus fisheries have caused large population declines.In southeast Australia (Fig. 4.5), exploitation of school sharks began in the1920s, but production increased greatly during the war years. Catchesreached 2000 tonnes live weight in 1949 (Walker et al., 1995) due todemand for shark liver oil. Catches remained relatively high between1949 and 1957 as the fishery spread from inshore to offshore waters(Olsen, 1959; Walker et al., 1995). In 1964, decline of the liver oil marketled to development of the shark meat market and a switch to gillnetting.This new market allowed production to increase rapidly, peaking in 1969 at3158 tonnes, although the proportion of gummy shark (M. antarcticus) in thecatch was also increasing. Following a ban on the sale of large G. galeus in1972 because of reported high mercury concentration in the meat, catchesdeclined for about 10 years and gummy sharks took over as the principaltarget species in the fishery (Stevens et al., 1997). With relaxationof mercury laws in the early 1980s, catches again increased, reaching


3060 tonnes in 1986. However, concerns of population reduction promptedby a measured 84% reduction of mature biomass resulted in the implemen-tation of a dedicated fishery management plan in 1988 (Stevens et al., 1997,2000) and ongoing research initiatives (Punt and Walker, 1998; Punt et al.,2000; Walker, 1992; Walker et al., 1998). In New Zealand, G. galeus havebeen harvested since the late 1940s and have followed a similar trend tothe Australian fishery. With the demise of the liver oil fishery in the 1950s,a market for the flesh developed with a small export market to Australia.Catches peaked at 5000 tonnes live weight in 1984 (Francis, 1998).

3.1.2.3. Northern Territory, Australia shark fishery Many dedicated sharkfisheries tend to be small and target highly productive species (Stevens et al.,2000; Walker, 1998). An example of one such fishery is the north Australianshark fishery in the Northern Territory (Fig. 4.5). This is a small tropicalshark fishery with only 13 licences and only 7–9 vessels operating currently.Target species are primarily the Australian blacktip (Carcharhinus tilstoni) andspot-tail sharks (C. sorrah), but frequent switches to teleosts such as greymackerel (Scomberomorus semifasciatus) occur. A variety of secondary sharkspecies are also caught including tiger (G. cuvier), pigeye (Carcharhinusamboinensis) and hammerhead sharks (Sphyrna spp. and Eusphyra blochii)(Field et al., 2008). The fishery has developed slowly from 1984 to itspresent management system (Australia Department of Environment andHeritage, 2005) with an annual shark catch that peaked in 2004 at 1089tonnes (Northern Territory Department of Primary Iindustry Fisheries andMines, 2005). It has remained relatively stable ever since. An increase inCPUE and in proportional catch of non-primary target species from 2000 to2003 prompted questions regarding the industry’s future sustainability(Australia Department of Environment and Heritage, 2005). Due to marketdemand, grey mackerel currently dominates the catch in terms of single-species catch, and there has been a reduction in fishing effort to preventrapid changes or growth of new fisheries enabled by technological advan-tages (Northern Territory Department of Primary Iindustry Fisheries andMines, 2005). Research projects to address concerns of sustainability wereimplemented in 2004 to include stock monitoring (Northern TerritoryDepartment of Primary Iindustry Fisheries and Mines, 2005), risk assess-ment (Pillans, 2007) and observation and tagging studies (Field et al., 2008).

As with many shark fisheries, the history of shark harvest in northernAustralia is more complex than the current industry’s structure mightsuggest. From the early 1970s until mid-1986, a Taiwanese pelagic gill-net fleet operated in the waters around northern Australia targeting shark,longtail tuna (Thunnus tonggol) and mackerel (Scomberomorus spp.). Since itwas largely unmanaged, the fleet’s extent caused concern (Stevens andDavenport, 1991). The areas accessible to the Taiwanese fleet changedover the course of the fishery’s lifetime following the implementation of


the Australian Fishing Zone in 1979, limiting it to mainly offshore regionsranging from the North West Shelf to north of the Gulf of Carpentaria(Fig. 4.5). The catch was subsequently reduced from around 17,000 tonnesper year to an annual quota of 7000 tonnes. Before 1980, reporting of catchand effort was limited (Walter, 1981), but afterwards basic catch composi-tion and effort data were collected under Taiwanese and independentlogbook programmes. These records indicated that total catch compositionby weight was approximately 80% shark, with blacktip (primarily C. tilstoniwith an unknown proportion of Carcharhinus limbatus) and spot-tail(C. sorrah) sharks accounting for 60% of the total catch (Stevens andDavenport, 1991). During the early 1980s, fishing effort almost doubled,while CPUE decreased from 16 to 7 kg/km/h (Stevens and Davenport,1991). Data from the Taiwanese fleet showed some signs of populationreduction (Stevens and Davenport, 1991). Other data also indicated agestructure changes; length-frequency distributions indicated fewer matureC. tilstoni were caught from 1981 to 1986, and there was also a decrease inthe abundance of mature female C. sorrah and a decrease in median size ofsharks caught for both C. tilstoni and female C. sorrah. Further restrictionswere imposed in 1986, eventually leading to the decision by the Taiwaneseto abandon the fishery for economic reasons. However, Taiwanese gillnet-ting continued outside the Australian Fishing Zone.

3.1.3. Mixed fisheries and by-catchAlthough directed fishing can have severe effects on target species, possiblythe greatest potential threat to chondrichthyans worldwide is indirect har-vest, or in mixed-species fisheries where they represent ‘by-catch’ (Bonfil,1994; Camhi et al., 1998; Musick, 1999b; Stevens et al., 2000, 2005;Walker, 1998). Sharks can be caught incidentally in trawl nets, gillnets,purse seines, and longlines, and mortality from these as by-catch mightexceed that from directed fisheries (e.g. oceanic fisheries for tuna and bill-fishes, Bonfil, 1994; Francis and Griggs, 1997; Polacheck, 1989). In suchcases, the fisheries can enter regional or international trade with little or noreporting or tracking of produce. This is of particular concern for small-scale commercial and artisanal fisheries, especially for trade in ‘rare’ specieswith small population sizes such as sawfishes (Camhi et al., 1998) andpossibly basking sharks (Magnussen et al., 2007; Sims, 2008).

The two main problems with mixed-species fisheries that catch non-target species are the (1) low priority and economic value of secondaryspecies catches and (2) limited or no reporting of captured and discarded by-catch species. Such fisheries can generally remain economically viable, atleast over the medium term, because the primary species tend to be moreproductive than secondary species that can eventually sustain large popula-tion declines or be driven to extinction (Baum et al., 2003; Casey andMyers, 1998; Essington et al., 2006; Musick, 1999b; Myers and Worm,


2003; Stevens et al., 2000). Poor catch recording of secondary species infisheries in domestic and international waters severely limits our capacity tounderstand and manage by-catch (Alverson et al., 1994; Nakano and Clarke,2006). Even today most countries do not require by-catch data to becollected. The few data that are collected from either logbooks, landingstatistics or observer programmes are limited in coverage, especially forhigh-seas fisheries, and are generally too imprecise even to identify reliablythe species composition of the catch (Dulvy et al., 2000; Nakano andClarke, 2006). Although some shark by-catch is landed and reported offi-cially, the majority is only estimated. As such, some have argued that by-catch might represent up to 50% of the total worldwide shark catch (Bonfil,1994). These two components mean that large discrepancies and uncer-tainty in population trends impair management.

Mixed-species fisheries occur across a range of marine habitats, fromcoastal demersal to open-ocean pelagic regions, although historically deep-water habitats have likely escaped much of the exploitation pressure but areconsidered especially vulnerable in the future (Garcıa et al., 2008). Theconstraints of deepwater fishing might have led to these habitats becomingconservation refuges for many shark species, given that up to 35% of allshark species primarily occupy deepwater habitats (Camhi et al., 1998;Garcıa et al., 2008; Stevens et al., 2005). Many by-catch species are har-vested mainly by trawlers across a broad range of life stages (Stevens et al.,2000), and several examples exist of by-catch chondrichthyans showingsigns of moderate to severe population decline.

3.1.3.1. Examplesofmixed-species fisheries impacting chondrichthyans Inthe early 1980s, a severe decline in common skates (Dipturus batis) of theIrish Sea was reported, to the extent that the population was thought to be atthe ‘brink of extinction’ (Brander, 1981). More recently, the barndoor skate(Dipturus laevis), a species that is taken as by-catch in the New England andCanadian Atlantic ground fish fisheries, has become the first well-docu-mented example of localised extinction (Casey and Myers, 1998; Fig. 4.5),although non-peer-reviewed reports from Canada and USA concluded thepopulations have not even been severely reduced (Boelke et al., 2005; Kulkaet al., 2002). Other large skate species might be potentially threatened withextinction (Dulvy and Reynolds, 2002), and several other studies havedocumented reduced diversity in demersal chondrichthyans (Aldebert,1997; Jukic-Peladic et al., 2001; Rogers and Ellis, 2000). In the north-western Mediterranean, there has been a clear decline of several sharkspecies commercially captured by trawls due to increased fishing intensityand technological advances in fishing gear. This pattern has also beenobserved in some coastal areas around the United Kingdom (Fig. 4.5)where trawling has changed demersal fish assemblages by reducing theabundance of large sharks, skates and rays such as D. batis and the angel


shark Squatina squatina (Rogers and Ellis, 2000). A similar decline inspecies richness and distribution has been reported for several largeshark and rays species in the Adriatic between 1948 and 1998 ( Jukic-Peladic et al., 2001).

Pelagic fisheries using longlines, gillnets and driftnets also pose a largepotential threat to chondrichthyans, some of which have been the focus ofmuch research and concern over the last decade. In both the Pacific andAtlantic Oceans there have been large declines in many fish stocks caught intuna and billfish longline fisheries associated with extensive by-catch(Christensen et al., 2003; Schindler et al., 2002). Pelagic longline fisheriesworldwide remove up to 8 million sharks per year, or one-third of the worldcatch of all sharks and rays (Bonfil, 1994); however, the actual rate could beup to four times higher (Clarke et al., 2006).One of themain by-catch speciesin the Pacific and Atlantic open-ocean fisheries (Fig. 4.5) is the blue shark(P. glauca) which accounts for around 50% of the total worldwide shark by-catch (Bonfil, 1994; Stevens et al., 2000). This species has relatively highgrowth and fecundity compared to other chondrichthyans, and so is thoughtto be relatively resilient to current fishing pressure (Aires-da-Silva andGallucci, 2007). Prior to the 1980s, there was little demand for blue sharksbecause of their softmuscle tissue and strong ammonia odour (Walker, 1998).As such, most blue shark by-catch was discarded or returned alive, whichacted to reduce fishing mortality (He and Laurs, 1998).

With the expansion of the Asian fin market in the 1980s, there was alarge increase in the demand for blue shark fins. This led to an increase infinning, the practice of removing the fins from a carcass and discarding thetrunk overboard, sometimes with the de-finned shark still alive. Since driedfins do not take up much valuable space in freezers on ships or on land, theyrepresent an economically attractive by-product. In the Hawaiian longlinefishery where no sharks were reported being harvested solely for fins priorto 1990, up to 61,000 individual blue sharks were caught and finned in 1998alone (McCoy and Ishihara, 1999). This increase in dedicated harvest causedpopulation declines from the 1980s onward, although fisheries assessment todetermine changes in catch rates have provided conflicting results. Forexample, it has been estimated that blue shark numbers in the Pacific havedeclined by 20% between 1982 and 1993, but no such trend was observed inIndian Ocean fisheries and only contrasting evidence of a decline in theAtantic Ocean (Aires-da-Silva et al., 2008; Baum et al., 2003; Nakano,1996; Nakano and Clarke, 2005). Neither was there a decrease in blueshark catch rates observed in Australian longline fisheries (Stevens andWayte, 1999). Recently however, these trends have been questionedand there now appears to be evidence of declines (Aires-da-Silva et al.,2008; Baum et al., 2003; Simpfendorfer et al., 2002). Based on fishery-independent data from 1977 to 1994, Simpfendorfer et al. (2002) foundevidence for an 80% decrease in the abundance of male, but not female, blue


sharks, whereas an analysis of the US North Atlantic catch logbook dataconcluded an overall 60% decline in catches (Fig. 4.5; Baum et al., 2003).

Newer techniques have been used to determine the status of blue sharks(Aires-da-Silva and Gallucci, 2007; Clarke et al., 2006; Schindler et al., 2002;Simpfendorfer et al., 2002) that link life history traits and vital rates to harvestscenarios. These modelling approaches use stochastic age-structured popula-tion models to assess population dynamics. By estimating the intrinsic rate ofpopulation increase, blue shark populations are at risk of declining once 20%of the original biomass is removed, and juveniles are more at risk if heavilyharvested (Aires-da-Silva and Gallucci, 2007). Furthermore, sexual segrega-tion gradients have also been reported for this and other shark species thatwould exacerbate over-exploitation for some populations (Mucientes et al.,2009). Overall, evidence from market surveys (Clarke et al., 2006) suggeststhat populations are currently at or just over the MSY for this species.Therefore, the strength of evidence at present shows that most blue sharkpopulations are currently stable; however, some have declined and harvestrates require careful management and monitoring, particularly when there isthe possibility of sexual segregation of populations and a likelihood ofdestabilising population structures (Mucientes et al., 2009).

3.1.3.2. Chondrichthyan decline controversies For other harvestedchondrichthyan species caught in coastal and oceanic fisheries, there havebeen population declines (Aires-da-Silva et al., 2008; Cavanagh, 2005;Cortes et al., 2002; Musick et al., 1993, 2000b; Simpfendorfer et al., 2002;Stevens et al., 2000). Some studies even suggest that several species are closeto extinction (Baum et al., 2003, 2005; Myers and Worm, 2005; Wormet al., 2005). In these cases, the conclusion of high, imminent extinction riskhas generated extensive debate (Baum et al., 2005; Burgess et al., 2005a,b),especially with respect to the status of species such as tiger (G. cuvier), greatwhite (Carcharodon carcharias), requiem (Carcharhinus spp.), hammerhead(Sphyrna lewini, Sphyrna mokarran, Sphyrna zygaena), shortfin mako (Isurusoxyrinchus), oceanic whitetip (Carcharhinus longimanus), thresher (Alopiasvulpinus and Alopias superciliousus), and porbeagle sharks (L. nasus)(Fig. 4.5). Some of the differences in opinion expressed to date mighthave arisen in part from competing views of fisheries biologists and conser-vation ecologists (Hilborn, 2007); however, we attempt in the following toprovide a neutral summary of the contentious issues around the reportedspecies declines, to which almost all agree are real, even though the magni-tude remains under debate.

Although some mention of species decline had been made previously(Cortes et al., 2002; Musick, 1999a; Musick et al., 1993), it was not untilBaum et al. (2003) published their report of severe declines of some sharkspecies in the Northwest Atlantic that serious concerns regarding extinctionrisk in sharks were raised and received broad national and international


media attention. The logbook data set on which their analyses were basedcovered the US pelagic longline fishery targeting tuna and billfish from 1986to 2000, encompassing a total of 214,234 longline sets (mean ¼ 550 hooks/longline). This data set was proposed to be one of the longest time series forshark harvest ever analysed, with six species or species groups recorded from1986 onward, and eight species from 1992 onward. Their results presentedstrong evidence that hammerhead, great white and thresher sharks hadsuffered the greatest declines, with reductions of over 75% in relativeabundance over the past 15 years. Tiger, coastal requiem (carcharhinid),blue and oceanic whitetip sharks were also substantially reduced by 65%,61%, 60% and 70%, respectively, and shortfin mako sharks declined mod-erately. These trends were then extrapolated to the entire region of theNorth Atlantic. Further evidence in support of large shark declines camesoon after from the Gulf of Mexico, where longline records showeddeclines of 99% and 90% for oceanic whitetip and silky sharks (Carcharhinusfalciformis), respectively, between 1954–1957 and 1995–1999 (Baum andMyers, 2004). A number of other coastal shark species in the region haveapparently declined due to high harvest rates, including sandtiger (Carchar-hinus taurus) and dusky (Carcharhinus obscurus) sharks (Fig. 4.5). Thesepopulations declined because of catches persisting until the late 1980s, andshowed only modest signs of recovery after 10 years (i.e. a few generations)of regulation. The more productive sandbar shark (Carcharhinus plumbeus),although reduced in population size, continues to sustain fisheries (Musick,1999a; Musick et al., 1993).

The above-mentioned studies, among others (Dulvy et al., 2008), havehad a large influence on recent conservation decisions to list many sharkspecies under the Convention on International Trade in Endangered Spe-cies (CITES) and the World Conservation Union’s (IUCN) Red List.However, the methods on which the conclusions were based have sincebeen called into question (Baum et al., 2005; Burgess et al., 2005a,b; Wormet al., 2006). According to Burgess et al. (2005a), the weaknesses of theBaum et al. studies are related to the nature of logbook reporting, choice andsize of data sets used, the temporal and spatial context of the data, and thestandardisations made.

One of the greatest concerns raised regard coverage and quality of thedata set, in addition to assumptions and standardisation of catch data, toprovide indices of relative abundance based on small sample sizes (Burgesset al., 2005a; Hilborn and Walters, 2001). Use of the US pelagic longlinelogbook data set was considered problematic for two main reasons. Firstly,another 25 data sets were available for the region from other sources,including from US observers on US and Japanese boats, Canadian observerson Canadian and Japanese boats, and from other scientific and recreationalsurveys. Although, Burgess et al. (2005a,b) recognised that the US pelagiclongline data set gives the best temporal and spatial resolution, they


contended that other data sets and studies were not used or cited; forexample, stocks assessment of coastal shark populations from the northwestAtlantic and the Gulf of Mexico were not discussed (Cortes et al., 2002).Apparent oversight of these additional lines of evidence that provide mixedsupport for and against the conclusion of severe declines in some specieswere identified as a shortcoming (Burgess et al., 2005a,b). However, someof these additional data sets were not freely available (Baum et al., 2005).Furthermore, other originally unused data sets have been considered byShepherd and Myers (2005) and in some unreported studies (Baum et al.,2005), and all of these support the initial conclusions.

Secondly, the data sets used (Baum et al., 2003) might not adequatelyrepresent the large, less common coastal species relative to pelagic species,and catches might not reflect the true status of the coastal sharks (Burgesset al., 2005a). Also less commonly caught species were not considered,despite other studies showing no evidence of decline in species such assandbar sharks (C. plumbeus) (Burgess et al., 2005a). Baum et al. (2005)conceded that their data set does not allow modelling of individual coastalshark species and that trends can vary among species; however, they madeno inferences about individual trends in abundance. The capacity for speciesmisidentification in the logbook data might also have inflated catchesreported for some species, if indeed this was systematic. For example,Burgess et al. (2005a) contended that oceanic whitetip and other sharksbearing white skin patches are often reported as ‘white sharks’, which couldbe mistaken for C. carcharias, the great white shark. Other species misiden-tifications were thought to be likely with any large ‘brown’ sharks oftenreported as ‘tiger’ sharks, and shortfin makos as ‘blue’ sharks. However, thedegree of potential misreporting was not determined by either grouping.

Concerns were also raised over the particular spatial analyses used andinterpretation of results for a number of studies reporting severe declines(Baum et al., 2003; Myers andWorm, 2003). Walters (2003) questioned theinterpretation of widespread declines due to errors which can lead to over-estimated reduction by summing and averaging catch data over broad areaswithout taking local ‘weighting’ into consideration (Hilborn and Walters,2001; Walters, 2003). Burgess et al. (2005a) also identified that changes infishing practices, target species, gear and management policy during theperiod over which the data were collected invalidated some of the temporalcomparisons in catch composition. There were changes in the type of hooksand leaders used over the data set interval, with newer gear possiblyreducing shark by-catch, especially for larger species. Finally, there waslikely to be high error associated with data standardisation used to controlfor environmental heterogeneity, including oceanographic conditions andhabitat type (Burgess et al., 2005a).

Even after debating the data sets and methods used (Baum et al., 2005;Burgess et al., 2005a,b), there remains some contention over the original


conclusion of near extinction for many large sharks. Regardless of thedebate, however, the overarching trends on which there is agreementindicate that there have been general declines in many of the fished sharkspecies in the north-western Atlantic. The debate is instead centred on themagnitude of the declines, and there is new agreement that to resolve theaforementioned problems, more research and monitoring are required. Allparties also agree that a precautionary approach is most certainly advisable,given the signs that a problem exists. One view is that this must be based onstock assessments that rely on a range of data sets including catch rates, sizeand age composition, tagging returns, and other measurements of ecologicaland life history traits.

3.1.4. Illegal, unreported and unregulated (IUU) fishingAlthough sharks have historically been of relatively low economic value,IUU fishing is generally seen as a potentially serious threat to chondrichth-yan species richness and abundance (Clarke et al., 2006). IUU fishing refersto harvesting that does not comply with national, regional or global fisheriesconservation and management obligations (Agnew et al., 2008; Ainsworthand Pitcher, 2005; Gewin, 2004; Sumaila et al., 2006). In the context ofchondrichthyans, illegal harvest principally targets species for the highlylucrative trade in fins, for example, sawfishes (Pristis spp.) and blue sharks(Clarke et al., 2006). IUU fishing on the high seas or in distant waters fromlanding ports can be a highly organised, mobile and elusive activity thatundermines the sustainable management efforts of fish resources under thejurisdiction of responsible countries. International cooperation is thereforeessential to combat this serious problem effectively, especially consideringthat conservative estimates place the harvest due to IUU fishing at threetimes that of managed fishing quotas (Agnew et al., 2008; Gewin, 2004).

As an example, IUU fishing continues to thrive in the northern region ofAustralia’s Fishing Zone (AFZ) and is largely undertaken by traditional orsmall-scale Indonesian vessels (Field et al., 2009). Indonesian fishermeninvolved in IUU fishing in this area target specific species such as shark,reef fish, sea cucumber (Holothuria spp.) and trochus (Trochus spp.) that aredestined for the Asian market (Field et al., 2009). Since 1974, traditional,non-motorised, Indonesian vessels have been allowed access to a definedarea of the AFZ north west of Broome (Fig. 4.5) in which Australia agreesnot to enforce its fisheries laws allowing traditional access; this area is knownas the Memorandum of Understanding (MoU) 1974 Box (Field et al.,2009). Historically, IUU fishing by Indonesian vessels occurred either inthe MoU Box as a result of opportunistic fishing in other areas of the AFZ,or around the MoU Box contrary to the agreed rules. More recently, therehas been a noticeable shift away from what could be termed ‘traditional’fishing. Motorised vessels are being found as far east as the Torres Strait, andare largely targeting sharks for their valuable fins. This has led to marked


changes in the abundance and species composition of sharks in the region(Field et al., 2009) and is predicted to have ecosystem and economicconsequences (Pascoe et al., 2008).

3.1.5. Recreational fishingRecreational fishing is a popular and growing activity in many parts of theworld (Stevens et al., 2005). Although chondrichthyans are mainly by-catchspecies formany recreational fishers, they are also targeted by others as game orsport fishes (Stevens et al., 2005).Recreational fishing catches are typically smallrelative to commercial catches, although few data are available specifically forchondrichthyans due to a general absence of formal reporting requirements ordedicated surveys. The few data that do exist provide some interesting insight;however, the impact of recreational fishing on chondrichthyans is difficult topredict. In Australia and New Zealand, recreational catches are relatively low.The total commercial shark catch reported to the FAO (Food and AgricultureOrganization of the United Nations, 2000) for Australia was approximately7500 tonnes in the year 2000. At the same time, a national recreational andindigenous fishing survey estimated that the total shark catch was around1200 tonnes (Henry and Lyle, 2003), representing approximately 16% of theannual commercial catch, although about 81%was reported as ‘released alive’.This is slightly more than the proportional catch reported for recreationalfishers in New Zealand targeting rig (Mustelus lenticulatus), spiny dogfish andelephant fish (Callorhinchus milli) (Fig. 4.5), where recreational fishers caughtbetween 6% and 8% of the total reported commercial shark catch (Francis,1998).The largest recreational catch for sharks on the east coast of theUSA andin the Gulf of Mexico is estimated at around 35,000 tonnes per year, of whichapproximately 30% were reported killed (Musick et al., 1993). Recently,catches have been revised to 11.1 million individual sharks from all speciescaught by recreational fishers, and 0.448 million of these were harvested(Marine Recreational Fisheries Statistics Survey, 2001). More specifically,catches of large coastal sharks (e.g. great white, sandbar, blacktip, mako sharks)in the region are thought to be greater than that taken by the commercialfishery (Cortes et al., 2002), such that the two mortality sources together arehypothesised to be the primary drivers of the decline in blacktip (C. limbatus)and sandbar sharks (C. plumbeus) (Baum and Myers, 2004; Cortes et al., 2002;Musick et al., 1993; Shepherd and Myers, 2005) (Fig. 4.5).

Other types of recreational fishing can also reduce chondrichthyanspecies abundance. For example, the recreational spearfishing of greynurse sharks (Carcharias taurus) during the 1960s and 1970s on the eastcoast of Australia (Fig. 4.5) contributed to a large decline in populationsize, leading to legislation for protection in 1984 (Pollard, 1996). Today, thisspecies is fully protected throughout Australia, although concerns regardingtheir future still remain (Environment Australia, 2002; Otway and Burke,2004; Otway et al., 2004).


Another concern is that recreational fishing usually takes place in inshorewaters, close to coasts and in bays, estuaries and rivers. These areas have beenidentified as important habitats for many chondrichthyans, especially forbreeding, pupping or nursery areas (Stevens et al., 2000, 2005). Recreationalfishing often affects juveniles more than adults. Indeed, recreational fishers inTasmania (Fig. 4.5)were responsible for declines in gummy and school sharksin the 1960s and 1970s by gillnetting in nursery areas (Williams and Schaap,1992). In recent years, however, growing emphasis on catch and live release ishoped to reduce the negative impacts of recreational fishing on many sharkspecies, while also providing important scientific information for effectivespecies management (Stevens et al., 2000).

3.2. Beach meshing

Shark attacks worldwide are rare (Stevens et al., 2005). However, at beacheswhere attacks were historically common, authorities in Australia and SouthAfrica continue to protect swimmers by setting dedicated shark nets anddrum-lines (Burgess and Simpfendorfer, 2005). In response to a number ofunprovoked shark attacks in Sydney Harbour, beach meshing programmesstarted in New SouthWales, Australia in 1937 using 50–60 cm gillnets. Thissuccess led to similar programmes in South Africa in 1952, Hawaii in 1959,Queensland in 1962, New Zealand in 1969 and Hong Kong in 1995(Burgess and Simpfendorfer, 2005).

