28/03/13

Open research data = win-winTom Webb | @tomjwebb | t.j.webb@sheffield.ac.uk | www.sheffieldmeme.org

Disclaimer…

✤ I’m an ecologist

✤ I’m not an open data scholar

✤ The plural of ‘anecdote’ may not be ‘data’, but is could be this talk about data…

Towards policy-relevant ecologyIt’s a matter of scale…

0

0.2

0.4

0.6

0.8

1

Pro

port

ion

of

pap

ers

1988Year

Other

Biogeographical

Regional

National

Local

1989 1990 1991 1992 1993 1994 1995 1996 1997

CHAPTER 1

10

papers in the 10-year period 1988–97 (Fig. 1.13). The second largest category is usually ‘other’, which includes all those studies that cannot be categorizedby spatial scale. Large-scale studies (lumping regional, national and bio-geographical categories) generally contributed only between 10 and 15% of the papers published in Ibis in any one year, and just over 10% of the papers in total. There is no hint that this proportion has been increasing over the last decade.

This emphasis on small spatial scales is typical of ecology in general(Kareiva & Andersen 1988; May 1994a; Baskin 1997; Lawton 1999). In a similarvein, most ecological studies are of very short duration, usually two or threeyears at the most (Weatherhead 1986; Tilman 1989; Elliott 1994; Malmer 1994;Baskin 1997). Most focus on just a few species, and there is some evidence that both the proportion of community studies and the number of species per

Fig. 1.13 The proportion of papers in the journal Ibis in the 10-year period 1988–97concerning different spatial scales. This classification does not include short communications(comments) or papers in supplements. Studies were classified as ‘local’ if they wereperformed over restricted areas (e.g. at well-defined sites), or if they were performed at a few reasonably well-separated sites but this separation was irrelevant to the aim of thestudy. Thus, the paper by Yamagishi and Eguchi (1996) on the comparative foraging ecologyof Madagascan vangids was classified as local, even though it involved work at several well-separated sites. The separation was irrelevant to the study, which could equally well havebeen carried out at one site had all the vangid species been present. By contrast, Matthysen’s(1997) study of geographical variation in nuthatch song types, which was carried out at ninesites in northern Belgium, was classified as regional, because here the site separation wasrelevant. ‘Regional’ studies were those concerning scales roughly equivalent to an English orAmerican county, or a restricted part of a country. The ‘national’ scale refers to studies acrossregions roughly equivalent to whole countries, whereas ‘biogeographical’ studies considermultinational, continental or global scales. Studies that could not readily be assigned to anyclass in this scheme, or for which scale was not relevant, were lumped into the ‘other’category. These principally comprised taxonomic, experimental and review papers.

Scale in Ecology

✤ Most studies are small scale, short term

✤ Most societally relevant questions are large scale, long term

Policy relevant

Tractable to individual researcher

Policy relevantProject lifespan

Gaston & Blackburn 2000 Pattern & Process in Macroecology (Blackwell); Tilman 1989 pp136-157 in Likens (ed) Long-Term Studies In Ecology (Springer)

Space

Time

Beck et al. (2012). What's on the horizon for macroecology? Ecography doi:10.1111/j.1600-0587.2012.07364.x6-EV

macroecological perception is dominated by biodiversity patterns and inferences about underlying drivers at large grain sizes ( 100 km2), and there is a wide-spread believe in the scale invariance of these findings (Rahbek 2005). !is is astonishing as even early macroecological works demonstrated that, among relatively similar, large grain sizes, results might nonetheless vary significantly (Kaufman and Willig 1998, Rahbek and Graves 2001). More recently, comprehensive reviews have demonstrated that the di"erences increase when medium or small grain sizes are included (Rahbek 2005, Field et al. 2008). While considering coarse-grained data might be su#cient for

Generally, ecologists acknowledge that ecological processes act at di"erent spatial scales (Turner and Tjørve 2005), and thus the patterns detected and their underlying processes will normally be scale-dependent (Willig et al. 2003). ‘Scale’ refers to both ‘extent’ and ‘grain’ (Shmida and Wilson 1985, Rahbek 2005). While macroecology essentially considers large extent, this can be combined with coarse or fine grain. However, data at large extent derived from distribution atlases, as they are typically applied in macroecology, pri-marily have large grain sizes (Robertson et al. 2010). Hence, studies with a small grain but covering a large spatial extent are extremely scarce (Fig. 5). !erefore, up to now the

Extent

regional national multi-national continental multi-continental global

plot or trap

site or population

< 1 m!

