murdoch dissertation (c)2007
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A FUNCTIONAL GROUP APPROACH FOR PREDICTING THE COMPOSITION OF HARD CORAL ASSEMBLAGES IN FLORIDA AND BERMUDAA Dissertation Submitted to the Graduate Faculty of the University of South Alabama in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Marine Science byThaddeus J. T. MurdochB.Sc., Dalhousie University, 1988B.A. Honours, Dalhousie University, 1991M.S., University of South Alabama, 1998Copyright c 2007 Thaddeus J. T. MurdochAll rights reservedTRANSCRIPT
A FUNCTIONAL GROUP APPROACH FORPREDICTING THE COMPOSITION OF
HARD CORAL ASSEMBLAGESIN FLORIDA AND BERMUDA
A Dissertation
Submitted to the Graduate Faculty of theUniversity of South Alabama
in partial fulfillment of therequirements for the degree of
Doctor of Philosophy
in
The Department of Marine Science
byThaddeus J. T. Murdoch
B.Sc., Dalhousie University, 1988B.A. Honours, Dalhousie University, 1991M.S., University of South Alabama, 1998
Copyright c 2007 Thaddeus J. T. MurdochAll rights reserved
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ACKNOWLEDGEMENTS
The Keyswide Coral Reef Expedition was funded by NOAA’s National Undersea
Research Center at the University of North Carolina, Wilmington; NOAA’s Sanctuaries
and Reserves Division; The U.S. National Park Service, Biscayne National Park; The
Munson Foundation; The Florida Institute of Oceanography; and the Harbour Branch
Oceanographic Institution. The Expedition was carried out under permits from the
Florida Keys National Marine Sanctuary, the U.S. National Park Service, and the State of
Florida.
The Bermuda Project was supported by a fellowship from the University of South
Alabama; a PADI Aware grant; and a Bermuda Programme award from the Bermuda
Institute of Ocean Sciences. Additional support was provided by the Bermuda
Biodiversity Project, Bermuda Zoological Society, the Ernest E. Stempel Foundation, and
the Department of Conservation Services, Bermuda Government.
The research in this dissertation could not have been done without the help of many
people. I am grateful to John Ogden and Steven Miller for organizing the Keyswide Coral
Reef Expedition, and to Ken Johns and Otto Rutten for running the program of
continuous nitrox diving during the cruises. They, Dennis Hanisak and Laura Seimon
participated in the field work that formed the basis of the Florida section of this
dissertation. Dione Swanson provided valuable assistance in both the field and
laboratory. I am grateful to my committee members, and the professors and students of
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the Dauphin Island Sea Lab and the Bermuda Institute of Ocean Sciences for their
assistance, interest and support of this project.
Field work in Bermuda would not have been possible without the lively assistance of
the members of Robbie Smith’s Benthic Ecology Research Lab during 2000 – 2003 and
the BREAM team at BZS from 2004 – 2006. I am also thankful to Annie Glasspool and
Jack Ward for supporting me while I wrote up the dissertation. Jon Martin, Julie Prerost,
Toby Bolton, Jeannette Loram, Alexander Venn , Philippe Rouja, Mike Colella, Gerardo
Toro Farmer, and Matt Ajemian provided invaluable scientific and moral support. I am
deeply indebted to my family for unwavering encouragement.
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TABLE OF CONTENTS
LIST OF TABLES..............................................................................................................ix
LIST OF FIGURES...........................................................................................................xii
ABSTRACT.......................................................................................................................xx
CHAPTER 1: THE NEED FOR A FUNCTIONAL GROUP APPROACH TO
DESCRIBE THE STRUCTURE OF CARIBBEAN HARD CORAL
ASSEMBLAGES.........................................................................................1
Introduction..................................................................................................1
Functional traits and functional groups in reef corals..................................4
Assigning species to functional groups using the Adaptive
Strategies Theory..........................................................................................6
Characteristics of each Adaptive Strategy..................................................12
The graphic model of the Adaptive Strategies Theory...............................15
Assigning Caribbean reef corals to functional groups and
defining the critical tests............................................................................21
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Characteristics of each functional group of coral.......................................27
Sources of environmental stress and disturbance on coral reefs................32
Testing the applicability of the functional group approach
for reef corals..............................................................................................35
Similarities in distribution of species between and among FG......35
Rank abundance by species and functional groups........................39
Percent cover of all corals..............................................................40
Percent cover per functional group................................................41
Total species richness....................................................................45
Functional group richness..............................................................47
Species richness within functional groups.....................................52
Testing the adaptive strategies theory on Caribbean coral reefs................54
CHAPTER 2: THE RESPONSES OF FUNCTIONAL GROUPS OF CORALS TO
DIRECT AND INDIRECT GRADIENTS ON THE FLORIDA REEF
TRACT.......................................................................................................56
Introduction................................................................................................56
Objectives...................................................................................................61
Similarities in distribution of species between and among FG......62
Rank abundance by species and functional groups........................63
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Percent cover and abundance per functional group.......................64
Species richness of all corals.........................................................66
Functional group richness..............................................................66
Species richness per functional group............................................67
Methodology...............................................................................................68
Geographic setting.........................................................................68
Data collection and analysis...........................................................69
Statistical Analysis.........................................................................73
Results ........................................................................................................75
Similarities in distribution of species between and among FG......75
Rank abundance by species...........................................................82
Rank abundance per functional group...........................................88
Percent cover of each functional group vs. W................................92
Percent cover of each functional group vs. total coral cover.........94
Total species richness vs. W...........................................................98
Total species richness vs. total coral cover....................................99
Functional group richness vs. W..................................................101
Functional group richness vs. total coral cover...........................105
Species richness within functional groups vs. W.........................109
Species richness within functional groups vs. total coral cover. .112
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Discussion.................................................................................................118
Dominance by species and functional groups..............................118
Percent cover per functional group..............................................121
Total species richness..................................................................123
Functional group richness............................................................124
Species richness within functional groups...................................125
Conclusions..............................................................................................128
CHAPTER 3: THE GEOGRAPHY AND ENVIRONMENTAL
CHARACTERISTICS OF THE NORTH LAGOON OF
BERMUDA..............................................................................................133
Introduction...............................................................................................133
Previous research into the distribution of corals across the North
Lagoon......................................................................................................141
Predominant environmental factors in operation across the study
area 143
Suspended particulate matter.......................................................143
Water temperature........................................................................146
Solar radiation..............................................................................147
The effect of depth and turbidity.....................................147
The effect of aspect..........................................................148
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Wave energy and currents............................................................150
Project 1: Mapping of the lagoonal reefs.................................................151
Introduction and Methodology....................................................151
Results and Discussion................................................................154
Project 2: Assessing the three dimensional light field over a range
of depths.........................................................................................................
157
Introduction and Methodology....................................................156
Results and Discussion................................................................157
Project 3: Cross-platform differences in downwelling light
availability................................................................................................162
Introduction and Methodology....................................................162
Results and Discussion................................................................164
Discussion.................................................................................................169
CHAPTER 4: THE DISTRIBUTION OF CORAL SPECIES AND FUNCTIONAL
GROUPS OVER PHYSICAL GRADIENTS ACROSS THE NORTH
LAGOON OF BERMUDA......................................................................173
Introduction..............................................................................................173
Objectives.................................................................................................175
ix
Similarities in the distribution of species and functional groups.175
Similarities among sites in species assemblages.........................178
Percent cover and abundance per functional group.....................178
Species distributions across sites.................................................179
Species richness of all corals.......................................................180
Functional group richness............................................................180
Methodology.............................................................................................181
Data collection.............................................................................181
Data analysis................................................................................186
Statistical analysis........................................................................190
Results ......................................................................................................192
Depths per reefs...........................................................................192
Similarity in species distributions across sites on each reef........195
Similarity among sites in species assemblages............................199
Distribution patterns of coral species...........................................215
Frequency of occurrence........................................................215
Standard measures for coral reefs................................................242
Section 1: Tops of reefs only.................................................242
A. Average percent coral cover.......................................243
B. Species richness...........................................................243
C. Functional group richness...........................................243
D. Percent cover of the branched viviparous FG.............244
E. Percent cover of the massive viviparous FG...............244
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F. Percent cover of the massive oviparous FG................245
Section 2: Tops and south sides of reefs................................249
A. Average percent coral cover.......................................249
B. Species richness...........................................................249
C. Functional group richness...........................................250
D. Percent cover of the branched viviparous FG.............250
E. Percent cover of the massive viviparous FG...............252
F. Percent cover of the massive oviparous FG................252
G. Percent cover of the folious and plating
viviparous FG..............................................................253
Discussion.................................................................................................262
Species and functional group distribution across sites................262
Percent cover per functional group..............................................264
Management issues......................................................................265
CHAPTER 5: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS............269
REFERENCES................................................................................................................283
APPENDICES.................................................................................................................306
Appendix A Digital video image capture methodology...........................308
Appendix B: Applescript computer program to place dots on frames.....313
Appendix C: A list of coral species observed in Bermuda.......................317
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Appendix D: Bermuda climatology..........................................................318
Appendix E: Logistic regression of rank abundances; Florida data.........319
BIOGRAPHICAL SKETCH...........................................................................................325
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LIST OF TABLES
Table Page
1.01 The characteristic differences in biological attributes between
competitive, stress-tolerant and ruderal plant species (modified from
Grime 1979).....................................................................................................10
1.02 Life history characteristics of massive scleractinian corals as defined in
Table 3 in Soong (1993)..................................................................................23
1.03 The ranking of each proposed functional group in ten critical traits, and
the adaptive strategy to which they most closely represent.............................26
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2.01 Results of one-way analysis of similarity of the Bray-Curtis similarities
of the abundance data of the most abundant 11 species observed across
20 reef sites located on the Florida Reef Tract................................................79
2.02 Results of one-way analysis of similarity of the Bray-Curtis similarities
of the abundance data of all species observed across 20 reef sites
located on the Florida Reef Tract.....................................................................81
2.03 A table of the number of occurrences with which each the 36 most
abundant species ranked from 1 to 20 across all 200 transects........................85
2.04 A table of the observed number of times each functional group ranked
from 1 to 4 across the 200 transects surveyed.................................................90
2.05 Results of two-way t-test of the linear correlation between coral cover
of each functional group and W on 10 reef sites along the Florida Reef
Tract, testing whether the slopes are zero........................................................94
2.06 Results of orthogonal contrasts on whether the linear regressions of
percent coral cover for each functional group versus total coral cover at
each reef site were significantly different from zero.......................................97
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2.07 Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions of FG cover versus total coral cover were
significantly different from zero......................................................................97
2.08 Results of orthogonal contrasts on the linear regressions of functional
group richness for each level of constraint versus W.....................................102
2.09 Results of orthogonal contrasts on the second-order coefficients for
polynomial regressions of functional group richness for each level of
constraint versus W........................................................................................102
2.10 Presence or absence matrices of the presence or absence of functional
groups across the ten reefs of the environmental gradient W. The rules
for inclusion of functional groups are as in Figure 2.18, above....................104
2.11 Results of orthogonal contrasts on the linear regressions of functional
group richness for each level of constraint versus W.....................................107
2.12 Results of orthogonal contrasts on the second-order coefficients for
polynomial regressions of functional group richness for each level of
constraint versus W........................................................................................107
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2.13 Results of analyses of variance of the linear regression of species
richness versus W for each functional group.................................................110
2.14 Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions for species richness of each functional group
versus W were significantly different from zero............................................110
2.15 Results of two-way t-tests of the linear regression of species richness
for each functional group versus total coral cover for each functional
group..............................................................................................................114
2.16 Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions of FG species richness versus total coral
assemblage cover were significantly different from zero..............................114
2.17 Sorted matrices of species presence or absence for each functional
group across 20 transects at each of the 20 sites of the Keyswide Coral
Reef Expedition.............................................................................................116
3.01 Characteristics of each zone of the survey area across the Bermuda
Lagoon, and the patch reefs contained therein...............................................155
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3.02 Two-way analysis of variance of the effects of depth and aspect on the
proportion of surface light reaching a hemispherical sensor.........................161
3.03 ANOVA table of the differences in light intensity across the five
locations from the data illustrated in Figure 2.13..........................................168
3.04 Results of a Tukey’s post hoc analysis of the significance in the
differences in the amount of luminance at 8-m depth over the hours of
11 am to 1 pm between the five locations across the reef platform...............168
4.01 Details of the 18 surveyed reefs surveyed across the North Lagoon.............185
4.02 Results of an ANOSIM analysis of distinctness in clustering of each
functional group.............................................................................................198
4.03 ANOSIM table for the factor Aspect across all sites, including the
results of pairwise post-hoc tests...................................................................203
4.04 Significance levels of separate ANOSIM tests comparing similarities
between reef sites located on the south versus north sides of reefs in
each zone and at different depths...................................................................204
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4.05 ANOSIM table for the factor Depth, calculated from data at each depth
from across all sites........................................................................................207
4.06 Significance levels of pair-wise tests comparing similarities between
reef sites located on different depths.............................................................207
4.07 ANOSIM table for the factor Zone across all sites........................................210
4.08 SIMPER analysis of the dominant species that differ between zones
across the Bermuda Platform.........................................................................211
4.09 Results of the 2-way ANOVAs of the six parameters across the 18 reef
sites located on the tops of patch reefs located in three replicate “legs”
across six zones located across the north lagoon in Bermuda.......................248
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LIST OF FIGURES
Figure Page
1.01 Percent cover for each of the 38 species recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition............................................3
1.02 A modified diagram of Grime’s (1979) Adaptive Strategy Theory for
classifying habitats according to levels of stress and disturbance...................11
1.03 The Adaptive Strategies Theory graphic model, also known as the CSR
model, depicted as a ternary diagram..............................................................16
1.04 Generalized model of community dominants by Steneck and Dethier
(1994) that refines to Grime’s (1977) AST model (shaded in light gray).......18
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1.05 A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)
generalized two-dimensional model of FG dominance within habitat
types.................................................................................................................20
1.06 Representation of how varying levels of the four most important
environmental factors act to promote growth, or act as a stressor or
disturbance agent to corals..............................................................................34
1.07 An illustration of different hypothetical distributions of species and
functional groups across an environmental gradient (A to D), and how
they appear when graphed as (i) abundances, (ii) tabulated in a matrix
of presence vs. absence, and (iii) graphed using a multivariate
ordination technique, such as Multidimensional Scaling (MDS)....................37
1.08 An illustration of how total assemblage biomass is predicted to vary
across habitat types characterized by different levels of resource
availability and disturbance.............................................................................41
1.09 Diagrams depicting the differing ways in which the abundances of
competitive (C), stress-tolerant (S) and ruderal (R) functional groups of
corals are predicted to vary across habitats located across the range of
stress and disturbance gradients encompassed by the AST mode...................43
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1.10 The distribution of species richness predicted to occur across habitats by
Grime’s (1977) Adaptive Strategies model.....................................................46
1.11 A diagram illustrating the range of strategies encompasses by (a) annual
herbs, (b) biennial herbs, (c) perennial herbs and ferns, (d) trees and
shrubs, (e) lichens and (f) bryophytes.............................................................48
1.12 A three dimensional model of the levels of biomass predicted for set of
functional groups of species across habitat types characterized by
varying levels of disturbance potential and productivity potential..................49
1.13 A diagram illustrating how functional groups are predicted to be
dispersed across patches located with habitats defined by varying rates
of resource gain and loss.................................................................................52
2.01 The elongated oval within this square diagram of state space represents
the hypothetical range within the AST (CSR) model that was occupied by
the sites of the Florida Reef Tract that are the focus of this chapter...................58
2.02 Relationship between total percent cover of the entire coral assemblage
and the measure of environmental disturbance due to island passes, W.........60
2.03 Map of South Florida and the Florida Keys.....................................................69
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2.04 A dendrogram showing the similarities in response patterns among the
eleven most abundant species assessed in Florida...........................................77
2.05 MDS showing the similarities in response patterns among the eleven
most abundant species assessed in Florida in two-dimensional state
space................................................................................................................78
2.06 MDS showing the similarities in response patterns among all 36 species
assessed in Florida in two-dimensional state space.........................................80
2.07 The log percent relative abundance of the species observed at the 200
transects assessed.............................................................................................83
2.08 The distribution of the proportion of ranks over the 200 sites that the
most dominant species, Montastrea faveolata, displayed...............................87
2.09 The proportion of ranks displayed by each functional group across the
200 transects surveyed.....................................................................................89
2.10 The relationship between rank per functional group and total abundance
per transect for the 200 transects surveyed......................................................90
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2.11 Relationship between percent coral cover of each functional group and
environmental influence of island passes, (W)................................................93
2.12 Orthogonal relationship between average percent coral cover for each
functional group and the total coral cover for the 20 reef sites surveyed
on the Keyswide Coral Reef Expedition.........................................................95
2.13 The same graphs illustrating the relationship between average percent
coral cover for each functional group and the total coral cover for the 20
reef sites surveyed as in Figure 2.12, but with different scales on the y-
axes..................................................................................................................96
2.14 Relationship between species richness of all corals and environmental
influence of island passes, W, at each reef site................................................98
2.15 Relationship between species richness and total coral cover across the
20 reef sites....................................................................................................100
2.16 Relationships between functional group richness under the four levels
of membership constraint and the environmental gradient of W across
reef sites.........................................................................................................103
xxiii
2.17 Regression of functional group richness versus total coral cover for each
site..................................................................................................................106
2.18 Relationship between species richness of each functional group and
environmental influence of island passes, W, at each reef site......................109
2.19 Regressions of species richness for each functional group on total coral
cover for each site..........................................................................................113
2.20 Percent cover for each of the 38 species recorded on the 20 reefs
surveyed on the Keyswide Coral Reef Expedition........................................129
2.21 Functional group cover for each of the four predominant functional
groups recorded on the 20 reefs surveyed on the Keyswide Coral Reef
Expedition......................................................................................................130
3.01 A photomosaic map of the Bermuda Islands and surrounding reef
platform.........................................................................................................134
3.02 An illustrated map of the islands and surrounding lagoonal patch reefs
of Bermuda, with important geographic features labeled (produced by
the author as part of the Bermuda Zoological Society).................................137
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3.03 A graph charting the number of passages by ships traveling through the
southern shipping channel in 2004................................................................145
3.04 An aerial photograph of a cruise ship traversing the south shipping
channel of Bermuda in a westerly direction, and leaving a plume of
sediment in its wake......................................................................................146
3.05 Temperature record for 2 subsurface temperature data loggers located
either near North Shore (Inshore) or on the forereef at 30 ft depth
(Offshore) for a three year period from 1998 – 2000 (modified from de
Putron 2003)..................................................................................................147
3.06 A graph of the hourly positions and paths the sun appears to take as it
crosses the sky in Bermuda over the course of a day during the summer
and winter solstices, and either equinox........................................................149
3.07 Zonal boundaries, locations of the north and south shipping channels,
and location of patch reefs distributed across the study area
encompassing the North Lagoon...................................................................153
3.08 A diagram illustrating the modified Li-Cor scalar PAR sensor.....................159
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3.09 Mean proportion of surface light (± standard error) originating from
four directions at five depths, as measured by the hemispherical sensor......160
3.10 Map of the five reef sites, indicated by the light-bulb symbol......................163
3.11 Light intensity readings taken over five days from sensors positioned at
8-m depth at 5 reef sites located at different distances from shore across
the area of study.............................................................................................166
3.12 Average light intensity (Lumens ±SE) measured from 11 am to 1 pm
local standard time over the first of the five days of deployment, by
light sensors located at 8-m depth at five reef sites positioned at
increasing distances from the North Shore of Bermuda................................167
3.13 Representation of how varying levels of the four most important
environmental factors act to promote growth, or act as a stressor or
disturbance agent to corals............................................................................171
4.01 A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)
generalized two-dimensional AST model of FG dominance within
habitat types, incorporating the concession that biota can only survive
in habitats within which the rate or amount of resource acquisition
xxvi
(resource abundance) is greater than the rate or amount of resource loss
(or disturbance)..............................................................................................177
4.02 General design of the study, in which survey sites (circles) were
surveyed at a range of depths on the north, south and top sides of
replicate patch reefs within each of six zones located at increasing
distances from shore......................................................................................183
4.03 A map of the lagoonal reefs located within and around the research area
and the 18 patch reef sites surveyed in the videographic analyses................184
4.04 Diagram illustrating the average depths of each site on patch reefs
located on different sides (aspects) and at varying distances from shore......194
4.05 Dendrogram of Bray-Curtis similarities of species and functional groups
clustered according by group-averaging........................................................196
4.06 Multidimensional scaling diagram (MDS) of square-root transformed
relative abundance data for coral species averaged across sites located
on replicate reefs and over different aspects, depths and distances from
shore...............................................................................................................197
xxvii
4.07 MDS of square-root transformed relative abundance data of species for
all sites...........................................................................................................202
4.08 MDS of square-root transformed relative abundance data of species for
all sites depths on all reefs.............................................................................206
4.09 MDS of square-root transformed relative abundance data of species for
all sites...........................................................................................................209
4.10 The sites surveyed across the Bermuda platform cluster into three
groups with different coral species composition, which also match three
different environmental conditions................................................................214
4.11 MDS of square-root transformed frequency of occurrence data of all
coral species for all sites, as in the three figures abov...................................216
4.12 The average proportion of frames with any coral present across all sites,
illustrated as a line graph per site per reef (A) and as a bubble graph per
depth and zone (B).........................................................................................217
4.13 Four MDS graphs of square-root transformed frequency of occurrence
data of Branched Viviparous species as a group, and for M. decactis, M.