These programmeshave generally been successful in reducing incidences ofshark attacks onhuman swimmers, although this has come at a cost. InAustraliaand South Africa, around 1500 and 1200 sharks, respectively, are caught eachyear. In general, catch rates in these programmes show a rapid initial decline,afterwhich they become stable, although there is considerable variation amongspecies and locations (Reid and Krogh, 1992; Simpfendorfer, 1992). It is alsothought that beach meshing has the greatest negative impact when deployedalong coastlines rather than around single beaches, increasing the overallprobability of capture while also serving to fragment habitat and disruptmigratory behaviour. Total catches are relatively small compared to fisherycatches, but beachmeshing is an important mortality source for small endemicpopulations. In Australia, a decline in grey nurse sharks is evident from beachmeshing figures: in New SouthWales grey nurse sharksmesh catches declinedfrom 19 individuals per month in 1937 (Coppleson, 1962), to 0.29 individualsper month between 1972 and 1990 (Krogh, 1994). Beach meshing and spear-fishingwere considered themain cultprits (Otway et al., 2004). Beachmeshingalso kills many harmless chondrichthyans; for example, the Queensland(Australia) beach-meshing programme caught 13,765 rays between 1962 and1988, and inNewSouthWales, 2074 rayswere caught between1972 and1990(Krogh and Reid, 1996).


3.3. Habitat loss

Chondrichthyans have evolved to fill many niches across a broad range ofhabitats (Compagno, 1990) and it is unlikely that they will be able to adaptquickly to human-induced changes in their environments (Cortes, 2002;Garcıa et al., 2008). Therefore, species with highly specialised life histories(e.g. ontogenetic spatial and cephalopod diet specialisation by Hemigaleusaustraliensis; Taylor and Bennett, 2008) and limited spatial or environmentalranges are predicted to be more at risk from habitat change. Habitatdegradation and loss alter the dynamics, distribution and possibly behaviourof its inhabitants. This includes both reduction in spatial extent of habitat(habitat loss) and the composition and interactions of the biological com-munities that rely on them (habitat degradation).

Habitat requirements can vary considerably over the different stages ofthe life cycle of species, so habitat loss and degradation can operate insidi-ously to reduce aspects of performance in terms of reproduction, dispersal orforaging ecology (Martinez et al., 2007; McMichael, 2001; Musick et al.,2000a). Most chondrichthyan species use some type of specific habitat forbreeding, shelter or feeding that can encompass everything from freshwaterrivers and lakes, shallow estuaries and coastal bays, to coral reefs, kelp forestsand the deep sea (Stevens et al., 2005). A number of species require shallowcoastal areas as nurseries protected from large predators and inclementenvironmental conditions. Juveniles can remain in these areas during theirearly development to maximise survival. As such, the loss of estuarine andcoastal nursery habitats from the destruction of mangrove forests, aquacul-ture and other coastal developments can compromise the recruitment insome species. The continuing loss of these important habitats could exacer-bate the extinction risk of associated species in addition to direct threats ofover-harvest (Kinney and Simpfendorfer, 2009).

The effects of fishing itself can be far more wide-reaching than justremoval of individuals. Destructive fishing practices such as trawling anddynamite fishing change habitat structures by reducing substratum com-plexity and diversity. Some of these effects can be most detrimental fordeepwater species that tend to be adapted to relatively stable environments.Unfortunately, dedicated research examining effects of habitat loss anddegradation on shark populations has generally been lacking, with currentpredictions based largely on the expectation of chondrichthyans’ roles inecosystem function (see Section 5).

3.4. Pollution and non-indigenous species

Water pollution is a major problem that affects almost all freshwater andmarine environment habitats and ecosystems, and it can directly affectchondrichthyans through changes in water quality and habitat degradation.


There are four main types of pollutants: (1) those that affect the physicalproperties of the environment, (2) those that cause eutrophication, (3)poisons and (4) pathogens that can affect the health of an individual orinfluence community or ecosystem structure. Pollutants can even havemultiple effects, such as sewage effluent containing harmful toxins thatcause eutrophication leading to dissolved oxygen depletion (Pastorok andBilyard, 1985).

Pollutants that alter the physical properties of water and cause eutrophi-cation have greater effects on the ecosystems on which chondrichthyansrely, than on individuals directly. This is because sharks and rays aregenerally highly mobile animals that can remove themselves from harmfulsituations if required. However, endemic species or populations restricted tosmall regions might be at greater risk to broad-scale pollution events.Certain life stages can also be more sensitive to the effects of pollutionthan others, especially embryos or juveniles with higher metabolic rates thanadults. Chondrichthyans can bio-accumulate heavy metals such as mercury(Lyle, 1984; Walker, 1976, 1988; Watling et al., 1982), especially coastalspecies that live in shallow turbid environments where freshwater outflowmeets marine waters (e.g. Fairey et al., 1997). Bio-accumulation of otherpollutants can occur also, such as organic chemical compounds (Davis et al.,2002; Fisk et al., 2002; Gelsleichter et al., 2005; Storelli and Marcotrigiano,2001; Storelli et al., 2005). These metals and organic compounds can haveadverse effects on reproductive, immune, endocrine and nervous systems(Betka and Callard, 1999; Clarkson, 1994; Gelsleichter et al., 2005; Koller,1979; Scheuhammer, 1991). In male sharks, heavy metals such as cadmium(a known spermatotoxicant) have been observed in high concentrations insome species (Betka and Callard, 1999). In female bonnethead sharks(Sphyrna tiburo), exposure to organic compounds such as PCBs can reducefertility through disruption of the endocrine system (Gelsleichter et al., 2005).Although many chondrichthyans have been exposed to bio-accumulatingpollutants, their effects are still relatively unexplored.

Other sources of pollution include oil spills and leaks that can contami-nate tissues when ingested (Anonymous, 1993), flotsam and jetsam that cancompromise digestion or entrap individuals (Sazima et al., 2002), and ghostnetting (Stevens et al., 2005). Other types of environmental pollutioninclude increased thermal outflows and discharges, and disruption of naturalelectro-magnetic fields by generation of artificial fields around underseacables that can alter chondrichthyan behaviour because of their relianceon electro-magnetic sensory perception for foraging (Filer et al., 2008;Hoisington and Lowe, 2005; Walker, 2001).

A final primary source of marine pollution to consider is from ships’ballast water from large commercial vessels that travel worldwide, and cantransport non-indigenous marine species to new habitats (Drake et al.,2007; Elliott, 2003; Ruiz et al., 2000). There is little direct evidence that


non-indigenous species threaten chondrichthyans; however, increasinginvasions might erode the integrity of natural ecosystems upon whichchondrichthyans rely.

4. Chondrichthyan Extinction Risk

Given acceleration in species loss globally due mainly to human-mediated changes to the biosphere, there has been a growing interest inidentifying and ranking the species characteristics and environmental con-texts that could predict the proneness of species to extinction (Dulvy et al.,2003; McKinney, 1997; Pimm et al., 2006; Purvis et al., 2000a; Sodhi et al.,2008a,b). A capacity to predict species’ responses to threats based onintrinsic ecological, life history or environmental traits is important toimprove management efficiency and prioritise efforts to recover threatenedtaxa (Pimm et al., 2006; Sodhi et al., 2008b). For example, predictors of thepredisposition of species to extinction could be used for selecting potentiallysensitive taxa to monitor for early detection of population decline, enablingdecision makers to choose how best to allocate finite conservation andmanagement resources (Duncan and Young, 2000).

Current evidence supports the notion that particular combinations of lifehistory and ecological characteristics (organism size, dispersal capacity andnative geographic range) and other reproductive, dispersal, morphologicaland physiological attributes can influence a species’ proneness to extinction(Duncan and Young, 2000; Sodhi et al., 2008b), with the strength of effectoften depending on environmental context (Brook et al., 2008; Pimm et al.,2006; Sodhi et al., 2008a). Indeed, rare species tend to have lower repro-ductive effort and dispersal capacity and more restricted geographic rangesthan common species (Blackburn and Cassey, 2004; Kunin and Gaston,1993, 1997; Pocock et al., 2006). A population’s distribution will also affectits probability of extinction, especially over longer timescales. Widespreadspecies are generally more resilient to local environmental disturbances andecosystem changes because entire range-wide catastrophes become progres-sively less likely as a distribution increases (Brook et al., 2008). Fragmentedpopulations are also more vulnerable due to the loss of connectivitybetween subpopulations, reducing geneflow and resilience of the popula-tion to change (Caughley and Gunn, 1996; Dulvy et al., 2003; Saunderset al., 1991).

Species’ traits such as body size are closely correlated with other lifehistory attributes such as a geographic extent, potential fecundity, dispersalcapacity and niche breadth. Thus, the extinction risk of a species can beclassified based on the suite of characteristics that permit recovery fromover-harvesting or changes in the environment such as habitat loss.


Specialised life histories that suit narrow ecological niches can increase therisk of extinction by limiting the ability of the species to adapt rapidly tochange. Likewise, large body size tends to correlate positively with extinc-tion risk (Cardillo et al., 2005; Johnson, 2002; Olden et al., 2007), andhigher reproductive rates can increase capacity to recover from depletion(Purvis et al., 2000b).

4.1. Drivers of threat risk in chondrichthyans and teleosts

Marine species were once considered to have a lower risk of extinction thanterrestrial taxa due to the their longer presence in the fossil record (Culotta,1994; Norse, 1993), high relative fecundity and larger geographic ranges(Dulvy et al., 2003). However, this view is now contested (McKinney,1998). Despite recent debate on the number of marine fish that havebecome globally extinct (del Monte-Luna et al., 2007; Dulvy et al., 2003),the number is but a small fraction of the extant species. Dulvy et al. (2003)suggested that three species have become extinct within the human time-frame (New Zealand grayling Prototroctes oxyrhynchus, green wrasse Ana-mpses viridis, and Galapagos damsel Azurina eupalama), although del Monte-Luna et al. (2007) confirmed the loss of P. oxyrhynchus and A. viridis andprovided evidence for the debate over the believed loss of A. eupalama.Currently, only four species found in brackish and/or saltwater are listed onthe IUCN’s Red List as Extinct: the European sturgeon (Huso huso)and bastard sturgeon (Acipenser nudiventris) due to over-harvest, theNew Zealand grayling due to the release of introduced species, and theMadagascan lampeye (Pantanodon madagascariensis) due to habitat loss.There are, however, many species listed as currently experiencing localand regional declines, thus rendering them vulnerable to extinction.

Of all the larger marine taxa, chondrichthyans (sharks, rays and chi-maeras) are considered the most vulnerable to extinction because of theirtendency toward large size, slow growth and late maturation (Cortes, 2000;Garcıa et al., 2008). In fact, the number of chondrichthyan species that arelisted as either locally, regionally or globally extinct equals the total numberof teleost extinctions (Dulvy et al., 2003), but Red-Listed chondrichthyansoutnumber the total number of teleost species listed. This raises the ques-tions: are chondrichthyans at greater risk of extinction than teleosts orperhaps other marine taxa? If so, then what are the principal life historytraits that drive this difference? Do chondrichthyans simply represent ahigher proportion of listed species because of their high profile for protec-tion (Pimm et al., 2006)? Despite the repetition of their apparent greater riskin the literature (e.g. Baum et al., 2003; Camhi et al., 1998; Cortes, 2000;Myers and Worm, 2005; Robbins et al., 2006), there has been little, if any,direct qualitative or quantitative analysis of the available data to test theassertion.


With the understanding that there has not yet been a comprehensiveoverview and formal analysis of chondrichthyan threat risk relative toteleosts, we constructed a detailed analysis of the ecological, life historyand human-relationship data relative to the IUCN’s Red List categorisationfor extant chondrichthyans and teleosts. This includes classes Elasmobran-chii (sharks and rays), Holocephali (chimaeras), Actinopterygii (ray-finnedfishes) and Sarcopterygii (lobe-finned fishes) (Table 4.1). We excludedClasses Cephalaspidomorphi (lampreys) and Myxini (hagfishes) from allanalyses. Our main aim was to determine the primary drivers of threat riskfor each taxon and whether overall susceptibility differed between chon-drichthyans and teleosts.

4.2. Global distribution of threatened chondrichthyan taxa

To examine the spatial distribution of threatened Chondrichthyan speciesfrom marine and estuarine habitats in the IUCN Red List, we examined allpopulations listed as critically endangered, endangered and vulnerable(International Union for the Conservation of Nature and NaturalResources, 2008) using the websites www.iucnredlist.org and www.fishbase.org. From these, we plotted the approximate centroid of eachthreatened population’s distribution in latitude and longitude coordinates(0.5� precision). These data provide a map of the relative global distributionof threatened chondrichthyan populations from least (vulnerable) to most(critically endangered) threatened (Figs. 4.6 and 4.7). Generally, the central

Table 4.1 Summary of chondrichthyan [including Classes Elasmobranchii (sharksand rays) and Holocephali (chimaeras)] and teleost [including Classes Actinopterygii(ray-finned fishes) and Sarcopterygii (lobe-finned fishes)] species’ taxonomic sampledistribution

Class Orders Families Genera Species (marine) Analysed n

Chondrichthyans

Elasmobranchii 11 44 175 961 (937) 216–218

Holocephali 1 3 6 37 (37) 3–9

Total 12 47 181 998 (974) 219–227

Teleosts

Actinopterygii 45 468 4592 27,388 (15,397) 141–385

Sarcopterygii 3 4 4 11 (2) 1

Total 48 472 4596 27,399 (15,399) 142–386

Totals 60 519 4777 28,397 (16,373) 367–612

Total number of species is presented for all milieus and marine only. The final number of species analyseddepended on the particular set of attributes included in the model sets (see Tables 4.3 and 4.4), so samplesize ranges are shown.



http://www.fishbase.org


47

48

41

58

57

51

71

6137

27

21

3134

87

77

Vulnerable

Endangered

CriticallyEndangered

67

18

180�

70�

50�

30�

10�

10�

30�

50�

70�

160� 140� 120� 100� 80� 60� 40� 20� 0� 20� 40� 60� 80� 100� 120� 140� 160� 180�

81

88

Figure 4.6 Global distribution of IUCN Red-Listed threatened chondrichthyan species. Each dot represents the approximate centroidcoordinate (0.5� precision determined from cross-referencing data from www.iucnredlist.org and www.fishbase.org) for sub-populations of115 separate chondrichthyan species listed as vulnerable (light grey), endangered (mid-tone grey) or critically endangered (dark grey)according to the IUCN Red List (www.iucnredlist.org).




47

48

41

58

57

51

71

6137

27

21

3134

87

77Vulnerable

Endangered

CriticallyEndangered

67

18

180�

70�

50�

30�

10�Dipcol

TriacuMuswhi

Trimac

Dipgua

SphmokCarlim

CarlonNarbanCarobs

Carcar

DiplaeSquaca

Squaca

Rhityp

Carcar

SphtudPripecIsooxy

RhibraBenkreGalmin

SchsauAtlpla

SymacuZapbre

Distsc

BatalbBatgri

Dipchi

Lamnas

CarcarGalgal

Scyque

Sphmok

Dipcro

PripriUroukp

RhirhiRhylueRhicem

RhitypPsebre

Rhydji

CarleiRhityp

UroaspRhigra

RhiobtNebfer

Himflu

Squaca

SquacaPrimic

Mobmob

SphmokDasgar

OxycenCengra

RosalpCetmax

DipbatCensqu

CarcarGymalt

Cetmax

Rhifor

NarbreRhityp

AetzonCarbraRhyaus

UrojavRhitho

Carbor Rhityp

Pricla

HemhalDasflu

HemstrMylham Aulkan

Squmit

HetcolUrosufUrovir

UrobucGalgal

UrooraCartauRhityp

Lamnas

Aetnic

Rhylae

10�

30�

50�

70�

160� 140� 120� 100� 80� 60� 40� 20� 0� 20� 40� 60� 80� 100� 120� 140� 160� 180�

81

88

Figure 4.7 Global distribution of IUCN Red-Listed threatened chondrichthyan species (see Fig. 4.6 for details) with species labels: aetfla,Aetobatus flagellum; aetmac, Aetomylaeus maculatus; aetnic, Aetomylaeus nichofii; aetves, Aetomylaeus vespertilio; aetzon, Aetoplatea zonura; anocus,Anoxypristis cuspidata; atlcas, Atlantoraja castelnaui; atlcyc, Atlantoraja cyclophora; atlpla, Atlantoraja platana; aulkan, Aulohalaelurus kanakorum;batalb, Bathyraja albomaculata; batgri, Bathyraja griseocauda; benkre, Benthobatis kreffti; carbor, Carcharhinus borneensis; carbra, Carcharhinusbrachyurus; carcar, Carcharodon carcharias*; carhem, Carcharhinus hemiodon; carlei, Carcharhinus leiodon; carlim, Carcharhinus limbatus; carlon,Carcharhinus longimanus; carobs, Carcharhinus obscurus; carsig, Carcharhinus signatus; cartau, Carcharias taurus; cengra, Centrophorus granulosus;cenhar, Centrophorus harrissoni; censqu, Centrophorus squamosus; cetmax, Cetorhinus maximus; dasflu, Dasyatis fluviorum; dasgar, Dasyatisgarouaensis; daslao, Dasyatis laosensis; dipbat, Dipturus batis; dipchi, Dipturus chilensis; dipcol, Diplobatis colombiensis; dipcro, Dipturus.

distribution of threatened sharks covered much of the coastal regions ineastern North America, north-western and south-eastern South America,western Africa, Europe (including the Mediterranean), Indian Ocean, southand south-eastern Asia, and eastern Australia (Figs. 4.5 and 4.6). Obviousclusters of threatened species were found in five regions: (1) south-easternSouth America along the coasts of southern Brazil, Uruguay and Argentina;(2) western Europe and the Mediterranean; (3) western Africa; (4) SouthChina Sea and Southeast Asia and (5) south-eastern Australia. The highestconcentration of critically endangered species was in western Europe,western Africa and Southeast Asia (Figs. 4.5 and 4.6).

4.3. Ecological, life history and human-relationship attributes

For each species, we compiled attributes likely to contribute to the propen-sity to become threatened and by proxy, extinct (Brook et al., 2008; Garcıaet al., 2008; Olden et al., 2007; Sodhi et al., 2008b; Traill et al., 2007). Theseincluded information on size, fecundity, mode of fertilisation, longevity,age at maturity, geographic range, growth rates, natural mortality, migratorybehaviour, habitat, general temperature regime, salinity preference,

crosnieri; dipgua, Diplobatis guamachensis; diplae, Dipturus laevis; dipmen,Dipturus mennii;distsc, Discopyge tschudii; galgal, Galeorhinus galeus; galmin, Galeus mincaronei; glygan,Glyphis gangeticus; glygly,Glyphis glyphis; gurdor,Gurgesiella dorsalifera; gymalt,Gymnuraaltavela; hemhal, Hemiscyllium hallstromi; hemleu, Hemitriakis leucoperiptera; hemstr,Hemiscyllium strahani; hetcol, Heteroscyllium colcloughi; himcha, Himantura chaophraya;himflu, Himantura fluviatilis; himoxy, Himantura oxyrhyncha; himsig, Himantura signifer;isooxy, Isogomphodon oxyrhynchus; isupau, Isurus paucus; lamnas, Lamna nasus; leumel,Leucoraja melitensis; mobmob, Mobula mobular; musfas, Mustelus fasciatus; mussch, Mus-telus schmitti; muswhi, Mustelus whitneyi; mylham, Myliobatis hamlyni; narban, Narcinebancroftii; narbre, Narcine brevilabiata; nebfer, Nebrius ferrugineus; negacu, Negaprion acu-tidens; odofer, Odontaspis ferox; oxycen, Oxynotus centrina; pricla, Pristis clavata; primic,Pristis microdon; pripec, Pristis pectinata; priper, Pristis perotteti; pripri, Pristis pristis; prizij,Pristis zijsron; psebre, Pseudoginglymostoma brevicaudatum; rhianc, Rhina ancylostoma; rhi-bra, Rhinoptera brasiliensis; rhicem, Rhinobatos cemiculus; rhifor, Rhinobatos formosensis;rhigra, Rhinobatos granulatus; rhihor, Rhinobatos horkelii; rhijav, Rhinoptera javanica;rhiobt, Rhinobatos obtusus; rhirhi, Rhinobatos rhinobatos; rhitho, Rhinobatos thouin; rhityp,Rhincodon typus*; rhyaus, Rhynchobatus australiae; rhydji, Rhynchobatus djiddensis; rhylae,Rhynchobatus laevis; rhylue, Rhynchobatus luebberti; rosalb, Rostroraja alba; schsau, Schroe-derichthys saurisqualus; scyque, Scylliogaleus quecketti; sphmok, Sphyrna mokarran; sphtud,Sphyrna tudes; squaca, Squalus acanthias; squacu, Squatina aculeata; squarg, Squatinaargentina; squgug, Squatina guggenheim; squmit, Squalus mitsukurii; squocc, Squatinaocculta; squocu, Squatina oculata; squsqu, Squatina squatina; stefas, Stegostoma fasciatum;symacu, Sympterygia acuta; taemey, Taeniura meyeni; triacu, Triakis acutipinna; trimac,Triakis maculata; uroasp, Urogymnus asperrimus; urobuc, Urolophus bucculentus; urojav,Urolophus javanicus; uroora, Urolophus orarius; urosuf, Urolophus sufflavus; uroukp, Uro-gymnus ukpam; urovir, Urolophus viridis; zapbre, Zapteryx brevirostris; *, globaldistribution.


commercial importance, whether the species was a target of recreationalfishing, and if it was considered dangerous to humans (Table 4.2). Lifehistory and environmental data for 28,505 species of marine and estuarinefish were extracted from FishBase (Froese and Pauly, 2004). Where therewere data available for multiple populations per species, they were groupedby species, with mean, minimum and maximum values calculated for eachparameter. Species with aquaculture populations were excluded from thedata set. Complete data were missing for most species, so we examined onlythe most complete data to maximise the number of species considered in theanalyses. The final data set for analysis included the following terms:

Length (LNG). Extinction risk in many taxa has been linked to organismsize (Brook et al., 2008; Cardillo et al., 2005; Johnson, 2002; Olden et al.,2007; Purvis et al., 2000b; Raup, 1994; Sodhi et al., 2008a). Most lengthmeasurements were either ‘standard’ or ‘total length’, but we could notstandardise length measurements due to a lack of data on species-specificrelationships.

Range (RGE). Range extent is an important indicator of the propensityof a species to become threatened (Brook et al., 2008; Croci et al., 2007;Oborny et al., 2005; Pimm et al., 2006). This is because widespread speciestend to have a higher capacity to tolerate new environments given that theyhave already encountered a variety of climatic and habitat conditions intheir evolutionary history and acquired relatively high phenotypic plasticity(Croci et al., 2007). FishBase provides information on the number of FAOFisheries Areas occupied by a particular species. We initially considered thevariable as an ordinal integer, but due to high skewnesss, we re-classified thevariable into a three-level factor ([1] 1 FAO area, [2] 2 FAO areas, and [3]>2 FAO areas).

Habitat (HBT). The type of habitat occupied by a species can influenceits distribution given the variation in abiotic factors that dictate habitatdistributions (Garcıa et al., 2008). Species were categorised into one ofthree habitat classes: [1] demersal (including bathydemersal and demersal),[2] pelagic (including bathypelagic, benthopelagic and pelagic), or [3] reef-associated (around reefs from 0 to 200 m; Froese and Pauly, 2004).

Environmental temperature class (ETP). As a measure of latitudinal andbathymetric variation in the probability of being classed as threatened(Worm et al., 2005), we also included a three-level factor describing theprincipal temperature environment occupied by each species. Theseincluded [1] tropical (including subtropical and tropical), [2] temperate(including high-latitude or strictly temperate species) or [3] deep-water(see also Garcıa et al., 2008).

Commercial fisheries interest (CMI). We hypothesised that species wouldbe, on average, more likely to be classed as ‘threatened’ if targeted byfisheries (Pauly et al., 1998; Roberts, 2003; Roberts and Hawkins, 1999).We therefore classified each species with respect to its primary interest tofisheries: [1] of commercial interest, [2] of primarily artisanal interest


Table 4.2 Summary of marine fish (chond, chondrichthyan; teleo, teleost) species’ threat status (threatened, critically endangered,endangered or vulnerable; not threatened, least concern, lower risk, or near threatened) and ecological, life history and human-relationshipattributes with a list of the species frequency (available data) for the different category levels

Parameter

abbreviation Description Levels

n Marine species with data (%)

Chond Teleo

TH08 Threatened (IUCN, 2008) [0] No 246 (70) 212 (59)

[1] Yes 108 (30) 145 (41)

LNG Length Continuous (cm) 754 12,408

HBT Habitat [1] Demersal 756 (78) 7729 (50)

[2] Pelagic 111 (11) 3535 (23)

[3] Reef-associated 107 (11) 4135 (27)

ETP Environmental temperature [1] Deep water 374 (38) 3263 (21)

[2] Temperate 84 (9) 1936 (13)

[3] Tropical 516 (53) 10,198 (66)

RGE Range (FAO areas) [1] 1 395 (41) 6798 (44)

[2] 2 279 (29) 3830 (25)

[3] > 2 299 (30) 4751 (31)

CMI Commercial fishing [1] Artisanal 213 (41) 1569 (32)

[2] Commercial 128 (25) 1661 (34)

[3] No fishing interest 175 (34) 1636 (34)

GME Game fished? [0] No 869 (89) 14,590 (95)

[1] Yes 105 (11) 809 (5)

DGR Dangerous? [0] No 799 (82) 14,755 (96)

[1] Yes 175 (18) 619 (4)

WT Max. weight Continuous (g) 107 980

LGV Longevity Continuous (years) 33 510

FEC Max. fecundity Continuous

(eggs/female)

153 395

(continued )

Table 4.2 (continued)

Parameter

abbreviation Description Levels

n Marine species with data (%)

Chond Teleo

MTL Length maturity Length at min fecundity (cm) 3 150

MTA Age maturity Female minimum

age at maturity

38 165

LVB Max. asymptotic length Max. von Bertalanffy

length (L1)

2 94

GRT Growth Max. growth

constant (K)

2 94

MNT Natural mortality Max. natural mortality

rate (per year)

2 94

RMO Reproduction mode [1] Dioecism 855 (100) 2029 (83)

[2] Parthenogenesis 0 2 (0.8)

[3] Protandry 0 56 (2)

[4] Protogyny 0 312 (13)

[5] Hermaphroditism 0 42 (2)

FTM Fertilisation method [1] External 2 (0.2) 2007 (85)

[2] Brood pouch 0 46 (2)

[3] In mouth 0 6 (0.3)

[4] Oviduct 850 (>99) 291 (12)

[5] Other 0 4 (0.2)

MGR Migratory behaviour [1] Amphidromous 2 (4) 74 (4)

[2] Anadromous 0 129 (7)

[3] Catadromous 0 59 (3)

[4] Limnodromous 0 3 (0.2)

[5] Non-migratory 0 1111 (60)

[6] Oceanodromous 45 (96) 447 (24)

[7] Potamodromous 0 22 (1)

Parameters in boldface were included in the threat risk analysis (see Tables 4.3 and 4.4).