1 m! " < 10 m!

10 m! " < 100 m!

100 m! " < 1000 m!

1000 m! " < 10 000 m!

1 ha " < 10 ha

10 ha " < 100 ha

1 km! " < 10 km!

10 km! " < 100 km!

100 km! " < 1000 km!

1000 km! " < 10 000 km!

10 000 km! " < 100 000 km!

>= 100 000 km! Frequency

1

5

10

Figure 5. Extent and grain sizes used in macroecological studies published between 2007 and 2009 (for details on the literature search see Supplementary material Appendix 4). Dot size represents the number of studies conducted for a given extent and grain size. Dot size varies continuously; the legend shows frequencies 1, 5, and 10 for orientation. Studies that did not use a defined grid but sampled single sites, populations, or traps are given separately in the two bottom rows.

0%

5%

10%

15%

20%

25%

30%

35%

Europe Asia

North America

South AmericaAfrica

Australia and

Oceania Antarctica

Proportion areaProportion paper

Terrestrial65%

Limnic8%

Marine27%

Figure 4. Distribution of macroecological papers in ISI Web of Science (3 April 2010) regarding terrestrial, limnic, and marine habitats (pie chart). !e bar chart depicts the geographic distribution of the terrestrial studies to continents and relates this to the proportional surface of each continent (for details on the literature search, see Supplementary material Appendix 3).

Gra

in

Macroecology to dateGrain versus Extent

Consuming open dataSharing data to fill the gaps

Nerc Marine Ecosystems Call

✤ Large consortium project, 4 years, ~£4M

✤ Budget for research cruises

✤ BUT: Nowhere near enough money to thoroughly sample even one region

✤ ONLY OPTION is to collate and use existing - available - data

MacroBen

✤ Developed within EU Network of Excellence MarBEF

✤ Integration of 44 datasets, c. 0.5M distribution records, >7K taxa, >22K sampling stations

✤ A robust process of QC, excellent metadata provision

MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 382: 287–296, 2009doi: 10.3354/meps07754

Published April 30

INTRODUCTION

Macroecology draws on insights from fields includingecology, biogeography, palaeontology, macroevolutionand applied statistics to understand how large-scaleprocesses affect the organisation of ecological systemsat multiple scales (Brown 1995, Gaston & Blackburn2000, Blackburn & Gaston 2006). It has defined noveland important concepts and methodological techniquesto describe the form and structure of large-scale eco-logical patterns and has developed in a relatively shorttime into a thriving and productive discipline (Gaston &

Blackburn 2000, Blackburn & Gaston 2003). The impor-tance of a macroecological approach becomes still moreapparent with the realisation that human impacts onecological systems are detectable at the same verylarge scales that interest macroecologists (Chapin et al.2000, Kerr et al. 2007), and that many of the most press-ing issues in applied ecology involve very generalquestions relating to habitat modification, invasive spe-cies, over-exploitation, pollution and climate change(Sutherland et al. 2006). In a marine context, consider-able large-scale changes in ecosystems have alreadyoccurred without rigorous documentation (Jackson

© Inter-Research 2009 · www.int-res.com*Email: t.j.webb@sheffield.ac.uk

Addresses for other authors are given in the Electronic Appen-dix at www.int-res.com/articles/suppl/m382p221_app.pdf

Macroecology of the European soft sediment benthos: insights from the MacroBen database