mirabilis and P. porites corals separately for all sites...................................219
xxviii
4.14 The average proportion of frames with corals of the Viviparous
Branching (VB) functional group present across all sites, illustrated as a
line graph per site per reef (top) and as a bubble graph per depth and
zone (bottom).................................................................................................220
4.15 The average proportion of frames with corals of the species Madracis
decactis present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................221
4.16 The average proportion of frames with corals of the species Madracis
mirabilis present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................222
4.17 The average proportion of frames with corals of the species Porites
porites present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................223
4.18 MDS graph of square-root transformed frequency of occurrence data of
the coral species Agaricia fragilis, the only member of the Foliose and
Plating Viviparous (FP) functional group observed in the North lagoon
in Bermuda in this study................................................................................225
xxix
4.19 The average occurrence frequency of the species Agaricia fragilis
across all sites, illustrated as a line graph per site and reef (top) and as a
bubble graph per depth and zone (bottom.....................................................226
4.20 Four MDS graphs of square-root transformed data of occurrence
frequency by Massive Viviparous species as a group, and for F. fragum,
P. astreoides and S. radians corals separately, for all sites...........................228
4.21 The average proportion of occupied frames per transect with corals
belonging to the Massive Viviparous functional group present across all
sites, illustrated as a line graph per site per reef (top) and as a bubble
graph per depth and zone (bottom)................................................................229
4.22 The average proportion of frames with corals of the species Favia
fragum present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................230
4.23 The average proportion of frames with corals of the species Favia
fragum present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................231
4.24 The average proportion of frames with corals of the species
Siderasterea radians present across all sites, illustrated as a line graph
xxx
per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................232
4.25 Seven MDS graphs of square-root transformed relative abundance data
of (a) Massive Oviparous species as a group, and for (b) M. cavernosa,
(c) M. faveolata, (d) M. frankesi, (e) D. labyrinthiformis, (f) D. stigosa
and (g) S. intersepta separately for all sites...................................................234
4.26 The average proportion of frames with corals of the Massive Oviparous
(MO) functional group present across all sites, illustrated as a line graph
per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................235
4.27 The average proportion of frames with corals of the species
Montastraea cavernosa present across all sites, illustrated as a line
graph per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................236
4.28 The average proportion of frames with corals of the species
Montastraea faveolata present across all sites, illustrated as a line graph
per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................237
xxxi
4.29 The average proportion of frames with corals of the species
Montastraea franksi present across all sites, illustrated as a line graph
per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................238
4.30 The average proportion of frames with corals of the species Diploria
labyrithiformis present across all sites, illustrated as a line graph per site
per reef (top) and as a bubble graph per depth and zone (bottom)................239
4.31 The average proportion of frames with corals of the species Diploria
strigosa present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom)......................240
4.32 The average proportion of frames with corals of the species
Stephanocoenia intersepta present across all sites, illustrated as a line
graph per site per reef (top) and as a bubble graph per depth and zone
(bottom).........................................................................................................241
4.33 Average percent coral cover for (A), (B) species richness, (C) functional
group richness as well as (D – F) the average percent cover for each
functional group on the tops of each of three replicate reef sites in each
of the six zones..............................................................................................246
xxxii
4.34 Percent cover, species richness and functional group richness of corals
surveyed on sites located on the tops and southern flanks of patch reef.......254
4.35 Percent cover of the Branched Viviparous, Massive Viviparous and
Massive Oviparous functional groups of corals surveyed on sites
located on the tops and southern flanks of patch reefs..................................254
4.36 Percent cover of the three species of Branched Viviparous functional
group..............................................................................................................257
4.37 Percent cover of Agaricia fragilis, the one species of the Foliose and
Plating functional group found within the lagoonal sites surveyed...............258
4.38 Percent cover of the three species of Massive Viviparous functional
group..............................................................................................................259
4.39 Percent cover of the two of the five species of Massive Oviparous
functional group.............................................................................................260
4.40 Percent cover of the three other species of Massive Oviparous
functional group.............................................................................................261
xxxiii
5.01 Diagrams depicting the differing ways in which the abundances of
competitive (C), stress-tolerant (S) and ruderal (R) functional groups of
corals are predicted to vary across habitats located across the range of
stress and disturbance gradients encompassed by the AST model, and
depending on the degree of niche overlap exhibited by each functional
group..............................................................................................................272
5.02 A diagram illustrating how the Zero Net Growth Intercepts (ZNGI) of
each of the predominant functional groups of Caribbean coral found in
Florida and Bermuda are dispersed across the Adaptive Strategies
Theory model.................................................................................................273
5.03 The bounded area laid over the modified Adaptive Strategies Theory
shown in Figure 5.02 represents the range of habitat types surveyed in
Florida............................................................................................................274
5.04 The bounded area laid over the modified Adaptive Strategies Theory
shown in Figure 5.02 represents the range of habitat types surveyed in
Bermuda.........................................................................................................275
5.05 A network of interacting corals on the Bermuda fore reef............................278
xxxiv
ABSTRACT
Murdoch, Thaddeus James Thomas, Ph.D., University of South Alabama, December 2007. A Functional Group Approach for Predicting the Composition of Hard Coral Assemblages in Florida and Bermuda. Chair of Committee: Dr. Richard B. Aronson
In Florida the functional-group approach provided new insights into the manner in
which varying levels of disturbance affected species richness across sites. Despite the
chaotic patterns in biomass displayed by each assemblage of coral species when
separately plotted across reefs, each functional group of corals responded to direct and
indirect gradients of disturbance in a orderly and group-specific manner. Functional
groups displayed a nested distributional pattern, indicating that negative interactions
between functional groups are probably weak
Terrestrial and marine ecologists have found that a functional group approach can
accurately predict how organisms will respond to changes in environment conditions. A
functional group approach categorizes organisms, regardless of phylogeny, according to
similarities and differences in life history and other ecologically relevant traits. One such
model, the "CSR plant strategy theory" developed by Phillip Grime in 1973 for
terrestrial plants, predicts the assemblage structure of biota over gradients of stress and
disturbance. To test the CSR model, coral assemblages on reefs from Florida and
Bermuda were assessed at the hierarchical levels of species and functional groups. The
data were used to address the question of whether the functional-level approach provides
information about community structure that species-level analysis fails to provide.
xxxv
Additionally, the predictions of the CSR model were tested regarding how coral cover,
species diversity and assemblage structure should vary in habitats characterized by
differing levels of disturbance and resource-limitation.
In Bermuda, functional groups of corals also displayed a nested pattern across sites
located over a range of depths and reef zones. When species were aggregated according
to shared habitat, species from the same genus co-occurred in almost every case. This
implies that these closely related species also share many functional traits and yet still
coexist in many habitats
The Adaptive Strategies Theory provides a series of simple, testable hypotheses that
can be used to guide ecological research in an iterative and informative manner. The
Adaptive Strategies Theory is a powerful theoretical framework, which can be modified
to give it great heuristic value for guiding ecological research.
xxxvi
CHAPTER 1: THE NEED FOR A FUNCTIONAL GROUP APPROACH TO DESCRIBE THE STRUCTURE OF CARIBBEAN HARD CORAL ASSEMBLAGES
Introduction
Coral reefs are in decline around the globe (Aronson and Precht 2001, Knowlton
2001, Gardner et al 2003, Wilkinson 2004). Concerns that assemblages of reef corals may
have lost their ability to resist disturbance are mounting (Jackson et al 2001; Nyström and
Folke 2001; McClannahan et al 2002; Bellwood et al 2004; Hughes et al 2005; Aronson
and Precht 2006; Nyström 2006), as exhibited by dramatic changes in the community
structure of coral reefs, from a state of high coral biomass and low algal biomass to an
alternate condition of high algal biomass and low coral biomass Gardner et al. 2003.
In the Caribbean, the most obvious change is the loss of the three dominant species of
coral (Acropora cervicornis, A. palmata and Montastraea annularis species complex),
and the clear zonation patterns these species once produced (Done 1983; Graus and
Macintyre 1989; Jackson 1991; Hughes 1994). Nonetheless, on many of the same reefs,
it appears that subordinate coral species have not decreased to the same extent (e.g. Bak
and Engel 1979; Aronson and Precht 1999). While it is well known that corals differ in
their sensitivities to a range of environmental and biological factors, coral ecology as a
science does not yet provide the means for predicting which species will be affected by
specific changes in their environment nor in the manner in which changes will manifest
themselves.
1
If we are to effectively manage coral reef communities and prevent further declines of
corals, we must improve our understanding of how all species of coral respond to
changes in physical and biological processes. We need to be able to determine whether
predictable patterns in the abundance, co-occurrence and diversity of corals occur across
habitats that vary in environment or in disturbance history. We also must ascertain the
role that all species of corals play in providing function to reef ecosystems, including reef
growth, nutrient cycling, the inhibition of invasive species, and the enhancement of
biodiversity. With the exception of what historically were some of the more abundant
coral species, such as Acropora cervicornis, Montastraea annularis and Porites
astreoides, there has been very little advancement in these areas.
Expanding our focus to all of the corals that live on a coral reef will require
developing techniques for simplifying the complicated data that accompany such an
increase in perceptional scope. The degree of complexity inherent in multi-species data
from a large-scale ecological assessment can be seen in the following example. During
the Keyswide Coral Reef Expedition of 1995 (Murdoch and Aronson 1999), 19,055
individual corals, representing 38 species, were recorded from 200 video transects filmed
on twenty reefs located across the entire 350-km long Florida Reef Tract. When the
percent cover data for each species on each reef surveyed was plotted (Figure 1.01), the
resulting graph appears to have little structure. Instead the graph may best be
described as a chaotic tangle of species varying in occurrence across reefs in an
idiosyncratic manner. The lack of pattern found in data from Florida is typical for
monitoring projects that cover large regions (e.g. Goreau 1959; Done 1982), and
2
illustrates the need for techniques with which to organize and simplify species-level data
so that they can be interpreted in an ecologically meaningful way.
Figure 1.01. Percent cover for each of the 38 species recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition. Letters represent individual sites on reefs separated by ~ 10 km. Data from each reef are plotted from western-most to eastern-most location.
Recently it has been suggested that a revived focus on the biological traits of
organisms and the manner in which they vary across environmental gradients will
promote the development of better ways of measuring and interpreting ecological
information (McGill et al. 2006). Biological traits are specific, quantifiable characteristics
of an organism that can be compared across individuals both within and among species.
3
Gradient analysis can include either indirect gradients, such as differences in depth down
a fore reef, or direct gradients of a particular physical or chemical parameter, such as
light intensity or oxygen concentration. A trait-based approach uses the properties of
environmental gradients to tease apart the relative form that functionally important traits
take in an assemblage of organisms located across the gradients, in much the same
manner that glass prisms can be used to split a beam of white light into its component
colors (Keddy 1992).
Functional Traits and Functional Groups in Reef Corals
Corals are affected by and react to environmental and biological factors through their
physiological, morphological and behavioral traits. Within a geographic region, the
members of the species pool that are found within a particular habitat are presumed to
possess the traits that allow their recruitment and continued presence, whereas the species
that are absent are assumed to lack these same critical characteristics (Bradbury and Loya
1978; Sorokin 1993; Sullivan and Chiappone 1993; Edinger and Risk 1995; Hughes et al.
1999). Many researchers have attempted to detect theoretically meaningful correlations
between the traits that different coral species possess and the species’ abundance within a
habitat. For instance, Lang (1973) looked for patterns in competitive dominance
hierarchies of corals by ranking species according to their aggressive abilities. Porter
(1976) and Green et al. (1987) grouped species by polyp size in order to ascertain
whether species with similar polyps shared trophic position and thus depth zones on
forereefs. Szmant (1986), Edinger and Risk (1995), Hughes et al. (1999), Knowlton
(2001) and others have grouped corals by reproductive mode. Corals that brood planula
4
larvae were compared with corals that broadcast spawn, and predictions regarding their
relative abundance or distribution were made based on the differences in energy
allocation, dispersal method and dispersal range between brooders and spawners. Barnes
(1973), Jackson (1979), Bellwood et al. (2004), and others grouped corals and other reef
biota according to morphology. They theorized that, since morphology is related to the
rates of light collection, sediment shedding and fragmentation, morphology could be used
to predict which coral species would dominate a particular habitat. However, all of these
attempts at using single kinds of traits to predict the presence or abundance of corals in a
particular habitat have been unsuccessful. This is because a single-trait approach cannot
define differences between all species, not can it encompass the broad range of energetic,
physical, chemical and biological factors and processes that affect corals on reefs. A
more powerful technique is to examine how sets of different kinds of co-occurring traits
are correlated with, or induced in response to, differences among habitats located along
environmental and biological gradients (Keddy 1992; Körner 1993)).
The manner in which species share groups of traits may be analyzed in two ways:
(1) Functional trait analysis
(2) Functional group analysis
Functional trait analysis looks at the form each trait takes separately at the hierarchical
level below the level of the species. Direct analysis of traits has been shown to be a
powerful technique for interpreting the causes of the spatial distributions of terrestrial
plants (e.g. Weiher et al. 1998; Mayfield et al. 2006), but it also further increases the
complexity and amount of information needed. Alternatively, in functional group
analysis, species that share life history or adaptive strategy are sorted into functional
5
groups, a hierarchical level above species. Functional group analysis has been shown to
be useful for interpreting terrestrial plant data, but it provides the added benefit of
simplifying species-level information, not making it more complex (Fagerstromm 1988;
Körner 1993).