(including subsistence and minor commercial interest) or [3] no majorinterest. We hypothesised that species of commercial interest would havea higher threat risk than other categories.

Game fish (GME). Much like the justification for the impact of fisheriesinterest in a species, we had sufficient information to include whether aspecies was a targeted game fish. We hypothesised that game fishing wouldincrease the threat risk of a species (Robbins et al., 2006).

Dangerous (DGR). The perceived or real threat of danger to humans isthought to have been responsible for the depletion of many local popula-tions of sharks prior to the recognition of this taxon’s plight (Burgess andSimpfendorfer, 2005). We therefore classed each species as [1] dangerous(including high predation risk, toxic, venomous) or [0] harmless.

4.4. Threat risk analysis

Todetermine the relationships between the ecological, life history andhuman-relationship traits and the threat risk of the compiled species, we fitted general-ised linear mixed-effect models (GLMM) to the data using the lmer functionimplemented in the R Package V2.5 (R Development Core Team, 2009).For each GLMM, we coded species threat probability [i.e. IUCNRed-Listed(critically endangered, endangered or vulnerable) or not] as a binomialresponse variable and each trait as a linear predictor (fixed factors), assigningeach model a binomial error distribution and a logit link function. Weaccounted for potential spatial bias in listing probability (i.e. some regions ofthe Earth might receive greater species assessment scrutiny than others) byremoving all non-listed species or those listed as data deficient (InternationalUnion for the Conservation of Nature and Natural Resources, 2008)(cf. Olden et al., 2007). We also removed all species coded as extinct/extinctin thewild or those listed because of range restrictions (i.e. listed underCriteriaB, D2 or both). This latter category was removed to avoid circularity inassessing correlates of threat risk among taxa (e.g. Bradshaw et al., 2008;Sodhi et al., 2008a).

Species are phylogenetic units with shared evolutionary histories and arenot statistically independent (Felsenstein, 1985). We therefore decomposedthe variance across species by coding the GLMM random-effects errorstructure as a hierarchical taxonomic effect (Blackburn and Duncan, 2001).We had adequate replication to use the nested random effect of Order/Family, but insufficient replication at finer taxonomic resolution. Theamount of variance in threat probability captured by each model consideredwas assessed as the per cent deviance explained (%DE) in the binomialresponse, expressed relative to the deviance of a null model with no fixedeffects, but retaining the hierarchical random effect (Brook et al., 2006).

We constructed the model sets to reflect particular a priori hypotheses toidentify the most important drivers of threat risk in the IUCN-listed species


collated (Tables 4.3 and 4.4). We first split the modelling approach into twophases to examinedifferent aspects of the relationships: (1) Phase 1examined therelationship between threat risk (species coded as threatened or not threatened)and the four ecological and life history traits length, range, habitat and environ-mental temperature. Threatened species were those classed as criticallyendangered, endangered or vulnerable, with near threatened and least concerntaken as not threatened.We also considered a second set of models where nearthreatened species were removed from the not threatened group; results weresimilar although there was amoderate increase in the% deviance explained andmodel ranking (results not shown). No interactions were considered in thisphase. Combinations of these traits were constructed to produce seven models(Table 4.3A); (2) Phase 2 examined the influence between the threat responsevariable and the three human-relationship variables commercial fisheries inter-est, game-fished and dangerous, but also included the principal ecological andlife history traits identified in Phase 1 (see Table 4.3B and Section 4.2). Weapplied the same two-phase approach to all chondrichthyan and teleost species

Table 4.3 Generalised linear mixed-effect models used to examine the correlationbetween fish threat status (either for chondrichthyan or teleost species groupsseparately) and a set of ecological, life history and human-relationship attributes

Model No. Term combinations Analytical theme

(A) Phase 1 (P1): Ecology and life history

1 �LNG Allometry (body size)

2 �RGE Range

3 �LNG þ RGE Allometry þ range

4 �LNG þ RGE þ HBT Allometry þ range

þ habitat

5 �LNG þ RGE þ ETP Allometry þ range

þ temperature

6 � LNG þ RGE

þ HBT þ ETP

Saturated

7 �1 Null (intercept)

(B) Phase 2: Human relationship

1 � ½P1þ � � �� Supported Phase 1 terms

2 � ½P1þ � � �� þ CMI þCommercial fishing

interest

3 � ½P1þ � � �� þGME þGame fishing

4 � ½P1þ � � �� þ CMIþ GME þGeneral fishing interest

5 � ½P1þ � � �� þDGR þDanger to humans

6 � ½P1þ � � �� þ CMIþ GMEþDGR Saturated


Model combinations, derived a priori, represent particular analytical ‘themes’ grouping related traits. Termsinclude LNG, length; RGE, geographic range; HBT, habitat; ETP, environmental temperature class;CMI, commercial fishing interest; GME, game-fished; DGR, dangerous to humans (see also Table 4.2).


separately, and then added the fixed termGroup to test for different threat risksbetween the two taxonomic groups explicitly.Wealso considered theGroup�length interaction (Table 4.4) to examine whether the relationship betweenlength and threat risk differs between groups. We only considered species thatwere restricted to the marine environment.

We used an index of Kullback–Leibler (K–L) information loss, Akaike’sInformation Criterion corrected for small sample sizes (AICc), to assign

Table 4.4 Generalised linear mixed-effect models used to examine the correlationbetween fish threat status (for chondrichthyan and teleost species combined) and aset of ecological, life history and human-relationship attributes

Model

No. Term combinations Analytical theme

(A) Phase 1: Ecology and life history

1 �LNG Allometry

2 �LNG þ GRP Allometry þ group

3 �LNG þ GRP

þ (LNG � GRP)

Allometry þ group

interaction

4 �RGE Range

5 �RGE þ GRP Range þ group

6 �RGE þ GRP þ (RGE � GRP) Range þ group interaction

7 �LNG þ RGE þ GRP Allometry þ range

þ group

8 �LNG þ RGE þ HBT þ GRP Allometry þ range

þ habitat þ group

9 �LNG þ RGE þ ETPþ GRP Allometry þ range

þ temperatureþ group

10 �LNG þ RGE þ HBT þ ETP þGRP þ LNG þ RGE

þ HBT þ ETP þ GRP

Saturated


(B) Phase 2: Human relationship

1 � ½P1þ � � �� Supported Phase 1 terms

2 � ½P1þ � � �� þ CMI þCommercial fishing

interest

3 � ½P1þ � � �� þ GME þGame fishing

4 � ½P1þ � � �� þ CMIþ GME þGeneral fishing interest

5 � ½P1þ � � �� þDGR þDanger to humans

6 � ½P1þ � � �� þ CMIþ GMEþDGR Saturated


Model combinations, derived a priori, represent particular analytical ‘themes’ grouping related traits.Terms include LNG, length; GRP, taxonomic grouping (chondrichthyan or teleost); RGE, geographicrange; HBT, habitat; ETP, environmental temperature class; CMI, commercial fishing interest; GME,game-fished; DGR, dangerous to humans (see also Table 4.3).


relative strengths of evidence to the different competing models (Burnhamand Anderson, 2002) as well as the dimension-consistent Bayesian informa-tion criterion (BIC), an approximation of the Bayes factor given no informa-tive prior information on relative model support (Burnham and Anderson,2002). These indices of model parsimony identify the relative evidence ofmodel(s) from a set of candidatemodels. The relative likelihoods of candidatemodels were calculated using AICc and BIC weights (Burnham andAnderson, 2002), with the weight (wAICc and wBIC) of any particularmodel varying from 0 (no support) to 1 (complete support) relative to theentire model set. However, the K–L prior used to justify AICc weighting canfavour more complex models when sample sizes are large (Burnham andAnderson, 2004; Link and Barker, 2006). We therefore considered bothweightings for determining the contribution of the most important majorcorrelates of extinction risk and to identify any weak tapering effects(Burnham and Anderson, 2004; Link and Barker, 2006).

4.5. Modelling results

We compiled data for a total of 28,397 fish species (998 chondrichthyans;27,399 teleosts); however, specific ecological, life history and human-rela-tionship data were missing for most species (see Table 4.1). Of the species inthe database, 525 (52%) chondrichthyan and only 2,272 (8%) teleost specieswere Red-Listed (see also Table 4.1), so subsequent threat-risk analyseswere limited in sample size (Tables 4.5–4.7). Of the listed species, 518 wereclassed as data deficient (175 chondrichthyans; 343 teleosts). Excluded fromthe analyses were the 99 species that were classed as extinct/extinct in thewild (all teleosts).

The distribution of species among the IUCN categories revealed agenerally higher threat risk for teleosts than sharks (Fig. 4.8). Ordering thecategories from least concern through to extinct/extinct in the wild (i.e.from lowest to highest risk categories) shows a biased distribution for theproportion of teleost species in the higher-risk categories (i.e. to the right ofFig. 4.8) compared to chondrichthyans, but a similar proportion of leastconcern species in both taxonomic groups. Of the IUCN Red-Listedspecies, there is a higher proportion of data-deficient species among thechondrichthyans (Fig. 4.8).

The principal correlates of threat risk in the Red-Listed species generallysupport what is known for many other taxa, but the drivers of risk differedbetween chondrichthyans and teleosts. Our exploration first revealed thatmarine species for which there was information available on threat risk,there was only evidence for weak correlation (Spearman’s �) among attri-butes considered. The maximum jrj was 0.445 between length and range forlisted chondrichthyans, and 0.500 between game fish and habitat for listedteleosts. We are thus confident that the results of our GLMMs were not


unduly biased. For chondrichthyans, threat risk was correlated principallywith body length (larger species are more threatened), accounting for 0.61 ofthe AICc weight in the Phase 1 analysis; however, this attribute accountedfor only 3.9% of the deviance explained (%DE) after taking taxonomy(phylogeny) into account (Table 4.5A). There was also weak support for asmall effect of range on threat risk (decreasing threat with increasing range;Table 4.5A; Fig. 4.9A), so we included these two terms into the Phase2 model set as ‘control’ variables. Although there was some wAICc supportfor the models including environmental temperature and habitat (Table 4.5 Aand B), model predictions appeared to support the idea that reef-associatedand deep-water chondrichthyans had lower threat risk (Fig. 4.9A). ThePhase 2 analysis for chondrichthyans examining whether human-relation-ship attributes further influenced threat risk revealed that the term dangerous

Table 4.5 Correlates of marine chondrichthyan threat risk

Model k LL DBIC wBIC DAICc wAICc %DE

(A) Phase 1

�LNG 4 �112.228 0.000 0.860 0.000 0.614 3.9

�LNGþRGE 6 �111.400 9.094 0.009 2.556 0.171 4.6

�LNGþRGE

þETP

8 �110.124 17.292 <0.001 4.297 0.072 5.7

�LNGþRGE

þHBT

8 �110.126 17.296 <0.001 4.301 0.072 5.7

�LNGþRGE

þHBTþETP

10 �108.306 24.407 <0.001 5.039 0.049 7.3

(B) Phase 2

�LNGþRGE 6 �119.625 2.182 0.238 0.000 0.387 5.5

�LNGþRGE

þDGR

7 �118.866 6.067 0.034 0.615 0.284 6.1

�LNGþRGE

þGME

7 �119.474 7.283 0.019 1.831 0.155 5.7

�LNGþRGE

þCMI

8 �118.828 11.394 0.002 2.692 0.101 6.2

�LNGþRGE

þCMIþGME

9 �118.742 16.624 <0.001 4.692 0.037 6.2

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecologicaland life history correlates and (B) Phase 2: human-relationship attributes, after accounting for the effectsof length and range (n = 216 species). Models include nested (hierarchical) taxonomic (order/family)random intercepts. Models are ranked according to the small-sample Akaike’s Information Criterion(AICc). Terms shown are LNG = length, RGE = range, HBT = habitat, ETP = environmentaltemperature, CMI = commercial fisheries interest, GME = status as game fish, DGR = danger tohumans. Also shown are number of parameters (k), maximum log-likelihood (LL), difference in theBayesian Information Criterion (BIC) and AICc for each model from the most parsimonious model(DBIC, DAICc), model weight (wBIC, wAICc), and per cent deviance explained (%DE) in the responsevariable (threat probability) by the model under consideration.


(whether a species was considered potentially harmful to humans) had somesupport (Table 4.5B; Fig. 4.10C)—contrary to expectation, potentiallyharmful sharks had a lower threat risk than harmless species (Fig. 4.10C).

For marine teleosts, length again was positively related to threat risk butaccounted for only 6.1% of the deviance in the response (Table 4.6A). Theaddition of range improved model fit, raising %DE to 11.9% (Table 4.6A).Environmental temperature and habitat also received high support (Table 4.6A),

Table 4.6 Correlates of marine teleost threat risk


(A) Phase 1

�LNGþRGE

þETP

8 �96.069 6.099 0.033 0.000 0.357 14.0

�LNGþRGE 6 �98.449 0.000 0.692 0.482 0.280 11.9

�LNGþRGE

þHBT

8 �96.483 6.928 0.022 0.829 0.236 13.6

�LNGþRGE

þHBTþETP

10 �94.953 14.727 <0.001 2.125 0.123 15.0

�LNG 4 �104.907 2.057 0.247 9.197 0.004 6.1

(B) Phase 2

�LNGþRGE

þETPþHBT

10 �94.953 4.471 0.095 0.000 0.447 15.0

�LNGþRGE

þETPþHBT

þGME

11 �94.690 9.374 0.008 1.682 0.193 15.2

�LNGþRGE

þETPþHBT

þDGR

11 �94.916 9.825 0.007 2.134 0.154 15.0

�LNGþRGE

þETPþHBT

þCMI

12 �94.059 13.540 0.001 2.648 0.119 15.8

�LNGþRGE

þETPþHBT

þCMIþGME

13 �93.491 17.927 <0.001 3.856 0.065 16.3

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecologicaland life history correlates and (B) Phase 2: human-realationship attributes, after accounting for the effectsof length and range (n = 228 species). Models include nested (hierarchical) taxonomic (order/family)random intercepts. Models are ranked according to the small-sample Akaike’s information criterion(AICc). Terms shown are LNG = length, RGE = range, HBT = habitat, ETP = environmentaltemperature, CMI = commercial fisheries interest, GME = status as game fish, DGR = danger tohumans. Also shown are number of parameters (k), maximum log-likelihood (LL), difference in theBayesian Information Criterion (BIC) and AICc for each model from the most parsimonious model(DBIC, DAICc), model weight (wBIC, wAICc), and per cent deviance explained (%DE) in the responsevariable (threat probability) by the model under consideration.


with lower risk predicted for pelagic and higher risk for deepwater species(Fig. 4.9B and C). Including length, range, habitat and environmental tem-perature in the Phase 2 models, teleosts demonstrated little response to any ofthe human-relationship attributes considered (Table 4.6B; Fig. 4.10). Com-bining the two taxonomic groups (marine species only) and setting theGroup

Table 4.7 Correlates of marine chondrichthyan and teleost threat risk


(A) Phase 1

�LNGþRGE

þETPþGRP

9 �210.160 8.870 0.005 0.000 0.456 8.4

�LNGþRGE

þGRP

7 �212.349 1.056 0.246 0.219 0.409 7.4

�LNGþRGE

þHBTþETP

þGRP

11 �210.000 20.740 <0.001 3.875 0.066 8.5

�LNGþRGE

þHBTþGRP

9 �212.336 13.223 0.001 4.352 0.052 7.5

�LNGþGRP 5 �217.917 0.000 0.417 7.235 0.012 5.0

(B) Phase 2

�LNGþRGE

þETPþGRP

9 �210.160 0.000 0.654 0.000 0.378 8.4

�LNGþRGE

þETPþGRP

þGME

10 �209.509 4.793 0.060 0.791 0.254 8.7

�LNGþRGE

þETPþGRP

þDGR

10 �209.968 5.711 0.038 1.709 0.161 8.5

�LNGþRGE

þETPþGRP

þCMI

11 �209.352 10.574 0.003 2.579 0.104 8.8

�LNGþRGE

þETPþGRP

þCMIþGME

12 �209.624 5.132 0.059 2.209 0.117 9.1

The five most parsimonious generalised linear mixed-effect models investigating (A) Phase 1: ecologicaland life history correlates and (B) Phase 2: human-relationship attributes, after accounting for the effectsof length and range (n = 444 species). Models include nested (hierarchical) taxonomic (order/family)random intercepts. Models are ranked according to the small-sample Akaike’s information criterion(AICc). Terms shown are GRP = taxonomic group chondrichthyan or teleost), LNG = length, RGE =range, HBT = habitat, ETP = environmental temperature, CMI = commercial fisheries interest,GME = status as game fish, DGR = danger to humans. Also shown are number of parameters (k),maximum log-likelihood (LL), difference in the Bayesian Information Critertion (BIC) and AICc foreach model from the most parsimonious model (DBIC, DAICc), model weight (wBIC, wAICc), and percent deviance explained (%DE) in the response variable (threat probability) by the model underconsideration.


0

100

200

300

400

500

600

700

800

ChondrichthyansTeleosts

Num

ber

of s

peci

es li

sted

DD LCLR/lc

LR/cdLR/nt NT VU EN CR

EX/EW

DD LCLR/lc

LR/cdLR/nt NT VU EN CR

EX/EW

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

IUCN category (2007)

Pro

port

ion

of to

tal s

peci

es li

sted

Figure 4.8 Frequency distribution (top panel: number of species; bottom panel:proportion of species listed per taxonomic group) of chondrichthyans (Classes Elasmo-branchii and Holocephalii) and teleosts (Classes Actinopterygii and Sarcopterygii) inthe 2008World Conservation Union’s (IUCN) Red List (www.iucnredlist.org). Cate-gories are ordered left to right from least threatened to most threatened. DD, datadeficient; LC, least concern; LR/lc, lower risk/least concern; LR/cd, lower risk/conservation dependent; LR/nt, lower risk/near threatened; NT, near threatened;VU, vulnerable; EN, endangered; CR, critically endangered; EX/EW, extinct/extinctin the wild.



1 FAO area 2 FAO areasRange

>2 FAO areas0.0

0.1

0.2

0.3

0.4

0.5 ChondrichthiansTeleosts

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

Demersal PelagicHabitat

Reef0.0

0.1

0.2

0.3

0.4

0.5

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

Deep water Temperate Tropical0.0

0.1

0.2

0.3

0.4

0.5

Environmental temperature regime

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

A

C

B

Figure 4.9 Phase 1 predicted threat risk of IUCN Red-Listed marine chondrichthyan(Classes Elasmobranchii and Holocephalii) and teleost (Classes Actinopterygii andSarcopterygii) based on generalised linear mixed-effect models that account for phylo-genetic relatedness among species (nested random effect ¼ order/family). Risks arepredicted as a probability between 0 and 1 relative to the different levels of the three


term as a fixed effect revealed important support for taxonomic group evenafter accounting for length (Table 4.7A). This demonstrates that teleosts have agenerally higher threat risk than chondrichthyans even after accounting for sizedifferences, although the effect is weak (Table 4.7B).

4.6. Relative threat risk of chondrichthyans and teleosts

Our quantitative threat risk analysis revealed some important insights intothe relative threat risk of the major marine fish taxa, some of which canappear somewhat counter-intuitive. Of particular importance was thefinding that listed teleosts are in general placed more frequently into thehigher-risk categories of the IUCN Red List relative to chondrichthyans.However, this is not because the relatively few listed teleosts just happen tobe larger-species. Indeed, Red-Listed teleosts were in fact smaller on aver-age than the distribution of all teleosts for which length data were available(Fig. 4.11).

The relatively higher threat risk of teleosts compared to chondrichthyanscould be misleading, however, if not properly contextualised. Of foremostimportance is that only a small proportion of all marine teleosts have beendescribed adequately for a reliable Red Listing (�8%), whereas >52% of allknown chondrichthyan species have been Red Listed, although manyadmittedly are placed within the data-deficient category. Therefore, extra-polating true threat risk to the entire marine teleost taxon from the smalldata set described here is potentially unreliable. Another possible bias is thatbecause of their generally larger size, their stigma in the public eye, and therecent attention brought to the conservation literature regarding theirapparently high threat risk, there might be a tendency to list chondrichthyanspecies at least within the lower threat-risk categories following the precau-tionary principle.

We also found reasonable evidence that disparities in relative threat riskbetween the two groups did not arise solely from the different size distribu-tions; sharks are approximately one order of magnitude larger on average

ecological and life history trait factors considered: range (number of FAO FishingAreas – www.fao.org), habitat and environmental temperature regime. See text for fulldetails. The observed threat probability 95% confidence intervals (chondrichthyans:dotted horizontal lines; teleosts: solid horizontal lines) were determined by a 10,000-iteration bootstrap of the probabilities predicted by the saturated model over 216(chondrichthyan) and 228 (teleost) species. Changes to extinction probability relativeto each term level were calculated by adjusting the original dataset so that all specieswere given the same value for that level (each level value in turn), keeping all otherterms in the model as in the original dataset. Error bars represent the 10,000 iteration-bootstrapped upper 95% confidence limits.


http://www.fao.org

Artisinal CommercialFisheries interest

No fisheries0.0

0.1

0.2

0.3

0.4

0.5 ChondrichthiansTeleosts

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

Yes No0.0

0.1

0.2

0.3

0.4

0.5

Game fishing

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

Yes No0.0

0.1

0.2

0.3

0.4

0.5

Dangerous species

Pr(

thre

at fo

r IU

CN

Red

-Lis

ted

spec

ies)

A

C

B

Figure 4.10 Phase 2 predicted threat risk of IUCNRed-Listed marine chondrichthyan(Classes Elasmobranchii and Holocephalii) and teleost (Classes Actinopterygii andSarcopterygii) based on generalised linear mixed-effect models that account for phylo-genetic relatedness among species (nested random effect ¼ order/family). Risks arepredicted as a probability between 0 and 1 relative to the different levels of thethree human-relationship factors considered: fisheries interest, whether a species was


than teleosts (Fig. 4.11). Indeed, even after accounting for the positiveinfluence of size (length) on threat risk, teleosts were still more likely thanchondrichthyans to be classified as threatened. However, we found noevidence for an interaction between Group and the allometry of threatrisk, suggesting that the reason for an average higher susceptibility rankingamong the teleosts is due to inherently different extinction pronenessbetween the two groups. While sharks might not have necessarily experi-enced the same magnitude of deterministic decline as Red-Listed teleosts(the declining population paradigm), their larger size and lower fecundity(the latter not included in the analysis) could indeed predispose the taxon toa higher risk of extinction overall (the small population paradigm) (Brooket al., 2006, 2008; Caughley, 1994; Traill et al., 2007).

Another important consideration is that total chondrichthyan species rich-ness is considerably lower than for teleosts. Indeed, there are nearly 30 timesmore teleost species listed in FishBase than chondrichthyans (Table 4.1). Thisimplies that the relative effect of extinction on total chondrichthyan speciesdiversity is considerably higher than the loss of a single species on teleostdiversity. This alone could be argued as sufficient justification to considerchondrichthyans as a special case for marine fishes, although it does not negatethe obvious conclusion that there are insufficient data for teleosts to makestrong inference regarding the true threat risk of that taxon.

5. Implications of Chondrichthyan

Species Loss on Ecosystem Structure,

Function and Stability

5.1. Ecosystem roles of predators

The loss of a single species is an evolutionary tragedy in its own right;however, when species loss triggers the degradation of entire biologicalcommunities, the importance of their conservation increases. There is nowa rich body of evidence and theory demonstrating how predators of allmajor trophic levels influence the ecosystems in which they live (Baum and

game-fished and whether a species was considered dangerous to humans. See text forfull details. The observed threat probability 95% confidence intervals (chondrichthyans:dotted horizontal lines; teleosts: solid horizontal lines) were determined by a 10,000-iteration bootstrap of the probabilities predicted by the saturated model over 216(chondrichthyan) and 228 (teleost) species. Changes to extinction probability relativeto each term level were calculated by adjusting the original dataset so that all specieswere given the same value for that level (each level value in turn), keeping all otherterms in the model as in the original dataset. Error bars represent the 10,000 iteration-bootstrapped upper 95% confidence limits.


0.0 0.5 1.0 1.5 2.0 2.5 3.00.0

0.3

0.6

0.9

1.2

1.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0All chondrichthyansAll teleostsRed-listed chondrichthyansRed-listed teleosts

log10 length (cm)

log10 weight (g)

Den

sity

Density (IU

CN

red-listed species)

0.4 1.4 2.4 3.4 4.4 5.4 6.4 7.40.0

0.1

0.2

0.3

0.4

0.5

0.6

Den

sity

0 1 2 3 4 5 6 7 80.0

0.2

0.4

0.6

0.8

1.0

log10 maximum fecundity (eggs/female)

Den

sity

Figure 4.11 Distribution of life history traits between chondrichthyans (Classes Elas-mobranchii and Holocephalii) and teleosts (Classes Actinopterygii and Sarcopterygii).Top panel: density distribution of log10-transformed body length (cm), showing allspecies and only the IUCN Red-Listed species for each taxon used in the threat-riskanalyses. Middle panel: density distribution of log10-transformed body weight (g).Bottom panel: density distribution of log10-transformed fecundity (eggs/female).


Worm, 2009). Most pertinent is the suite of processes known as trophiccascades which are defined as ‘reciprocal predator–prey effects that alter theabundance, biomass or productivity of a population, community or trophiclevel across more than one link in a food web’ (Pace et al., 1999). Thisconcept has been further simplified into two discrete categories knownpopularly as ‘top-down’ or ‘bottom-up’ control. Top-down control is atrophic cascade where lower food-web component species are regulated byan upper-level predator, whereas, in contrast, ‘bottom-up’ control is theregulation of food-web components by primary producers or the input oflimiting resources into a system (Pace et al., 1999). Although a system candemonstrate a predominant type of trophic cascade, many ecosystemsdemonstrate elements of both bottom-up and top-down control (Paceet al., 1999).

There are many examples of terrestrial trophic cascades, although mostof the empirical evidence and theory has been garnered from lakes, streamsand intertidal zones (Pace et al., 1999). Examples range from killer whalesregulating kelp forest growth via predation on otters and the subsequentincrease in herbivorous sea urchins (see more detail in Section 5.2), tomosquitoes affecting protozoan abundance that changes bacteria composi-tion in pitcher plants (see Pace et al., 1999 for a review). The main way inwhich predators tend to propagate indirect effects down trophic webs is bydirectly altering the numerical abundance of herbivores, but predators canalso modify herbivore foraging behaviour in response to variation in per-ceived predation risk (Schmitz et al., 2004). Indeed, there is evidence thatshifting predation risk in the presence of different predator types affects plantcommunity composition, leading to changes in net primary production andnutrient cycling (Schmitz, 2003, 2008; Schmitz et al., 2004).