T. J. Webb1,*, I. F. Aleffi, J. M. Amouroux, G. Bachelet, S. Degraer, C. Dounas, D. Fleischer, A. Grémare, M. Herrmann, H. Hummel, I. Karakassis, M. Kedra, M. A. Kendall, L. Kotwicki, C. Labrune, E. L. Nevrova, A. Occhipinti-Ambrogi, A. Petrov, N. K. Revkov, R. Sardá, N. Simboura, J. Speybroeck, G. Van Hoey,

M. Vincx, P. Whomersley, W. Willems, M. W8odarska-Kowalczuk

1Department of Animal & Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK

ABSTRACT: Macroecology provides a novel conceptual framework for analysis of the distributionand abundance of organisms at very large scales. Its rapid development in recent years has been dri-ven primarily by studies of terrestrial taxa; the vast potential of marine systems to contribute to themacroecological research effort remains largely untapped. International collaborative efforts such asMarBEF have provided fresh impetus to the collation of regional databases of species occurrences,such as the newly available MacroBen database of the European soft sediment benthic fauna. Here,we provide a first macroecological summary of this unique database. We show that in common withalmost all previously analysed assemblages, the frequency distribution of regional site occupanciesacross species in the MacroBen database is strongly right-skewed. More unusually, this right skewremains under logarithmic transformation. There is little evidence for any major differences betweenhigher taxa in this frequency distribution (based on the 8 animal classes for which we have sufficientdata). Indeed, considerable variation in occupancy persisted across the taxonomic hierarchy, suchthat most variation occurred between species within genera. There was a weak positive relationshipbetween local population density and regional occupancy across species, but this abundance–occu-pancy relationship varied considerably between higher taxa and between geographical areas. Ourresults highlight the potential of databases such as MacroBen to consolidate macroecological gener-alities and to test emerging theory.

KEY WORDS: Marine macroecology · Macrobenthic · Europe · Large marine ecosystems · Species–range size distributions · Phylogeny · Abundance–occupancy relationships

Resale or republication not permitted without written consent of the publisher

Contribution to the Theme Section ‘Large-scale studies of the European benthos: the MacroBen database’ OPENPEN ACCESSCCESS

T.J. Webb1

OBIS

✤ Marine species occurrence data from all of the world’s oceans

✤ Open access via www.iobis.org

✤ 35.5M records, >1,000 datasets, c.150,000 species, global coverage

LETTERS

Global patterns and predictors of marine biodiversityacross taxaDerek P. Tittensor1, Camilo Mora1, Walter Jetz2, Heike K. Lotze1, Daniel Ricard1, Edward Vanden Berghe3

& Boris Worm1

Global patterns of species richness and their structuring forceshave fascinated biologists since Darwin1,2 and provide critical con-text for contemporary studies in ecology, evolution and conser-vation. Anthropogenic impacts and the need for systematicconservation planning have further motivated the analysis ofdiversity patterns and processes at regional to global scales3.Whereas land diversity patterns and their predictors are knownfor numerous taxa4,5, our understanding of global marine diversityhas been more limited, with recent findings revealing some strik-ing contrasts to widely held terrestrial paradigms6–8. Here weexamine global patterns and predictors of species richness across13 major species groups ranging from zooplankton to marinemammals. Two major patterns emerged: coastal species showedmaximum diversity in the Western Pacific, whereas oceanicgroups consistently peaked across broad mid-latitudinal bandsin all oceans. Spatial regression analyses revealed sea surface tem-perature as the only environmental predictor highly related todiversity across all 13 taxa. Habitat availability and historicalfactors were also important for coastal species, whereas otherpredictors had less significance. Areas of high species richnesswere disproportionately concentrated in regions with mediumor higher human impacts. Our findings indicate a fundamentalrole of temperature or kinetic energy in structuring cross-taxonmarine biodiversity, and indicate that changes in ocean temper-ature, in conjunction with other human impacts, may ultimatelyrearrange the global distribution of life in the ocean.