Assigning Species to Functional Groups using the Adaptive Strategies Theory
Ecologists use functional classification schemes for two separate reasons (Gitay and
Noble 1997). When investigating the effects of organisms on ecosystem processes,
species are categorized into functional effects groups (e.g. Walker et al. 1999).
Alternatively, when the goal is to determine the manner in which organism will react to
environmental change, species are categorized into functional response groups (e.g.
Lavorel et al. 1997). The research described in this manuscript focuses on the patterns
manifested by functional response groups at locations that vary in environmental
condition.
There are as many ways to assign species to functional response groups as there are
ecological factors of interest (Körner 1993). However, I propose that one particularly
constructive way of classifying modular, sessile organisms such as plants, and perhaps
corals, into functional groups is by using a modified version of Grime’s (1979) Adaptive
Strategies Theory (AST; Keddy 1992; Andersen 1995; Steneck and Dethier 1996; Airoldi
1998). Grime (1979) used first principles to categorize all habitats into four primary kinds
(Figure1.02), which I will refer to as habitat types, according to the relative measure
within each habitat of two fundamental environmental factors. These two
environmental conditions are (1) the availability or supply rate of resources (i.e. nutrients,
6
energy) employable for biomass maintenance and growth, and (2) the likelihood or rate
that biota within a habitat will sustain damage or the loss of resources, biomass or
physiological function (which is defined as disturbance). Following Grime’s (1979)
scheme, the reciprocal of resource availability is defined as “stress”, and is considered to
be different from disturbance. Accordingly, stress is defined as a lack of resources
available for use by an organism, and disturbance is defined as a loss of the resources
already acquired by the organism under consideration (Grime 1979), . Other terrestrial
(Wilson and Keddy 1986; Chapin 1991) and marine (Kautsky and Kautsky 1989; Steneck
and Dethier 1996) ecologists utilize the same convention, although the distinction
between stress and disturbance is not usually made by coral ecologists (e.g. Dollar 1981;
Grigg 1995; Hughes and Connell 1999)
The specific suite of environmental conditions in which an organism finds itself
affects the relative benefits and costs of allocating resources to different biological
functions. Additionally, since the organism often finds itself in an environment with
limiting resources, it must balance, or tradeoff, the amount of resources allocated to each
function, based on the current adaptive value of that function, and relative to the adaptive
value of the other functional structures and behaviors in which it could also invest. The
organism must also minimize the risks inherent in allocating resources to a functional
structure that has a high probability of being damaged or made redundant.
All organisms must allocate resources to the following biological functions and
behaviors:
Resource acquisition
Maintenance and repair of body function
7
Resource and energy storage
Defense: The development of biochemical, structural or behavioral characteristics
that prevent or inhibit other organisms from taking part of its body structure or resources.
Aggression: The development of biochemical, structural or behavioral
characteristics that which facilitate competitive superiority for space, or other kinds of
resource, over other organisms.
Growth
Sexual reproduction
Recycling of damaged or obsolete body structures and organelles.
Additionally, clonal organisms such as corals can allocate resources to asexual
reproduction in any of three ways. First, they can reproduce asexually via fragmentation
of viable parts of the colony, the rate of which dependent on the rate of growth and
growth form of the species (Highsmith 1987). Second, some corals, such as Porites
astreoides, are also capable of asexual reproduction by self-fertilization (Brazeau et al.
1998). Third, some corals, such as Pocillopora, may produce planulae asexually
(Stoddart 1983; Sherman et al. 2006).
Of the ten ways to allocate resources described above, three in particular play a key
role in determining the life-history and functional characteristics of an organism and its
survival abilities in different environmental conditions (Table 1; Grime 1973). These
three primary processes to which an organisms must allocate resources in order to persist
within a habitat are:
(1) Growth,
(2) Defense and Resource Storage, and
8
(3) Sexual Reproduction.
Within habitats characterized by high levels of available resource, and a low risk of
disturbance (Figure 1.02), ecologically successful organisms will be those that primarily
allocate resources to growth. Similar rates of growth could not be supported in habitats
with low levels of resource availability, even with low levels of disturbance, and survival
in such an environment would instead require resource allocation primarily to storage and
defensive structures and behaviors. Alternatively, organisms are likely to lose stored or
growth-directed biomass in habitats characterized by high levels of resource, but high
rates or intensity of disturbance. In these heavily disturbed environments, resources
should primarily be allocated to reproduction, so that offspring may escape to less-
disturbed habitats. Following the logic of Grime (1973), no strategy exists that permits
the survival of an organism under the concurrent conditions of intense disturbance and
negligible resources for repair or reproduction.
9
Table 1.01. The characteristic differences in biological attributes between competitive,
stress-tolerant and ruderal plant species (modified from Grime 1979).
Adaptive Strategy
Attribute Competitive Stress-tolerant Ruderal
Maximum Size Large Small Small
Longevity Long or short Very long Very short
Reproductive Maturity Late Late Early
Reproductive Effort Small Small Large
Reproductive Method Both Clonal Sexual
Growth Rate Rapid Slow Rapid
Stress response Rapid Slow Reproduces
Palatability Variable Low High
10
Figure 1.02. A modified diagram of Grime’s (1979) Adaptive Strategy Theory for classifying habitats according to levels of stress and disturbance. The diagram also illustrates the optimal strategy predicted to be exhibited by the biota found within each habitat type, based on the optimal use of resources and the likelihood of incurring damage.
11
Characteristics of each Adaptive Strategy
Competitive dominant species
Organisms that primarily utilize a strategy in which growth is favored are termed
“competitive dominants” by Grime (1979; Figure 1.02). Allocation of resources to
growth is an optimal strategy when resources are abundant and levels of disturbance are
low, because growth promotes further resource capture and allows even more growth.
This positive feedback loop allows competitive species to reach large sizes, when in
benign habitats, relative to species employing other strategies. High rates of growth also
permit competitive species to expand (laterally and vertically) more quickly than less
competitive species, and thereby dominate previously unoccupied space. Occupied space
can also be actively acquired using growth, via either the over-topping or shading-out of
slower growing organisms. In benign habitats the storage of resources is disadvantageous
for competitively-superior species, since stored resources cost resources and energy to
store and also tie-up resources that would be better used in the acquisition of more space
and more resources.
Asexual reproduction via fragmentation or similar mechanisms, which Grime (1977)
refers to as vegetative reproduction, is expected to be enhanced in competitive species,
since high growth rates, coupled with of partial mortality, will result in the generation of
disconnected clones of relatively large size. Alternatively, the proportion of resources
used for sexual reproduction in competitive species is expected to be relatively small,
since the release of gametes represents a risky loss of resources that could also be used
for additional growth and acquisition of space (Williams 1975; Bazzazz et al. 1987; Hall
12
and Hughes 1996; Heino and Kaitala 1999). As disturbances occur in all habitats,
however, some level of reproduction is necessary for survival by species using all
strategies. Reproductive onset in competitive species is predicted to be delayed until the
organisms have grown to a large size. When initiated, reproduction is expected to occur
after the season of maximal potential productivity or during the season of highest
likelihood of disturbance. When exposed to either periods of stress or of disturbance,
competitive species are expected to further reduce the allocation of resources to
reproduction or storage, in favor of continued growth or tissue repair (Grime 1979).
Ruderal Species
Organisms that allocate most resources to reproduction are defined by Grime as
“ruderal” or weedy species. Ruderal species are those that are capable of surviving in
habitats characterized by high levels of disturbance, but only when abundant resources
are also available. Ruderals are predicted to have life history strategies that differ
substantially from those of competitive species, except that they share in the ability to
rapidly capture resources. Since the likelihood or intensity of disturbance is high for
ruderal organisms, they are likely to experience high rates of partial or total mortality and
rarely reach large sizes. Species that allocate resources to the development of structures
or physiological attributes that reduce the effects of disturbance would be more likely to
persist in disturbed environments, but at a cost in the amount of resources available for
the development of other tissues or for reproduction. Initial growth rates may be high in
ruderal species, but since the relative cost of reproduction outweighs the risk that
reproduction will reduce survivorship in highly disturbed environments, ruderal species
13
are predicted to initiate reproductive effort at a small size. Resource storage would be
disadvantageous in ruderal species since lifespan is likely to be short. Fragmentation rates
are predicted to be high in ruderal species. However, since fragment size is likely to be
smaller than in competitive species, the fragments of ruderal species may have a lower
likelihood of survival. Under periods of stress, ruderals are expected to increase resource
allocation to reproduction, since the likelihood of continued survival within the habitat is
reduced.
Stress-tolerant species
Species that allocate resources predominantly to storage and defense are termed
“stress-tolerant species” by Grime (1979). Since the rate or probability of acquisition of
resources is low, stress-tolerant organisms should possess structures that maximize
resource capture and storage when resources are present. Allocation of resources for
biochemical, structural or behavioral modifications that reduce the loss of biomass by
predation or competition would also be maximally advantageous under stressed
conditions. Low rates of resource capture will limit growth and reproductive output and
delay the initiation of reproduction in these organisms to “mast” years when resources are
particularly high. However, despite slow rates of growth the eventual attainment of a
large size would be possible if the organisms were located within a habitat experiencing
very low levels of disturbance. Additionally, the slow rates of growth and low density of
biomass in stressed habitats slow the rates of competition, allowing a high number of
species to coexist (Huston 1994).
14
The Graphic Model of the Adaptive Strategy Theory
In this section I describe in detail the graphic model of Grime’s (1979) Adaptive
Strategy Theory. I then explain how it has been refined by various investigators since it
was first proposed. I also offer my own modifications to the graphic model, with which I
hope to improve both the model’s clarity and the way it logically corresponds with
reality.
As shown in Figure 1.02, above, the initial graphic model of the adaptive strategy
theory was a square subdivided into four boxes, each representing an extreme in
environmental condition possible within a habitat (Grime 1979). However, since the high
stress and disturbance environment was defined as uninhabitable by all biota, Grime
rearranged the square habitat model as a triangle, or ternary diagram. In this new
configuration, competitive ability, intensity of disturbance and intensity of stress are
represented by three axes (Figure 1.03). The C, S and R axes of the ternary graph are the
source for a second name for the Adaptive Strategies Theory, which is the “CSR model”.
Secondary and tertiary strategies, which represent compromises in adaptive traits
between the three primary strategies, such as “Competitive-Ruderal”, are hypothesized to
exist in habitats characterized by intermediate levels of stress or disturbance (Grime
1979).
15
Figure 1.03. The Adaptive Strategies Theory graphic model, also known as the CSR model, depicted as a ternary diagram. Primary functional strategies are represented as follows: C = competitively dominant, S = stress-tolerant, R = Ruderal. Secondary and tertiary strategies represent a compromise between two or three of the primary strategies, and are represented in the model by combinations of these three letters.
Grime (1977) added the variable “Competition” and modified the graphic model into
a ternary diagram so that the trade-offs between the adaptive strategies that confer
advantage under each of the three strategies could be represented illustratively in a simple
and intuitive manner. However, one problem with the ternary version of the model is that
it represents three variables constrained within two dimensions. To be more accurately
represented, the three variables should be considered to be independent of each other, and
thus each should have their own axes on a three-dimensional model (Loehle 1988). This
error in the graphic model means that the relative overall cost of response to each species
is constrained to the same level of cost as all other species under study. Such a graphic
constraint is consistent with the role of trade-offs between the three adaptive strategies
16
that Grime intended. However, it is more likely that some species will be better or worse
than others at acquiring resources or at balancing the trade-off between the intensity of
interspecific competition, resource availability and disturbance level, or that the trade-
offs are not linear. Therefore, Loehle (1988) contended, to more accurately depict nature,
each species should be located on points within a relatively bigger or smaller triangles in
the CSR ternary model. Of course Grime’s intent was to produce a relatively simple
model of all possible adaptive strategies, which Loehle’s proposed three-dimensional
model would not be. More importantly, however, it could be argued that adding
competition to the square graphic model to make it a ternary model mixes the two
independent variables, representing the environmental condition of the habitats, with the
dependent competitive response that the organisms within the habitats are predicted to
make (Steneck and Dethier 1994; Wilson and Lee 2000).
In order to avoid the problems associated with combining the dependent variable of
competition and the two independent variables in the graphic AST model, Steneck and
Dethier (1994) restructured the CSR ternary diagram of Grime (1977) back into a two
dimensional graphic (Figure 1.04). This reconfiguration restores resource availability
and disturbance to their capacity as independent variables, and C, S and R as dependent
response variables within the environmental state space.
17
Figure 1.04. Generalized model of community dominants by Steneck and Dethier (1994) that refines to Grime’s (1977) AST model (shaded in light gray). Primary strategies are in accordance with the AST with the addition of disturbance-adapted biota in the upper right corner of the model, which Grime later refuted (Grime 1995). Secondary strategies are indicated by letter designations.
However, I contend that Steneck and Dethier (1994) made a different error in their
graphic model (Figure 1.04). In their restructured model, Steneck and Dethier (1994)
included as inhabitable, areas under the graph in which resources are at very low levels
but in which disturbances are moderately high. If one assumes: (1) that the disturbance
gradient represents a range of rates of resource loss, (2) the gradient of stress on the y
axis represents a range of rates of resource gain, (3) that similar positions on the two axes
are intended to represent comparable levels of resource flux (albeit opposing directions of
flux), and (4) that habitat types in which rates of resource loss are greater than resource
gain cannot support organisms, then logically one should conclude that locations on the
graph representing a loss-gain ratio greater than 1 should be empty of functional groups.
To encompass these assumptions and conclusion, I suggest that the graphic model should
18
be redrawn as in Figure 1.05. In this further revision of the AST/CSR graphic model,
viable biological strategies are only shown to exist in the areas of state-space in which the
rate of resource gain is greater than the rate of resource loss. The line defining the
boundary between viable and intolerable environmental conditions represents the zero net
growth intercept (ZNGI) of the entire assemblage under investigation, in a manner
similar to that used by Tilman (1982; 1989), Chase and Leibold (2003) and others. With
the revised graphic model one can better represent how changes across habitats in the
environmental factors of resource availability and disturbance affect the characteristics of
coral assemblages. In Chapter 2 I delineate how the AST predicts each functional group
of corals will exhibit different levels of abundance, species richness and functional
ecology on reefs located across natural or anthropogenic gradients of stress and
disturbance.
19
Figure 1.05. A modified version of Grime’s (1977) and Steneck and Dethier’s (1994) generalized two-dimensional model of FG dominance within habitat types. This modified version incorporates the concession that biota can only survive in habitats within which the rate or amount of resource acquisition is greater than the rate or amount of resource loss. The boundary between the white and grey areas is the ZNGI of the assemblage as a whole. Letter designations for adaptive strategies are as in Figure 2.
Assigning Caribbean Reef Corals to Functional Groups and
Defining the Critical Tests
Functional classification schemes such as the AST have been most typically applied
to the study of terrestrial and marine plants (e.g. Grime 1979; Steneck and Dethier 1994;
reviewed in Solbrig 1994). Some animals, such as ants, also possess many of the same
characteristics that allow plants to be grouped according to functional response, such as
20
modularity, a dispersive reproductive phase and a sessile adult phase, and competition for
space, and for this reason have also been investigated under various functional
classification schemes (Andersen 1995). Reef corals equipped with zooxanthellae also
share many of the characteristics that plant ecologists use to differentiate functional
groups in plants (Furla et al. 2005), and for this reason may also be meaningfully
classified into functional groups using the sorting strategies developed by plant
ecologists.
Like plants, reef corals possess a modular structure and can be composed of an
indeterminate number of repeating multicellular units. Corals adopt many of the same
basic morphological shapes as plants, and these shapes typically share terminology, such
as foliose, palmate or bushy. It is not important that corals do not produce the exact same
morphologies as plant, just that corals and plants are both capable of utilizing their
modular character to produce a wide range of morphologies that differ in functional
effect and response to the environment and to competition. Corals and plants have
comparable life histories, with a dispersive reproductive phase followed by a sessile adult
phase. Both kinds of organisms also generally rely on light-driven photosynthesis and the
acquisition of water-dissolved nutrients for the resources and energy needed for growth
and other life-sustaining processes. Some corals and some plants are “ecosystem
engineers” (Jones et al. 1994), which produce topographic complexity that provides
habitat for other organisms, thereby enhancing the biological diversity of the habitats
they occupy. Additionally, both corals and plants maintain their spatial position through
interference competition with neighboring sessile organisms.
21
I contend that Caribbean reef coral species and the potential functional groups can be
assigned to positions within Grime’s Adaptive Strategies model, through reference to the
same kinds of attributes and characteristics in corals as Grime utilized for plants. Reef
corals appear to possess sets of traits that are indicative of adaptive strategies similar to
those defined for plants by Grime (1977). For example, Soong (1993) observed that
different species of massive (in this case, meaning hemispherical or mound-shaped,
following Budd et al. 2006) reef corals that shared maximum size (large or small) also
exhibited similar rates of growth and recruitment, reproductive mode, reproductive
season, and the size at which each species reached sexual maturity (Table 2).