The loss of predators in many ecosystems reduces species richness,leading to reduced community stability, lower productivity and nutrientcycling (Duffy, 2006; Schmitz, 2008; Schmitz et al., 2000; Stachowicz et al.,2007; Worm et al., 2006) (Fig. 4.12). This in turn reduces ecosystemresilience to stochastic perturbations that operate independently of commu-nity structure or species abundance (such as severe El Nino events, intensestorms and tsunamis) (Hughes et al., 2005). Such changes in communitystructure are thought to arise through direct reduction in predator abun-dance that leads to cascading trophic imbalances and re-equilibration to newstable states (see Scheffer et al., 2001). These situations of ‘predator release’of prey usually change the foraging capacity (such as increased herbivore ormeso-predator survival rates) and alter foraging behaviour (O’Connor andBruno, 2007). The subsequent decline in plant biomass through increasedgrazing pressure depends on the strength and number of linkages in aparticular food web (Halaj and Wise, 2001; Polis and Strong, 1996).Therefore, the strength of top-down effects of predator reduction and losswill vary between ecosystems with the complexity of food webs, and


compensation can occur where changes in the upper trophic levels do notnecessarily impact lower levels (Pace et al., 1999). Furthermore, ecosystemchanges can arise from the different functions of a predator species wherethere is niche partitioning of age and life-cycle stages (Bolnick et al., 2003;Field et al., 2005; Pace et al., 1999; Polis, 1984; Schmitz et al., 2004; Taylorand Bennett, 2008).

5.2. Predator loss in the marine realm

Worldwide, there is much concern regarding changes seen in marineenvironments through observed shifts in ecosystem composition and thesubsequent loss of resources and ecosystem services (Hughes et al., 2005;Shurin et al., 2002; Worm et al., 2006). Although the effects of marinepredator loss in marine systems is difficult to quantify given the clandestinelifestyle of many large predators (Bradshaw, 2007), there is growing empir-ical evidence describing the role of predatory species in modulating trophiccascades and top-down control across a range of marine ecosystems(Bascompte et al., 2005; Bruno and O’Connor, 2005; Byrnes et al., 2006;Duffy, 2006; Dulvy et al., 2004b; Frank et al., 2005, 2007; Hughes et al.,

• High diversity• High structural complexity• High fish production• High water clarity• High sediment stability• High resilience

• Low diversity• Low structural complexity• Low fish production• Low water clarity• Low sediment stability• Low resilience

Eutrophication

Overfishing

Benthic HabitatDisturbance

Figure 4.12 An example of how predator removal and other human-mediatedchanges to marine ecosystems reduce species richness, habitat structure and ecosystemfunction. Here, over-fishing of higher fish predators, eutrophication and benthic habitatdisturbance all lead to a depauperate biological community in this seagrass ecosystem(reproduced with permission from Duffy, 2006).


2005, 2007; Jennings and Kaiser, 1998; O’Connor and Bruno, 2007;Osterblom et al., 2006). However, the true function of large marine pre-dators and the potential implications of their loss is still not clearly under-stood for most ecosystems (Bruno and O’Connor, 2005).

A good example of a marine trophic cascade is the top-down control ofkelp (Macrocystis spp.) forests by sea otters (Enhydra lutris) and other predators(Byrnes et al., 2006; Estes et al., 1998). In western Alaska, sea otter popula-tions transformed nearshore reefs from two- to three-trophic level systemsby limiting the distribution and abundance of herbivorous sea urchins,thereby promoting kelp forest development (Estes et al., 1998). Manyotter populations are now in abrupt decline over large areas due to increasedkiller whale predation. This has reduced predation rates by otters on seaurchins, leading to higher urchin densities and greater deforestation of kelpbeds. Other predators influence these trophic cascades in kelp forests whereotters are absent. Byrnes et al. (2006) showed that crabs (Cancer productus andCancer magister) and starfish (Pycnopodia helianthoides) play a large role inmaintaining kelp forest biomass by regulating herbivore numbers includingthe snails Tegula brunnea and Tegula funebralis, urchins Strongylocentrotuspurpuratus and Strongylocentrotus franciscanus, and a crab Pugettia producta.Although no evidence for direct links between predator and prey densitieswas found, changes in kelp mass were related to changes in herbivoreforaging behaviour with relative predation risks. Similar effects have beenseen in seagrass communities (Byrnes et al., 2006; Duffy, 2006). Predator-induced changes have also been described for other coastal ecosystemswhere carnivorous fishes (such as blennies Hypleurochilus geminatus andHypsoblennius hentzi, killifish Fundulus heteroclitus and pinfish Lagodon rhom-boides) have regulated numbers of herbivores that control algal diversity andbiomass (Bruno and O’Connor, 2005; O’Connor and Bruno, 2007).

Another example documented in the Caribbean, Indian and westernPacific Oceans is the change of coral reef ecosystems tomacroalgal-dominatedcommunities (Dulvy et al., 2004b; Hughes et al., 2003, 2005, 2007; Pinnegaret al., 2000; Rogers and Beets, 2001). These are often complex systems withfeedback loops through mechanisms such as nutrient cycling (McClanahan,1997) and Allee population effects (Dulvy et al., 2004b).

In continental-shelf and open-ocean ecosystems, trophic cascades orchanges in fish community structure (Frank et al., 2005; Hughes et al.,2005; Levin et al., 2006; Link and Garrison, 2002; Mangel and Levin,2005; Osterblom et al., 2006; Shiomoto et al., 1997) can occur, althoughthere is some debate (see Frank et al., 2007; Parsons, 1992; Reid et al.,2000). Trophic changes have been noted in relatively simple systems likethe Barents Sea where top-down and size-selective predation by fish haveinfluenced zooplankton composition and abundance (Reid et al., 2000), andin the North Pacific for salmon predation on zooplankton altering theabundance of phytoplankton (Shiomoto et al., 1997). Until recently,


however, continental-shelf ecosystems were thought to be largely immuneto top-down control because of their relatively wide-distribution, highspecies diversity and food web complexity (Steele, 1998). Currently, it isthought that these can affect elements of the trophic web or the entireecosystem (Frank et al., 2005) as a combination of top-down and bottom-upprocesses. This has resulted in predator replacement, increased productionat lower trophic levels and/or long-term ecosystem-level change (Franket al., 2007). Furthermore, these long-term ecosystem changes might beresponsible for the slow or failed recovery many previously exploited fishpopulations (Hutchings, 2000; Shelton et al., 2005; Worm and Myers,2003).

5.3. Ecosystem roles of chondrichthyans

Chondrichthyans are generally apex predators, so predicting the effects of theirremoval are complex. As with other large species of predatory fishes, not onlydoes their removal release prey populations from a major mortality source, thereduction in predators can sometimes have unexpected second- and third-degree implications for non-prey species through trophic linkages (Baum andWorm, 2009; Schindler et al., 2002; Stevens et al., 2000) that can in turn affectecosystem functions (Worm et al., 2006). The role of sharks in maintainingdiversity and ecosystem structure are virtually unexplored (Camhi et al., 1998).Although there have been many diet studies (e.g. Bethea et al., 2006; Ellis andMusick, 2007; Estrada et al., 2006; Huveneers et al., 2007; Polo-Silva et al.,2007; Saidi et al., 2007; Simpfendorfer et al., 2001; Stevens andWiley, 1986),only a few recent studies have explored the role of chondrichthyan predators inecosystem structuring, and most have focused on species or ecosystems ofeconomic importance (Kitchell et al., 2002; Stevens et al., 2000).

Ecosystem modelling using ECOPATH/ECOSIM models (Walterset al., 1997) predicted the effects of top-predator removal on many ecosys-tems, with varying results (Kitchell et al., 2002; Stevens et al., 2000). Stevenset al. (2000) modelled these effects in three environments: a tropical shelfecosystem in Venezuela, a Hawaiian coral reef and a North Pacific oceanicecosystem. This comparison of a broad range of ecosystems, each domi-nated by a different functional group of sharks, demonstrated differentoutcomes when predators were reduced or removed, but predictionswere imprecise. Each model showed that some relatively minor prey speciesfor the sharks in each system underwent large increases in biomass aftershark removal. For example, turtles and reef sharks following reductions oftiger sharks in Hawaii; seals in the North Pacific following the removal ofsalmon sharks, and croakers (e.g. Plagioscion spp.) in Venezuela following theremoval of small triakid sharks, principally the smooth dogfishMustelus canis.In contrast, some seemingly important prey groups decreased in biomass. Inthe North Pacific and Venezuelan systems, at least one non-shark prey


group decreased in abundance, most likely as a result of complex trophicinteractions. The main conclusion was that the effects of shark reductionsacross ecosystems are often difficult to foresee, but might be ecologically andeconomically important and persist over long periods of time.

Another ECOPATH/ECOSIM modelling exercise examined thepotential role of sharks and longline fisheries on pelagic ecosystems in thecentral North Pacific. Kitchell et al. (2002) evaluated changes in trophicinteractions for the central Pacific Ocean and showed that the removal ofblue sharks produced compensatory responses favouring other shark speciesand billfishes, and that their removal had only modest effects on the majorityof species. However, intra- and inter-specific predation on juvenile elasmo-branchs produced strong, non-linear declines in shark populations. Overall,the model revealed that blue sharks in this system are not ‘keystone’ pre-dators, although if more sharks are removed by longline fisheries, food webswere predicted to degrade.

One of the first studies to identify predatory release of elasmobranchmesopredators was in the Gulf of Mexico where coastal shrimp fishingcaused by-catch population declines of over 95% in bonnethead sharks(S. tiburo), Bancroft’s numbfish (Narcine bancroftii) and smooth butterfly ray(Gymnura micrura) (Shepherd and Myers, 2005). Combined with fishingreductions in other large shark species in the pelagic longline fishery (Baumet al., 2003), increases in deeper water elasmobranchs such as Atlantic angelsharks (Squatina dumeril) and smooth dogfish (M. canis) were observed.

Open-ocean ecosystemshavebeen consideredmore resilent topredator loss(Steele, 1998), although changes in both the size of shark catches and speciescomposition have been described in the Pacific Ocean (Ward and Myers,2005). Removal of individuals from larger species, for example, blue, silkyand thresher sharks, black marlin (Makaira nigricans) and blue marlin(Makaira indica), caused a coincident increase in smaller species such as pelagicstingray (Dasyatis violacea), skipjack tuna (Katsuwonus pelamis) and pomfrets(Bramidae).

More recent empirical evidence has demonstrated how changes tochondrichthyan abundance and structure, mainly through harvest, havealtered marine communities and caused trophic cascades. The loss of elas-mobranch diversity in the coastal northwest Atlantic has had cascadingeffects down to even invertebrate species (Myers et al., 2007). Over thelast 35 years, there has been a large reported decline in 11 of the great sharkspecies (i.e.>85% for bull, dusky, smooth and scalloped hammerhead, tiger,blacktip and sandbar sharks; Fig. 4.5) that hunt other elasmobranch meso-predators. These declines have allowed many mesopredator populations toincrease and restructure the ecosystem, with the corollary that large sharkshave become functionally eliminated. Higher densities of cownose ray(Rhinoptera bonasus) were linked to large reductions in bivalve biomass(Blaylock, 1993) such as scallops Argopecten irradians (Peterson et al., 1996).


Indeed, the subsequent reduction and likely depletion of scallop populationscan cause rays to switch to soft and hard clams (e.g. Mya arenaria, Mercenariamercenaria) and oysters (Crassostrea virginica) that themselves have beenreduced by harvesting and other anthropogenic impacts. Other species ofmesopredators such as skates in the north-eastern Atlantic (Dulvy et al.,2000) and the long-headed eagle ray (Aetobatus flagellum) around Japan(Yamaguchi et al., 2005) might have also been released from predation bylarger sharks, although these systems have not yet been examined in suffi-cient detail.

Of course, many chondrichthyans, especially smaller species, are not apexpredators. Yet, there is some evidence that many benthic and demersal speciescan have important functional roles in marine systems. For the cownose ray,foraging behaviour is also destructive to shallowhabitats through theuprootingof seagrasses (Smith and Merriner, 1995), thus exacerbating any cascadingeffects that might arise from apex predator reduction. Skates can play animportant functional role in benthic systems. On the Scotian Shelf, the pro-portional biomass of skates is low, and therefore might not be consideredimportant for demersal fishes (Duplisea et al., 1997). However, skates have asimilar ecological role to flatfishes (Pleuronectidae), and together the twogroups represent the majority of the benthic fish biomass on the ScotianShelf. These species provide an important energy-flow pathway from thebenthos and at least one component of the demersal fish assemblage by eatingand processing benthic invertebrates (Martell and McLelland, 1994). There-fore, changes in abundance or diversity of either of these mesopredator groupsare likely to have an effect on both benthic and demersal ecosystems.

In support of evidence found in the terrestrial realm (e.g. Schmitz, 2008),the mere presence of shark predators can alter the foraging behaviour of theirprey species, leading to altered ecosystem states. An example of non-lethalpredator effects is the regulation of green sea turtle (Chelonia mydas) foragingbehaviour by tiger sharks (Heithaus et al., 2007). Turtles in poor bodycondition foraged on higher quality seagrass beds with high risk of predationby sharks, whereas turtles in good condition foraged on lower quality seagrassbeds where fewer predators hunted. A reduction or removal of tiger sharks istherefore predicted to result in greater foraging pressure on high-qualityseagrass beds leading to potential overgrazing (Rose et al., 1999).

6. Synthesis and Knowledge Gaps

6.1. Role of fisheries in future chondrichthyan extinctions

Despite the controversies and general paucity of good data, there is noquestion that fishing decreases the probability of survival of individual fishes.Relying on the assumption of density compensation, sustainable and


low-impact harvests are certainly possible for any exploited fish species,especially for those with rapid generation times and fast growth rates(Hilborn and Walters, 2001; Walters and Martell, 2004). It is only whenpopulations are reduced at rates greater than any gains achieved throughdensity compensation that large population decline becomes inevitable. Pop-ulation decline itself does not necessarily result in heightened extinction risk,especially if initial population size is large. The declining population paradigmon which much of the IUCN’s Red List classification is based does tend toindicate when population decline becomes cause for concern. In other words,decline can become an issue if the current population size is vastly inferior tosome original baseline estimate. However, only when population sizes fallbelow a MVP size does the risk of extinction rise to non-negligible values(Traill et al., 2007, 2009). Of course, a rare species might already have smallinitial population sizes, in which case the probability of dropping belowMVPwith fishing harvest is much higher.

Do fisheries contribute to higher extinction risk in chondrichthyans? Asfor all deterministic drivers of population decline, the answer is ‘yes’;however, it depends entirely on the species in question, the magnitude ofdecline and the population’s relative distance from a species-specific MVPsize (Traill et al., 2009). Our review has highlighted and reinforced theunderstanding that large species with correspondingly slower growth rates,longer generation times and later ages of maturity are more susceptible topossible extinction risks. Importantly, we have determined that althoughRed-Listed teleosts have a generally higher assessed threat risk than chon-drichthyans, the relatively larger chondrichthyans with lower fecundity, inthemselves, suggest that high harvest-rate fisheries have a potentially greatercapacity to drive certain chondrichthyan populations to sub-MVP size,especially those that already exist at low densities.

There is little debate regarding the future of demand for fish products.An ever-increasing human population and greater propensity for coastalliving means that chondrichthyans stand to experience some intense harvestas demand for their products continues to rise (Clarke et al., 2006; Food andAgriculture Organization of the United Nations, 2005). Indeed, as coastalresources become more and more heavily harvested, it is likely to be thepelagic mixed-species fisheries that will be called upon to supply the bulk ofthe demand. As highlighted, these mixed-species fisheries and their asso-ciated by-catch represent some of the greatest mortality sources for rarechondrichthyans, and currently there is little to no management or moni-toring of any high-seas fisheries (Mucientes et al., 2009). Coupled withmore advanced technological capacity (Roberts, 2002), an increasinghuman population also means that the quest for previously unavailable ordifficult-to-access fish resources will expose more and more species to apreviously unknown mortality source. In particular, deepwater fishing isgrowing in reach and expanse. This is potentially problematic given the


predicted slower life histories of cold water, deep-dwelling species that havelikely much lower intrinsic rebound potential than meso-pelagic species.

The endeavour to determine a species-specific MVP size and relateestimates of stock size to this should be one of the foremost goals of anymanagement strategy for chondrichthyan harvest. However, ensuring that apopulation does not fall below MVP should only be regarded as an absoluteminimum baseline, for MVP is typically estimated as the population sizebelow which the probability of (quasi)extinction becomes unacceptable,typically greater than 1% (Shaffer, 1981; Traill et al., 2007). True sustain-ability should therefore regard the harvest in terms of population trendsrather than population size. In other words, instead of setting PVA toestimate the probability of falling below a quasi-extinction threshold, thefocus should shift to setting a minimum population size above whichdecline becomes unlikely. If a population does, however, fall below itsMVP, then continued fishing pressure might be outweighed by stochasticfactors that act synergistically to increase extinction risk (Brook et al., 2008).

In summary, sustainable chondrichthyan fisheries are possible, but thesemust strive for stability rather than attempt to maximise yield (Hilborn et al.,2003). In the words of Hilborn (2007):

It is almost universally recognized that the future of sustainable fisheries lieswith much less fishing effort, lower exploitation rates, larger fish stocks,dramatic reduction in bycatch, increased concern about ecosystem impactsof exploitation, elimination of destructive fishing practices, and much morespatial management of fisheries, including a significant portion of marineecosystems protected from exploitation.

6.2. Climate change

The current rate of global climate warming is greater now than at any timein the last 1000 years (Walther et al., 2002) and has been of increasingconcern and research focus in recent decades (e.g. Graham and Harrod,2009; Hughes et al., 2003; Munday et al., 2008; Roberts and Hawkins,1999; Roessig et al., 2004). As a result of climate change, extinction ratesover the next century are predicted to be greater than otherwise expected(e.g. Hansen et al., 2006), particularly for endemic and range-restrictedspecies (Ahonen et al., 2009; Brook et al., 2008; Munday et al., 2008). Inaddition to the predicted effects associated with increases in both maximumand minimum temperatures, daily minimum temperatures are increasingmore rapidly than daily maximum temperature (Vose et al., 2005), withhigh spatial heterogeneity expected in the response of organisms, popula-tions and ecological communities (Genner et al., 2004). Chondrichthyes istherefore one taxon that could be, on average, at relatively high risk toclimate change effects due to slow rates of evolution and low phenotypic


plasticity that might otherwise enable quick adaptation to rapidly changingenvironmental conditions (Daufresne et al., 2009; Harley et al., 2006; Visser,2008).

Climate change will also probably influence the phenology and physiol-ogy of some species (Sims et al., 2001, 2004), with the most probable responseincluding shifts in distribution and changes in the timing of migrations. Theresultant changes to top-down control by shifting densities and configurationof the large predator guild, and the corresponding bottom-up changesexpected from shifting community structure in lower trophic levels andnutrient cycling pathways (Walther et al., 2002) are complex and presentlyimpossible to predict reliably. Although it is possible that climate changesmight benefit some species, the rapid pace of change combined with pressurefrom other threats might mean that more species will respond negatively(Brook et al., 2008; Daufresne et al., 2009; Visser, 2008).

The direct effects of environmental change likely to affect chondrichth-yans are the same that will influence all marine life, namely increases intemperature, and changes to water chemistry (Fig. 4.13). Although mostspecies demonstrate some physiological plasticity in their tolerances toenvironmental conditions, many species are expected to shift their distribu-tions to areas conducive to maintaining physiological optima, thus we mightexpect a shift toward higher latitudes (McMahon and Hays, 2006; Rose,2005). Migratory fish species are already showing changes in their ranges.For example, basking shark foraging behaviour is highly correlated withthermal ocean features, and shifted distributions northward might haveoccurred in the recent past (Sims and Reid, 2002), and would be morelikely to occur in the future as more rapid climate warming alters thermalstratification and the strength and persistence of fronts with consequentdistribution changes of its plankton prey (Cotton et al., 2005; Sims, 2008).

Temperature and salinity changes are also having effects on oceancirculation (Clark et al., 2002). These will enhance changes to local envi-ronmental conditions and the distributional response of their biologicalcommunities (Harley et al., 2006). Another direct effect might be theincreasing prevalence of disease and emergence of novel pathogens withincreasing temperatures (Clark et al., 2002; Harvell et al., 1999, 2002, 2004;Ward and Lafferty, 2004). For coastal shark and rays species, sea-level risewill alter shallow water environments, affecting especially those that havespecific habitat requirements (e.g. mangroves) for breeding, pupping orfeeding (Heupel et al., 2007). Sea-level rise might also lead to large-scalehabitat loss for some species and disrupt coastal and estuarine ecosystems.The effects of increasing frequency of extreme weather condition andintense storm events are likely to affect behavioural changes, destroy habitatsand change community structure (Heupel et al., 2003; Scheffer et al., 2001).

Other effects of climate change that might influence bottom-up pro-cesses are ozone depletion and ocean acidification. Ozone depletion affects


surface phytoplankton (Zepp et al., 2003) and subsequent productivity ofother trophic levels. Ocean acidification has also been identified as a majorthreat to corals and some calciferous organisms through dissolution of theirexternal calcium carbonate skeletons (Orr et al., 2005). Although acidifica-tion to this extent will be unlikely to affect chondrichthyans directly, largepotential changes are likely to alter habitat, marine community structure andprey availability for shark predators.

6.3. Extinction synergies

Recent empirical and theoretical work is beginning to identify how differ-ent factors interact synergistically to exacerbate extinction risk (Brook et al.,2008). Even when systematic threats such as intensive harvest via fishing donot result in immediate extinction, a combination of secondary processescan eventually cause a species to become extinct. For example, habitatfragmentation and over-harvesting can be exacerbated by climate change.Co-extinctions represent another synergistic process which precipitatesspecies loss more rapidly than otherwise expected. Examination of inter-specific dependencies demonstrated that many thousands of currently non-Red-Listed species could go extinct alongside their listed symbionts due tothese dependencies (Koh et al., 2004). Dependencies might also derive from

Sea-levelrise

Increased watertemperature

IncreasedCO2Intensified

upwelling (?)

Increased stormfrequency

Increased airtemperature

Human activities Increased greenhousegas concentrations

IncreasedUV

Intensified atmosphericpressure gradients

Decreased pH

Figure 4.13 Abiotic changes to oceans predicted from climate change (reproducedwith permission from Harley et al., 2006). The burning of fossil fuels and deforestationincrease atmospheric greenhouse gas concentrations, which lead to physical and chem-ical changes to ocean waters. The effect of climate change on upwelling and currentprocesses is most uncertain.


community interactions such as the meso-predator release examplesprovided in Section 5 (e.g. the reduction in large predatory sharks leadingto an expansion of medium-sized chondrichthyans that in turn drive adecline in scallops; Myers et al., 2007). From the chondrichthyan perspec-tive specifically, synergies among harvesting, habitat changes and climate-induced changes to marine environments are most likely to occur in thecoastal realm.

6.4. Research needs

There have been great leaps in our understanding of Chondrichthyes popula-tions since Camhi et al. (1998) identified a series of research needs for thistaxon. Our review has expanded and updated this list by highlighting theimportant remaining knowledge gaps required to assess extinction risk in thistaxon. We therefore offer a list of priorities for research that will enable betterassessment and reduce the probability of overlooking and underestimatingthreats within a precautionary management and conservation framework.In order of relative importance, these are (1) estimation of minimum popula-tion sizes and the degree of life history specialisation, (2) trophic interactionsand cascades, (3) expanded fisheries monitoring, (4) potential and measuredeffects of climate change, (5) assessing the implications of habitat loss anddegradation and (6) the consequences of genetic erosion on populationdynamics and resilience. Despite the recommended hierarchy, all recommen-dations are interlinked, as are their influences and consequences. As with mostecological research, carefully planned and orchestrated multi-disciplinaryapproaches can provide robust and cost-effective data.

In recent years, many chondrichthyan species have been added to theIUCN Red List. However, none of these are based on quantitative assess-ments of populations relative to estimated MVP size. Instead, most listingsunderstandably rely on sparse data describing possible distribution and relativeabundance changes. PVA are sorely needed for most of the species of highestconcern, and these all require specific demographic and population data.However, there are limited demographic and population data available atpresent for most chondrichthyan species. Often surrogate demographic esti-mates from congeners or family members have been used in place of knowninformation. Therefore, the highest priority for research is to obtain species-specific demographic data such as survival rates, fertility patterns and spatialrange. Detailed information is also required on the degree of life historyspecialisation, including studies examining ontogeny, foraging niches, andintra- and inter-specific competition. These data are essential to determinewhether particular life stages are relatively more vulnerable to specific threats,which can inflate estimates of extinction risk for entire populations or species.

The ecological interactions between chondrichthyans and their capacityto induce trophic cascades require much more focused study, including


experimental, observational and modelling approaches. Although therehave been a few ECOSIM/ECOPATH modelling studies (Kitchell et al.,2002; Stevens et al., 2000) and some quantitative analyses of time series inthis regard (e.g. Myers et al., 2007), we currently have only a rudimentaryunderstanding of how ecosystem changes will influence chondrichthyanextinction risk and affect the marine communities to which they belong.

With increasing demand for fisheries to provide food for a large, growinghuman population, we need better, more systematic andwide-coveragemon-itoring of chondrichthyan catch data and market trends to identify species indecline (e.g. Casey and Myers, 1998; Mucientes et al., 2009). Baseline data,even if they donot represent unexploited biomass, are required for themajorityof harvested species.Monitoring designsmust also include detailed inventoriesof species and sex composition and age/size structure from catches so thatwhole-population status can be assessed more readily. Such monitoringrequires an important at-sea component to measure the magnitude of by-catch, especially in mixed-species fisheries, and the proportion of non-morbidindividuals returned alive. Market surveys can also provide information toassess the relative contributionof IUUfishingonpopulation trends (e.g.Clarkeet al., 2006). Historical and commercial data sets must also be made freelyavailable to the research community for effective cross-examination and inter-pretation (e.g. Baum et al., 2005; Burgess et al., 2005a).