We compiled data on the global distribution of 11,567 speciesacross 13 different taxonomic groups (Table 1 and SupplementaryTable 1) and spanning 10 orders of magnitude in body mass. In

contrast to previous syntheses on latitudinal gradients9, our focuswas on groups where we could analyse two-dimensional spatialpatterns on a global scale. These included marine zooplankton(foraminifera and euphausiids), plants (mangroves and seagrasses),invertebrates (stony corals, squids and other cephalopods), fishes(coastal fishes, tunas and billfishes, oceanic and non-oceanic sharks),and mammals (cetaceans and pinnipeds). For each group, wemapped the global distribution of species richness and assessed theextent to which it covaried across taxa. We investigated furtherwhether observed patterns were consistent with mechanisms pro-posed to structure global-scale species diversity patterns, and howmarine richness overlapped with recently mapped cumulativehuman impacts across the world ocean10.

We found two distinct spatial patterns of marine species richness.Primarily coastal taxa had peaks of diversity in the western Pacificand showed clear latitudinal gradients along the coasts of continents(Fig. 1a–g). Pinnipeds were an exception, peaking at higher latitudes(Fig. 1d). They depicted an interesting contrast to all other groupsowing to their low tropical diversity. Primarily oceanic taxa tended toshow pantropical or circumglobal distributions with diversity peak-ing at latitudes between 20u and 40u in all oceans (Fig. 1h–m).Correlations among diversity patterns supported this separation ofoceanic and coastal taxa (Supplementary Table 3).

Total species richness across taxa was mostly driven by fishes, themost diverse group we examined, with regional peaks in SoutheastAsia (Pacific), Southeast Africa (Indian) and the Caribbean (Atlantic)(Fig. 2a). By normalizing diversity for each taxon, then averagingacross all taxa present in each cell, we derived a synthetic pattern ofmean diversity (Fig. 2b). The highest mean diversity occurred in

1Department of Biology, Dalhousie University, 1355 Oxford Street, Halifax B3H 4J1, Canada. 2Department of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street,New Haven, Connecticut 06520-8106, USA. 3Institute of Marine and Coastal Sciences, Rutgers University, New Brunswick, New Jersey 08901-8521, USA.

Table 1 | Spatial modelling of species richness

Species group Speciesrichness

Per cent ofknown

SST SSTslope

Coastlinelength

Primaryproductivity

SSTrange

Oxygenstress

IndianOcean

PacificOcean

Pseudo R2

Primarily coastal speciesCoastal fishes 9,713 79 10.7*** 7.9*** 3.7** 4.5*** 0.71Non-oceanic sharks 480 100 7.1*** 2.4* 13.0*** 3.6** 22.5* 0.75Non-squid cephalopods 122 25 7.1*** 6.5*** 21.8* 22.8** 0.89Pinnipeds 36 100 210.0*** 4.3** 4.5*** 5.5*** 23.2** 0.88Corals 794 95 7.7*** 3.1** 3.8** 3.5** 0.73Seagrasses 60 100 4.4*** 4.3** 2.6* 2.0* 0.75Mangroves 32 60 9.3*** 2.0* 0.85Primarily oceanic speciesTunas and billfishes 12 63 7.0*** 3.1** 23.6** 0.76Oceanic sharks 27 100 11.8*** 5.8*** 0.81Squids 85 25 4.0** 2.7** 0.88Cetaceans 81 96 6.6*** 12.1*** 0.89Euphausiids 86 100 6.6*** 3.9** 3.4** 27.8*** 0.85Foraminifera 39 88 16.6*** 3.3** 22.8** 22.3* 0.79

Number and completeness (per cent of known) of species by taxa and minimal-adequate SLM results for environmental correlates are given. Numbers are z-values; stars represent significance levelsat P , 0.05 (*), 0.01 (**) or 0.00001 (***). Ocean column z-values represent contrast against the Atlantic Ocean.