Specifically, large massive corals appeared to exhibit a more K-selected strategy, with a
spawning reproductive mode, relatively high rates of colony growth as adults, delayed
puberty and low reproductive investment. Conversely, small massive species of corals
exhibited a more ruderal strategy, with a brooding reproductive mode, slower growth as
adults, and higher investment in reproduction and recruitment. The same ranges of and
trade-offs in trait values can be seen in Grime’s competitive and ruderal adaptive
strategies for plants. These similarities between Soong’s (1993) data for corals and
Grime’s (1979) plant groups imply that:
1) corals are also constrained in the manner in which they allocate resources to
critical ecological functions and
2) additional functional groups of corals, defined according to other morphological
and reproductive life history strategies, may match Grime’s other adaptive
strategies.
22
Table 1.02. Life history characteristics of massive scleractinian corals as defined in Table 3 in Soong (1993).
Character Large Species Small Species References* Reproductive Broadcasting Brooding 2, 11, 12Mode
Reproductive Once, Many Times, 11, 12Season Annual Cycle Lunar Cycle
Puberty Size Large Small 13
Recruitment Low? (sic) High? (sic) 3, 5, 6, 7, 8,10, 11, 12
Growth Rate High Low 1, 4, 9 _____ 1: Vaughan (1915); 2: Stimpson (1978); 3: Bak and Engel (1979);4: Highsmith (1979); 5: Rylaarsdam (1980); 6: Rogers et al. (1984); 7: Fitzhardinge (1985); 8:Hughes and Jackson (1985); 9: Hudson (1985);10: Wallace (1985); 11: Szmant (1986); 12: Soong (1991); 13: Soong 1993.
Johnson et al. (1995), in their investigation into the extinction selectivity of corals
with different ecological and life history traits, also found that sets of traits covaried in
Caribbean corals. In both extinct and extant corals, they found that branching species
were significantly more likely to have small corallites and small colonies than other
morphologies; massive corals were significantly more likely to have large corallites, large
colonies, and be oviparous; and that plating corals were more likely to have intermediate
sizes of corallites and be viviparous. Also oviparous corals were more likely to be
gonochoric, while viviparous corals were more likely to be hermaphroditic; a relationship
which was independently described by Carlon (1999).
Hughes and Tanner (2000) noted similar characteristic differences between large and
small, massive coral species as did Soong (1993). They found that Montastrea annularis,
23
a large massive spawning coral, displayed slower growth, was longer lived, and exhibited
sporadic (seasonal) recruitment; all life history strategies of K-selected organisms.
Conversely, Agaricia agaricites, a small brooding coral, has a shorter lifespan and more
consistent recruitment, under even marginal conditions; both of which were recognized as
ruderal strategies (Knowlton 2001).
Edinger and Risk (1999) proposed the use of a reef classification scheme for
Indonesian corals derived from Grime’s AST model. Their classification scheme
primarily used coral morphology as a means of categorizing Indonesian corals into one of
three adaptive strategies. In their scheme, conservation status of corals, equivalent to
functional groups, were as follows:
Competitive: Non-Acropora and foliose corals
Ruderal: Acropora species
Stress-tolerant: Massive and submassive corals
Edinger and Risk (2000) demonstrated that the conservation status could be predicted
for Indonesian reefs by classifying them according to the relative dominance of these
conservation classes. However, Edinger and Risk (2000) emphasized that their grouping
strategy and conservation classes were designed explicitly for Indonesian coral reefs and
that in other regions the categories should be changed to match regionally appropriate
coral species and conservation goals.
Attributes used for Classification
The scheme I propose, morphology and reproductive mode are the primary traits used
to define functional groups of coral species (Appendix 1). As indicated in Table 3,
24
reproductive mode and morphology are the combined traits that indicate a broad suite of
other functional characteristics of reef corals. The functional groups proposed are:
Competitive dominant: Branched oviparous corals,
Competitive-Ruderal: Branched, viviparous corals
Ruderal: Massive, viviparous corals
Competitive – Stress-Tolerant: Massive, oviparous corals,
Stress-Tolerant: Plating, foliose and solitary corals, (only viviparous in the
Caribbean).
25
Table 1.03. The ranking of each proposed functional group in ten critical traits, and the adaptive strategy to which they most closely represent. Smaller numbers represent higher rank and greater levels of each attribute. The morphological categories are: B: Branched; M: Massive; P: Plating and Solitary. The reproductive categories are: O:Oviparous; V: Viviparous. The reproductive methods are; F: Fragmentation; X: sexual reproduction. The adaptive strategies are: C: Competitive; CR: Competitive – Ruderal; CS: Competitive – Stress-tolerant: R: Ruderal; S: Stress-tolerant.
Trait BO BV MO MV PV Review Reference
Maximum Size (Genet) 1 3 2 5 4 Johnson et al. 1995
Longevity (Ramet) 3 4 2 5 1 Hughes 1984
Longevity (Genet) 1 2 3 5 4 Highsmith 1987
Reproductive Maturity 5 2 4 1 3 Richmond 1998
Reproductive Effort 4 2 3 1 5 Richmond 1998
Reproductive Method F>X F:X F>X F<X F<X Highsmith 1987
Growth Rate 1 2 3 4 5 Huston 1985b
Stress Response 3 4 2 5 1 Bak and Meesters 1998
Aggression 3 4 5 2 1 Lang 1973
Palatability 3 2 4 1 5 Rotjan and Lewis 2005
Adaptive Strategy C CR CS R S
26
Characteristics of Each Functional Group of Coral
Competitive dominant: Branched oviparous corals
In the Caribbean, branched, oviparous corals are represented by Acropora and
Oculina species (Appendix 1; Fadlallah 1983; Harrison et al. 1984; Richmond and
Hunter 1990; Brooke and Young 2003). Corals of these two genera have high growth
rates (Huston 1985b), indeterminate growth (Highsmith 1987) and typically dominate the
surface of most coral reefs (Richmond and Hunter 1990; Brooke and Young 2003).
Sexual reproduction occurs in late summer, the period when both resource availability
and the risk of damage due to hurricanes are most likely, and thus when the risk of
wasting resources via reproduction is offset the most (Woodley et al. 1981). Recruitment
rates are typically very low (Bak and Engel 1979, Rogers et al. 1984, Harrison and
Wallace 1990; Smith 1992, Richmond 1997), which confirms their status as competitive
dominants which allocate resources to growth versus reproduction. These branched
corals fragment easily and can apparently utilize this form of asexual reproduction to
successfully disperse over small distances (Highsmith 1987, Lirman 2000). Their
branched structure allows survival under high sediment loads, although episodic
occurrences of high turbidity may inhibit rapid growth fueled by photosynthesis. Rapid
growth and a tall, branched structure allows these corals to overgrow all other corals
under benign environmental conditions. They are moderately aggressive in direct
interactions with other corals (Lang 1973). While their skeletal structure provides
moderate protection from predation by parrotfish, Acroporids are prone to corallivory by
polychaetes (Woodley et al. 1981) and snails (Baums et al. 2003). The corals of this
functional group should demonstrate low spatial variability among sites at one depth
27
within a reef, but high variability across areas of varying water quality (e.g. Lidz and
Shinn 1991 ). Also, sections of the reef tract that receive more frequent or very intense
disturbances, such as areas exposed to the open ocean, should have lower cover of
branched spawning corals compared to less frequently disturbed areas (e.g. Geister 1977;
De Meyer 1998; Parker and Oxenforn 1998).
28
Competitive-Ruderal: Branched, viviparous corals
Branched corals of the genera Porites and Madracis, as well as the species Agaricia
tenuifolia utilize a viviparous reproductive strategy (Appendix 1; Morse et al. 1988;
Johnson et al. 1995; Richmond 1998). These corals typically have a digitate, branched, or
morphologically plastic form (Smith 1984; Bruno and Edmunds 1996; Veron 2000) and
can dominate large areas (Lewis and Snelgrove 1990; Chornesky 1991; Aronson et al.
1998). While the colonies can be very large, living tissue often does not connect
neighboring branches (Smith1984; Lewis and Snelgrove 1990; Veron 2000), implying
that branch longevity is much shorter than colony longevity. Branched viviparous corals
release planulae over an extended period of time (Richmond 1997), resulting in relatively
high rates of recruitment (Bak and Engel 1979; Smith 1992). Since they can also disperse
through fragmentation (Highsmith 1987; Bruno and Edmunds 1997), corals of this
functional group are able to take advantage of both asexual and sexual reproduction as a
means of escaping disturbances and spreading across a reef (Bruno and Edmunds 1997).
Branched viviparous corals exhibit weak aggression towards other coral species (Lang
1973). Additionally they are not structurally defended from corallivory, and can suffer
high levels of predation by parrot fish (Murdoch, Looney and Aronson unpublished
document; Grottoli-Everett and Wellington 1997, Miller and Hay 1998). The enhanced
tolerance to disturbance and mix of reproductive strategies should allow branched
viviparous corals to show moderate to high cover and low variability across reefs in
marginal habitats (Aronson et al. 2005) , and low cover in areas where parrotfish or
competitively dominant species are abundant.
29
Ruderal: Massive, viviparous corals
Massive (mound-shaped), viviparous corals are found within a broad range of genera,
including Agaricia, Favia, Manicinia and Porites (Appendix 1). Corals of these genera
have smaller colony sizes (than massive, oviparous corals), determinate growth, a short
lifespan, and high reproductive output (Soong and Lang 1992; Soong 1993). These corals
tolerate greater extremes in disturbance than mound-shaped spawners (Sammarco 1985;
Connell 1997), but are not good competitors for space (Lang 1973), and reproduce at a
young age (Richmond 1990). Additionally many massive oviparous corals are capable of
self-fertilization (Brazeau et al. 1998). As they reproduce continually over the year, less
energy is available for growth (Hall and Hughes 1998). These factors indicate a ruderal
lifestyle that is maximally adapted to frequent settlement and rapid growth within patches
of marginal quality generated by disturbance. These corals are likely to be the first to
settle in newly disturbed areas, and indeed may be the only corals present if conditions
are extreme. Like viviparous branched corals, massive viviparous corals also are not well
defended and are subject to high levels of corallivory by parrotfish (Rotjan and Lewis
2005). The corals of this functional group should demonstrate low variability among sites
within reefs, as they have a wide range of environmental tolerance and high recruitment
rates. Mound-like brooding corals should also show low variability from reef to reef, for
the same reasons. As they are neither good competitors nor aggressive, ruderal corals
should be less abundant than competitively dominant species on most reefs.
Competitive – Stress tolerant: Massive oviparous corals
30
Massive oviparous corals include species from the genera Montastrea, Diploria,
Colpophylia, as well as additional genera (Appendix 1). Corals that are mound-like and
that spawn gametes generally possess moderate to high growth rates as adult colonies,
indeterminate growth and can reach very large sizes (Soong 1993). As they only
reproduce during part of the year, and generate gametes which need to be fertilized in the
water column, they have moderate to low recruitment success (Smith 1992). Partial
mortality may create large fragments with high survivorship. Massive oviparous corals
are generally sensitive to sedimentation (Nugues and Roberts 2003), although this
weakness may be offset by the corals’ ability to grow rapidly (Logan et al. 1994).
However, their shape and size may aid in the survival of intense disturbances such as
storms and hurricanes (Woodley et al. 1981, Liddell and Olhorst 1987). Massive
oviparous corals have moderately large and plocoid corallites, which protect polyp tissue
from predation by fish such as parrotfish. The corals of the massive oviparous group
probably demonstrate high spatial variability in coral cover from reef to reef, depending
on the water quality of each reef. Reefs in clear oligotrophic ocean water should have a
high cover of large massive oviparous corals, with a large proportion of the population
composed of competitively superior genets. Reefs in turbid or nutrient-rich water should
have a lower cover of these corals, and the ones present should be smaller and more
fragmented. The within-reef variability of this group of corals could be high or low,
depending on the levels and history of disturbance, and age of the reef in question.
Stress Tolerant: Plating, foliose, and solitary corals
31
Plating, foliose, and solitary corals, such as species within the genera Agaricia,
Mycetophyllia and Scolymia, have slow growth rates and generally a moderate to small
colony size (Johnson et al. 1995, Veron 2000). They tend to have thick tissue relative to
skeletal thickness (Budd et al. 2006), and thus fragment rarely. However, since they
produce brooded planulae (Johnson et al. 1995; Richmond 1998) which may be capable
of settlement soon after release from the parent, recruits may tend to cluster in
environments for which they have an adaptive advantage. The corals in this group
generally rank high in Lang’s (1973) aggression scale, and often have complex skeletal
structures, such as coarse septal dentition, (Budd et al. 2006) which may prevent
complete tissue loss to polyps by either competition or predation. Stress-tolerant corals
should be very patchily distributed on all scales, since they recruit near to the parent
colony and are susceptible to disturbance and interference competition by most other
types of coral.
Sources of Environmental Stress and Disturbance on Coral Reefs
The four environmental factors that most strongly play a role in determining the
characteristics of a coral assemblage at a reef site are temperature (Weber and White
1974; Glynn and Stewart 1973; Walker et al. 1982)), light (including UV light)
(reviewed in Falkowski et al. 1990), current speed (Geister 1977), and suspended
sediment load (Dodge and Vaisnys 1977; Acevedo et al. 1989; Anthony 1999). All four
of these factors may be considered a source of enhanced growth or as a source of
disturbance to corals, depending on the intensity or rate at which the coral is exposed to
each factor.
32
Corals are adapted to a specific range of temperatures, and are negatively affected if
exposed to temperatures that are only 2° above or below this range (Figure 1.06A;
Walker et al. 1982; Glynn 1988). Cold temperature can be viewed as a stress, in that
physiological processes are restricted by low temperatures. Conversely, high
temperatures act as a disturbance by damaging the tissue of the coral host and also
causing the expulsion of the symbiotic zooxanthellae in the process of coral bleaching
(reviewed by Browne 1997).
Corals are also adapted to a specific range of light conditions (Figure 1.06B), with
excessive light causing damage to the both the coral host and also damage or the
expulsion of their symbiotic zooxanthallae (Falkowski et al. 1990; Browne 1997). Since
light is required by zooxanthallae for photosynthesis of carbohydrates, which are made
available to the coral host, low levels of light result in a loss of resources to the coral
colony.
Suspended sediments (Figure 1.06C) negatively affect coral increasing the turbidity of
the water column and there by blocking light transmission (McCarthy et al. 1974),
smothering the coral polyps (Hubbard and Pocock 1972; Rogers 1990), or by abrading
coral tissue (Rogers 1990). Alternatively, suspended sediments may provide nutrition to
corals that are not otherwise available in oligotrophic waters (Anthony 1999; Mills et al.
2004) and corals may be nutrient stressed when both dissolved and particulate sources of
nitrogen are in low concentration.
Waves and other forms of water motion generate currents which affect corals in
different ways depending on their strength (Figure 1.06D). Water motion is required to
carry dissolved and particulate nutrients to the coral (Anthony 1999; Mills et al. 2004)
33
and low current speeds result in less nutrient resources being available to the coral colony
due to the development of a boundary current. On the other hand, currents with a high
rate of flow can break corals (Geister 1977; Tunnicliffe 1981) or suspend sediment and
thereby abrade coral tissue (Rogers 1990).
34
Figure 1.06. Representation of how varying levels of the four most important environmental factors act to promote growth, or act as a stressor or disturbance agent to corals.
35
Testing the Applicability of the Functional Group Approach for Reef Corals
In this dissertation, I test several hypotheses regarding how each different functional
group of reef corals varies across environmental gradients of stress and disturbance. The
specific predictions are as follows:
Similarities in Distribution of Species Between and Among FG
Species within functional groups are hypothesized to be redundant in terms of their
functional responses to the environment. If this is so then species belonging to the same
functional group should differ little in their distributions across sites, due to the shared
responses to environmental and biological conditions (Steneck and Dethier 1994; Gitay
and Noble 1997; Hooper et al. 2002). Conversely, the distribution patterns of species
belonging to the functional groups should be substantially different due to disparate
environmental tolerances. Under the above paradigm, species within environmental
functional groups are hypothesized to be redundant in terms of their functional responses
to the environment. If this is so then species belonging to the same functional group
should differ little in their distributions across sites, due to the shared responses to
environmental and biological conditions (i.e. Figure 1.07C).
If, however, the traits used to distinguish species into functional groups are those
primarily utilized for resource acquisition, and not environmental tolerance, then species
within functional groups should be too similar to be able to persist within the same
habitats (following Gause 1934). Under this scenario species that belong to the same
resource-based functional groups (also termed “guilds”) should tend to occur in different
habitats (reviewed in Fox 1999). Also species from different guilds should be able to
36
coexist to a greater degree than species from the same guild. Patterns of species
distributions when grouped into guilds should match the pattern in Figure 1.07D, below.
Conversely, if functional groups do not exist, or if the species within functional
groups do not respond in unison to changes in environmental condition, then a serial
(Figure 1.07A) or nested pattern (Figure 1.07B) of species turnover may occur across
sites. Analysis of species abundance data, species presence-absence across sites, or the
ordination of multidimensional species data for sites can be used to determine which of
the above patterns are exhibits by corals in sites located across environmental gradients.
37
Figure 1.07. An illustration of different hypothetical distributions of species and functional groups across an environmental gradient (A to D), and how they appear when graphed as (i) abundances, (ii) tabulated in a matrix of presence vs. absence, and (iii) graphed using a multivariate ordination technique, such as Multidimensional Scaling (MDS). In the second column of figures, columns in the matrix represent sites and rows represent species and functional groups. Filled cells in a row represent the presence of a species and empty cells represent its absence. Each row represents a different hypothetical distribution, as follows:
(A) The pattern of species presence when species and functional groups are replaced in series across an environmental gradient.