There is a good understanding of the potential effects of temperaturechange for many individual marine species. However, the simplistic relation-ships between temperature and biota do not necessarily provide a goodpredictive platform for understanding climate change effects on future marinecommunity structure and composition (Harley et al., 2006). More dedicatedexperimental and time series data are required to test specific hypotheses onpotential range shifts, adaptation capacity and physiological tolerance envel-opes for most species (Graham and Harrod, 2009). Synergies among extinc-tion drivers require greater focus, especially for species living in environmentswhere risks overlap (see Halpern et al., 2008). Chondrichthyans have evolvedover many hundreds of millions of years and the taxon has persisted in spite oftwo mass extinction events. The genetic implications of small, bottleneckedpopulations must also be of primary focus in molecular studies to determinethe relative contribution of potential inbreeding depression on estimates ofchondrichthyan extinction risk.

7. Concluding Remarks

We are still in the fortunate situation that there are no recorded casesof chondrichthyan extinction in modern times. However, we have identi-fied that the largest, most range-restricted and heavily harvested species


might be easily pushed below their MVP sizes, which could be much largerthan those estimated under stable environmental conditions.

Fishing, at all scales, represents one of the largest mortality sources formany chondrichthyan species, but there are some examples of small localfisheries that have operated without clear declines in population size oftargeted species. However, mixed-species fisheries that harvest poorlymeasured, but presumably large quantities of chondrichthyans are of partic-ular concern, as is IUU fishing. The lack of specific management andreporting mechanisms for the latter types means that many species mightalready be reduced to densities where extinction risk is unacceptably high. Itis almost universally recognised now that so-called ‘sustainable’ fisheries willhave to be the norm if they are to survive economically, and that they willhave to demonstrate negligible or minimal impacts to ecosystems throughcareful management and stewardship (Hilborn, 2007). IUU fishing canaffect shark populations and community structure, and this might be a fargreater challenge to control. Recreational fishing and beach meshing canalso contribute to local declines. Climate change and habitat degradationwill further erode certain populations to the point where extinction riskrises appreciably.

The idea that chondrichthyans have life history characteristics that mightpredispose them to extinction in a rapidly changing world (e.g. relativelylow reproductive potential, growth and capacity for population recovery;Pratt and Casey, 1990) is generally upheld by our results. Furthermore,because chondrichthyans tend to occupy the highest trophic levels, it isarguable that degradation of marine communities might limit the preyquality and quantity available to chondrichthyan predators, further exacer-bating population reductions.

We found no strong evidence, from admittedly simple models with fewparameters, that chondrichthyans are intrinsically more susceptible toextinction than other marine fishes in relation to their evolved niches andlife history characteristics. However, chondrichthyans tend to be larger thanmany other marine fish taxa, and large body size generally correlates withslower growth and lower reproductive capacity. As such, it is the rapid paceof environmental change and harvesting that have the greatest potential toimpede certain species from maintaining large population sizes. Any speciescan withstand moderate to even extreme exploitation if it does not outpaceintrinsic replacement rates and adaptation potential (Brook et al., 2008).

We were unable to examine all plausible correlates of threat risk due todata paucity. Many studies have examined age at maturity and growth ratesin terms of vulnerability to extinction, with late-maturing and slow-grow-ing species apparently at greater risk (Reynolds et al., 2005). Therefore, abetter compilation of data incorporating these and other possible correlatescould reveal further subtleties in the drivers of threat risk in this taxon andother marine fishes. Another caveat is that predictors of threat risk indicate a


species’ sensitivity to the largely systematic (deterministic) drivers of popu-lation decline (declining population paradigm) (Cardillo, 2003; Sodhi et al.,2008a), whereas actual extinction appears to correlate poorly with ecologi-cal and life history traits given that the final coup de grace tends to resultfrom largely stochastic processes that act independently of a species’ evolu-tionary history (Brook et al., 2006, 2008; Sodhi et al., 2008b; Traill et al.,2007)

There are many examples of how large predators influence communitiesand ecosystems via top-down (and in some cases, bottom-up) control ofspecies occupying lower trophic levels. Thus, the removal of large predatorscan elicit trophic cascades and destabilise the relative abundance of smallerprey and non-prey species. However, these effects are still poorly under-stood, especially for large, complex trophic webs where interactions arelargely unquantified. Specifically, chondrichthyans can alter prey diversityand size distributions, and their mere presence can affect the foragingbehaviour of prey that alters ecosystem functions such as nutrient recyclingand structural habitat complexity. Severe predator depletions can lead topermanent shifts in marine communities and alternate equilibria.

Management of shark populations must therefore take into account therate at which drivers of decline affect specific species. Only through detailedcollection of data describing demographic rates, habitat affinities, trophiclinkages and geographic ranges, and how environmental stressors modifythese, can extinction risk be estimated and reduced. The estimation of MVPsizes is an essential component of this endeavour and should, in our view,eventually accompany the current approaches used to manage sharksworldwide.

ACKNOWLEDGEMENTS

We thank V. M. Peddemors and D. Sims for helpful comments to improve the manuscriptand K. Mines for assistance compiling the database. This work was supported by anAustralian Research Council (ARC) Linkage Project grant LP0667702, the NorthernTerritory Government (Fisheries Group) and the Northern Territory Seafood Council.

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C H A P T E R F I V E

Effects of the Prestige Oil Spill on

the Biota of NW Spain: 5 Years

of Learning

Milagros Penela-Arenaz, Juan Bellas, and Elsa Vazquez

Contents

1. Introduction 366

2. Effects of the Prestige Oil Spill on the Marine Biota 373

2.1. Adtidal 373

2.2. Plankton 373

2.3. Benthos 376

2.4. Fishing resources 383

2.5. Seabirds 384

2.6. Marine mammals and turtles 386

3. Conclusion 386

References 390

Abstract

On 19 November 2002, the oil tanker Prestige broke into two and sank in the

Atlantic Ocean 260 km off the north-western coast of Spain, releasing about

63,000 tonnes of Bunker C oil. The accident represented one of the largest

environmental catastrophes in the history of European navigation. More than

1000 km of coastline and a huge variety of habitats were affected, ranging from

supralittoral, intertidal and sublittoral levels to oceanic and bathyal environ-

ments. In this chapter, we review published results regarding the impact of the

Prestige oil spill on marine organisms, at levels of biological organisation

ranging from the molecular to the ecosystem. Although some research is still

in progress, all results indicate a strong initial impact during the first year after

the spill, mainly on intertidal communities and fishing resources, with recovery

by 2004.



Departamento de Ecoloxıa e Bioloxıa Animal, Facultade de Ciencias do Mar, Universidade de Vigo,36310 Vigo, Spain

365

1. Introduction

The oil tanker Prestige broke into two and sank in the Atlantic Ocean260 km off the north-western coast of Spain on 19 November 2002,releasing about 63,000 tonnes of Bunker C oil. The accident representedone of the largest environmental catastrophes in the history of Europeannavigation (CEDRE, 2009). More than 1000 km of coastline were affected,from the northern coast of Portugal to Brittany and the southern coast ofthe United Kingdom, including protected areas of great ecological andeconomic value (Rousseau, 2003). A huge variety of habitats were affectedby the Prestige oil spill (hereafter, POS), ranging from supralittoral, intertidaland sublittoral levels to oceanic and bathyal environments, which includeimportant fisheries and highly diverse biological communities (Fig. 5.1).

The economic losses in Galicia, due to the POS, have been estimated at!566.97 million (lower bound estimate) for the period 2002–2004, includ-ing short-term losses in all economic sectors affected, accountable environ-mental losses, and cleaning and recovery costs (Loureiro et al., 2006). Thetotal costs associated with the POS are therefore rather significant for a smalleconomy such as that of Galicia, since they represent about 1.57% of thetotal Galician Gross Domestic Product (!36,097 million in 2002). Totallosses in the affected area (Galicia, Asturias, Cantabria and the Basque

© E

SA

200

2

Sinking site19/11/2002

BA

Accident13/11/2002

50 km

0 100 200

kilometres

Spain

France

Portugal

Figure 5.1 (A) Satellite image (European Space Agency) showing the trail of crude oilleft by the tanker Prestige, from the initial spill on 13 November to the final sinking siteon 19 November 2002. (B) Map of the shorelines polluted by the Prestige oil spillin northern Spain and south-western France. Source: Oficina Tecnica de VertidosMarinos. Ministerio de Educacion y Ciencia (http://otvm.uvigo.es/accidentprestige/litoralafectado.html).

366 Milagros Penela-Arenaz et al.

http://otvm.uvigo.es/accidentprestige/litoralafectado.html



Country) in 2002–2004 amounted to !770.58 million, according to esti-mates from Loureiro et al. (2006).

Crude oil consists of a complex mixture of compounds predominated byhydrocarbons. The compounds include straight, branched or cyclic chains,including aromatic compounds (with benzene rings) which constitute themost toxic components of oil for marine biota. Non-hydrocarbon com-pounds containing sulphur, nitrogen or metals may constitute up to 25% ofthe oil (Clark, 2001). The Prestige oil was classified as fuel oil No. 6, thecharacteristics of which include low solubility and low capacity for disper-sion, slow degradation, and high viscosity, adherence and density. Thevolatility of the oil is also relatively low (5–10%) because it containsrelatively high amounts of high-molecular-weight hydrocarbons, such aspolycyclic aromatic hydrocarbons (PAHs) (Table 5.1). After the POS,the oil showed a tendency towards the formation of stable emulsions inwater; these emulsions sank due to the strong swell, which favoured theirdeposition on the sea bottom and movement of the oil toward the coast.

Analyses carried out by the Spanish National Research Council (CSIC)showed that the Prestige fuel oil was mainly composed of 22% saturatedhydrocarbons, 35% resins and asphaltene and 50% aromatic hydrocarbons(CSIC, 2003a), some of which are known to be carcinogenic and/or muta-genic to aquatic organisms (Albers, 2003). Furthermore, the fuel containedsome trace metals such as Ni, V, Cu and Zn (CSIC, 2003b) (Table 5.1).

The POS in Galicia was one of the major oil spills to have occurred in theregion, however, it was not an isolated disaster, since Galicia has received 8 ofthe 20 major oil spills to have taken place in Europe during the last 50 years(CEDRE, 2009; Hooke, 1997; ITOPF, 2009). Hence, Galicia is one of theregions with the highest number of oil spills in the world (Table 5.2).

An oil spill may cause a serious impact on the marine coastal environmentsince it does not only affect organisms directly, but also destroys or damageshabitats that support aquatic communities (Kennish, 1992). In general, effectscaused by an oil spill can be divided into three categories: direct lethal effects,direct sublethal effects and indirect effects. Direct lethal effects refer tophysical and chemical effects produced by direct oil contact, even withoutingestion of pollutants by organisms. These effects are detected as an increasein mortality rates due to smothering, hypothermia (very common in oiledseabirds), coating (which interferes with an individual’s movement, hinderingfood capture, and escape from predators), or acute toxicity of fuel (see reviewby Kennish, 1992; NOAA, 1992). Mass mortalities are usually reported incoastal rather than offshore habitats, where hydrocarbons are usually presentat lower concentrations and observations are more difficult. For instance, thebenthic macrofauna was almost wiped out at heavily oiled sites 2 days after theFlorida oil spill (Kennish, 1992) and after a spill of Bunker C oil in SanFrancisco Bay, where more than four million intertidal animals, principallyacorn barnacles, died (Chan, 1973).

Prestige Oil Spill Effects on Biota 367

Sublethal effects, which are more difficult to detect than acute effects, arebrought about by the permanence of different fuel components in theenvironment. Such effects may not cause the death of organisms, but mayreduce the fitness of the affected species owing to the impact on the physio-logy, behaviour or reproductive capability of the organisms (NOAA, 1992).These alterations may also alter the distribution, abundance, compositionand diversity of impacted communities. By comparison, indirect effects

Table 5.1 Physicochemical properties of Prestige fuel oil

References

Physical

properties

Density 0.99 g/cm3

(15 �C)Saybolt-Letonia

quality certificate

(CEDRE, 2009)

Viscosity 615 cSt

(50 �C)30,000 cSt

(15 �C)

Saybolt-Letonia

quality certificate

(CEDRE, 2009)

Chemical

properties

Elemental

composition

CSIC (2003a)

% C 86.8

% H 11.0

% S 2.28

% N 0.69

General chemical

composition

CSIC (2003a)

% Saturated

hydrocarbons

22

% Aromatic

hydrocarbons

50

% Resines and

asphalthenes

28

Metal

concentrations

(ppm)

CSIC (2003b)

Na 1000–10,000

Al, Ca, Fe, K,

Mg, Ti

100–1000

Br, Ni, V 10–100

B, Ba, Mn, Mo,

Sr, Zn

1–10

As, Co, Cr, Cu,

Li, Se

0.1–1


Table 5.2 List of major oil tanker spills (1965–2002) including those occurring on theGalician coast (grey shaded)

Tanker Location Year Type of oil

Amount

spilled

(mT)

Yanxilas Rıa de Vigo,

Galicia, Spain

1965 Undetermined

oil

16,000

Torrey Canyon Scilly Islands,

UK

1967 Kuwait crude

oil (no. 3)

40,000

Spyros Lemnos Fisterra, Galicia,

Spain

1968 Venezuelan

heavy crude

oil

15,000

Polycommander Rıa de Vigo,

Galicia,

Spain

1970 Arabian light

crude oil

15,000

Sea Star Gulf of Oman 1972 Crude oil 115,000

Jakob Maersk Oporto,

Portugal

1975 Iranian crude

oil (no. 2)

88,000

Argo Merchant Massachusetts,

USA

1976 Fuel oil (no. 6),

Cutter stock

(no. 4)

26,000

Monte Urquiola A Coruna,

Galicia, Spain

1976 Arabian light

crude oil

(no. 3),

Bunker fuel

(no. 4)

108,000

Hawaiian

Patriot

Off Hawai 1977 Indonesian light

crude oil

95,000

Andros Patria Off Cape

Ortegal,

Galicia, Spain

1978 Iranian heavy

crude oil

60,000

Amoco Cadiz Brittany, France 1978 Arabian light

crude oil

(no. 2), Iranian

light crude oil

(no. 2),

Bunker C

(no. 4)

223,000

(continued )




Amount

spilled

(mT)

Independenta Bosphorous,

Turkey

1979 Es Sider crude oil

(no. 2)

95,000

Atlantic

Empress

Off Tobago 1979 Crude oil 287,000

Ixtoc I oil well Campeche Bay,

Mexico

1979 Crude oil (no. 3) 350,000

Irenes Serenade Off Pylos

Harbour,

Greece

1980 Iraqi crude oil

(Kirkuk blend)

100,000

Scaptrade Ribadeo,

Galicia, Spain

1980 Light crude oil 32,000

Castillo de

Bellver

Off Cape Town,

South Africa

1983 Light crude oil

(Murban and

Upper

Zakum)

252,000

Odyssey Off Nova Scotia,

Canada

1988 North Sea Brent

crude oil

132,000

Khark 5 Off Canary

Islands, Spain

1989 Iranian heavy

crude oil

(no. 4)

80,000

Exxon Valdez Prince William

Sound, Alaska

1989 Alaska North

Slope crude oil

(no. 3)

38,000

Haven Genoa, Italy 1991 Iranian heavy

crude oil

(no. 3)

144,000

ABT Summer Off Angola 1991 Iranian heavy

crude oil

260,000

Katina P. Off Maputo,

Mozambique

1992 Crude oil 72,000

Aegean Sea A Coruna,

Galicia, Spain

1992 Brent blend light

crude

74,000

Braer Shetland Isles,

UK

1993 Norwegian

Gullfarks light

crude oil,

Heavy

bunker oil

85,000

x


include changes in habitat, predator–prey dynamics, interactions amongcompetitors, productivity levels and food webs, due to the loss of keyspecies (Freire and Labarta, 2003). It has been stated that such effects mayslow down the recovery processes to a decade or more (Peterson, 2001).However, we need to be aware of the difficulties involved in the assessmentof recovery after a pollution event such an oil spill, which are probablyhigher than the assessment of the initial damage. Marine ecosystems arecomplex environments subjected to many causes of ecological change asidefrom oil pollution (e.g. human disturbance, physical habitat alteration,commercial fishing, climate, other pollutants), and therefore, the recoveryprocesses may be occurring in a different environmental scenario than whenthe oil spill first occurred (NRC, 2003).

Different factors determine the degree of the effects caused by an oilspill. Oceanographic and meteorological conditions will control the driftvelocity of the spill, the location on the shoreline where oil may run up, andthe rate of the weathering processes. Timing is also critical, since the impactwill be greater if the spill coincides with periods of high primary production,spawning, embryonic and larval development, or the presence of migratoryspecies. The intensity of the impact will also differ depending on the habitat,and will be less intense in offshore than in coastal habitats, as communitiesare more diverse and higher concentrations of hydrocarbons are found inthe latter. Furthermore, the degree of shelter will determine residencetimes, which will be shorter in high-energy environments than in shelteredhabitats (NOAA, 1992). Impacts will be more damaging for species withsmall populations (Pineira et al., 2008) and/or restricted reproductive andbreeding habitats such as rıas, bays, estuaries or coastal marshes, which are



Amount

spilled

(mT)

Sea Empress Milford Haven,

UK

1996 Forties blend

North Sea

crude oil

70,000

Erika Brittany, France 1999 Heavy fuel oil

(no. 6)

30,000

Prestige Off Fisterra,

Galicia, Spain

2002 Heavy fuel oil

(no. 6)

63,000

Data sources: CEDRE (2009), Hooke (1997), and ITOPF (2009).


more susceptible to localised pollution events such as oil spills (Freire andLabarta, 2003). This is because these low-energy environments tend to trapoil and to accumulate hydrocarbon pollutants in the sediments increasingthe likelihood of long-term impact (Kennish, 1992).

The effects of hydrocarbon pollution also depend on the speciesimpacted. Gastropods and polychaetes are usually the least sensitive species,while corals, bivalves, decapod crustacea and echinoderms are the mostsensitive (NRC, 1985). Such differences in responses to oil pollution areconsidered to be caused by their different behaviour, physiology and mor-phology (Swedmark et al., 1973). Nevertheless, the same species may displaydifferent responses depending on duration of exposure (recovery is moredifficult after a long exposure), sex, age (eggs and larvae are often moresensitive), and their history of contamination (animals previously exposed tocertain compounds can exhibit a lower or a greater tolerance when testedlater) (NOAA, 1992). However, few valid generalisations about ecologicaleffects can be applied to the majority of spills, since the variations amongorganisms, environmental conditions and types of oil transform each oil spillinto a different event (Day et al., 1997).

The assessment of oil-spill impacts is normally made on the basis ofhistorical data from the same site, comparison with nearby unimpacted sites,comparison with model predictions, or through expert opinion. However,there are two major difficulties in assessing accidental impacts, oneassociated with statistical aspects and the other with biological aspects.Randomisation and replication of treatments that characterise an experi-ment obviously do not take place during an unplanned environmentalimpact such as an oil spill. Treatments are not randomly located andreference areas are not true controls, since they must be defined after thespill (Wiens and Parker, 1995). As a result, it is usually very difficult todistinguish effects of the contaminant from effects of environmental differ-ences across localities. Natural factors vary and may co-vary with thecontamination in different ways depending on the area. Furthermore, if acommunity has not been monitored prior to a spill, studies carried out afterthe spill are often unable to conclude that the oil spill was the cause of anypresumed change (Forde, 2002). Nevertheless, in evaluating the effects ofunplanned environmental impacts, post facto designs, which document bothinitial effects and subsequent recovery, can provide information about themagnitude of the damage (Page et al., 1995; Wiens and Parker, 1995).

With regard to the clean-up procedures used after the POS, beach-cleaning operations were mainly focused on the large-scale manual removalof the fuel covering the sand. Additionally, mechanical and manual skim-mers were used to remove the oil that had been buried in deep layers.On the other hand, hydro-cleaning machines were chosen as the preferen-tial method to remove oil from exposed rocky shores. However, areasvirtually inaccessible to mechanical cleaning methods (over 60,000 m2 of


rocky surface area) were treated by bioremediation (Ministerio de MedioAmbiente, 2005). Oil recovery at sea was carried out by different oilresponse vessels from several European countries (Spain, UK, Belgium,Germany, Italy, The Netherlands, Norway and Denmark). The recoverysystems used were weir, belt and oleophilic skimmers as well as nets andsurface trawl systems. In addition, it is worth mentioning the direct partici-pation of Spanish fishermen using simple manual collection systems(CEDRE, 2004).

In this chapter, we review the results published to date on the effects ofthe POS on marine organisms, at levels of biological organisation rangingfrom the molecular to the ecosystem, and use this overview to inform aboutany longer term effects and the time scales of recovery in this system.

2. Effects of the Prestige Oil Spill

on the Marine Biota

2.1. Adtidal

Most of the communities of the terrestrial adlittoral system were directlyaffected, not only by the POS hydrocarbons deposited upshore by strongwaves, but also indirectly by cleaning activities (Urgorri et al., 2004). Loss ofspecies diversity (relative to the situation before the black tides) was detectedin communities of Crithmo-Armerietum, Cisto-Ulicetum, Euphorbio-Agropyre-tum, Othanto-Ammophiletum and Iberidetum. Coating particularly affectedArmeria pubigera, Crithmum maritimum, Spergularia rupicola and Puccinelliamaritima. Crest dunes and fixed dunes communities, composed of Elymusfarctus, Ammophila arenaria, Artemisia crithmifolia, Honkenya peploides, Eryn-gium maritimum, Calystegia soldanella, Festuca rubra and Juncus maritimus, werenot directly affected by the spill, although important damage was caused bycleaning activities and the opening up of new trails to reach impacted areas.

A reduction in the surface cover of a large number of Bryophytes species(such as Bryum dunense, Trichostomum crispulum, Tortella flavovirens, Tortularuraliformis, Pleurochaete squarrosa, Homalothecium lutescens, Dicranella hetero-malla, Didymodon acutus, Didymodon trifarius and Weissia controversa) wasobserved in affected localities.With regard to rocky substrates, the abundanceof Grimmia trichophylla, Campylopus pilifer, Racomitrium heterostichum andPolytrichum juniperinum decreased in several localities affected by the POS.

2.2. Plankton

Planktonic organisms, particularly those living in the top few centimetres ofthe water column (neuston), are supposed to be especially susceptible to theacute effects of the oil spills due to their proximity to the highest


concentrations of the water-soluble oil compounds. However, no long-term effects on the planktonic community are expected due to their highregenerative potential (short generation times) and the recruitment fromoutside the impacted areas. Clark (2001) states that low concentrations ofhydrocarbons (<50 ng/g) may enhance photosynthesis, presumably becausethey have a nutritive effect, whereas inhibition of photosynthesis occursabove this level. Also, an increase in phytoplankton biomass and productiv-ity was reported after the oil spill from the tanker Tsesis in 1977, due to thedecline in grazing zooplankton populations ( Johansson et al., 1980). Thus, ithas been suggested that typically, phytoplankton recovers quickly from anoil spill, returning to previous population levels, as observed after the wreckof the Amoco Cadiz in 1978 (Cabioch, 1981). In general, it is assumed thatzooplankton is more sensitive to oil pollution than phytoplankton, althoughcontradictory results have been reported. For instance, Samain et al. (1980)observed a high zooplankton mortality in affected areas from the north coastof Brittany during the first weeks following the Amoco Cadiz oil spill andidentified biochemical succession of population groups over a 1-yearperiod. Guzman del Proo et al. (1986) also found a high decrease inzooplankton biomass in the southern part of the Gulf of Mexico followingthe Ixtoc-1 spill. On the other hand, Batten et al. (1998) concluded thatplankton communities from the southern Irish Sea were not significantlyimpacted after the Sea Empress wreck, when compared with long data seriesfrom previous years, although a minor shift in species composition wasdetected after the spill.

Plankton community structure was not seriously affected by the POS.Only occasional variations were observed, but were associated with thenatural variability of the ecosystem (Varela et al., 2006), probably because ofthe low solubility of the Prestige oil, with a tendency to sink (Serrano et al.,2006); the movement of the water, which spreads the fuel and cleans thewater column; bacterial biodegradation, the activity of which increasedsignificantly 1 year after the spill, particularly during winter and summer(Bode et al., 2006); the biological mechanisms that transfer the fuel from thesurface waters to the sea floor; the capability of plankton to metabolisehydrocarbons and, especially, the large and mesoscale hydrographic pro-cesses, which introduce high natural variability in the plankton, maskingeffects of the oil (Varela et al., 2006).

Medina-Bellver et al. (2005) demonstrated that natural populations ofbacteria capable of degrading components of the Prestige crude oil werepresent on the Galician shore, which can be explained by the continuedexposure of the indigenous populations to oil components. The bacterialcommunity was principally composed of a-Proteobacteria, although repre-sentatives of g-Proteobacteria, Bacteroidetes and Actinobacteria groups were alsodetected ( Jimenez et al., 2007).


Early developmental stages of invertebrates have been shown to be moreresponsive to toxicants than adults (see review by His et al., 1999). SinceWoelke (1972) proposed use of the oyster Crassostrea gigas embryogenesisbioassay to indicate water quality for the protection of marine resources,bivalve and sea-urchin embryos and larvae have been increasingly used fortesting the biological quality of seawater and to evaluate marine pollution(e.g. His and Beiras, 1995; His et al., 1997; Kobayashi, 1995; McFadzen,1992). An evaluation of the exposure of embryos and larvae of bivalves andechinoids to environmental samples (collected in affected areas) indicatedthat fuel-polluted seawater was more toxic than sediment elutriates col-lected immediately after the POS. Prestige oiled water clearly inhibitedembryogenesis in Venerupis rhomboideus and Paracentrotus lividus, while sedi-ment elutriates only caused moderate toxicity in V. rhomboideus or notoxicity in Venerupis pullastra and C. gigas (Beiras and Saco-Alvarez, 2006;Marino-Balsa et al., 2003) (Fig. 5.2). Likewise, bioassays carried out withsediment elutriates 9 months after the event did not reveal any differences inthe success of embryogenesis in V. pullastra (Franco et al., 2006), which issupported by the concentration of total PAHs, well below the sedimentquality criteria of 4022 mg/kg dry weight suggested by Long et al. (1995).In contrast, bioassays carried out with sediment elutriates sampled 18

Concentration of WSF/oil-polluted water

0,1 1 10 100 1000

% b

iolo

gica

l res

pons

e

0

20

40

60

80

100 Cyprinodon larvae (WSF)

Sea-urchin larvae(oil-polluted water)

Clam larvae(oil-polluted water)

Sea-urchinlarvae (WSF)

Mussel larvae (WSF)

Acartia (WSF)

Figure 5.2 Concentration–response curves of oil-polluted seawater collected on theGalician coast during the first days after the Prestige spill, and the water-soluble fraction(WSF) of the Prestige oil diluted with clean seawater, for mussel larvae (opendiamonds), clam larvae (filled-in circles), Acartia tonsa (open squares), sea-urchin larvae(open triangles for oil-polluted water, filled-in squares for WSF), and Cyprinodonvariegatus larvae (filled-in triangles) (after Beiras and Saco-Alvarez, 2006; Marino-Balsaet al., 2003; Saco-Alvarez et al., 2008).


months after the POS showed failure of P. lividus embryogenesis in thestations with the highest concentrations of PAHs (Fernandez et al., 2006a).