doi:10.1038/nature09329

1Macmillan Publishers Limited. All rights reserved©2010

Biodiversity’s Big Wet Secret: The Global Distributionof Marine Biological Records Reveals ChronicUnder-Exploration of the Deep Pelagic OceanThomas J. Webb1*, Edward Vanden Berghe2, Ron O’Dor3

1 Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom, 2 Ocean Biogeographic Information System, Institute of Marine and Coastal

Sciences, Rutgers University, New Brunswick, New Jersey, United States of America, 3 Census of Marine Life, Consortium for Ocean Leadership, Washington, D. C., United

States of America

Abstract

Background: Understanding the distribution of marine biodiversity is a crucial first step towards the effective andsustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us toassemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge ofparticular marine regions. In particular, the deep pelagic ocean – the largest biome on Earth – is chronically under-represented in global databases of marine biodiversity.

Methodology/Principal Findings: We use data from the Ocean Biogeographic Information System to plot the position inthe water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominatethis global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of theocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the seabed. Midwater biodiversity is drastically under-represented.

Conclusions/Significance: The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity’s bigwet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in theprovision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there isa pressing need to increase our knowledge of Earth’s largest ecosystem.

Citation: Webb TJ, Vanden Berghe E, O’Dor R (2010) Biodiversity’s Big Wet Secret: The Global Distribution of Marine Biological Records Reveals Chronic Under-Exploration of the Deep Pelagic Ocean. PLoS ONE 5(8): e10223. doi:10.1371/journal.pone.0010223

Editor: Thomas M. Brooks, NatureServe, United States of America

Received February 8, 2010; Accepted March 29, 2010; Published August 2, 2010

Copyright: ! 2010 Webb et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was made possible by a Royal Society (www.royalsoc.ac.uk) Research Fellowship to TJW, and by support from the Sloan Foundation (www.sloan.org/) to OBIS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: t.j.webb@sheffield.ac.uk

Introduction

The tragedy of studying biodiversity during an extinction crisisis that we are losing our subject matter faster than we are able todescribe it [1]. This is especially true in the marine environment,where the need to value and conserve taxa and habitats that weknow little about has been termed a paradox of marineconservation [2]. Recent efforts by international networks suchas the Marine Biodiversity and Ecosystem Functioning EUNetwork of Excellence (www.marbef.org) and the Census ofMarine Life (www.coml.org) have substantially advanced ourknowledge of the marine diversity of specific regions [3,4] andhabitats [5], in large part by harnessing the power of integrateddatabases [6]. As well as highlighting what we know about marinebiodiversity, however, such databases also allow us to quantifywhat we do not know. For instance, global synthetic analyses haverevealed that even for the best known marine taxa, regionalinventories remain worryingly incomplete [7]. Spatial biases arealso apparent. In particular, the deep pelagic ocean is revealed asbiodiversity’s big wet secret.

The marine pelagic environment is the open oceans and seas,away from the coasts and above the sea bed; and the deep pelagicocean is typically defined as that part of the water column deeperthan 200m. It constitutes a vast biovolume of space in whichorganisms can exist – by far the largest on Earth at over a billionkm3 [8-11]. We know that this vast realm and the organisms livingin it provide globally important ecosystem services [11], includingthe support of fisheries, the provision of a range of naturalproducts of potential use in medicine and other applications, aswell as the regulation of climate and ocean chemistry through thecapture and storage of atmospheric carbon and the production ofmarine carbonate. But, the limits of our knowledge of this systemare continually exposed by the regular discovery of new clades ofoften large, active and conspicuous organisms [12] wheneversurveys are undertaken. Even a charismatic, widely distributed andvery large species, the megamouth shark Megachasma pelagios, wasnot discovered until 1976, and has since been recorded so rarelythat each individual specimen has become well known [13].