(B) An alternate pattern, in which the range of sites inhabited by organisms with lower tolerances are nested within the range of sites occupied by more tolerant species and functional groups.
(C) The distribution pattern in which functional groups exhibit turnover in response to the environmental gradient but species within functional groups coexist and have the same distributions (i.e. FG underdispersion).
(D) A different pattern in which species only compete strongly within functional groups but not between functional groups. Under this scenario species of different functional groups are predicted to co-occur while species within functional groups distribute themselves with turnover across the environmental gradient (i.e. FG overdispersion)
38
Rank Abundance by Species and Functional Groups
According to the AST (Grime 1979), species and functional groups should differ in
dominance depending upon the levels of stress and disturbance of the habitat they are in.
Alternately, the unified neutral theory (UNT) suggests (Hubbell 2001) that all coral
39
species are functionally equivalent, and the ranking of any species will be random from
site to site, regardless of the environmental conditions of the reef in which it is found. If
the paradigm of UNT is in operation, no species is expected to exhibit greater dominance
when examined across a large number of sites. Conversely, it may be that species differ
in dominance, but that no within-functional group similarities in dominance patterns
exist. This would indicate that each species is different from all other species but that
they do not share functional group affiliation as I previously designated them above. If,
however, species from the same functional group tend to have similar dominance patterns
across transects, this would indicate that functional groups exist and that species within
functional groups tend to be fairly equivocal. In other words the UNT may apply within
FG but not between FG. In Under this model, the pattern of dominance of species would
conform with both the AST and a version of the UNT (Hubbell 2005).
If the predictions of the AST are true, then the corals of the MO (massive oviparous)
functional group should dominate on reefs with high colony density. This is because they
are predicted to use growth to dominate when resources are abundant and levels of
disturbance low. However, since low total colony abundance was shown above to be
highly correlated with W, which I showed above is a proxy for disturbance, and the MO
functional group is predicted to have low growth rates and survivorship when levels of
disturbance or stress are high, it is predicted to not dominate on reefs with low total
colony abundance. Conversely, species of the stress-tolerant and the ruderal functional
groups, which are the foliose and plating functional group and the massive viviparous
functional groups, are predicted to dominate reefs with low total colony density. The
rank abundance of the species from each group will drive the rank abundance of each
40
functional group as a whole, and if this is the case then the MO functional group is
predicted to dominate most reefs with the other functional groups occupying a
subordinate position.
Percent Cover of All Corals
The first line in Grime’s (1977) classic paper defines stress and disturbance as
“external factors limiting (plant) biomass”. In this scenario, the level of stress represents
the relative rate of resource availability to organisms within a habitat, and disturbance the
relative rate of resource removal or loss to organisms within a habitat. Habitats
characterized by the presence of more resources (i.e. a high rate of resource gain), and
fewer disturbances (i.e. a lower rate of resource loss), should exhibit more organisms,
higher amounts of biomass or a higher percentage of cover by corals than habitats
exposed to higher levels of disturbance or stress (Figure 1.08).
41
Figure 1.08. An illustration of how total assemblage biomass is predicted to vary across habitat types characterized by different levels of resource availability and disturbance.
Percent Cover per Functional Group
According to the AST, each functional group is adapted to survive only within a
specific range of disturbance, stress and competition, representing that functional groups’
environmental and biological niche. If functional groups are affected by the environment
in this manner, each primary functional group (C, ST or R) will dominate one of the three
environmental extremes (see Figure 1.09A below), and also will decline in abundance
rapidly in habitats characterized by other environmental conditions. Also each
intermediate strategy (such as C-R, S-R or C-S) should peak in abundance at a midpoint
42
between environmental extremes. The abundance of each functional group is also
expected to display little overlap from HT to HT according to this model.
More recent theoretical and empirical evidence (O’Neill et al. 1988; O’Neill 1989;
Peterson et al 1998; Bolker and Pacala 1999) indicates that the pattern in which each
functional group heavily dominates one area within the AST model may not apply.
Instead all functional groups may be capable of coexistence in almost all habitat types
except the three extreme environments. If the functional groups that are not competitively
dominant utilize either (1) recently cleared patches of high resource availability via
source-sink dynamics (ruderals), or (2) patches of low resource quality (i.e. heavily
shaded; stress-tolerant species), then they could persist in habitats exposed to low
disturbance and high stress, despite the spatial dominance of the competitive group
(Bolker and Pacala 1999). If these adaptive strategies are in effect, then ruderal and
stress-tolerant species may also reach maximum cover in habitats with highest resource
availability, and the overlap between functional groups will be high (Figure 1.09B and C
below).
43
Figure 1.09. Diagrams depicting the differing ways in which the abundances of competitive (C), stress-tolerant (S) and ruderal (R) functional groups of corals are predicted to vary across habitats located across the range of stress and disturbance gradients encompassed by the AST model. Each model illustrates a different degree of niche overlap that may plausibly be exhibited by each functional group. In all graphs X and Y represent graphs of abundance relative to levels of disturbance (X) or stress (Y). Z represents the modified CSR square diagram, with the zero net growth intercept (ZNGI) illustrated for each functional group. Graph A matches Grime’s original predictions in which functional groups are limited to specific regions of adaptive niche phase space with no overlap in niche boundaries. Graphs B and C represent alternate models in which competitive species do not negatively interact with stress-tolerant or ruderal species. In graph B the functional groups exhibit minimal overlap in niche boundary, whereas in graph C the functional groups exhibit maximal overlap in niche boundary. In all models C, S an R functional groups maintain dominance under differing environmental conditions.
Regardless of whether the niche model or the competitive hierarchy model is the more
accurate description of reality, and irrespective of the level of overlap between species,
the following predictions can be made:
The competitive group will exhibit it’s highest level of cover at the least disturbed
and least stressed site.
The competitive group will exhibit higher cover than all other groups at the least
disturbed and least stressed site.
44
Other functional groups may peak in cover at some moderate level of disturbance
or stress.
All functional groups should display lowest cover at the most disturbed or stress
site.
The C, CS, and S groups should decline in cover more rapidly than R groups
across gradients of disturbance. The S group should decline to minimal levels before the
C group across a disturbance gradient.
C, CR and R groups should decline in cover more rapidly than S groups across
gradients of stress.
Total Species Richness
As previously stated in the Intermediate Disturbance Hypothesis (Grime 1973;
Connell 1978; Sousa 1979; Aronson and Precht 1995; Dial and Roughgarden 1998 and
many more), the number of species found within certain kinds of habitat will be limited
by both environmental conditions and biological interactions. High levels of stress or
disturbance should restrict species richness by limiting the rates of growth or by depleting
populations faster than they can recover (Figure 1.10). Under low levels of stress or
disturbance, species with the best ability to acquire resources and procure territory from
other species will inevitably maintain a competitive advantage. The monopolization of
space by these competitive species will obstruct the settlement and growth of subordinate
species within patches, thus limiting the number of species within habitats that have low
levels of stress and disturbance. For these reasons, in Grime’s Adaptive Strategies model
(1977) a peak in species richness is expected to appear at the location within the model
45
where rates of population growth and rates of recovery from disturbance are both at
moderate levels (Figure 1.10).
Figure 1.10. The distribution of species richness predicted to occur across habitats by Grime’s (1977) Adaptive Strategies model. High represents a peak in species richness at the midpoint between resource loss and gain. Low represents areas of reduced species richness due to environmental or biological factors. Circles enclose areas of equal species diversity.
Functional group richness
Functional group richness represents the number of functional groups found within a
particular habitat. While Grime (1977) does not make any explicit predictions about how
functional group richness or diversity varies across his ternary model, he does plot the
general location of different plant groups, such as trees, shrubs and herbs, within the
46
ternary diagram (Figure 1.11). In his illustration, the greatest number of plant functional
types occurs at the midpoints of the two axes of resource flux, with fewer plant types
found towards the edges. Unfortunately, Grime (1977) does not provide a theoretical
reason for the pattern he predicts to occur.
Alternatively, Steneck and Dethier (1994) predict that the number of functional
groups will peak across habitat types in the same manner as does total biomass of the
assemblage across the adaptive strategies model (Figure 1.12). Their pattern is based on
the empirical results of their research into the distribution of marine plant functional
groups across tropical and temperate sub-tidal habitats. In their graphical model the most
stress- and disturbance-tolerant species are grouped into one inclusive category, and are
located across all survivable habitat types. Additional functional groups then appear
towards the corner of the square in which resources are not limited and disturbance levels
are low. This pattern directly contradicts the general predictions of the Adaptive
Strategies Model (Grime 1979), where ruderal species are defined as intolerant to stress,
and stress-tolerant species are defined as incapable of persisting under heightened
disturbance. Another problem with the Steneck and Dethier (1994) model is that no
theoretical explanation for their predicted (nested) pattern is provided either.
47
Figure 1.11. A diagram illustrating the range of strategies encompasses by (a) annual herbs, (b) biennial herbs, (c) perennial herbs and ferns, (d) trees and shrubs, (e) lichens and (f) bryophytes. For the distribution of strategies within the model see Figure 4. Modified from Grime (1977).
48
Figure1.12. A three dimensional model of the levels of biomass predicted for set of functional groups of species across habitat types characterized by varying levels of disturbance potential and productivity potential. Modified from Steneck and Dethier (1996).
As stated above, there are considerable shortcomings with both of the above models.
The prediction of Steneck and Dethier (1994) of a peak in the Competition section of the
ternary model is counter that of Grime (1977), who states that the peak in functional
diversity should occur in habitats experiencing the lowest levels of competition. Neither
theory incorporates a prediction of how the richness or diversity of species within each
functional group will vary across habitat types. Finally, both models lack a theoretical
underpinning. In order to address these issues, in the next paragraph I put forward a
theoretical explanation for how the components of (1) functional group diversity, and (2)
the diversity of species within each functional group will vary across habitats of varying
resource flux, as illustrated in the Adaptive Strategies Model.
49
In the restructured model I propose, I define positions within the graphical Adaptive
Strategies Model as habitats, in which each habitat is composed of a patchwork of habitat
types that differ slightly in environmental condition (Figure 1.13; Connell and Keough
1985). Each position within the model defines the upper limit in the rate or amount of
resource flux (gain or loss) within each habitat. In this manner, highly stressed habitats
should only contain a small range of resource availability due to a low rate of resource
gain, disturbed habitats should contain a small range of resource availability due to high
rates of resource loss outpacing resource gain, while benign habitats should possess
patches exhibiting a wide range of resource availability, due to resource gain outpacing
resource loss.. Following this reasoning, stressed or disturbed habitats should be limited
in the range of species and functional groups they can harbor, while benign habitat types
should exhibit the full complement of functional groups. More functional groups are
predicted to survive within benign habitat types despite the dominance of space by
competitive dominants because some patches are likely to exist that possess lower levels
of resource availability or higher levels of disturbance which the competitors cannot
tolerate. Accordingly, functional diversity should peak in the upper left corner of the
model, as it does in the model of Steneck and Dethier (1994), and not as predicted by
Grime (1977). However, in the proposed model, unlike that of Steneck and Dethier
(1994), ruderal functional groups are not predicted to occur within stressed habitats, and
stress-tolerant functional groups are predicted to be absent from habitats subject to high
levels of disturbance. Such a pattern is in accordance with the original Adaptive Strategy
Theory (Grime 1977).
50
Figure 1.13. A diagram illustrating how functional groups are predicted to be dispersed across patches located with habitats defined by varying rates of resource gain and loss. Larger squares represent habitats. The smaller nested squares represent patches within habitats. Letters represent the functional group occupying each patch. C represents the competitive functional group. S represents the stress-tolerant group and R represents ruderals. Grey squares represent empty patches. The black field on the lower right side of the diagram represents the range of habitats in which high relative rates of resource loss limit biomass.
51
Species richness within functional groups
The differences in life history strategy of each functional group should affect how the
species within each group interact across gradients of stress or disturbance. Competitively
dominant organisms are predicted to compete heavily under benign environmental
conditions, but it may be that competition is only directed towards other members of the
competitive functional group and not members of the other functional groups. Ruderal
species are typically the poorest competitors for space, in both direct contact and
overgrowth competition. Stress-tolerant species are characterized as the strongest
defenders of space, but also recruit to patches that possess low levels of resource that
could potentially reduce their rates of competition substantially. If it is true that
competitive dominant species only compete with each other, then the species richness of
the competitive group should be reduced in habitats where resources are more abundant
and where disturbance levels are low. Under this scenario, the stress-tolerant and ruderal
species would be expected to display highest levels of species richness in low stress and
disturbance patches. Alternately if the species within the competitive functional group
does compete against all other species regardless of life-history, or if species within each
functional group compete strongly with other members of the same group, than all FG
will display a reduction in species as resources increase and disturbance levels decline.
Regardless of the potential differences in competitive interaction between functional
groups, all functional groups are predicted to display a reduction in species richness in
habitats characterized by low resource levels or high disturbance. The species richness of
the competitive dominant and stress-tolerant functional groups should decline faster than
the ruderal group’s species richness as disturbance levels increase, and the species
52
richness of the competitive dominant and ruderal functional groups should decline faster
than stress-tolerant functional group’s species richness as resources levels decline across
sites.
Testing the adaptive strategies theory on Caribbean coral reefs
In the chapters to follow, I will examine the ability of the proposed functional group
approach to predict the structure of coral assemblages at sites on reefs located across the
environmental and biological gradients found across the Florida Keys reef tract and the
Bermuda reef platform. In Chapter 2, I test the predictions of the adaptive strategies
model with coral data from reefs in Florida. The Florida data are from deep fore reef
sites located at 13 to 19 m depth. These reefs are characterized by a spur-and-groove
geomorphology and separated by deeper, sandy areas. An earlier investigation
determined that the Florida Reef tract displays distinctive scales of variability in total
coral cover and abundance. Chapters 3 and 4 describe how I collected data from sites
located at multiple aspects (i.e. compass bearing) and depths from patch reefs located at
intervals across the lagoon that is found north of the island of Bermuda. By selecting sites
that vary in depth and distance from shore, the responses of species and functional groups
of coral to two distinct environmental gradients can be examined. In Chapter 5 I
summarize the conclusions of the previous chapters and discuss their implications.
53
CHAPTER 2: THE RESPONSES OF FUNCTIONAL GROUPS OF CORALS TO
DIRECT AND INDIRECT GRADIENTS ON THE FLORIDA REEF TRACT
Introduction
In this chapter I examine how functional groups of corals are distributed across a
gradient of disturbance (i.e., along the C-R axis of the AST model; Figure 2.01), over
which the range of the resource (stress) gradient is at a minimum. This was done by
comparing coral assemblages located at a single depth across reef sites known to vary in
water quality. Standardizing the environmental conditions in this way allowed the
examination of the hypothesized competition-colonization trade-off displayed between
competitive and ruderal corals, while limiting the expected range of responses by the
stress-tolerant functional groups.
The 1995 Keyswide Coral Reef Expedition was a multidisciplinary survey of coral reef
habitats located along the entire Florida Reef Tract. The results and mapping these coral
assemblages showed that coral cover, colony abundance and diversity varied among reefs
on deeper forereef habitats (13-19 m depth) (Aronson and Murdoch 1996; Murdoch 1998;
Murdoch and Aronson 1999). Each biological measure (i.e. cover, abundance, diversity)
showed little variability across sites separated by 1 km within reefs, demonstrated high
variability among adjacent reefs separated by less than 10 km, and showed little variability
54
across regions sampled at the 50-km scale. Furthermore, focused analysis in the Middle and
Lower Keys regions determined that exposure to inimical water from Florida Bay reaching
the reefs through passes between the keys was a likely source of the high variability in
community structure observed from reef to reef (Murdoch 1998). Florida Bay water does
not flow into the other regions of the Florida Keys where reefs were assessed by Murdoch
(1998), and so only reefs within the Middle and Lower Keys were including in the focused
analysis.
Florida Bay water possesses several characteristics that can limit coral growth or
survival. These characteristics include extreme variability in temperature and salinity,
and high nutrient and sediment loads (Shinn et al. 1989, Szmant and Forrester 1996). To
test the hypothesis that Florida Bay water negatively affected the coral assemblages on
spur-and-groove reefs in the Middle and Lower Keys, the average coral cover, as
surveyed in the Keyswide Coral Reef Expedition (Murdoch and Aronson 1999), was
compared with a dependent variable (W) by Murdoch (1998). The variable W was
derived from (A) the average flow rate of Florida Bay water traveling through individual
passes, which was measured by Smith (1994), divided by (B) the linear distance to the
nearest up-current pass in km, as determined by maritime charts:
W = flow rate (m sec-1) / linear distance from pass to reef (km) (1)
55
Figure 2.01. The elongated oval within this square diagram of state space represents the hypothetical range within the AST (CSR) model that was occupied by the sites of the Florida Reef Tract that are the focus of this chapter.
56
Visual inspection of the graph and regression analysis of average coral cover at each
site with W (Figure 2.02) indicated that coral cover declined in a linear fashion with an
increase in W (i.e., an increase in flow rates or a decrease in the distance to the nearest
pass). The least squares regression analysis of data describing the change in coral cover
with change in W produced the equation:
Coral cover = 17.381 - 0.2367(W) (2)
The independent variable W (flow rate/distance to pass) explained much of the
variance in coral cover. A t-test determined that the slope of the best-fit line differed
highly significantly from zero [r2 = 0.8318, df = 9; t-ratio = -6.29, p = 0.0002].