The water-soluble fraction (WSF) of the Prestige fuel oil did not affectgrowth of the freshwater alga Chlorella vulgaris and did not have deleteriouseffects on the cladoceran Daphnia magna (Navas et al., 2006). However,despite differences in methods of obtainingWSF, high toxicity was reportedfor the copepod Acartia tonsa and for the embryo-larval development ofboth sea-urchin (P. lividus) and mussel (Mytilus galloprovincialis) (Fernandezet al., 2006b; Saco-Alvarez et al., 2008). The toxicity of the Prestige fuel WSFobtained in laboratory conditions (Saco-Alvarez et al., 2008) was alsocomparable to the toxicity of natural samples of seawater affected by thePOS (Beiras and Saco-Alvarez, 2006) (Fig. 5.2).

2.3. Benthos

Intertidal benthic organisms are highly prone to coating, smothering and tothe acute toxicity of oil components after an oil spill. Macroalgae andinvertebrates such as coelenterates, crustaceans, echinoderms and molluscsusually suffer high mortalities (Peterson et al., 2003). The pattern of succes-sion after an oil spill includes the loss of dominant herbivores and colonisa-tion of the substrate by green algae. Such changes in the benthic communitywere reported to last for 4 or 5 years after the Torrey Canyon or the ExxonValdez oil spills (Peterson, 2001; Southward and Southward, 1978). Subtidalareas can also be reached by oil which adsorb to particulate matter, or byheavier fractions of weathered oil that may eventually sink. This oil accu-mulates on the bottom and may affect the benthic community by directcontact or by the generation of anaerobic conditions (Roberts, 1989). Also,the direct toxicity which mainly occurs during the early acute phases of thespill may cause strong differences in diversity and abundance on subtidalcommunities (Sanders et al., 1980). In addition, when oil is mixed or buriedin the sediments, it can remain a continuing source of toxicity for years, andcause delayed ecosystem effects which persist long after the direct toxiceffects of the oil have disappeared (Peterson et al., 2003; Roberts, 1989).

2.3.1. Rocky intertidalAs was seen after the Torrey Canyon spill on British shores (Southward andSouthward, 1978) and the Exxon Valdez oil spill in Alaska (Highsmith et al.,1996), the upper intertidal zone was the most seriously affected by the POS(Urgorri et al., 2004). Six months after the POS, there was more uncolo-nised substrate—both bare rock and dried oil—in the upper intertidal zoneof the most heavily oiled localities than in the lightly or non-oiled areas. Inthe latter areas, the upper intertidal zone was mainly covered with thecirripede Chthamalus montagui, a characteristic species on Galician-exposedrocky shores, whereas the cover by C. montagui was less than 10% at the


most heavily oiled sites (Fig. 5.3A). Mortality ofC. montaguiwas also greaterin highly oiled localities than in medium oiled ones (Fig. 5.3B) (Urgorriet al., 2004). Similar massive mortalities of barnacles caused by an oil spillhave been recorded elsewhere (Chan, 1973; North et al., 1964; Southwardand Southward, 1978; Straughan and Abbot, 1971).

Populations of sea urchins (P. lividus), goose barnacles (Pollicipes pollicipes)and mussels (Mytilus galloprovincialis), which are all commercially exploitedin rocky intertidal areas in Galicia, were affected to different degrees and atdifferent shore levels. Sea urchins disappeared completely from areas thatwere densely populated before the POS (Urgorri et al., 2004) and musselsalmost totally disappeared from the upper intertidal areas in the heaviestoiled sites, although they remained in other areas moderately affected by thespill (Fig. 5.3A). It can be speculated that covering of gill filaments by oil

0

20

40

60

80

100

CAI CAM CAL AGU CIE OIA

% m

orta

lity

of C

. mon

tagu

i

y = −43.58x + 150.23r 2= 0.347

0

20

40

60

80

100

1,5 2 2,5 3 3,5log[sum40PAHs] (mg/kg dw)

% c

over

/abu

ndan

ce

A

B

aLO

bMO b,c

HO

aMO

c,dMO d

LO

Figure 5.3 (A) Decrease in the cover of Chthamalus montagui (squares) and Mytilusgalloprovincialis (triangles), and in the abundance of Patella spp. (circles) with increasingtissue concentrations of PAHs (mg/kg dry weight). (B) Mortality of C. montagui atdifferent localities of the Galician coast after the Prestige oil spill. LO, lightly oiled sites;MO, medium oiled sites; HO, heavily oiled sites. a, b, c, d indicate homogeneousgroups obtained with the Games-Howell post hoc test. After Urgorri et al. (2004).


would have impaired feeding, with the consequent mortality of mussels bystarvation. In addition, byssal thread activity may have been impaired,resulting in detachment from the substrate (Swedmark et al., 1973), asoccurred with Mytilus trossulus after the Exxon Valdez spill (Highsmithet al., 1996). Recruitment of P. pollicipes was lower than in the same periodin the previous year in most of the areas surveyed. However, recruitmentfluctuations may be attributable to the characteristically high natural varia-bility of barnacle recruitment, a phenomena widely reported in manydifferent studies (e.g. Caffey, 1985; Hawkins and Hartnoll, 1982; Jenkinset al., 2000; Kendall et al., 1985).

Labarta et al. (2005) observed sublethal effects in wild mussel spatcollected 3 months after the POS. Lower survival rates and alteration oflipid metabolism—with a higher percentage of triglycerides and a decreas-ing proportion of phospholipids—were found in mussel spat from sites withhigher PAH concentrations. Such differences in lipid composition were alsoobserved in mussel spat from Pindo (a strongly affected area) transplanted toa raft culture in the Ares-Betanzos Rıa (Peteiro et al., 2007), but only at theonset of the experimental culture. In addition, the growth in weight and thepercentage of mussels classified as ‘large’ at harvest was significantly lower inmussels from Pindo spat than in individuals from less impacted areas (Peteiroet al., 2006).

A large decrease in the abundance of limpets (Patella spp.) was observedat upper shore levels in heavily oiled localities (Fig. 5.3A) (Urgorri et al.,2004). Mortality of Patella spp. may have been caused by oil toxicity,smothering, lack of available food, or clean-up activities, as occurred withanother limpet, Tectura persona, after the Exxon Valdez oil spill (Highsmithet al., 1996; Houghton et al., 1991). After the Torrey Canyon spill, Patella spp.were nearly eradicated and, because of the absence of these dominantherbivores, algae colonised the bare rock and inhibited settlement of Patellaand barnacles for 5 years (Southward and Southward, 1978); but, as men-tioned above the decrease in the recruitment of the barnacle P. pollicipes afterthe POS might have been attributable to variability in the natural condi-tions. It must be noted that the excessive use of dispersants after the TorreyCanyon oil spill caused major damage to marine biota (Smith, 1968) andtherefore comparisons with the POS are not straightforward.

One and a half years after the POS, no significant reductions in geneticvariability were found in populations of Littorina saxatilis, which hadsuffered drastic reductions in population size following the spill (Pineiraet al., 2008). There are different possible reasons why genetic variability didnot decrease in this species, which was chosen as a model species because ofits low dispersal ability, direct development, high population density andwidespread distribution on Galician shores. Firstly, the effects on geneticdiversity would be small if the reduction in population size that occurredafter the spill occurred over a short time period. Secondly, recolonisation of


the affected localities may have taken place from the presence of juvenileshidden in crevices and behind rocks, or to a lesser extent, as a consequence ofmigration from unaffected locations nearby. Nevertheless, polluted popula-tions have shown some genetic effects, principally on amplified fragmentlength polymorphism variation and quantitative shell traits, probably as aresult of natural selection (Pineira et al., 2008).

The effect of the POS on algae resulted in decreases in biomass andspecies diversity in Chondrus crispus, Gelidium sesquipedale and Gigartinapistillata communities 6 months after the event (Urgorri et al., 2004). TheMastocarpus stellatus community showed the greatest changes in relation tothe pre-spill situation. Biomass and size were lower after the spill but specificrichness and diversity were much higher. This was explained as a decrease inbiomass of the dominant species, which most likely made more spaceavailable for another species to colonise. Communities of M. stellatus arecharacteristic of sheltered coves, which owing to the retention of the fuel inthese locations, may have been more strongly affected than areas witha stronger swell and a faster rate of ‘self-cleaning’. Lobon et al. (2008)compared abundance data for macroalgal assemblages before (September2002) and then 10 months after the spill (September 2003) at upper andlower intertidal levels in affected areas along the coasts of Galicia, Asturiasand the Basque Country. The latter study concluded that the abundance ofthe main taxa did not change greatly after the spill and that dilution of fueldue to intense winter mixing and advection following the accident were themost likely causes for the lack of severe effects on macroalgal assemblages.Moreover, the mucilaginous slime layer that covers the outer surface ofmany benthic macroalgae has been reported to serve as a barrier to thepenetration of oil providing a protective covering (GESAMP, 1977).

Biomarkers are cellular, biochemical and molecular features that providepowerful means of detecting environmental disturbances since they indicatethe existence of pollutants (exposure biomarkers) or the response of exposedorganisms (effect biomarkers) (McCarthy and Shugart, 1990), allowingchanges at high levels such as population, community, or ecosystem to beanticipated (Cajaraville et al., 1993). Different biomarkers in mussels(M. galloprovincialis) were used to assess the biological effects of the POS.Mussels are commonly used as sentinel organisms in pollution monitoringprogrammes because of their ability to accumulate contaminants, theirresistance to high levels of pollutants, and their widespread distribution(Goldberg, 1975). Thus, the high levels of PAHs in coastal seawater causedby the POS (max. 2.1 � 103 mg equiv. of chrysene per litre) were reflectedin a peak of PAH accumulation in mussel (M. galloprovincialis) tissues (max.5.9 � 103 mg/kg dw); this was followed by a depuration period until thefollowing winter, when a slight increase in PAH concentrations (abovebackground levels) was detected as a consequence of the remobilisation dueto winter storms (Nieto et al., 2006).


Biomarkers of exposure (induction of acyl-CoA oxidase) and effect(lysosomal responses and alterations in morphology and composition ofcell types in the digestive gland) in mussels sampled along the northerncoast of Spain in 2003 and 2004 revealed exposure to toxic chemicals andeffects on the health of mussels due to the POS (Orbea et al., 2006), with thedegree of disturbance being higher in the most severely impacted areas.Some degree of recovery was observed in 2004 and was associated with areduction in total PAH concentrations in mussels (Cajaraville et al., 2006).However, a battery of exposure and effect biomarkers did not reveal anyclear effect in mussels fed with Tetraselmis spp. pre-exposed to the water-accommodated fraction of the Prestige oil. Only NADH reductases and lipidperoxidation levels were affected by the exposure, which may have beendue to the low PAH levels measured in exposed individuals as a result of thelow solubility of the Prestige oil (Sole et al., 2007).

The composition of free amino acids (FAA), used as an index of stress,was analysed in juvenile specimens of M. galloprovincialis collected fromdifferent Galician rocky shore areas in February 2003 (Babarro et al.,2006). Total FAA and derived indices (taurinease/glycine ratio, sum ofserine and threonine, alanine) were not affected by pollution. In fact, thechanges in the FAA profiles of soft tissues were associated with endogenousfactors in juvenile stages, such as protein content and condition index, andare used as indices of the energetic status of growing individuals.

DNA damage in mussel gills, assessed by the comet assay, was detectedbetween August 2003 and June 2004 in two areas of the Galician coastintensely affected by the POS, relative to reference areas (Laffon et al.,2006). DNA damage was significantly higher in fuel-exposed mussels thanin control mussels, before and after a 7-day period in the laboratory duringwhich they were held in clean, fresh seawater. During this recovery stage, aslight reduction in comet tail length was observed, suggesting a certaindegree of DNA repair in exposed animals, which is consistent with thereported reversibility and non-persistence of such damage (e.g. Nacci et al.,1992).

Effects on the immune response of M. galloprovincialis were confirmed byNovas et al. (2007), since the mechanisms responsible for nitric oxide (NO)synthesis in haemocytes appeared absent between January 2003 andDecember2004. An increase in the proportion of phagocytic SH cells, probably as a resultof the depressed immune potential, was also detected during these years.Nevertheless, these cells were more sensitive to apoptosis and necrosis-induc-ing agents. On the contrary, Ordas et al. (2007) did not observe any significanteffects on the immune system of mussels exposed to Prestige fuel oil for4 months; no differences in several cellular immune parameters (haemocyteviability, phagocytic activity, NO production and chemiluminescenceemission) were found between oil-treated and control individuals.


2.3.2. Sandy intertidalThe areas most affected by the oil spill were the swash zone and dry sandzone. The latter not only received high amounts of oil but was also affectedby clean-up activities. These activities involved the removal of sand, affect-ing mainly those species which occur on the sand surface or those with lowmobility, and the elimination of the algal wrack, used by the supratidalmacrofauna as food and refuge (de la Huz et al., 2005; Junoy et al., 2005).A similar impact also occurred after the Exxon Valdez oil spill, wherecleaned beaches took longer to recover than beaches that were not cleaned(Peterson, 2001).

A decrease in the number of species was detected in 16 of the 18 beachesstudied along the Galician coast 6 months after the POS, with a negativerelation between the degree of pollution and number of species. The heavilyoiled beaches lost about 66.7% of the total species richness compared withdata from September 1995 and 1996 (de la Huz et al., 2005; Junoy et al.,2005). The latter authors stated that the large difference observed before andafter the spill could not be attributed to the seasonal variation of the species.There was a large reduction in the abundance of the isopod Eurydice, nemer-teans and Diptera after the spill. The bivalveDonax trunculus disappeared fromfive of six beaches where it was known to be consistently present before thespill (de la Huz et al., 2005). The isopod Sphaeroma rugicauda decreased inabundance or disappeared frommost of the beaches, whereas there was a largeincrease in cumaceans and mysids in the swash zone. An increase in abun-dance of oligochaetes and the practical disappearance of the insects was notedin the retention and dry sand levels, where higher concentrations of hydro-carbons were observed. A clear reduction in the abundance of talitrid amphi-pods and the semi-terrestrial isopod Tylos was also observed after the spill.Furthermore, the abundance of the opportunistic polychaete Scolelepis squa-mata decreased after the spill when compared to data from June to September1997, probably due to cleaning operations, since this species usually adaptseasily to oil spills (de la Huz et al., 2005). Surprisingly, the abundance of theamphipod Pontocrates arenarius increased after the POS, whereas amphipodsdisappeared immediately after the Amoco Cadiz and the Aegean Sea spills(Gomez-Gesteira and Dauvin, 2000).

A significant effect was also noted in the meiofaunal composition(Urgorri et al., 2004). The faunistic heterogeneity and density of theinterstitial fauna were low in nearly all samples. Ostracods were eliminatedfrom Corrubedo beach and together with Turbellaria from Barranan beach.Foraminifera almost totally disappeared from the beaches affected by thePOS. However, the presence of early benthic stages of bivalves and poly-chaetes in the most polluted sediments 6 months after the spill suggested thatthe recovery, at least with temporary meiobenthic fauna, had alreadystarted, as reported by Rodriguez et al. (2007). By comparison, after the


Monte Urquiola oil spill only some Turbellaria survived, whereas nematodesand harpacticoid copepods were completely eliminated. Nevertheless, therecovery of communities had already started 1 year after the spill, even onthe most severely affected beaches (Giere, 1979).

Several studies have also evaluated the quality of the sediments affectedby the POS. The burrowing behaviour of juvenile clams (V. pullastra andTapes decussatus) in sediments taken from moderately affected beaches a fewdays after the spill was not significantly different from the behaviour incontrol clams (Marino-Balsa et al., 2003), which supports the generalassumption that laboratory toxicity tests are insufficient for ecotoxicologicalrisk assessment. In contrast, Morales-Caselles et al. (2007a) found toxiceffects of sediments from impacted sites after use of the MicrotoxÒ andthe amphipod (Corophium volutator) tests, and identified PAHs as the com-pounds causing the toxic effects. However, the toxicity of Galician sedi-ments affected by the POS was lower than the toxicity of sedimentschronically polluted by oil spills in the Bay of Algeciras. Sediments collected4 years after the POS did not cause acute mortality in the amphipodAmpelisca brevicornis or the polychaete Arenicola marina in 10-day bioassaysand no toxicity was detected with the MicrotoxÒ test (Morales-Caselleset al., 2008), which suggests some recovery of sediment quality fromaffected areas. However, a significant accumulation of PAHs in organismsexposed to sediments collected from impacted sites indicates that there maystill be a risk to the biota in the affected areas (Morales-Caselles et al., 2008).

2.3.3. SublittoralSurveys carried out 6 months after the POS did not show any obvious effectson benthic coastal organisms (Urgorri et al., 2004). Furthermore, pollution-sensitive species, such as amphipods and the sea-urchin Echinocardium corda-tum, were even found in sediments containing oil aggregates. Serrano et al.(2006) indicated that the distribution of benthic communities on the bottomof the Galician continental shelf was not affected by the tar aggregates thatsettled after the POS, as had occurred after the Braer (Kingston et al., 1995)and the Exxon Valdez oil spills (Feder and Blanchard, 1998), when nosignificant effects on benthic fauna were detected. In fact, the changes inthe communities that were detected were attributed to changing sedimentcharacteristics rather than to concentrations of hydrocarbons. The low bio-availability of Prestige tar aggregates may explain the lack of correlationbetween distributions of macroscopic tar aggregates and shelf-benthiccommunities.

These results and the lack of toxicity detected in bioassays carried outwith sublittoral sediment (Franco et al., 2006) strengthen the conclusion thatthe POS had no important impact on the Galician sublittoral benthiccommunities, probably because of the spatial dispersion of the fuel whenit reached the sea bottom.


2.4. Fishing resources

Sandeel (Gymnammodytes semisquamatus) catches per unit effort were signifi-cantly reduced in 2003. High rates of mortality, similar to those registeredafter the Torrey Canyon oil spill, were detected, although sandeels may alsohave migrated to avoid polluted sediments (Velando et al., 2005a). Significantreductions in the abundance of Norway lobster (Nephrops norvegicus), four-spot megrim (Lepidorhombus boscii) and Pandalid shrimp (Plesionika heterocarpus)were also observed over the Galician shelf when bottom trawl surveys carriedout after the POS were compared with time series data (1983–2004) (Sanchezet al., 2006). An important degree of recovery, evident from abundanceindices, of four-spot megrim and shrimp was subsequently recorded in 2004.In addition, the feeding patterns of the above-mentioned three species and ofEuropean hake (Merluccius merluccius) did not change in relation to the POS.

Even though tar aggregates and hake (M. merluccius) recruits were trans-ported by the same oceanographic events, no significant changes in theabundance or distribution of hake juveniles from Galician and CantabrianSea shelves were detected (Sanchez et al., 2006). Furthermore, a certaindegree of recovery in recruitment was observed during the 2 years followingthe POS.

Large increases in abundance and richness of parasite communities, andsignificant changes in individual and functional group parasite abundancepatterns were found in samples of bogue (Boops boops) collected in Malpicaand Vigo 2 and 3 years after the POS (Perez-del Olmo et al., 2007).Nematode parasitisation in liver of European anchovy (Engraulis encrasicolus)and European hake (M. merluccius) was registered at several locations inGalicia and the Bay of Biscay between April and September 2003. How-ever, it was not possible to relate this to the POS because of the lack of pre-spill data (Marigomez et al., 2006).

Biomarkers were also used to assess the impact of the POS in fishes. Anincrease in EROD activities and histopathological lesions of the juveniles ofSparus aurata, as a result of the increasing PAH concentrations in sedimentscollected 2 years after the POS, was detected, with gill tissues more severelydamaged than liver tissue (Morales-Caselles et al., 2007b). In L. boscii, gluta-thione-S-transferase, glutathione reductase and catalase activities were signif-icantly higher in the most severely affected locations in the northern Iberianshelf 5 months after the accident (Martınez-Gomez et al., 2006). The activitieswere positively correlated with the density of POS tar aggregates. In addition,high levels of 1-naphthol, a marker of recent exposure to petrogenic com-pounds, were measured in bile from L. boscii and Trisopterus luscus collected inthe Galician area 1 year after the POS (Fernandes et al., 2008). Nevertheless,the lack of historical data and the chronic contamination in the studied areameant that the changes could not be directly and/or exclusively attributed tothe POS. Similarly, and despite the prominence of hepatocellular nuclear


polymorphism in liver of E. encrasicolus and M. merluccius registered at severallocations in Galicia and the Bay of Biscay between April and September 2003,no relation with the POS could be established, because of the lack of pre-spilldata (Marigomez et al., 2006).

In the case of Solea senegalensis, short-term (24, 48, and 72 h) exposure toenvironmentally realistic PAH levels from the WSF of the Prestige fuel oildid not cause oxidative stress or neurotoxicity in juveniles (Sole et al., 2008).The low PAH levels reached in this study may be one of several possiblereasons for the lack of effects. Similarly, Gonzalez-Doncel et al. (2008)investigated the effects of different oil fractions (WSF, crude oil, andweathered oil) on the embryo-larval development of the medaka (Oryziaslatipes). This study revealed a significant incidence of abnormalities inhatching and growth as well as mortality, which suggested that the environ-mental hazard of the Prestige fuel oil could not be linked exclusively to PAHsbut also to other components. Morales-Nin et al. (2007) and Saborido-Reyet al. (2007) also detected significant differences in otolith and somaticgrowth, both in length and weight, in juvenile turbot Scophthalmus maximuskept in captivity and fed on a prepared food containing 0.25–5% seawater-accommodated fuel oil collected immediately after the POS. Growth of fishwas slower in the tanks with food containing a relatively high proportion offuel oil, probably as consequence of the diminution in feeding activity and adecrease in the food energy conversion. High mortality rates were alsoregistered for fish larvae (Cyprinodon variegatus) exposed to the WSF ofthe Prestige fuel oil (Saco-Alvarez et al., 2008). Lastly, rainbow troutRTG-2 cells exposed to the WSF of Prestige oil did not show any cytotoxiceffects (Navas et al., 2006), although a dose-dependent increase of ERODactivity was induced.

2.5. Seabirds

Seabirds are probably the animals that suffer the greatest impact following anoil spill (Peterson et al., 2003) owing to their long contact with the seasurface and the oil accumulated on the coast, where they congregate tobreed (Irons et al., 2000). A total of 23,181 oiled birds were collected inSpain, France and Portugal, although some estimates suggest that the totalnumber of birds affected by the POS may have been between 115,000 and230,000 (Garcıa et al., 2003). The most severely affected species were thecommon guillemot Uria aalge (50.9% of the birds collected), the razorbillAlca torda (16.7%), the Atlantic puffin Fratercula arctica (16.6%), and theNorthern gannet Morus bassanus (3.4%).

Dehydration and exhaustion were probably the main cause of death forPOS-affected seabirds. Microscopic examination of tissue from birds withaccumulations of oil in the intestine revealed haemosiderin deposits, associatedwith cachexia and/or haemolytic anemia. In birds treated in the Bird Rescue


Center of Aviles, severe aspergillosis and ulcers in the ventriculus werediscovered, and were probably due to stress related to rehabilitation(Balseiro et al., 2005). Total PAH concentrations measured in 2004 in bloodsamples from yellow-legged gulls (Larus michahellis) from oiled colonies weretwo times higher than those from unoiled colonies (Perez et al., 2008),although there was a reduction in PAH levels over time. Measurements ofPAHs in blood samples are sensitive to the ingestion of small quantities of oil.

Shags (Phalacrocorax aristotelis) were not killed in large numbers after thePOS (Velando et al., 2005a). A skew in adult-female shag mortality wasdetected (85% of dead adults were females), probably because there weremore females at sea when the spillage took place, as males were presentat breeding sites (Martınez-Abraın et al., 2006). The number of immaturefemale and male corpses recovered was similar, probably because immaturebirds were not defending territories in breeding colonies. As a consequenceof this female-biased mortality, important decreases in breeding numberswere expected. In fact, Monte Carlo simulations considering sex-biasedmortality predicted a decrease of 11% in the number of breeding pairs(Martınez-Abraın et al., 2006). In 2003, the breeding success was 50%lower in polluted colonies than in unoiled ones (Velando et al., 2005b),and chick condition was poorer than in pre-spill years (Velando et al.,2005a). The reduction in reproductive success was probably due to oilpollution, sublethal effects, or lack of food after the oil spill. Lack ofbreeding and changes in survival caused the decline in oiled colonies(ca. 10%) compared with population trends before the spill and at unoiledcolonies (Velando et al., 2005b).

Azkona et al. (2006) studied a colony of European storm petrels (Hydro-bates pelagicus) on Aketx Island, in the Bay of Biscay. Although the popula-tion numbers varied greatly among years before the spill, in 2003 thenumber of breeding pairs and fledglings was lower than in any previousyear and the body condition of the former was poorer. In 2004, there wasanother reduction in the number of pairs that began breeding. The bodycondition of individuals was slightly better, although values registeredbefore the oil spill were not reached, and all clutches were successful.In 2005, there was a recovery in the number of individuals and breedingsuccess. Nevertheless, the minimum age of recaptured birds was lower,which indicates an effect on population structure.

The POS had a negative effect on the population of peregrine falcon(Falco peregrinus) in the Bay of Biscay. The effects were first noted as anincrease in the population turnover rate (from 21% to 30%) and in thenumber of deserted nests containing eggs or young chicks (Zuberogoitiaet al., 2006). The effects of pollution were detected inland because falconspredated affected seabirds during the migratory flights of the latter.

Measurements using biomarkers showed higher levels of aspartateaminotransferase (AST) and lower values of glucose, total protein, and


inorganic phosphorus in adult yellow-legged gulls (L. michahellis) breedingin oiled colonies 17 months after the POS, which suggests damage to somevital organs (i.e. liver and kidney) (Alonso-Alvarez et al., 2007a). The effectswere more evident in adults than in chicks, although total PAH levels inblood were similar in both age groups, probably because of the longerexposure of adults to pollutants just after the spill. The presence of PAHsin chicks suggests that these components were incorporated through con-taminated food. Lower levels of glucose and inorganic phosphorus in plasmaand a tendency for lower levels of creatinine were also observed in wildyellow-legged gulls fed with Prestige fuel oil, in comparison with control gulls,fed only with vegetable oil (Alonso-Alvarez et al., 2007b). AST activity wasalso higher, but only in oil-fed males. However, g-glutamyl transferaseactivity was higher in control females than in oil-fed females, in contrast tothe field data obtained in the previous study (Alonso-Alvarez et al., 2007a),revealing possible differences in the adaptive responses of these enzymes toshort-term exposure to fuel.