Although it is generally recognised that our knowledge of thedeep pelagic ocean is inadequate [9,11], it is useful to understand

PLoS ONE | www.plosone.org 1 August 2010 | Volume 5 | Issue 8 | e10223

Sharing dataThe second ‘win’ in ‘win-win’

MacroBen

“Crucial… was the willingness and the positive data-sharing attitude of the different data contributors. Development of a data policy that is highly aware of sensitivities and ownership issues of data providers was essential in the creation of this goodwill”

MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 382: 287–296, 2009doi: 10.3354/meps07754

Published April 30

INTRODUCTION

Macroecology draws on insights from fields includingecology, biogeography, palaeontology, macroevolutionand applied statistics to understand how large-scaleprocesses affect the organisation of ecological systemsat multiple scales (Brown 1995, Gaston & Blackburn2000, Blackburn & Gaston 2006). It has defined noveland important concepts and methodological techniquesto describe the form and structure of large-scale eco-logical patterns and has developed in a relatively shorttime into a thriving and productive discipline (Gaston &

Blackburn 2000, Blackburn & Gaston 2003). The impor-tance of a macroecological approach becomes still moreapparent with the realisation that human impacts onecological systems are detectable at the same verylarge scales that interest macroecologists (Chapin et al.2000, Kerr et al. 2007), and that many of the most press-ing issues in applied ecology involve very generalquestions relating to habitat modification, invasive spe-cies, over-exploitation, pollution and climate change(Sutherland et al. 2006). In a marine context, consider-able large-scale changes in ecosystems have alreadyoccurred without rigorous documentation (Jackson

© Inter-Research 2009 · www.int-res.com*Email: t.j.webb@sheffield.ac.uk

Addresses for other authors are given in the Electronic Appen-dix at www.int-res.com/articles/suppl/m382p221_app.pdf

Macroecology of the European soft sediment benthos: insights from the MacroBen database

T. J. Webb1,*, I. F. Aleffi, J. M. Amouroux, G. Bachelet, S. Degraer, C. Dounas, D. Fleischer, A. Grémare, M. Herrmann, H. Hummel, I. Karakassis, M. Kedra, M. A. Kendall, L. Kotwicki, C. Labrune, E. L. Nevrova, A. Occhipinti-Ambrogi, A. Petrov, N. K. Revkov, R. Sardá, N. Simboura, J. Speybroeck, G. Van Hoey,

M. Vincx, P. Whomersley, W. Willems, M. W8odarska-Kowalczuk

1Department of Animal & Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK

ABSTRACT: Macroecology provides a novel conceptual framework for analysis of the distributionand abundance of organisms at very large scales. Its rapid development in recent years has been dri-ven primarily by studies of terrestrial taxa; the vast potential of marine systems to contribute to themacroecological research effort remains largely untapped. International collaborative efforts such asMarBEF have provided fresh impetus to the collation of regional databases of species occurrences,such as the newly available MacroBen database of the European soft sediment benthic fauna. Here,we provide a first macroecological summary of this unique database. We show that in common withalmost all previously analysed assemblages, the frequency distribution of regional site occupanciesacross species in the MacroBen database is strongly right-skewed. More unusually, this right skewremains under logarithmic transformation. There is little evidence for any major differences betweenhigher taxa in this frequency distribution (based on the 8 animal classes for which we have sufficientdata). Indeed, considerable variation in occupancy persisted across the taxonomic hierarchy, suchthat most variation occurred between species within genera. There was a weak positive relationshipbetween local population density and regional occupancy across species, but this abundance–occu-pancy relationship varied considerably between higher taxa and between geographical areas. Ourresults highlight the potential of databases such as MacroBen to consolidate macroecological gener-alities and to test emerging theory.