The existence of a significant linear relationship between the variable W and coral
cover on the reefs of the Middle and Lower Keys provides support for the conclusion that
there exists a steep gradient of environmental factors in operation across these habitats
(Murdoch 1998), and that these factors vary with the factor W. Direct gradient analysis
can be done to determine how the coral assemblage varies relative to the factor W. As
stated above, investigating the manner in which functional traits and groups of corals
vary in relation to direct (environmental) gradients is most likely to produce powerful
models when done along obvious physical gradients such as the one observed in the
Florida Keys (Hutchinson 1957; Whittaker 1975; McGill et al 2006).
All 20 sites of the Keyswide Coral Reef expedition also varied in percent cover of the
total coral assemblage (hereafter referred to as “total coral cover”; Aronson and Murdoch
1996; Murdoch 1998), ranging from ~1% to ~20%. While the environmental causes of
57
Figure 2.02. Relationship between total percent cover of the entire coral assemblage and the measure of environmental disturbance due to island passes, W.
the variability of all 20 reefs is unknown, indirect gradient analysis may be used to test
the hypotheses detailed in Chapter 1 regarding whether the attributes of functional groups
of corals vary changes relative to total coral cover. Since total coral cover represents the
most commonly-used metric for determining the ecological condition of coral reefs, and
because the manner in which the attributes of functional groups of corals vary relative to
total coral cover are as yet unstudied, an investigation of the manner in which functional
traits and groups of corals vary in relation to the indirect (biological) gradient is also
important to determine.
58
OBJECTIVESFocusing on the functional groups of corals described in Ch 1, I examined how the
coral composition of 10 separate reefs located within the Middle and Lower Keys regions
changed in relation to the direct environmental gradient defined by the variable W. Only
these 10 reefs were surveyed relative to W as they are the only reefs within proximity to
the passes connecting the reef tract to Florida Bay. In particular, I examined how the (1)
rank-abundance (dominance) of species and functional groups (2) percent cover and
abundance of each functional group, (3) species richness of the total coral assemblage,
(4) functional group richness, and (5) species richness within each separate functional
groups varied across the Middle and Lower Keys reef sites previously shown to vary in
total coral cover in a linear manner relative to the distance from passes and the strength of
the currents flowing through each pass (Murdoch 1998).
I also investigated the relationship between the same five variables and the indirect
gradient of total coral cover on all 20 of the coral reefs surveyed in the Keyswide Coral
Reef Expedition, using model 2 (orthogonal) regression for functional group cover and
model 1 (least squares estimate) regression for all other comparisons. While the
environmental causes of the differences in total assemblage cover for the ten reefs not
included in the analysis of the direct gradient were not experimentally determined, all
twenty reefs were assessed for a couple of reasons. These reasons are: (1) percent cover
data represent a common means of evaluating the ecological condition of coral reefs
(Rogers 1994), and (2) gradient analysis of the 20 sites encompassing the entire Florida
Keys region may uncover patterns in the five independent factors that are not apparent in
59
the smaller dataset from the 10 sites in the Middle and Lower Keys sectors. The 20 sites
surveyed were not compared using
Based on the theoretical postulates stated earlier, I predict the following patterns in
the coral assemblage structure of these Floridian reefs:
Similarities in distribution of species between and among FG
Species within functional groups are hypothesized to be redundant in terms of their
functional responses to the environment. If this is so then species belonging to the same
functional group should differ little in their distributions across sites, due to the shared
responses to environmental and biological conditions (Steneck and Dethier 1994; Gitay
and Noble 1997; Hooper et al. 2002). Conversely, the distribution patterns of species
belonging to separate functional groups should be substantially different due to disparate
environmental tolerances. Under the above paradigm, species belonging to the same
functional group should differ little in their distributions across sites, due to the shared
responses to environmental and biological conditions (i.e. Figure 2.03C).
If, however, the traits used to distinguish species into functional groups are those
primarily utilized for resource acquisition, and not environmental tolerance, then species
within functional groups should be too similar in resource requirements to be able to
persist within the same habitats (following Gause 1934). Under this scenario, species that
belong to the same resource-based functional groups (also termed “guilds”) should tend
to occur in different habitats (reviewed in Fox 1999). Also species from different guilds
should be able to coexist to a greater degree than species from the same guild. Patterns of
species distributions of guilds should match the pattern in Figure 2.03D, below.
60
Rank abundance by species and functional groups
Examination of the rank-abundance patterns of species and functional groups was
done to test whether species and functional groups differ in dominance, as predicted by
the AST, or alternately, whether all coral species are functionally equivalent, as the
unified neutral theory (UNT) suggests(Hubbell 2001). If the UNT is correct then all
species will appear equally likely to be the most abundance on a transect, regardless of
the environmental conditions of the reef in which it is found, and no species will exhibit
greater dominance.
Alternately, it may be that species differ in dominance, but that no within-functional
group similarities in dominance patterns exist. This would indicate that each species is
different from all other species, but that they do not share functional group affiliation as I
previously designated them in Chapter 1. If, however, species from the same functional
group tend to have similar dominance patterns across transects, this would indicate that
functional groups exist and that species within functional groups tend to be fairly
equivocal. In other words the UNT would apply within FG but not between FG, which is
a pattern which conforms with both the AST and a version of the UNT (Hubbell 2005).
If the predictions of the AST are true, then the corals of the MO (massive oviparous)
functional group should dominate on reefs with high colony density. This is because they
are predicted to use growth to dominate when resources are abundant and levels of
disturbance low. However, since low total colony abundance was shown above to be
highly correlated with W, which I showed above is a proxy for disturbance, and the MO
functional group is predicted to have low growth rates and survivorship when levels of
61
disturbance or stress are high, it is predicted to not dominate on reefs with low total
colony abundance. Conversely, species of the stress-tolerant and the ruderal functional
groups, which are the foliose and plating functional group and the massive viviparous
functional groups, are predicted to dominate reefs with low total colony density, although
they should do so under different environmental conditions. The rank abundance of the
species from each group will drive the rank abundance of each functional group as a
whole, and if this is the case then the MO functional group is predicted to dominate most
reefs with the other functional groups occupying a subordinate position.
To test the null hypothesis that no species or functional group ranks higher than the
rest, the counts for each possible rank was tabulated for each species, and separately for
each functional group, across all 200 transects of the 20 sites. Chi-square analysis was
used to determine whether the resultant table possesses a non-random distribution of
ranks across sites for species and for functional groups. Logistic regression was also done
to determine whether the ranks of each functional group varied in a non-random manner
relative to the average coral cover of the 200 sites.
Percent cover and abundance per functional group
The percent cover for the species that make up the most competitive functional group
is predicted to peak on reefs far from passes, where sources of disturbance are most likely
to be low and light levels likely to be highest, or on reefs with maximum levels of total
coral cover. If different functional groups compete with each other then the cover of
stress-tolerant and disturbance-tolerant species is predicted to peak on reefs at moderate
62
distances from passes where levels of stress and disturbance are at moderately high levels
and where competitively dominant species are in relatively low abundance (Figs. 1.08A).
Alternatively, if functional groups do not compete with each other to a significant
degree, then the cover of all functional groups should peak in habitats within which
resources are highest and sources of disturbance are low (Figs. 1.08B,C). Under this
scenario, the competitive-dominant group is still predicted to have higher biomass on the
reefs farthest from passes than all other functional groups. The competitive and stress-
tolerant functional groups of coral (i.e., MO and FP) are also predicted to have a more
limited range of distribution across the disturbance gradient (W) than the disturbance-
tolerant functional groups of coral (i.e., Branched, Viviparous [BV] and Massive,
Viviparous [MV] corals). Additionally, if the AST model is correct, the competitive
dominant functional group should exhibit significantly higher percent cover on reefs with
low disturbance and stress than the other groups, while the stress-tolerant and
disturbance-tolerant functional groups should exhibit significantly lower percent cover,
regardless of which habitats they dominate. If the predictions of the unified neutral
theory (UNT) are correct all functional groups will be equivocal and will show no
significant differences in distribution or in abundance or biomass proxy (i.e., percent
cover) within or across reef sites.
These predictions, as well as those following, were tested using both linear and
second-order polynomial regressions. Linear regression were done to determine whether
functional groups increased or decreased in percent across the gradients. Second-order
polynomial regressions were done to determine whether the percent cover of each
functional group peaked at a midpoint along the gradient.
63
Species richness of all corals
Since depth was held constant among sites but turbidity most likely varied with
distance from passes, the amount of resources available as light and as suspended
particulate matter reaching each reef surface, as well as the level of sedimentation stress,
likely varied with distance from passes as well (Shinn et al. 1989). The relative levels of
stress and disturbance therefore probably vary with site location. According to the
predictions of the productivity-diversity hypothesis, which lead to CSR theory (Grime
1973; 1979), and which is also known as the intermediate disturbance hypothesis
(Connell 1978; Aronson and Precht 1994; Huston 1994; and many more), the habitat
types with intermediate levels of stress and disturbance should display greater species
richness than either the habitats with low levels of stress or disturbance and the habitats
with high levels of stress or disturbance.
Functional group richness
Grime (1977) predicts that the richness of functional groups will be low across sites,
as each functional group is replaced by another due to the combined effects of
environmental filtering and competitive exclusion between functional groups (Figure
1.08). Alternatively, if competition does not operate between FG, then all functional
groups are predicted to occur on reefs characterized by the lowest values of W (or highest
total cover), and functional group richness will decline as disturbance levels increase
(Figure 1.08), with the distribution of less-tolerant functional groups nested within more-
tolerant functional groups. If the UNT is correct, then functional groups do not exist and
64
the all species have an equal chance of being found at any site regardless of position
across the direct or indirect gradients.
Species richness per functional group
If the predictions of Grime (1977) are correct, then the number of competitive species
(i.e., those in the MO functional group) should peak on reefs in Florida that are
characterized by low levels of W or high levels of total coral cover, and decline steeply as
W increases or total coral cover increases. The number of ruderal and stress-tolerant
species should peak at moderate levels of disturbance, due to both environmental and
biological constraints. Accordingly there should be a turnover between functional groups
across the direct and indirect gradients (Figure 1.08).
If competition only operates between species within functional groups, however, then
the species richness of all functional groups should peak at moderate levels of W or total
coral cover, with the less tolerant functional group nested within the distribution of the
more tolerant functional groups. This unimodal pattern would occur within FG because
of the effects of competitive exclusion due to limiting similarities occurring between the
functionally similar species within FG at low levels of disturbance, and environmental
constraints limiting species membership within FG at high levels of disturbance (Figure
1.08).
METHODOLOGY
Geographic setting
65
The Florida Reef Tract lies at the southern tip of Florida and seaward of the Florida
Keys and is the third largest barrier reef in the world. The reefs and surrounding
mangroves, seagrass meadows and forested islands form a large, interconnected
ecosystem that sustains abundant wildlife, both above and below the sea surface (Florida
Keys National Marine Sanctuary Management Plan 1995). The ecological condition of
the Florida Reef Tract has been an issue of heightened national focus as coral cover and
diversity have declined substantially in recent decades (Jaap et al. 1988; Murdoch and
Aronson 1999; Miller et al. 2002; Aronson et al 2003; Wheaton et al. 2003).
The Florida Reef Tract is 350 km long and extends from Biscayne Bay at its
northeastern most end to the Dry Tortugas islands at its western most end (Figure 2.03).
A regional feature with a strong influence on the corals of the Florida reef tract is Florida
Bay. Florida Bay is a large, shallow body of water with limited circulation that lies to the
north and west of the Florida Keys. The water enclosed within Florida Bay is subject to
extremes of temperature, salinity, turbidity, and nutrient content (Vaughan 1918, Shinn et
al. 1989, Szmant & Forrester 1996). This water is forced by tides and winds onto the
Florida reef tract through the tidal passes in the Middle Keys (Wang et al. 1994, Smith
1994, 1997). Reef development is poor near the passes, probably because of the effects
of the water from Florida Bay on corals and other reef organisms (Shinn et al. 1989,
Ginsburg and Shinn 1994).
66
Figure 2.03. Map of South Florida and the Florida Keys. The reef tract is seaward of
Hawk Channel and forms a linear barrier reef roughly 350-km in length.
The ten reef sites included in the direct gradient analysis are lettered E
through N. All 20 of the reef sites are included in the indirect gradient
analysis.
Data collection and analysis
Videographic and species presence-absence data were collected during three research
cruises conducted over 26 days during August, September and October, 1995. The reef
tract was surveyed at twenty deeper habitats (13–19 m depth), which were chosen a
priori and located from Biscayne Bay to the Dry Tortugas. Subsequent to in situ
67
assessments, sixteen of the reef sites were defined as spur-and-groove habitats and four
sites as hard-ground communities. Almost all of the sites were positioned along the reef
slopes of named, emergent reefs The names of these reefs were retained as designations
for the survey sites (Figure 2.03).
Reef ridges are frequently present offshore of the emergent reefs along the Florida
Reef Tract (Lidz et al. 1991a, 1991b, 1997). These “outlier” reefs may protect the reefs
that are landward of them from storm-driven waves and other oceanographic influences.
The rule of the Keyswide research team was to sample the seaward-most section of reef
that was at the correct depth, not necessarily corresponding to the area directly downslope
from the emergent reef. For this reason, some of the reefs sampled were downslope
outlier reefs.
Transects were videographed and analyzed following the methodology described in
Aronson et al. (1994). One or two divers stretched 25-m long waterproof tape measures
down the middle of ten haphazardly selected spurs. Transects were generally 3–10 m
apart and the area videographically surveyed encompassed approximately 25m x 100m of
reef. Care was taken to avoid placing the transect lines over sand or off the ends of spurs.
Once each transect line was in place, another diver slowly swam down its length,
videotaping a 0.4 m wide x 25 m long swath of the reef. Videography was accomplished
with a Hi-8 video camera that was enclosed in a underwater housing and equipped with a
wide-angle lens and two 50 W waterproof lights. A 40 cm stainless steel rod projected
forward from the camera housing. This rod was used as a guide so the diver could
maintain a set distance of 40 cm between the camera lens and the reef surface. On the
end of this rod, a 15-cm wide gray plastic bar was mounted such that it appeared in the
68
field of view of the camera. The plastic bar served as a scale in the videotaped images.
During filming the underwater video camera was held perpendicular to the overall slope
of the reef, with the end of the stainless-steel rod suspended less than 2 cm from the reef
surface. This camera position ensured that the videographed images were of the reef in
plan view.
In order to accurately assess biological richness data on Caribbean coral reefs such as
those in the current study, Aronson et al. (1994) determined (using species saturation
curves) that more transects are required in comparison to the number of transects needed
to obtain accurate percent cover data. These additional transects are needed in order to
account for rare, widely dispersed species. Coral species presence data, for use in the
determination of species and functional group richness per reef site, were collected in the
present study from the 10 videographed transects as well as an additional 10 transects
surveyed visually, following the procedure in Aronson et al. (1994). The visually
assessed transects were placed in the same manner as the videographic transects, and
continued over an area of roughly equal size. The richness data therefore was collected
over twice the area of reef as the coral cover data.
The video transects were analyzed in the laboratory with a Hi-8 videocassette recorder
(VCR) attached to a high-resolution color monitor. Each transect was divided into 50
regularly spaced, non-overlapping frames, displayed by pausing the VCR. One of ten
clear plastic sheets, marked with ten random points, was laid over the monitor screen and
the sessile organism or substrate type present under each point identified and recorded
manually. The video was then advanced to the next frame and a new sheet of dots
haphazardly selected. This method is the more primitive predecessor of the computer-
69
automated method described in Chapter 4, but which results in identical data. By
following this protocol, each transect yielded 500 data points. Estimated percent cover of
coral species, other biological groups such as sponges and gorgonians, and of different
types of substrate was calculated from the point count data from the ten transects for each
reef site. The abundance of colonies for each species was also assessed from the video
data. Counts of colonies were made for each species on each transect, and the results
from the ten transects per site used to calculate the average abundance per species per
site.
The total species or functional group richness at each site was determined by
summing all species present within both the ten videographic transects and ten additional
transects of equal dimension that were assessed visually while diving the survey site,
following the standard protocol (Aronson et al. 1994). Functional group richness was
calculated using four increasingly-stringent procedures. (i) The least-stringent method
allowed a functional group to be recorded as present at a site if only one colony of any
member species was observed on all 20 transects. Three increasingly stringent conditions
for the indication of presence of a functional group on a reef were calculated by recording
member species of functional groups as present at a site when recorded over more than
(ii) 5, (iii) 10, and (iv) 15 transects. Increasing the number of transects that the member
species had to occur before the functional group was counted had the effect of
increasingly filtering out the less ubiquitous or transient species that were present at a
site.
70
Statistical analysis
Similarities in distribution of species between and among FG
Species that are grouped according to shared environmental tolerances should tend to
co-occur in habitats, while species that share resource requirements should tend displace
others from habitats. In order to examine the degree of similarity in the distribution of
species species within and between functional groups, I calculated an Analysis of
Similarity (ANOSIM; Table 2.01) on the raw colony count data of the 11 most abundant
species across the 200 transects. Bray Curtis similarities between square-root
transformed abundance data for all species were calculated and similarity trees and non-
metric multidimensional-scaled diagrams produced for visually comparison against the
hypothetical patterns illustrated in Figure 1.08.