Finally, acetylcholinesterase (AChE) activity decreased by 4% in Atlanticpuffins, 16% in exposed common guillemots, and 22% in razorbills relativeto non-exposed congeners (Oropesa et al., 2007), although the inhibitoryeffect on AChE activity of the exposure to the Prestige fuel oil was onlydemonstrated in razorbills.

2.6. Marine mammals and turtles

The effects of oil on marine mammals and turtles include short-term andchronic acute toxic effects ranging from coating of the fur (which causeshypothermia, smothering and drowning), ingestion of toxicants duringpreening, and ingestion of polluted prey, to disruption of vital social func-tions in socially organised species (Peterson et al., 2003). A total of 27cetaceans and 16 turtles strandings were recorded 1 month after the POS(Alonso-Farre and Lopez-Fernandez, 2002); however, it is difficult to finddirect evidence indicating fuel oil as the cause of the strandings.

3. Conclusion

Even though there is still some research in progress, the resultsobtained to date indicate a strong initial impact during the first year afterthe spill, mainly on intertidal communities and fishing resources (sum-marised in Table 5.3), with a relatively fast recovery by 2004. The time ofyear when the POS took place meant that damage was minimal. Forexample, the abundance of phytoplankton and zooplankton after thespill—between November and February—was at the annual minimum.Furthermore, many invertebrate species were not spawning and larvae


Table 5.3 Summary of the biological responses, from molecular to community levels, reported after the Prestige oil spill

Molecular Individual Population Community

Biological responses Effectsonbiomarkers

Effectsontheim

muneresponse

Alterationofmetabolism

Highmortalities

Failuresofem

bryo-larvaldevelopment

Lower

growth

rates

Poorerbodycondition

Alterationofparasitecommunities

Increase

inabundance

Reductionin

abundance

Lower

recruitment

Higher

adultmortality

Lossofspeciesdiversity

Higher

specific

richness

Decreasein

biomass

References

Adtidal Urgorri et al. (2004)

Vascular plants

communities

X

Bryophytes species X

Rocky intertidal Urgorri et al. (2004)

Algal

communities

X X Labarta et al. (2005)

Mastocarpus stellatus

community

X X Cajaraville et al. (2006)

Mytilus

galloprovincialis

X X X X X X Laffon et al. (2006)

Patella spp. X Orbea et al. (2006)

Paracentrotus lividus X X Peteiro et al. (2006, 2007)

(continued)


Molecular Individual Population Community

Biological responses Effectsonbiomarkers

Effectsontheim

muneresponse

Alterationofmetabolism

Highmortalities

Failuresofem

bryo-larvaldevelopment

Lower

growth

rates

Poorerbodycondition

Alterationofparasitecommunities

Increase

inabundance

Reductionin

abundance

Lower

recruitment

Higher

adultmortality

Lossofspeciesdiversity

Higher

specific

richness

Decreasein

biomass

References

Chthamalus montagui X Novas et al. (2007)

Pollicipes pollicipes X Saco-Alvarez et al. (2008)

Sandy intertidal Urgorri et al. (2004)

de la Huz et al. (2005)

Junoy et al. (2005)

Meiofaunal communities X

Ostracods X

Turbellaria X

Foraminifera X

Macrofaunal communities X

Diptera X

Nemerteans X

Oligochaetes X

Cumaceans X

Mysids X

Venerupis rhomboideus X

Donax trunculus X

Eurydice X

Sphaeroma rugicauda X

Pontocrates arenarius X

Fishing resources

Gymnammodytes

semisquamatus

X Velando et al. (2005a)

Oryzias latipes X Gonzalez-Doncel et al.

(2008)

Cyprinodon variegatus X Saco-Alvarez et al. (2008)

Boops boops X Perez-del Olmo et al.

(2007)

Sparus aurata X Morales-Caselles et al.

(2007b)

Lepidorhombus boscii X X Martınez-Gomez et al.

(2006)

Scophthalmus maximus X Saborido-Rey et al. (2007)

Nephrops norvegicus X Morales-Nin et al. (2007)

Plesionika heterocarpus X Sanchez et al. (2006)

Seabirds Garcıa et al. (2003)

Uria aalge X Velando et al. (2005a,b)

Alca torda X X Azkona et al. (2006)

Fratercula arctica X Martınez-Abraın et al.

(2006)

Morus bassanus X Zuberogoitia et al. (2006)

Larus michahellis X Alonso-Alvarez et al.

(2007a,b)

Phalacrocorax aristotelis X X Oropesa et al. (2007)

Hydrobates pelagicus X X

Falco peregrinus X

were not present in the water column at that time of year. Winter stormsalso favoured cleaning in most areas. If the POS had occurred during thespring blooms or summer upwellings, impacts on reproduction of organ-isms, plankton and, therefore, on food webs, would have been greater.

One difficulty in assessing the impact of the POS was the lack of timeseries or historical data formost of the areas or ecosystems affected by the spill.Without such information on the natural variability of the marine ecosystemit is very difficult to assess the real impact on the environment and to be able toattribute the observed responses to the spill. Furthermore, there was a highdegree of disorganisation in the scientific response during the first weeks ofthe crisis (Freire et al., 2006). In the aftermath of the oil spill, the threeadministrations responsible for marine research began to monitor the impactof the oil spill, but worked separately and without any coordination. It wasnot until 3 months after the catastrophe that the Spanish Ministry of Scienceand Technology took charge of coordinating the different groups. It wasevident that coordination among different administrations and the scientificcommunity needed to be improved to enable a faster, more structuredassessment of the real impact of the oil spill, an experience which is relevantto scientific responses to any future environmental crises in this region andelsewhere.

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TAXONOMIC INDEX

A

Acartia tonsa, 375–376Acipenser nudiventris, 309Aetobatus flagellum, 312, 335Aetomylaeus maculates, 312Aetomylaeus nichofii, 312Aetomylaeus vespertilio, 312Aetoplatea zonura, 312Alca torda, 384, 389Alopias superciliousus, 294, 300Alopias vulpinus, 294, 300Ammophila arenaria, 373Ampelisca brevicornis, 382Anampses viridis, 309Anoxypristis cuspidate, 312Arenicola marina, 382Argopecten irradians, 334Armeria pubigera, 373Artemisia crithmifolia, 373Atlantoraja castelnaui, 312Atlantoraja cyclophora, 312Atlantoraja platana, 312Aulohalaelurus kanakorum, 312Azurina eupalama, 309

B

Bathyraja albomaculata, 312Bathyraja griseocauda, 312Benthobatis kreffti, 312Boops boops, 383, 389Bramidae, 334Bryum dunense, 373

C

Calanus finmarchicus, 235, 240, 244Callorhinchus milli, 304Calystegia soldanella, 373Campylopus pilifer, 373Cancer magister, 332Cancer productus, 332Carcharhinus amboinensis, 296Carcharhinus borneensis, 312Carcharhinus brachyurus, 312Carcharhinus falciformis, 286, 294, 301Carcharhinus hemiodon, 312Carcharhinus leiodon, 312Carcharhinus leucas, 282

Carcharhinus limbatus, 312Carcharhinus longimanus, 294, 300, 312Carcharhinus obscurus, 286, 294, 301, 312Carcharhinus plumbeus, 294, 301–302, 304Carcharhinus signatus, 312Carcharhinus sorrah, 282, 294, 296–297Carcharias taurus, 283, 294, 304, 312Carcharinus limbatus, 294, 297, 304Carcharinus spp., 300Carcharinus tilstoni, 294, 296–297Carcharodon carcharias, 294, 300, 302, 312Caretta caretta, 153–155, 157–158, 166–167,

170–171, 173, 176, 178–179, 184–186Centrophorus granulosus, 312Centrophorus harrissoni, 312Centrophorus squamosus, 312Cetorhinus maximus, 282, 291, 293–295, 312Chelonia mydas, 154–155, 157–159, 166–168,

171, 175–176, 179–183, 186–187,189–190, 335

Cheloniidae, 154Chlorella vulgaris, 376Chondrus crispus, 379Chthamalus montagui, 376–377, 388Corophium volutator, 382Crassostrea gigas, 375Crassostrea virginica, 335Crithmum maritimum, 373Cyprinodon variegatus, 375, 384, 389

D

Daphnia magna, 376Dasyatis fluviorum, 312Dasyatis garouaensis, 312Dasyatis laosensis, 312Dasyatis spp., 283Dasyatis violacea, 334Dermochelyidae, 154Dermochelys coriacea, 154–156, 158–159, 168, 171,

175–178, 189Dicranella heteromalla, 373Didymodon acutus, 373Didymodon trifarius, 373Diplobatis colombiensis, 312Diplobatis guamachensis, 312–313Dipturus batis, 294, 298, 312Dipturus chilensis, 312Dipturus crosnier, 312–313

397

Dipturus laevis, 294, 298, 312–313Dipturus mennii, 312–313Discopyge tschudii, 312–313Donax trunculus, 381, 388Dugong dugon, 181

E

Echinocardium cordatum, 382Elymus farctus, 373Engraulis encrasicolus, 383–384Enhydra lutris, 332Entelurus aequoreus, 37Eretmochelys imbricata, 154–155, 158, 166,

169, 174, 183, 189Eryngium maritimum, 373Eurydice, 388Eusphyra blochii, 296

F

Falco peregrinus, 385, 389Festuca rubra, 373Fratercula arctica, 384, 389Fundulus heteroclitus, 332

G

Gadus morhua L., 213–252, 278Galeocerdo cuvier, 282, 294, 296, 300Galeorhinus galeus, 293–294, 296, 312–313Galeus mincaronei, 312–313Gelidium sesquipedale, 379Gigartina pistillata, 379Glyphis gangeticus, 312–313Glyphis glyphis, 312–313Grimmia trichophylla, 373Gurgesiella dorsalifera, 312–313Gymnammodytes semisquamatus, 383, 389Gymnura altavela, 312–313Gymnura micrura, 334

H

Halichoerus grypus, 248Hemigaleus australiensis, 306Hemiscyllium hallstromi, 312–313Hemiscyllium strahani, 312–313Hemitriakis leucoperiptera, 312–313Heteroscyllium colcloughi, 312–313Himantura chaophraya, 312–313Himantura fluviatilis, 312–313Himantura oxyrhyncha, 312–313Himantura signifier, 312–313Holothuria spp., 303Homalothecium lutescens, 373Honkenya peploides, 373Huso huso, 309Hydrobates pelagicus, 385, 389

Hypleurochilus geminatus, 332Hypsoblennius hentzi, 332

I

Iberidetum, 373Isogomphodon oxyrhynchus, 312–313Isurus oxyrinchus, 294, 300Isurus paucus, 312–313

J

Juncus maritimus, 373

K

Katsuwonus pelamis, 334

L

Lagodon rhomboides, 332Lamna ditropis, 282Lamna nasus, 293–294, 300, 312–313Larus michahellis, 385–386, 389Lepidochelys kempii, 154, 156, 158Lepidochelys olivacea, 154–155, 158–159, 173,

176, 189Lepidorhombus boscii, 383, 389Leucoraja melitensis, 312–313Littorina saxatilis, 378

M

Macrocystis spp., 332Makaira indica, 334Makaira nigricans, 334Manta birostris, 283Mastocarpus stellatus, 379, 387Melanogrammus aeglefinus, 222Mercenaria mercenaria, 335Merlangius merlangus, 222Merluccius merluccius, 383–384Mobula mobular, 312–313Morus bassanus, 384, 389Mustelus antarcticus, 288, 294–295Mustelus canis, 333–334Mustelus fasciatus, 312–313Mustelus henlei, 282Mustelus lenticulatus, 304Mustelus schmitti, 312–313Mustelus whitneyi, 312–313Mya arenaria, 335Myliobatis hamlyni, 312–313Mytilus galloprovincialis, 376–377, 379–380, 387Mytilus trossulus, 378

N

Narcine bancroftii, 312–313, 334Narcine brevilabiata, 312–313

398 Taxonomic Index

Natator depressus, 153–159, 173, 189Nebrius ferrugineus, 312–313Negaprion acutidens, 312–313Neodenticula, 92Neodenticula seminae, 119Nephrops norvegicus, 383, 389

O

Odontaspis ferox, 312–313Odontaspis taurus, 294Oryzias latipes, 384, 389Oxynotus centrina, 312–313

P

Pantanodon madagascariensis, 309Paracentrotus lividus, 375–377Patella spp., 378, 387Phalacrocorax aristotelis, 385, 389Phoca groenlandica, 248Phocoena phocoena, 248Plagioscion spp., 333Plesionika heterocarpus, 383, 389Pleurochaete squarrosa, 373Pleuronectidae, 335Pollicipes pollicipes, 377–378, 388Polytrichum juniperinum, 373Pontocrates arenarius, 381, 388Prionace glauca, 286, 288, 294, 299Pristis clavata, 312–313Pristis microdon, 312–313Pristis pectinata, 312–313Pristis perotteti, 312–313Pristis pristis, 312–313Pristis zijsron, 312–313Prochlorococcus, 29Prototroctes oxyrhynchus, 309Pseudoginglymostoma brevicaudatum, 312–313Puccinellia maritime, 373Pugettia producta, 332Pycnopodia helianthoides, 332

R

Racomitrium heterostichum, 373Rhina ancylostoma, 312–313Rhincodon typus, 283, 312–313Rhinobatos cemiculus, 312–313Rhinobatos formosensis, 312–313Rhinobatos granulates, 312–313Rhinobatos horkelii, 312–313Rhinobatos obtusus, 312–313Rhinobatos rhinobatos, 312–313Rhinobatos thouin, 312–313Rhinoptera bonasus, 334Rhinoptera brasiliensis, 312–313Rhinoptera javanica, 312–313

Rhizoprionodon taylori, 282Rhynchobatus australiae, 312–313Rhynchobatus djiddensis, 312–313Rhynchobatus laevis, 312–313Rhynchobatus luebberti, 312–313Rostroraja alba, 312–313

S

Schroederichthys saurisqualus, 312–313Scolelepis squamata, 381Scomberomorus semifasciatus, 296Scomberomorus spp., 296Scophthalmus maximus, 384, 389Scylliogaleus quecketti, 312–313Solea senegalensis, 384Sparus aurata, 383, 389Spergularia rupicola, 373Sphaeroma rugicauda, 381, 388Sphyrna lewini, 294, 300Sphyrna mokarran, 294, 300, 312–313Sphyrna spp., 296Sphyrna tiburo, 307, 334Sphyrna tudes, 312–313Sphyrna zygaena, 294, 300Squalus acanthias, 289–290, 293, 312–313Squalus mitsukurii, 312–313Squatina aculeate, 312–313Squatina argentina, 312–313Squatina dumeril, 334Squatina guggenheim, 312–313Squatina occulta, 312–313Squatina oculata, 312–313Squatina squatina, 294, 299, 312–313Stegostoma fasciatum, 312–313Strongylocentrotus franciscanus, 332Strongylocentrotus purpuratus, 332Sympterygia acuta, 312–313Synechococcus, 29

T

Taeniura meyeni, 312–313Tapes decussatus, 382Tectura persona, 378Tegula brunnea, 332Tegula funebralis, 332Tetraselmis spp., 380Thunnus tonggol, 296Tortella flavovirens, 373Tortula ruraliformis, 373Triaenodon obesus, 282Triakis acutipinna, 312–313Triakis maculate, 312–313Trichodesmium, 43–44, 76Trichostomum crispulum, 373Trisopterus luscus, 383

Taxonomic Index 399

Trochus spp., 303Tylos, 381

U

Uria aalge, 384, 389Urogymnus asperrimus, 312–313Urogymnus ukpam, 312–313Urolophus bucculentus, 312–313Urolophus javanicus, 312–313Urolophus orarius, 312–313Urolophus sufflavus, 312–313Urolophus viridis, 312–313

V

Venerupis pullastra, 375, 382Venerupis rhomboideus, 375, 388

W

Weissia controversa, 373

Z

Zapteryx brevirostris, 312–313Zostera marina, 182

400 Taxonomic Index

SUBJECT INDEX

A

ACC. See Antarctic circumpolar currentAllee effects, cod, 247–248Antarctic bottom water (AABW)

production, 97, 103Southern Ocean, 95warming trend until, 22

Antarctic circumpolar current (ACC)flow, 94–95mode and nurient-rich intermediate waters,

95–96potential candidate mechanisms, 98profound warming, 98silicic acid, 46Southern Ocean, 123–124upwelled water, 20–22

Arctic and seas adjacent to GreenlandArctic Ocean and Subarctic Seas

geographical features and bathymetry,80–81

surface atmosphere air temperature, 81warm rate, 81

comments, 93ecosystems

benthic–pelagic coupling, 92phytoplankton growing season, 91sea-ice cover reduction, 91–92

Greenland ice sheetIPCC AR4 report, 88, 89warmer temperature, 88

ice formation, 83methane hydrates

affect mechanisms, 90permafrost release, 91

modelling, 92–93river runoff, 83sea-ice cover

extent, 84, 85projected changes, 86–87retreat and feedbacks, 87seasonal and annual mean, Northern

Hemisphere, 84in September 2007, 84, 85thickness and volume changes, 84, 86

sub-polarcirculation, warm input, 82MOC and dense water formation, 82–83

trigger factors, sea-ice reductions, 86

Atlantic angel sharks, 334Atlantic cod Gadus morhua, climate and fishing

effectsactivity, metabolic scope, 229–230biogeographic changes

distributional limits, 224northward shift, 225–226thermal effect, 224–225

biology and distribution, 215–216debate, 244early life stages, 231–233genetic population structure

diversity regional patterns, 217–218gene flow, 216

growth, 237–238maturation and spawning, 230–231movement and activity

adult, 219–221larval dispersal, 222thermal habits, 221–222

physiologysublethal thresholds, 227–229tolerance limits and thermal preferences,

226–227population-level impact

Allee effects and management plans,247–248

North Sea, stock evaluation, 246–247stock assessment, 245–246

recruitment, 233–236status and recovery, North Sea, 249–250stocks

Northeast, 239–244Northwest, 238–239trait, 218–219

Atlantic multi-decadal oscillation (AMO), 13Atmosphere–ocean global circulation models

(AOGCMs), 106

B

Bayesian information criterion (BIC)marine, threat risk correlates

chondrichthyan, 321, 323teleost, 322, 323

on relative model support, 320Beach meshing, 305, 342Benthic system

bivalves and polychaetes stages, 381

401

Benthic system (cont.)demersal species, 335ecosystem

acidification effect, 73global carbon cycles, 36–37

habitat disturbance, 331invertebrates, 158macroalgae, 379macrofauna, 367marine plants and algae, 182organisms

and bottom sediments, 59coastal, obvious effects, 382coating, smothering, and oil component

toxicity, 376cope, temperature changes, 101deoxygenation and mortality, 71marine, calcification rates, 66

oviparous species, 283pelagic coupling, 92shallow-water, 75species poleward migration, 38water temperatures, 237

Benthos, Prestige oil spillrocky intertidal

algae, 379biomarkers, 379–380cover decrease, 377DNA damage, 380genetic variability, 378–379limpets, 378sea-urchins and mussels, 377–378upper intertidal zone, 376

sandy intertidaldegree of pollution and species number, 381meiofaunal composition, 381–382

sublittoral, 382subtidal areas, 376

BIC. See Bayesian information criterionBlue shark fins, 299–300, 303Brown sharks, 302

C

Carbon (CO2), climate changeacidification, 7–8biological pump, 56–57continental shelf pump, 57counter pump, 57–58cycle

and CH4, 51–52climatological mean distribution, 52–53DIC profile, 52, 54

dissolutionalkalinity, 68CaCO3 production, 68–69

formationaragonite saturation horizon depth, 66–67

calcification, 66mineral types, 65–66saturation state, surface waters, 66, 68

pumpbottom sediment distribution, 74CaCO3 budget, 75pCO2, 73

role, 58solubility pump, 54–56storage and transfer, 7uptake, 69–70

Chimaeras. See ChondrichthyesChondrichthyes

extinction riskanalysis, 317–320ecological, life history and human

relationship, 313–317global distribution, 310–313identification and ranking, 308modelling results, 320–326species traits, 308–309and teleosts, 309–310and teleosts relative threat, 326–328

life historyage and growth, 282niche breadth, 281–282reproduction and survival, 283–284

physical changes, habitat, 279–280population declines, 279species loss implication

ecosystem role, 333–335marine realm predator loss, 331–333

synthesis and knowledge gapsclimate change, 337–339extinction synergies, 339–340fisheries role, 335–337research, 340–341

threatsbeach meshing, 305fishing, 284–305habitat loss, 306pollution and non-indigenous species,

306–308Climate change, chondrichthyes

extinction rates, 337–338Ocean acidification, 339ozone depletion, 338–339phenology and physiology, 338

Climate change impacts, codactivity metabolic scope

sea surface temperature, 229–230swimming speed and foraging rate, 229

anthropogenic inputs, 222–223biogeographic

distribution, northwardshift, 225–226

stock depletion, 226thermal occupancy, 224–225

402 Subject Index

early life stageseggs, 231–232larvae and egg survival, 232–233ontogenetic shift, 232

and fishing population-level, 245–248growth

low temperatures, 237warmer climate, 237–238

maturation and spawningenergy provision and, 230male lekking behaviour, 231peak dates, 230–231

North Atlantic sea surface temperatures, 223physiology

sublethal thresholds, 227–229tolerance limits and thermal preferences,

226–227recruitment

biological responses vs. NAO index, 236extrinsic stochastic events, 233interannual variation, 233–234plankton community, 235temperature-driven variability, 234–235thermal effect, direct, 235–236

Climate modelsCO2, 112–113comments, 114–115heat transport

density contrasts, 109MOC flow, 109–110Southern Ocean circulation and limiters, 110

heat uptakeAOGCMs, 106limiters, 108regional distributions, 107–108

ocean–climate feedbacks, 106retro-modelling, past climate

change, 113–114sea ice

components and limiters, 112extents, 111–112

water cycle, 111Coastal zone color scanner (CZCS), 33, 59Commercial fisheries interest (CMI), 314, 318

D

Destabilisationglaciers, 25hydrates, 90ice sheet

in current models, 118Greenland and East Antarctic, 25–26

Dimethylsulphide (DMS)BrO interaction, 49CO2 fluxes and, 59emission, 49–50gas exchange/carbon uptake, 112–113production, 36

Dimethylsulphoniopropionate (DMSP), 50Dissolved inorganic carbon (DIC) system

bicarbonate input, 71CO2, high atmospheric, 69low concentrations, 75–76in ocean, 54re-equilibration, 52

Dissolved organic carbon (DOC), 52, 57DMS. See Dimethylsulphide

E

Ecosystem, chondrichthyanabundance and structure changes, 334–335benthic and demersal species, 335ECOPATH/ECOSIM models, 333–334elasmobranch mesopredators predatory

release, 334marine predator loss

continental shelf and open-ocean, 332–333effects, 331–332trophic cascade, 332

predators roleinfluence, evidence and theory, 328–330loss, 330–331terrestrial trophic cascades, 330

El Nino/Southern oscillation (ENSO), 12Embryos and hatchlings

air temperatureenvironmental factors, 167global warming, 164marine turtle life stages, 165turtles nesting, 166

rainfall, storms and cyclone, 167–168sea level and atmospheric patterns, 169

Environmental temperature class (ETP), 314Expendable bathythermograph (XBT), 14Extinction risk, chondrichthyan

ecological, life history and human-relationship,313–317

extinction proneness, 308modelling

IUCN category species distribution, 320, 324marine teleosts, 322, 326Red-Listed species, 320–322, 325

relative threat, teleostsFishBase species, 328Red Listing, 326–327sharks, 327, 328

species traits, 308–309taxa threatened, global distribution

IUCN Red-Listed, 311, 312species cluster, 313

and teleosts, 309–310threat analysis

Akaike’s information criterion corrected(AICc), 319–320

BIC, 320GLMM, 317–319

Subject Index 403

F

Fisheries, chondrichthyan extinctionfishes survival, 335–336minimum viable population and stock size, 337mixed-species and by-catch, 336–337risk, 336

Fishing, chondrichthyesbiological and social effects, 288collapsing, 284–285conservation biology paradigms, 288–289demographic variance, 289extinction, 288extirpations, 290–291global distribution, shark, 287IUU, 303–304local/population extinction, 290mixed fisheries and by-catch

barndoor skate, 298–299blue shark fins, 299–300decline controversies, 300–303occurrence, 298pelagic, 299problem, 297–298

rate vs. recruitment trade-off, 291recreational

Australia and New Zealand, 304inshore water, 305

sharks, 286spiny dogfish, 289–290target fisheries

commercial, 291–292directed shark, 292–293Northern Territory, Australia shark, 296–297tope, school/soupfin shark, 295–296

Fishing impacts, North Atlanticvs. climate change debate, 244Northeast stocks

Celtic Sea, 242–243Iceland, 243–244North Sea, 239–242

Northwest stocks, 238–239population-level and climate change

Allee effects and, 247–248North Sea stock evaluation, 246–247stock assessment, 245–246

G

Game fish (GME), 317Generalised linear mixed-effect models (GLMM),

317, 320Genetic population structure, cod

diversity change, 217living condition, 216regional patterns, diversity

co-occurring population, 218microsatellite DNA markers, 217substantial differences, 217–218

stock traits, 218–219Global primary production

aerosolsDMS emission, 49–50DMSP, 50

benthos, 36–37biodiversity functional groups

diatoms, 35ocean biomes, 35–36organisms role, 34–35PFT, 35–36

biological pump structure, 28CH4

causes, climate warming, 48–49net methane emissions, 48

chlorophyllNPP reduction, 34SeaWiFS data, 33–34

comments, 51iron and dust, 47microbial plankton, 30N2

Anammox denitrification, 43atmospheric concentration,

CO2 and N2O, 44availability vs. biosphere ability, 43–44cycle, 42–43

N and P mobilisation, 41nitrate availability, 40–41N2O and halocarbons, 49O2

OAEs, 38OMZs, 39reduction and decadal variability, 39–40

oceanicatmospheric oxygen and carbon fixation, 28light availability, 28–29plankton, 29and terrestrial ecosystems, 29–30

phosphorus, 45phyto-and zooplankton, 31–32plankton migration, 37–38silicon, 45–46

Greenland ice sheetIPCC AR4 report, 88, 89warmer temperature, 88

Grey nurse shark, 304

H

Habitat loss, chondrichthyans, 306

I

Illegal, unreported and unregulated (IUU) fishingAFZ and Indonesian vessels, 303–304high seas/distant water, 303shark population, 342