KEY WORDS: Marine macroecology · Macrobenthic · Europe · Large marine ecosystems · Species–range size distributions · Phylogeny · Abundance–occupancy relationships

Resale or republication not permitted without written consent of the publisher

Contribution to the Theme Section ‘Large-scale studies of the European benthos: the MacroBen database’ OPENPEN ACCESSCCESS

T.J. Webb1

MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 382: 287–296, 2009doi: 10.3354/meps07754

Published April 30

INTRODUCTION

Macroecology draws on insights from fields includingecology, biogeography, palaeontology, macroevolutionand applied statistics to understand how large-scaleprocesses affect the organisation of ecological systemsat multiple scales (Brown 1995, Gaston & Blackburn2000, Blackburn & Gaston 2006). It has defined noveland important concepts and methodological techniquesto describe the form and structure of large-scale eco-logical patterns and has developed in a relatively shorttime into a thriving and productive discipline (Gaston &

Blackburn 2000, Blackburn & Gaston 2003). The impor-tance of a macroecological approach becomes still moreapparent with the realisation that human impacts onecological systems are detectable at the same verylarge scales that interest macroecologists (Chapin et al.2000, Kerr et al. 2007), and that many of the most press-ing issues in applied ecology involve very generalquestions relating to habitat modification, invasive spe-cies, over-exploitation, pollution and climate change(Sutherland et al. 2006). In a marine context, consider-able large-scale changes in ecosystems have alreadyoccurred without rigorous documentation (Jackson

© Inter-Research 2009 · www.int-res.com*Email: t.j.webb@sheffield.ac.uk

Addresses for other authors are given in the Electronic Appen-dix at www.int-res.com/articles/suppl/m382p221_app.pdf

Macroecology of the European soft sediment benthos: insights from the MacroBen database

T. J. Webb1,*, I. F. Aleffi, J. M. Amouroux, G. Bachelet, S. Degraer, C. Dounas, D. Fleischer, A. Grémare, M. Herrmann, H. Hummel, I. Karakassis, M. Kedra, M. A. Kendall, L. Kotwicki, C. Labrune, E. L. Nevrova, A. Occhipinti-Ambrogi, A. Petrov, N. K. Revkov, R. Sardá, N. Simboura, J. Speybroeck, G. Van Hoey,

M. Vincx, P. Whomersley, W. Willems, M. W8odarska-Kowalczuk

1Department of Animal & Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK

ABSTRACT: Macroecology provides a novel conceptual framework for analysis of the distributionand abundance of organisms at very large scales. Its rapid development in recent years has been dri-ven primarily by studies of terrestrial taxa; the vast potential of marine systems to contribute to themacroecological research effort remains largely untapped. International collaborative efforts such asMarBEF have provided fresh impetus to the collation of regional databases of species occurrences,such as the newly available MacroBen database of the European soft sediment benthic fauna. Here,we provide a first macroecological summary of this unique database. We show that in common withalmost all previously analysed assemblages, the frequency distribution of regional site occupanciesacross species in the MacroBen database is strongly right-skewed. More unusually, this right skewremains under logarithmic transformation. There is little evidence for any major differences betweenhigher taxa in this frequency distribution (based on the 8 animal classes for which we have sufficientdata). Indeed, considerable variation in occupancy persisted across the taxonomic hierarchy, suchthat most variation occurred between species within genera. There was a weak positive relationshipbetween local population density and regional occupancy across species, but this abundance–occu-pancy relationship varied considerably between higher taxa and between geographical areas. Ourresults highlight the potential of databases such as MacroBen to consolidate macroecological gener-alities and to test emerging theory.

KEY WORDS: Marine macroecology · Macrobenthic · Europe · Large marine ecosystems · Species–range size distributions · Phylogeny · Abundance–occupancy relationships

Resale or republication not permitted without written consent of the publisher

Contribution to the Theme Section ‘Large-scale studies of the European benthos: the MacroBen database’ OPENPEN ACCESSCCESS

✤ Surveying North Atlantic plankton communities for >80y

✤ (Restricted) open data policy

✤ 36 papers published 2012, only 6 led by SAHFOS staff

✤ Making data available leads to collaboration, output, impact

The moral case for open data

Reproducable scholarship

Advancing science and society

✤ What were you funded to do?

✤ Will open data help or hinder progress towards that goal?

Advancing science and society

✤ What were you funded to do?

✤ Will open data help or hinder progress towards that goal?

Tom Webb | @tomjwebb | t.j.webb@sheffield.ac.uk | www.sheffieldmeme.org