To test the null hypothesis that no species or functional group ranks higher than the
rest, the counts for each possible rank was tabulated for each species, and separately for
each functional group, across all 200 transects of the 20 sites. Chi-square analysis was
used to determine whether the resultant table possesses a non-random distribution of
ranks across sites for species and for functional groups. Logistic regression was used to
determine whether the rank of each functional group changed in a non-random manner
relative to the total percent coral cover of each site.
The predictions of the remaining hypotheses described in Chapter 1 and above were
tested using regression analysis. For the tests of (1) percent cover of each functional
group, (2) total species richness, (3) functional group richness and (4) species richness
within functional groups against the predicted responses to both the environmental
gradient W and the biological gradient in total coral cover, the correlative relationships
71
between the variables were examined by computing linear and second-order polynomial
regressions. Orthogonal (Model 2) regression was used for comparing functional group
cover with total coral cover, since both variables were derived from the same data, and
thus had error variances of similar extent (Sokal and Rohlf 1995). Least squares
estimates (Model 1) regression was done for all other variables. All second-order
relationships were predicted to be concave-downward, in accordance with the hypotheses
of the intermediate disturbance hypothesis (Grime 1973; Connell 1978; Huston 1994).
Departures of linear regression coefficients from zero, and determinations of whether
second-order coefficients for polynomial regressions were significantly different from
zero, were done using one-tailed t-tests.
72
RESULTS
Similarity in distribution of species within and between functional groups.
Species within functional groups were hypothesized to be redundant in terms of their
functional responses to the environment (Grime 1979; Steneck and Dethier 1994). In
order to examine the degree of similarity in the functional responses of species within and
between functional groups, I calculated an Analysis of Similarity ANOSIM; Table 2.03)
on the raw colony count data of the 11 most abundant species across the 200 transects.
Bray Curtis similarities between each square-root transformed abundance data for species
were calculated and similarity trees and non-metric multidimensional-scaled diagrams
produced for visually comparison. (Figs. 2.04, 2.05).
The five of the six species of the MV functional group were more similar to each
other in multidimensional distributional space than they were to corals from the other
functional groups (Figure 2.05). The one exception was Stephanocoenia intercepta,
which was also the least abundant member of the MO functional group. The species of
the MV functional group also were more similar to each other in the patterns of
abundance they exhibited across the 200 reefs than to species of the other two functional
groups, with the exception of the one MO coral described above. The species of the BV
functional group were dissimilar to each other and to all 9 other species in the
comparison.
ANOSIM analysis (Table 2..01) determined that the MV and BV functional groups
were both significantly different from the MO in the manner in which the abundances
were distributed across the 200 survey sites. The MV and BV functional groups were not
73
found to differ significantly in their distribution pattern, although the failure to detect
significant differences may have been due to a type II error caused by the small number
of possible permutations that could be run with the data.
Bray-Curtis similarities were also calculated for all 36 species evaluated in the rank-
abundance comparisons. The many rare species appeared to display neutral patterns of
distribution across sites. Visual assessment of the MDS diagram (Fig. 2.06) confirms that
the rare species did not display any coherent patterns of similarity between each other. In
particular, the member species of the FP group were found to have low similarity values
among each other (i.e., less than 20 out of 100). The other species that displayed neutral
rank-abundances across the Florida reef sites also were not similar in distribution to
neither the rare nor the abundant species.
ANOSIM of the entire suite of species determined that the overall pattern of
abundance exhibited by the FP group was highly significantly different from that of the
MO functional group (p = 0.007; Table 2.02). All other comparisons were not
significant, except for the statistical comparison between the very abundant MO
functional group and the very scarce BV functional group.
74
Figure 2.04. A dendrogram showing the similarities in response patterns among the
eleven most abundant species assessed in Florida. Bray Curtis distances
were calculated based on square-root transformed coral colony counts.
Species were clustered using the group-linkage method..
75
Figure 2.05. MDS showing the similarities in response patterns among the eleven most
abundant species assessed in Florida in two-dimensional state space.
Species that are closer together and bound within similarity isoclines are
more alike than species farther apart or outside isoclines. Bray Curtis
distances were calculated based on square-root transformed coral colony
counts. Species were clustered using the group-linkage method.
76
Table 2.01 Results of one-way analysis of similarity of the Bray-Curtis similarities of the
abundance data of the most abundant 11 species observed across 20 reef sites
located on the Florida Reef Tract.
ANOSIM
Analysis of Similarities
Global Test
Sample statistic (Global R): 0.734
Significance level of sample statistic: 0.1%
Number of permutations: 999 (Random sample from 4620)
Number of permuted statistics greater than or equal to Global R: 0
Pairwise Tests
R Significance Possible Actual Number >=
Groups Statistic Level % Permutations Permutations Observed
MV, MO 0.66 2.4 84 84 2MV, BV 0.5 10.0 10 10 1MO, BV 0.875 3.6 28 28 1
77
Figure 2.06. MDS showing the similarities in response patterns among all 36 species
assessed in Florida in two-dimensional state space. Species that are closer
together and bound within similarity isoclines are distributed across sites in
a more similar manner than species farther apart or outside isoclines. Bray
Curtis distances were calculated based on square-root transformed coral
colony counts. Species were clustered using the group-linkage method.
78
Table 2.02. Results of one-way analysis of similarity of the Bray-Curtis similarities of
the abundance data of all species observed across 20 reef sites located on the
Florida Reef Tract
ANOSIM
Analysis of Similarities
Global Test
Sample statistic (Global R): 0.073
Significance level of sample statistic: 13.5%
Number of permutations: 999 (Random sample from a large number)
Number of permuted statistics greater than or equal to Global R: 134
Pairwise Tests
R Significance Possible Actual Number >=
Groups Statistic Level % Permutations Permutations Observed
BO, MV 0.563 7.1 28 28 2
BO, FP 0.141 21.8 55 55 12
BO, MO 0.646 3.0 66 66 2
BO, BV -0.010 60.7 28 28 17
BO, X -1.000 100.0 3 3 3
MV, FP -0.033 60.7 5005 999 606
MV, MO 0.066 22.8 8008 999 227
MV, BV 0.022 37.9 462 462 175
79
MV, X -0.333 71.4 7 7 5
FP, MO 0.178 0.7 92378 999 6
FP, BV -0.078 78.4 5005 999 783
FP, X -0.525 100.0 10 10 10
MO, BV 0.096 17.3 8008 999 172
MO, X -0.178 45.5 11 11 5
BV, X -0.556 100.0 7 7 7
80
Rank Abundance per Species
The six most abundant coral species out of the 34 species analyzed belonged to the
massive oviparous functional group (Figure 2.07; Table 2.03). Out of the 8097 coral
colonies that were counted across the 200 transects, 6330 colonies were accounted for by
these six species, which represents over 78% of all the colonies observed. The
probability that the six most abundant species observed would all belong to the MO
functional group (out of the four groups sampled) by chance, is highly significantly
small, at p = 3.61E-5.
The next three most abundant species were all of the massive viviparous functional
group, which were classified as ruderal corals. Represented by 831 colonies, these three
species accounted for approximately 10% of all coral colonies counted. The next two
most abundant species also members of a separate single functional group. These two
species were both branched viviparous corals (competitive-ruderal classification), and
accounted for ~4% of all colonies counted across the Florida Reef Tract, with 328
colonies total. The other 27 observed coral species accounted for less than 100 colonies
each across all transects.
The ranks of the most common eleven species across all transects examined
individually were also distributed in a highly non-random fashion (Table 2.04; Figs 2.07,
2.08). Most transects had an average of 11 total species, of these the three top-ranking
species tended to be consistently most abundant across most transects. The next three
species rarely ranked below sixth on most transects. The three massive viviparous corals,
which ranked seventh through ninth overall, were rarely in the top two ranks, but also
rarely ranked below ninth. All species of the foliose and plating functional group ranked
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equally as subordinate in rank, as were 4 out of 6 species of the branched viviparous
functional group. A chi-square test of the distribution of all species in proportional ranks
from 1 to 11 out of 34 possible rankings total was found to be very highly significantly
different from the null, at p = 7.8E-192.
Figure 2.07 (below). The log percent relative abundance of the species observed at the
200 transects assessed. Different shaped points represent the
different functional group memberships of the species.
82
83
Table 2.03. (below) A table of the number of occurrences with which each the 36
most abundant species ranked from 1 to 20 across all 200 transects. The designations of
rank are displayed along the top row of the table. For example, the species M. faveolata
ranked first on 79 transects, second on 35 transects, and so on. Darker-shaded cells
represent a greater number of occurrences. A chi-squared test determined that the
probability of the observed distribution of rank abundances occurred at random is
exceptionally significantly small, at p = 5.22E-148.
84
85
Figure 2.08. The distribution of the proportion of ranks over the 200 sites that the most
dominant species, Montastrea faveolata, displayed. The distribution of the
proportion of ranks if all corals shared dominance, as predicted by the UNT,
is also plotted for comparison. The null, or neutral distribution was
calculated for each rank by dividing the sum of all occurrences each species
by the number of occurrences of all species, and then multiplying the result
by the number of occurrences for the rank in question.
86
Rank Abundance per Functional Group
Since the highest-ranking 11 species were found to be most similar in dominance to
other species within the same functional group, I also analyzed the rank-abundance
distribution of each functional group across the 200 transects (Figure 2.09; Table 2.04).
The massive oviparous functional group, classified as competitive-stress-tolerant, was
found to rank highest (i.e., first) in dominance in 182 of the 200 transects. The massive
viviparous functional group, classified as ruderal, ranked second compared to the other
three functional groups. The BV functional group most often ranked third, and FP
functional was most often fourth ranking in abundance across all sites.
The ranks of each functional group were plotted against their total abundance value of
each transect. This comparison was conducted to determine if the competitive - stress-
tolerant functional group (i.e., MO) was consistently dominate even on transects
regardless of low colony abundance. Colony abundance was also shown to be highly
negatively correlated with proximity to passes (Murdoch 1998) and thus is a good proxy
for stress or disturbance. I also examined whether functional groups of corals
hypothesized to be disturbance-or stress-tolerant would increase in dominance rank
within these marginal transects (Figure 2.10).
The MO functional group ranked first on reefs with more than 25 colonies. The MO
group was subordinate on 18 reefs, all with low coral abundance. Conversely, the other
three functional groups rarely or never ranked first in abundance except when total coral
abundance was less than 25 colonies. Logistic regression of the rank data compared to
total coral abundance for sites found that the patterns displayed by each functional group
87
were highly significant at p values of < 0.001. The model formulae and significance
tests are presented in Appendix 2.01.
Figure 2.09. The proportion of ranks displayed by each functional group across the 200
transects surveyed. The pattern is exceptionally significantly different from
a neutral distribution, at p = 1.56E-173 (Table 2).
88
Table 2.04. A table of the observed number of times each functional group ranked from
1 to 4 across the 200 transects surveyed. Also tabulated is the expected
distribution of ranks under the UNT, as well as the chi-squared test
comparing the differences between the two matrices. The observed pattern
of rank abundances was found to be exceptional significantly different from
the expected null model, at p = 1.56E-173.
Figure 2.10. (below) The relationship between rank per functional group and total
abundance per transect for the 200 transects surveyed. Logistic regression
analysis and tests of significant of the data are presented in Appendix 2.01.
89
90
Percent coral cover of each functional group versus W
Functional groups did not appear to replace each other across the gradient of W
(Figure 2.11), and instead demonstrated a nested distribution pattern as the intensity of W
varied. All species peaked in cover at lowest values of W and declined in cover on reefs
with higher W values. Only the MS functional group displayed high levels of cover at
low levels of W, whereas all other functional groups of corals accounted for low cover
across all reefs, as predicted by the CSR theory.
The BV functional group did not vary significantly with W (Table 2.05; Figure 2.11a).
Coral cover by the branched brooding corals was very low at all sites, and ranged from
0.09% to 1.93%.
The foliose and plating, brooding functional group of corals also displayed very low
percent coral cover across all sites surveyed, with a range of 0.13% to 1.51%. Despite
the low cover overall, however, this functional group did display a highly significant
negative correlation with W (Table 2.05; Figure 2.11b).
The cover of the MV functional group of corals displayed little variation relative to W,
and ranged from 0.80% to 2.40% (Figure 2.12c). The coral cover of the MV group did
not vary significantly with W (Table 2.05; Figure 2.11c).
Percent coral cover of the MO functional group ranged from 0.76 to 12.09% (Figure
2.12d). Coral cover for the MO group was highly-significantly correlated with W and
formed a negative slope (Table 2.05; Figure 2.11d), indicating that massive corals that
spawn gametes are more abundant on reefs far from island passes.
91
Figure 2.11. Relationship between percent coral cover of each functional group and
environmental influence of island passes, (W). The best fit linear (–) and
second-order polynomial (- -) relationships are written in the lower left-hand
corner of each graph.
92
Table 2.05. Results of two-way t-test of the linear correlation between coral cover of
each functional group and W on 10 reef sites along the Florida Reef Tract,
testing whether the slopes are zero.
FG Estimate Standard Error
t Ratio Prob > |t|
BO 0.0014052 0.003028 0.4600 0.6550BV -0.009157 0.012911 -0.7100 0.4983FP -0.19733 0.005124 -3.8500 0.0049MV -0.018454 0.010043 -1.8400 0.1035MO -0.190742 0.025143 -7.5900 < 0.001
Percent cover per functional group versus total coral cover
When percent cover of each functional group was regressed against total cover of all
corals, only the MO functional group displayed an substantial change with cover across
sites, with a range from 0.1% to 18.7% over the 20 sites surveyed (Figs. 2.12, 2.13).
Alternatively, the BV, MV and FP functional groups each only displayed low coral cover
(between zero and less than 2.5% cover) across the same 20 sites (Figs. 2.13, 2.14).
The BV functional group displayed a significant increase in cover relative to total
coral cover (Table 2.06; Figs. 2.12a, 2.13a), while the FP, MO and MV functional groups
increased highly significantly with total coral cover across the 20 sites (Table 2.07, Figs
2.12b-d, 2.13b-d). Only the MV functional group displayed a significant second-order
polynomial regression with total coral cover, with a concave-down regression curve
(Table 2.07, Figs 2.12c, 2.13c).
93
Figure 2.12. Orthogonal relationship between average percent coral cover for each
functional group and the total coral cover for the 20 reef sites surveyed on
the Keyswide Coral Reef Expedition. The orthogonal fit linear (–) and
second-order polynomial (- -) relationships are written in the lower left-
hand corner of each graph. The thick diagonal line represents the maximum
possible value of cover for each functional group relative to total coral
cover.
94
Figure 2.13. The same graphs illustrating the relationship between average percent coral
cover for each functional group and the total coral cover for the 20 reef sites
surveyed as in Figure 2.12, but with different scales on the y-axes. The best
fit linear (–) and second-order polynomial (- -) relationships are written in
the lower left-hand corner of each graph. The thick diagonal line represents
the maximum possible value of cover for each functional group relative to
total coral cover.
95
Table 2.06. Results of orthogonal contrasts on whether the linear regressions of percent
coral cover for each functional group versus total coral cover at each reef site
were significantly different from zero.
FG Variance
Ratio
Correlation Prob.
BV 0.0077 0.4961 <0.05
FP 0.0006 0.8478 <0.005
MV 0.0104 0.6635 < 0.005
MO 0.7803 0.9894 < 0.0001
Table 2.07. Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions of FG cover versus total coral cover were
significantly different from zero.
FG Estimate Std Error t Ratio Prob>|t|
BV 0.002915 0.002915 -1.21 0.2444
FP 0.0002887 0.000496 0.58 0.5683
MV -0.006665 0.002531 -2.63 <0.0001
MO 0.0087727 0.004555 1.93 0.071
96
Total species richness versus W
A second-order polynomial regression between species richness and W was concave
downward and highly significant (r2 = 0.727919, t ratio = -3.16, p = 0.016; Figure 3.14).
A linear relationship between species richness and W was negative and marginally
insignificant (r2 = 0.3404, t ratio = -2.03, p = 0.077; Figure 2.14).
Figure 2.14. Relationship between species richness of all corals and environmental
influence of island passes, W, at each reef site. The best fit linear (–) and
second-order polynomial (- -) relationships are written in the lower left-hand
corner of the graph.
97
Total species richness versus total coral cover
Species richness ranged from a low of 20 species to a high of 34 species out of a total
number of 36 observed across all sites. A second-order polynomial regression between
the total number of species per site and the total coral cover per site was concave
downward and very highly significant (r2 = 0.7863, t ratio = -6.32, p < 0.001; Figure
2.15). A linear regression of the same data was also significant [r2 = 0.284602; t ratio =
2.68; p = 0.0154]. However, a plot of the residuals demonstrated that the two variables
were not well represented by a linear relationship. In the plot of residuals, all but one
point out of 12 between 4% and 15% cover were above the best fit linear line, and all
points outside the 4% to 15% range were below the best fit line, indicating the data did
not fit the assumptions of linear regression (Sokal and Rohlf 1995).
98
Figure 2.15. Relationship between species richness and total coral cover across the 20
reef sites. The best fit linear (–) and second-order polynomial (- -)
relationships are written in the lower left-hand corner of each graph.
99
Functional group richness versus W
Functional group richness appeared to vary depending on both the intensity of the
environmental gradient W and the degree of sparseness to which species were distributed
across sites (Tables 2.08, 2.09; Figure 2.16). When species observed across any one of
the twenty transects per site were included, the number of functional groups observed
across the 10 survey sites was 4 of 4, regardless of the value of W (Figure 2.16).