Inshore breeding ground reproduction

404 Subject Index

air and ocean temperaturebreeding grounds, 170hatchling production, 169life-history stages, 171mechanisms, 172

ocean–atmosphere patterns, 175–176rainfall, storms and cyclones, 173–174sea level, 174–175

Intergovernmental Panel on Climate Change(IPCC), 5, 9–14, 24, 26, 27, 52, 62, 70, 92,103, 106, 166

IUU fishing. See Illegal, unreported andunregulated fishing

J

Juveniles and adultsforaging, ocean water

ocean–atmosphere patterns, 180ocean temperature, 176–179wind and currents, 179–180

inshore foraging groundsocean–atmosphere patterns and

acidification, 183ocean temperature, 180–181rainfall, storms and cyclones, 181–182sea level, 182

L

Last glacial maximum (LGM)determination, barite measurement, 61sea levels, 186

Life history traits, chondrichthyans, 329

M

Marine turtle vulnerabilityadaptation and resilience

climate change, 188role, temperature, 187

beach nourishment, 190biology and life history

hatchlings, 156thermoregulatory capacity, 155types, 154

climate change, 163–164, 189embryos and hatchlings

air temperature, 164–167rainfall, storms and cyclone, 167–168sea level and atmospheric patterns, 169

genetic approaches, 190–191inshore breeding grounds reproduction

air and ocean temperature, 169–172ocean–atmosphere patterns, 175–176rainfall, storms and cyclones, 173–174sea level, 174–175

juveniles and adultsforaging ocean water, 176–180inshore foraging grounds, 180–183

oceanic migrationlong-distance movements, 184wind and currents, 185

oceans and atmosphereacidification, 162–163large-scale patterns, 162rainfall, storms and cyclones, 160–161sea level, 161temperature, 159–160wind and, 161–162

past climate changeforaging habitat, 187tropical sea surface temperatures, 186

trends, 189Meridional overturning circulation (MOC)

density-driven circulation and THC, 18forcing mechanisms, 17North Atlantic/Arctic

Arctic/Subarctic measurement, 19–20subtropical measurement, 18–19

reduction and NW Europe cooling, 21Southern Ocean/Antarctica, 20–22upwelling

eastern boundary regions, 22Pleistocene glaciations, 23role, 22–23

Minimum viable population (MVP)definition, 289estimation, 337, 343

MOC. See Meridional overturning circulationMovement and activity, Atlantic cod

adultmigration to spawning, 219–220Northeast Atlantic, 220–221residence and homing behaviour, 220

larval dispersal, 222thermal habits, 221–222

N

Net primary production (NPP)and global chlorophyll, 33reductions, 34

North Atlantic oscillation (NAO)Atlantic inflow, 86vs. biological response, 236

North Sea cod, status and recovery, 249–250Nutrients

iron and dust, 47nitrogen, 42–44phosphorus, 45silicon, 45–46

O

Ocean acidificationbuffering, climate change

atmospheric CO2 concentration, 63–64DIC increase, 64–65

Subject Index 405

Ocean acidification (cont.)Revelle factor, 64

CO2

dissolution, 67–69formation, 65–67pump, 73–75uptake, 69–70

comments, 79nutrients, 75–76palaeo-comparisons

air bubbles, polar ice core, 76Phanerozoic seafloors, 77–78silicate minerals weathering, 77

projected future levels, 70–71regional variation

benthos, 73coral reefs, 72–73plankton, 71–72

Ocean anoxic events (OAEs), 38Oceans and atmosphere

acidification, 162–163air temperature, 159–160large-scale patterns, 162rainfall, storms and cyclones, 160–161sea level, 161wind and, 161–162

Oceans impact, climate changeacidification

buffering, 63–65CO2, 65–75comments, 79nutrients, 75–76palaeo-comparisons, 76–79projected future levels, 70–71regional variation, 71–73

activities, 11Arctic and seas adjacent

Arctic Ocean and Subarctic Seas, 80–81comments, 93ecosystems, 91–92Greenland ice sheet, 88ice formation, 83–84methane hydrates, 88, 90–91modelling, 92–93river runoff, 83sea-ice cover, 84–87sub-polar seas circulation, 82–83trigger factors, sea-ice reductions, 86

circulation, 6–7climate models

CO2, 112–113comments, 114–115heat transport, 109–110heat uptake, 106–108ocean–climate feedbacks, 106retro-modelling, past climate change, 113–114sea ice, 111–112water cycle, 111

CO2

biological pump, 56–57carbonate counter pump, 57–58continental shelf pump, 57cycle, 51–54role, 58solubility pump, 54–56storage and transfer, 7

comments, 26–27, 61–62destabilisation

glaciers, 25ice sheet, Greenland and East Antarctic,

25–26elements, ocean–climate interactions, 10fertilisation, 61global and regional information, 59–60heat, 6IPCC AR4 reports, 12–13microbes role, 9MOC

density-driven circulation and THC, 18forcing mechanisms, 17North Atlantic/Arctic, 18–20reduction and NW Europe cooling, 22Southern Ocean/Antarctica, 20–22upwelling, 22–23

natural climate variability, 13nutrients, 9–10observation programmes, 12plankton productivity, oxygen content and

upwelling, 9polar regions, 8–9primary production, global

aerosols, 49–50benthos, 36–37biodiversity functional groups, 34–36biological pump structure, 28CH4, 47–49chlorophyll, 33–34comments, 51iron and dust, 47microbial plankton, 30–31N2, 42–44N and P mobilisation, 41nitrate availability, 40–41N2O and halocarbons, 49O2, 38–40oceanic, 28–30phosphorus, 45phyto- and zooplankton, 31–32plankton migration, 37–38silicon, 45–46

recommendationsacidification, 121–122Arctic Ocean, 122–123CO2, 120–121freshening waters, 117Greenland ice sheet, 123

406 Subject Index

methane, 123MOC and NW Europe cooling, 118modelling, 124–125nutrients, 120O2, 119ocean circulation and sea level changes,

117–118primary production, biodiversity and

non-native species, 119Southern Ocean, 123–124tropical storms, 118warming waters, 116–117

relationship, nutrients and climate change, 11salinification

evaporation/precipitation, 16south-to-north vertical section vs. western

Atlantic basin, 15–16vs. temperature, 16

sea level risecauses, 24effects, 10frequency/intensity, weather, 25regional changes, 24–25

Southern Oceancomments, 105–106future evolution, 103–105observed changes, 97–103role, 94–97

species biodiversitybenthos and sea bottom sediment, 59plankton, 58

temperatureheat content, 14–16SST, 13–14

tropical stormsAtlantic hurricane activity, 24intensity, 7role, 23

WWF workshop, 10–11Ocean temperature

heat contentclimate models, 15–16upper-ocean warming, 14–15XBT data, 14

SSTdecadal and regional variability, 13–14warming, 13

Oxygenminimum zones (OMZs), 39, 41, 117, 120

P

Pacific and Atlantic open-ocean fisheries, 294,299

Pacific decadal oscillation (PDO), 13Particulate inorganic carbon (PIC), 52, 56, 57, 72Particulate organic carbon (POC), 44, 52, 56, 57Plankton functional types (PFTs), 35–36Pollution and non-indigenous species

oil spills and leaks, 307ships ballast water, 307–308water, 306–307

Population viability analyses (PVA), 289, 337, 340Prestige oil spill effects, marine biota

adtidal, 373benthos

rocky intertidal, 376–380sandy intertidal, 381–382sublittoral, 382subtidal areas, 376

biological responses, 387–389clean-up procedure, 372–373direct lethal and sublethal, 367–368effects degree, 371–372fishing resources

biomarker, 383–384PAH level, 384sandeel, 383

Galicia, economic loss, 366–367impacts assessment, 372indirect, 368, 371mammals and turtles, 386oil components, 367oil tanker spills, 369–371physicochemical properties, 368plankton

acute effects, 373–374embryogenesis, 375WSF, 376zooplankton, 374

recovery process, 371seabirds

adaptive responses, 386affected species, 384breeding, 385oil accumulation, 384–385

R

Rays. See also Chondrichthyesglobal catch, 285pelagic longline fisheries, 299pup production, 284Queensland beach-meshing programme, 305and sharks, 307

S

Salinificationevaporation/precipitation, 16south-to-north vertical section vs. western

Atlantic basin, 15–16vs. temperature, 16

Sea level risecauses, 24effects, 10frequency/intensity, weather, 25regional changes, 24–25

Subject Index 407

Sea surface temperature (SST)Atlantic hurricane activity, 24CO2 reduction, 7decadal and regional variability, 13–14global, 26in ice reduction, 88isotherm, leatherback turtles, 176tropics and Indian Ocean, 23warming, 13

Sea-viewing wide field-of-view sensor(SeaWiFS), 33–35, 59

Sharks. See also Chondrichthyes; Fishing,chondrichthyes

attacks, 305blue sharks, 288, 299commercial catch report, FAO, 304global distribution, 287incidental catch, 297landing 1930–196, 295legal and illegal harvest, 286population management, 343pup production, 284and rays, 307role

diversity and ecosystem, 333pelagic ecosystems, 334

targeted fisheries, 291–297threatening processes, 280white sharks, 302

Southern annular mode (SAM), 55, 98Southern ocean and climate

comments, 105–106future evolution

Antarctic glaciers, 105CO2 sink, 104planetary-scale climate change, 103

observed changesAntarctic krill, 101circumpolar deep sea water, 101CO2 emissions, 99higher snowfall and glacier flow, 102–103low-lying ice shelves, 102sea-ice extent, Bellingshausen Sea, 100temperature differences, 98tidewater glaciers, Peninsula, 101wind field, SAM, 98

roleACC currents, 94–95biological productivity, 97global ocean circulation, 95–96lower and upper limb, MOC, 95–96

mode waters, 96regional geography, 93–94water column inventories, 96–97

Spawning, Atlantic cod, 215Spawning stock biomass (SSB)

Allee effects, 247fishing, 242–243and fish recruitment, 234fish stock assessment, 245–246North Sea, 234, 247

Species biodiversitybenthos and sea bottom sediment, 59plankton, 58

SST. See Sea surface temperature

T

Teleost threat risk, 322Tiger sharks, 302, 335Trophic cascades, 330Tropical storms

Atlantic hurricane activity, 24intensity, 7role, 23

Turtles, marineadaptation and resilience, 187–188biology and life history, 154–159climate change impacts

embryos and hatchlings, 164–169inshore foraging, juveniles and adults,

180–183juveniles and adults foraging, 176–180oceanic migrations, 184–185reproduction, inshore breeding grounds,

169–176IUCN Red List, 189oceans and atmosphere changes

acidification, 162–163air and temperature, 159–160large-scale patterns, 162rainfall, storms and cyclones, 160–161sea level, 161wind and ocean currents, 161–162

past climate change, 185–187

W

Water-soluble fraction (WSF), 375–376, 384West Antarctic ice sheets (WAIS), 26White sharks, 302Worldwide Fund for Nature (WWF), 10

408 Subject Index

15

10

5

0

−5

−101950

Oce

an h

eat c

onte

nt (

×10

22J)

1960 1970

Agung Chichon Pinatubo

1980 1990 2000

Philip C. Reid et al., Figure 1.2 Upper-ocean heat content (grey shading indicates anestimate of one standard deviation error) for the upper 700 m relative to 1961. Thestraight line is the linear fit for 1961–2003. The global mean stratospheric optical depth(Ammann et al., 2003) (arbitrary scale) at the bottom indicates the timing of majorvolcanic eruptions. The brown curve is a 3-year running average of these values,included for comparison with the smoothed observations. Figure modified fromDomingues et al. (2008).

0.5

0.1

0.05

0.03

0.015

−0.015

−0.03

−0.05

−0.1

−0.5

60�N

50�N

40�N

30�N

20�N

10�N

−10�S

−20�S

−30�S

−40�S

−50�S Eq

6000

5000

4000

3000

Dep

th b

elow

sea

sur

face

(m

)

Salinity difference (psu)

2000

1000

0

AAIW

UCDW UNADW

SMW

MOW

LSW

AABW

NEADW

LNADW DSOW

Philip C. Reid et al., Figure 1.3 South-to-north vertical section of salinity versus depthfor the western Atlantic basin, plotted as Salinity difference averaged for the period1985–1999 minus 1955–1969. Grey colour means that sampling was not sufficient toestimate mean salinity. Acronyms are for the different water masses; see original paper.From Curry et al. (2003).

30

20

10

MO

C s

tren

gth

(Sv)

01950 1960 1970 1980 1990 2000 2010

Philip C. Reid et al., Figure 1.4 Mean strength of the Atlantic MOC at 26.5 �Nbetween 1957 and 2005 and associated error bars. Blue data points are for measure-ments taken from ships (Bryden et al., 2005). The red data point is an average ofobservations taken in the first full year of the RAPID monitoring array, plus error bar(Cunningham et al., 2007). Units are Sv (1 Sv ¼ 1 million m3 s�1 of water passing the26.5 �N line). Values indicate a northwards net transport for water shallower than1000 m.

Philip C. Reid et al., Figure 1.5 Estimates of freshwater flux relative to S ¼ 34.8* inArctic and Subarctic Seas as determined during the ASOF project. Units are mSv andthe base map is a snapshot of modelled sea surface height courtesyW. Maslowski, NPS,Monterey (1 mSv ¼ 31.546 km3 year�1; * the numbers for PE, runoff and ice melt areindependent of the choice of reference salinity). From Dickson et al. (2007).

120�W60�W80�N

60�

40�

20�

0�

20�

A

B

40�

60�

80�N 60�W 0� 60�E 120�E 180� 120�W

60�

40�

20�

0�

20�

40�

60�

80�S

180�120�E60�E0�

80�S

Philip C. Reid et al., Figure 1.6 (A) Location of mode and intermediate waters in theglobal ocean. Low-density mode waters of the eastern subtropical gyres—pink. Thehighest density mode waters, which subduct in the subtropical gyres—red. AtlanticSub-polar Mode Water, North Pacific central mode water and Subantarctic ModeWater (SAMW)—dark red. (B) Covering a large area of the ocean, intermediate watersare found below the mode water, Labrador Sea intermediate water (LSW)—blue,North Pacific intermediate water (NPIW)—pale green, Antarctic intermediate water(AAIW)—green. These waters eventually re-emerge at the surface far from theirorigin. Primary formation areas for the intermediate waters are indicated with redcrosses. From Talley (1999): http://www-pord.ucsd.edu/�ltalley/papers/1990s/agu_heat/talley_agu_heat.html.

−180 −90−90

−45

0

Latit

ude

(deg

)

45

90

0

SeaWiFS global chlorophyll a (mg/m3)

Longitude (deg)90 180

0.01

0.03

0.10

0.30

1.00

3.00

10.0

>10.0

Philip C. Reid et al., Figure 1.8 Global image of mean surface chlorophyll for theperiod 1998–2007. Processed from SeaWiFS data by Takafumi Hirata, PML.

0�80�S

40�S

40�N

80�N

0�

90�E 90�W 0�

Ice

SP

LL-U

ST-SS

ST-PS

Eq-U

Eq-D

180�

Biome definitions

Philip C. Reid et al., Figure 1.9 The distribution of six different ocean biomes:(1a) equatorial—downwelling (Eq-D), (1b) equatorial—upwelling (Eq-U), (2) subtropicalgyre—permanently stratified (ST-PS), (3) subtropical gyre—seasonally stratified (ST-SS),(4) low latitude—upwelling (LL-U), (5) sub-polar (SP) and (6) marginal sea ice (Ice).From Sarmiento et al. (2004).

50

30

10

−10

−30

−50

−70

0 20 40 60 80 100

Oct 1909–Oct 2002ERSST v2

120 140 160 180 200 220 240 260 280 300 320 340 360

Philip C. Reid et al., Figure 1.10 Map showing modelled difference in nitrate avail-ability based on a temperature nitrate relationship, between October 1909 and 2002.Darker colours represent greater contrasts between the years. From Kamykowski andZentara (2005a,b). Green, nitrate in 1909 present at the surface > 2002; red, nitrate in2002 present at the surface > 1909; blue, stratification in 1909 between nitracline andsurface < 2002; grey, stratification in 1909 between nitracline and surface > 2002.

0�

100100

100

100

100200

200

100

50

50

100200

200

50

50

200

100

100

200

50

50

50

100

200

200

120� 240�

60�

0�

60�

240�120�0�

60�

0�

60�

Philip C. Reid et al., Figure 1.13 Annual production of biogenic silicon in the oceans(g m2 year�1). Source www.radiolaria.org

Surface methane (ppmv)

1.6 1.66 1.72 1.78 1.84

Philip C. Reid et al., Figure 1.14 Global map of surface methane concentrations. FromNASA: Credit: GMAO Chemical Forecasts and GEOS GHEM NRT Simulations forICARTT.

February

August

30� 60� 90� 120�150�180�150�120� 90� 60� 30� 0�80�

70�60�

50�

40�30�

20�

10�

0�

10�

20�

30�

40�

50�

60�70�

80�0�30�60�90�120�150�180�150�120�90�60�30�

80�70�

60�

50�

40�

30�

20�

10�

0�

10�

20�

30�

40�

50�

60�70�

A

B

80�

30� 60� 90� 120�150�180�150�120� 90� 60� 30� 0�80�

70�60�

50�

40�30�

20�

10�

0�

10�

20�

30�

40�

50�

60�70�

80�0�30�60�90�120�150�180�150�120�90�60�30�

2008 Apr 1 13:54:09

−9 −8 −7 −6 −5 −4 −3 −2 −1 0

Net flux (gC m−2 month−1)

1 2 3 4 5 6 7 8 9

80�70�

60�

50�

40�

30�

20�

10�

0�

10�

20�

30�

40�

50�

60�70�

80�

GMT

Philip C. Reid et al., Figure 1.15 Climatological mean distribution of CO2 flux (g Cm�2 month�1) between the air and sea or vice versa for February (A) and August (B) inthe reference year 2000. The wind speed data are from the 1979–2005 NCEP/DOEAMIP-II Reanalysis, and the gas transfer coefficient is computed using a (wind speed)squared dependence. Positive values (yellow–orange–red) indicate sea-to-air fluxes,and negative values (blue–magenta) indicate air-to-sea fluxes. Ice field data are fromNCEP/DOE-2 Reanalysis Data (2005). An annual flux of 1.4 � 0.7 Pg C year�1 isobtained for the global ocean by a summation of 12 monthly maps that were producedfrom approximately 12 million measurements. Figure from Takahashi et al. (2009).

80�N LGM > CTL LGM = CTL LGM < CTL LGM ? CTL

40�N

0�N

40�S

100�E 160�W 60�W 40�E

100908070605040302010

0−10−20−30−40−50−60−70−80−90

−100

Philip C. Reid et al., Figure 1.17 Observed (superimposed circles) and modelledchanges in export at the last glacial maximum (LGM) compared to the late Holocene(Bopp et al., 2003). Model results are in percent. Observations are qualitative only andindicate a higher (red), lower (blue) or similar (white) export in the LGM compared tothe present day. From Le Quere et al. (2005).

80�N

40�N

0�

40�S

80�S

50�E 150�E 110�W 10�WModel

Aragonite saturation depth Depth(m)

Depth(m)

A

B

3500

3250

3000

2750

2500

2250

2000

1750

1500

1250

1000

750

500

250

0

80�N

40�N

0�

40�S

80�S

50�E 150�E 110�W 10�WGLODAP

3500

3250

3000

2750

2500

2250

2000

1750

1500

1250

1000

750

500

250

0

Philip C. Reid et al., Figure 1.19 Depth of aragonite saturation horizon: lower mapfrom measurements recalculated from GLODAP after Key et al. (2004) and upper mapmodelled calculations. Figure from Gangstø et al. (2008).

A

C

E F

D

B

4.5

Equatorial area

Global ocean

High latitudes

80�N

40�N

40�S

80�S

80�N

40�N

40�S

80�S

80�N

40�N

40�S

80�S

50�E 150�E 110�W 10�W

0�

80�N

40�N

40�S

80�S

0�

50�E 150�E 110�W 10�W

0�

0�

80�N

40�N

40�S

80�S

0�

3.5

2.5

1.5

0.51900 1950 2000 2050 2100

1861

50�E 150�E 110�W 10�W

2050

50�E 150�E 110�W 10�W

2100

2000

50�E 150�E 110�W 10�W

2075

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

54.543.532.521.510.50

Mean omega aragonite

Philip C. Reid et al., Figure 1.20 Saturation state with respect to aragonite of surfacewaters (0–100 m): (A) time series of mean O for the global ocean, the equatorial areaand for high latitudes, and maps in year (B) 1861, (C) 2000, (D) 2050, (E) 2075 and (F)2100. Figure from Gangstø et al. (2008).

18018090

70

60

50

30

10

0

10

30

50

60

70

90Neretic

Abyssalclay

Calcareous oozeForaminifera Pteropod RadiolarianDiatom

Silicious ooze

Oceanic

150150 120120 9090 6060 3030 0

Philip C. Reid et al., Figure 1.22 Global map of the distribution of different sedimenttypes on the bottom of the ocean. Source: www.radiolaria.org.

WaterH2OH2

18OHDO

AirCO2CH4d15Nd40Ard18O...

ImpuritiesDust,sea salt,10Betrace elem.pollution,volcanism....

Philip C. Reid et al., Figure 1.24 Bubbles of air in polar ice observed in a thin sectionunder polarised light. Text redrawn from Raynaud D. EPICA lecture (2008 OceanSciences Meeting, Orlando, USA). Image: Copyright Michel Creseveur, CNRS/LGGE.

Bathymetric and topographic tints

(M)

0 25 50 75 100 200 300 400 500 600 700 800 1000 1500

Scale :Map projection:Standard parallel:Horizontal datum:

Varies with plot sizePolar stereographic

WGS 84 200

200 600

Kilometres (75�N)

0

0Nautical miles (75�N)

400

60�

90�

120�

150�180�150�

120�

90�

60�

30� 0� 30�

Glaciers larger than 90 km2 were plotted in whiteirrespective of elevation using the same shadingparameters as in the rest of the map.

75�N−5000 −4000 −3000 −2000 −1500 −1000 −500 −250 −100 −75 −50 −25 −10

Philip C. Reid et al., Figure 1.26 Map showing the geographical features and bathym-etry of the Arctic Ocean and adjacent seas. From Jakobsson et al. (2008).

0.08

0.06

0.04

�C p

er y

ear

0.02

0.00

120 100

SAT anomalies (�C)

Trend 0.94 �C/100years

80 60 40 20 0

Number of years before 2001

−0.02

Philip C. Reid et al., Figure 1.27 Surface atmosphere air temperature trends (�C peryear) averaged for the Arctic (green) and Northern Hemisphere (red) ( Jones et al.,1999) with 95% significance as dashed lines from Polyakov et al. (2002).

Lomonosovridge

Fram strait

Greenland gyre Icelandsea

Denmarkstrait Atlantic ocean

Surface water

Intermediate water

Deep water

Eurasian basinCanadian basin

Bering strait

Philip C. Reid et al., Figure 1.28 Schematic of Arctic circulation (ACIA, 2005).

16� 106

14

12

10

8

200720082009Unfiltered 2009Average of monthly sea-ice 1979−2007± 1 STD of monthly sea-ice

Uni

t:mill

ion

Sq.

km

6

4

2

The latest date in 2009 is march 31

Jan

Feb

Mar

Apr

May Jun 11 21 Jul

Aug

Sep Oct

Nov 11 21

Dec 11 22 Jan11 2211 2111 2211 2211 22 10 11 11 11 22212220

ICE_EXT, NORSEX SSM/I

Philip C. Reid et al., Figure 1.31 Extent of Arctic sea-ice (area of ocean with at least15% sea-ice) in 2007, 2008 and part of 2009 with the long-term average. Source:Nansen Environmental and Remote Sensing Center, via the Arctic-ROOS web site(http://arctic-roos.org).

Moles m−2

0 20 40 60 80

90�E 90�W 0�180�

60�N

30�N

30�S

60�S

EQ

60�S

30�S

30�N

60�N

EQ20

10 20

20

30 40

30

40607080

30

10 40

Philip C. Reid et al., Figure 1.36 Water column inventories of anthropogenic CO2 inthe ocean. Note in particular the band of high levels flanking the northern side of theACC, associated with mode and intermediate waters. Dissolved CO2 is lost tothe atmosphere south of the Polar Front, where NADW wells up to the surface closeto the coast (purplish colours) and gained from the atmosphere north of the Polar Frontwhere mode waters and intermediate waters sink in the subduction process (greencolours), making the Southern Ocean both a source and a sink for atmospheric CO2.From Sabine et al. (2004a).

−0.05 −0.04 −0.03 −0.02 −0.01 0

Temperature trend (�C per year), 1955−1998

0.01 0.02 0.03 0.04 0.05

0 m 20 m

100 m50 m

80�S

80�S

80�S70

�S60�S50

�S

40�S

70�S60

�S

50�S

40�S

120�W

100�W80�W 60�W 40�W

20�W

0�

80�S70

�S60�S

50�S

40�S

70�S60

�S

50�S

40�S

120�W

120�W

100�W80�W 60�W 40�W

20�W

0�

100�W80�W

60�W

40�W20�W

0�

120�W

100�W80�W 60�W 40�W

20�W

0�

Philip C. Reid et al., Figure 1.38 Trends in temperature during the second half of thetwentieth century in the vicinity of the Antarctic Peninsula. Four different depth levelsare shown, namely the surface, 20, 50 and 100 m. Note the strong, surface-intensifiedwarming at the western side of the Peninsula. From Meredith and King (2005).

�C

−1.0 −0.5 0.0 0.5 1.0

30�W

60�W

90�W

120�W

150�W 150�E

120�

E

90�E

60�E

30�E

Philip C. Reid et al., Figure 1.37 Temperature differences in the Southern Oceanbetween the 1990s and earlier decades, at approximately 700–1100 m depth. Note inparticular the marked warming around the circumpolar band. Figure from Gille (2002).

ANN

−0.3

−0.2

−0.1 0

0 0.1

0.2

0.3 �C per decade

0.35

0.15

0.20

0.25

0.300.35

0.350.300.250.15

0.10

0.15

0.15

0.200.2

0.20

0.15

0.20

0.350.30 0.25

0.15

0.20

0.100.20

0.25

0.3

0.15

Philip C. Reid et al., Figure 1.39 Predicted trends in surface temperatures over thenext 100 years from a weighted average of the 20 coupled models used in IPCC AR4.Note the ubiquitous Southern Ocean surface warming, with ocean ‘hotspots’ in theWeddell and Ross Seas. From Bracegirdle et al. (2008).

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