However, as the constraints regarding how many transects a species must be distributed
over before being counted (i.e., how ubiquitously distributed a species was) increased, a
consistent pattern could be seen (Table 2.10) in which first the species within the FP
functional group became increasingly sparse, then the species of the BV functional group,
and finally the species of the MO functional group , Functional groups tended to lose
ubiquitous species on reefs with high values of W , and so functional group richness
declined as W increased.
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Table 2.08. Results of orthogonal contrasts on the linear regressions of functional group
richness for each level of constraint versus W.
Term Estimate Std Error t Ratio Prob>|t|
Five -0.011 0.005 -2.14 0.065
Ten -0.007 0.010 -0.76 0.469
Fifteen -0.035 0.012 -2.91 0.020
Table 2.09. Results of orthogonal contrasts on the second-order coefficients for
polynomial regressions of functional group richness for each level of
constraint versus W.
Term Estimate Std Error t Ratio Prob>|t|
Five -0.00059 0.0001 -3.94 0.006
Ten -0.00027 0.001 -0.55 0.600
Fifteen -0.00083 0.001 -1.59 0.160
101
Figure 2.16. Relationships between functional group richness under the four levels of
membership constraint and the environmental gradient of W across reef
sites. The best fit linear (–) and second-order polynomial (- -) relationships
are written in the lower left-hand corner of each graph. The rules for
inclusion of functional groups in each graph were as follows:
ALL = At least one species per FG on one transect or more.
Five = At least one species per FG on more than five transects.
Ten – At least one species per FG on more than ten transects.
Fifteen = At least one species per FG on more than fifteen transects.
102
Table 2.10. Presence or absence matrices of the presence or absence of functional groups
across the ten reefs of the environmental gradient W. The rules for inclusion
of functional groups are as in Figure 2.18, above.
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Functional group richness versus total coral cover
Functional group richness declined as a function of increasing the constraints on
presence in a reef site and as when total coral cover were at the highest and lowest values
(Tables 2.11, 2.12; Figure 2.17). When the constraint of membership was relaxed,
functional group richness was four out of four across the 20 reef sites (Figure 2.17). As
the statistical constraints that filtered out sparse species within functional groups were
increased functional groups decline in presence on reefs in the order of FP, then BV, the
MO, while the MV functional group was observed on all reefs regardless of constraints
on detection.
As sparsely distributed species were filtered out of the data, FG richness took on a
unimodal distribution. At highest levels of total coral cover the FP and BV functional
groups were not present, while at the lowest levels of total coral cover the FP, BV and
MO functional groups were absent. These results indicate that the species of the FP
functional group were distributed most sparsely among transects between reefs overall,
and more so on reefs characterized by high and low coral cover. The BV functional
group displayed a similar pattern, but was less sparsely distributed across sites. The MO
functional group only displayed absences on two reefs that had low total coral cover. The
MV functional group was ubiquitous across all sites regardless of total coral cover.
104
Figure 2.17. Regression of functional group richness versus total coral cover for each
site. Each graph represents a different level of membership constraint,
labeled as in Figure 2.18 above. The best fit linear (–) and second-order
polynomial (- -) relationships are written in the lower left-hand corner of the
graph.
105
Table 2.11. Results of orthogonal contrasts on the linear regressions of functional group
richness for each level of constraint versus W.
Term Estimate Std Error t Ratio Prob>|t|
Five 0.0390 0.0190 2.05 0.0548
Ten 0.0586 0.0277 2.12 0.0485
Fifteen 0.0567 0.0305 1.86 0.0791
Table 2.12. Results of orthogonal contrasts on the second-order coefficients for
polynomial regressions of functional group richness for each level of
constraint versus W.
Term Estimate Std Error t Ratio Prob>|t|
Five -0.0052 0.0029 -1.79 0.0909
Ten -0.0143 0.0030 -4.75 0.0002
Fifteen -0.0145 0.0036 -3.98 0.0010
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Species richness within functional groups versus W
In contrast to percent cover for each functional group, in which one functional group
dominated in cover, all groups demonstrated high species richness across sites relative to
the strength of the environmental gradient of W (Figure 2.18). W was poorly correlated
with species richness within each functional group. The BV and FP functional groups
appeared to vary little in species richness except at the highest level of W. The MV and
MO functional groups displayed little change in species richness across the entire
environmental gradient.
The species richness of the branched, viviparous, functional group ranged from 3 to 6
species per site out of a maximum of 7 species (Figure 2.18a). Species richness for the
BV functional group was negatively correlated with W, but not significantly so (Table
2.13). A second-order polynomial regression of BV species richness on W was concave
downward but was also not significant (Table 2.14).
Species richness of FP functional group range across the 10 sites assessed, ranged
from between 5 and 10 species, out of a possible 10 species observed regionally (Figure
2.18b). A linear regression of FP species richness functional group on W was not
significant (Table 2.13), but a second-order polynomial regression between species
richness and W was significant and concave-downwards (Table 2.14; Figure 2.18b).
Neither the species richness of the MV functional group nor that of the and MO
functional group were not correlated significantly with W (Table 2.13). Additionally,
second-order polynomial regressions of species richness on W for both groups appeared
little different from the linear regression, and were also not significant (Table 2.14,
Figure 2.18c,d). The species richness of the MV functional group varied between 5 and 8
107
species (Figure 2.18c), while the MO functional group displayed a range from 8 to 10
species across the sites surveyed (Figure 2.18d).
Figure 2.18 . Relationship between species richness of each functional group and
environmental influence of island passes, W, at each reef site. The best fit
linear (–) and second-order polynomial (- -) relationships are written in the
lower left-hand corner of each graph.
108
Table 2.13. Results of analyses of variance of the linear regression of species richness
versus W for each functional group.
FG Estimate Std Error t Ratio Prob>|t|
BV -0.0305 0.0173 -1.77 0.1155
FP -0.0508 0.0257 -1.98 0.0836
MV 0.0080 0.0175 0.46 0.6591
MO -0.0266 0.0145 -1.84 0.1034
Table 2.14. Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions for species richness of each functional group versus
W were significantly different from zero.
FG Estimate Std Error t Ratio Prob>|t|
BV -0.0014 0.0007 -1.94 0.0939
FP -0.0026 0.0008 -3.01 0.0195
MV 0.0002 0.0008 0.19 0.8515
MO -0.0003 0.0007 -0.47 0.6554
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Species richness within functional groups versus total coral cover
Of 36 species observed across all 20 sites, six were branched viviparous corals, ten
were foliose or plating, viviparous corals, ten species were assigned to the MO functional
group and nine species were characterized by a massive morphology and a viviparous
reproductive mode. Across the 20 sites surveyed (Figure 2.19), the BV functional group
displayed a minimum value of 2 species and a maximum of six species. The FP
functional group ranged from three species to ten species. The massive oviparous
functional group displayed a maximum of ten species and a minimum of seven species,
while the massive oviparous functional group ranged from five to nine species across the
20 sites surveyed.
The species richness of the branched viviparous functional group displayed a
concave-down, highly significant second-order polynomial correlation when compared
against total coral cover (Table 2.16, Figure 2.19a). A linear regression of the same data
was not significant (Table 2.15).
A second-order polynomial regression of the species richness of the FP functional
group was also highly significantly correlated with total coral cover, and also displayed a
concave-down curve (Table 2.16, Figure 2.19b). When the FP functional group data was
divided between sites with coral cover values less than 10% and values greater than 10%
in a post-hoc analysis, it was subsequently found that species richness of the FP group
was linearly negatively correlated with total coral cover at a very high significance level
(Table 2.15, Figure 2.19b). In contrast, the species richness of the FP group was not
correlated with total coral cover at sites with coral cover values great than 10% (Table
2.16, Figure 2.19b).
110
In comparison with the BV and FP functional groups, the species richness of the MO
functional group remained at roughly 8 species across all sites, with no significant change
regardless of total coral cover (Table 2.15, Figure 2.19c). The species richness of the
massive viviparous functional group also remained high across all reefs and was found to
slightly increase in relation with total coral cover. However, linear regression analysis
determined that the MO functional group exhibited a marginally insignificant correlation
with total coral cover (Table 2.16, Figure 2.19d). The second-order polynomial
regression of the species richness for both the MO and MV functional groups versus total
coral cover per site was not significant (Table 2.16).
111
Figure 2.19. Regressions of species richness for each functional group on total coral
cover for each site. The best fit linear (–) and second-order polynomial
(- -) relationships are written in the lower left-hand corner of each graph.
112
Table 2.15. Results of two-way t-tests of the linear regression of species richness for
each functional group versus total coral cover for each functional group.
FG Estimate Std Error t Ratio Prob>|t|
BV 0.0336813 0.052473 0.64 0.5290
FPa 0.6828664 0.111125 6.15 <.0001
FPb -0.001081 0.050731 -0.02 0.9838
MV -0.02411 0.035353 -0.68 0.5039
MO 0.0590496 0.030219 1.95 0.0664
Table 2.16. Results of two-way t-tests on whether the second-order coefficients for
polynomial regressions of FG species richness versus total coral assemblage
cover were significantly different from zero.
FG Estimate Std Error t Ratio Prob>|t|
BV -0.02798 0.005511 -5.08 <.0001
FP -0.032122 0.006295 -5.1 <.0001
MV -0.008554 0.005512 -1.55 0.1391
MO -0.001785 0.005016 -0.36 0.7263
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Analysis of the presence or absence of each species across all sites in a sorted matrix
displayed the manner in which the species of each functional group responded to the
environmental differences that occurred across the 20 reef sites (Table 2.17). All species
included in the BV functional group were present at sites possessing moderate total coral
cover, but that functional group lost species on reefs that had the highest and lowest
percent coral cover values. The species Madracis decactis and Porites furcata were
present on all sites, whereas Porites divaricata and Madracis mirabilis were absent from
reefs with both exceptionally high and exceptionally low coral cover.
The FP functional group displayed a linear decline in species richness on reefs with
less than 10% coral cover. Visual analysis of a sorted matrix of the FP functional group
data illustrates this decline. All of the 10 FP species are present on at least some of the
reefs possessing 10% cover or more, but species are lost progressively across sites with
lower cover values. Only Eusmilia fastigata was found at all 20 sites, whereas Mussa
angulosa, Mycetophylia lamarkiana, My. ferox, My. danaana were absent from virtually
all reefs with less than 5% cover.
In contrast to the BV and FP functional groups, the species of the MO functional
group are present across all sites regardless of coral cover according to visual
examination of a sorted matrix of this group. Only the shallow-water species
Montastraea annularis is rare across all sites.
Examination of a sorted data matrix of the MV functional group illustrates that the
species of this group vary little in presence or absence across all sites regardless of total
coral cover. One notable exception is Favia fragum, which is present at sites with a total
114
coral cover below 10%, but not present at sites with a total coral cover above 10%.
Isophllastrea rigida and Isophyllia sinuosa are absent from almost all sites.
Table 2.17. (below) Sorted matrices of species presence or absence for each functional
group across 20 transects at each of the 20 sites of the Keyswide Coral Reef
Expedition. White cells represent absent species, grey cells represent present
species. The heavy black line running across each matrix represents the
predicted boundary between present and absent species if the perfect
nestedness of sorted species had occurred at each reef site. Species absent
below the bordered cells are expected to be present, and species present above
the bordered cells are predicted to be absent. Notice that the pattern of
bordered cells across sites in the table matches the pattern of points in the
graphs of species richness per functional group versus total coral cover
(Figure 2.19). MDP values represent the mid-point location of each species
across the gradient of reef sites, calculated by reciprocal averaging of the sites
of occurrence of each species.
115
116
DISCUSSION
Functional groups of corals were observed to respond to direct and indirect gradients
of disturbance in a manner that substantiates the premise that each group of species
allocate different functional responses to environmental and biological conditions on a
reef. Despite the chaotic patterns in biomass displayed by each coral species when
separately plotted across reefs (Figure 1.01), each functional group of corals responded to
the direct and indirect gradients in a orderly and group-specific manner. The gradient
replacement pattern predicted by Grime (1977), in which each functional group
dominated a particular region of the gradients, was not observed. Instead, functional
groups displayed a nested distribution pattern, indicating that if negative interactions
occur between functional groups they have little impact on distribution patterns. Instead
coexistence strategies of some form may be operating between functional groups or
functional groups have such different life-history strategies that they rarely interact. The
ecological significance of each statistical test is discussed below.
Dominance by species and functional groups
Examination of patterns of rank abundance determined that on the reefs considered in
this analysis, eleven species out of a pool of at least 36 species were substantially more
abundant than the rest (Figure 2.05). These species belonged to three different functional
groups and the species members of each group both (1) sorted by rank in a similar
manner and were (2) distributed across the 200 transects surveyed in a statistically similar
way across multivariate state space (Figs 2.10, 2.11, 2.12). The rarer species, alternately,
showed rank-abundances (Figure 2.05) and multivariate distributions across transects
117
(Figure 2.12) that were without apparent pattern. These results indicate that all coral
species are not equivalent in their functional responses. These results alone refute one of
the fundamental hypotheses of the UNT (Hubbell 1997, 2001) that all species of coral are
functionally identical and can be modeled accordingly. By ignoring the shape of the
rank-abundance curve, which is statistically similar to many other curves (McGill 2006),
I instead focused on manner in which each species was ranked across transects, while
taking into account its functional characteristics and the manner in which each species
and functional group was predicted to display abundance patterns across gradients of
disturbance and stress. This species-specific and functional-group specific analysis
uncovered exceptionally non-neutral distributions of rank by the 11 dominant species
within the habitat. Furthermore, species of corals that shared life-history and other
characteristics were distributed across transects in statistically similar patterns to other
members of the same functional group, confirming that functional groups are composed
of functionally (and statistically) similar species that all differ substantially in functional
responses when compared with the responses of the member species of other functional
groups.
The functional-group differences in rank-abundance were also highly non-random
(Table 2.02; Figs 2.08, 2.09). Furthermore, the relative levels of dominance by each
functional group in relationship to the total colony abundance of the set of 200 transects
fit the predictions of the AST, based on the life-history strategies that each functional
group possesses. For instance, the functional group that was predicted to be the
competitive dominate in the Florida reef habitat was the massive, oviparous functional
group, which is made up of corals with a domal morphology, generally large colony size
118
and a seasonal reproductive pattern. Theoretically another functional group, the branched
oviparous corals such as Acropora cervicornis would be considered more likely to
dominate reefs in good condition in Florida, but the members of this functional group
were ecologically removed by disease and coral bleaching (Aronson and Precht 1998).
With the BV functional group no longer ecologically important on the Florida reefs the
MO functional group are the fastest growing as adults and the most capable of allocating
resources for growth and domination of benign reef environments. The MO functional
group consistently ranked highest of the four functional groups across each of the 200
transects assessed.(Figure 2.08), except when the total colony abundance of a transect
was below 25 colonies per transect (Figure 2.09). These transects with low total colony
abundance were shown in Murdoch (1998) to represent heavily disturbed areas of reef.
High levels of disturbance would lead to colony damage that would likely outpace the
ability of the MO corals to acquire new resources for repair. The more weedy or more
stress-tolerant corals of the BV, MV and FP functional groups are theoretically better
suited to habitats exposed to higher levels of stress or disturbance, and the results above
did determine that these three groups each ranked highest in dominance only on the
transects with total colony abundance below 25 colonies per transect (Figure 2.09).
Other patterns of rank abundance also matched the predictions of the AST. The FP
functional group is characterized as stress-tolerant in the functional group framework I
developed in Chapter 1. Stress-tolerant species are predicted to have slow growth rates,
low rates of reproduction and to rarely fragment. For these reasons, colony abundance of
the FP functional group was expected to be ranked lower than that of the other functional
groups, a priori. Examination of the rank-abundances of each species and of the FP
119
functional group as a whole both confirmed that this functional group was consistently
lowest ranking in abundance on the vast majority of transects.
Unlike the FP functional group, the species of the MV functional group have a ruderal
life-history. These corals primarily utilize resources for reproduction and have higher
levels of recruitment than other types of corals. Although they also are poor competitors
for space, high levels of recruitment may permit the MV functional group to maintain a
secondary dominance on most reefs of high total colony abundance. On reefs with low
colony abundance the MV corals would be freed from competition with the MO
functional group, which may also allow the MV functional group to dominate these
habitats.
Percent coral cover per functional group
Grime (1977) predicted that different functional groups of sessile organisms would
dominate (in terms of biomass) specific zones of a disturbance gradient, due to: (1) their
distinct environmental tolerances limiting membership as disturbance levels increase
across sites; and (2) negative biological interactions between groups inhibiting
membership as disturbance decreases across sites (Figure 2.03a). Alternatively, if
functional groups are primarily affected by environmental conditions alone and do not
compete with each other, then an alternative pattern was hypothesized, in which the
ranges of the least environmentally-tolerant functional groups are nested within the
ranges across the environmental gradient of the more tolerant functional group. Linear
and second-order polynomial regression analysis of functional group percent cover (used
as a proxy for biomass by coral ecologists) and functional group richness across both a
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direct environmental gradient and an indirect biological gradient demonstrated that, on
the deeper spur-and groove fore reefs in the Florida Keys, coral functional groups
conform to the nested pattern with high overlap (i.e., Figure 2.03c) and not the
replacement pattern (Figure 1.03d).
The MO functional group, which is composed of large, broadcast-spawning head
corals, exhibited the highest cover at the least disturbed site in the direct gradient and
indirect gradient analysis. Additionally the MO functional group was consistently the
dominant functional group across all sites except at the individual sites where the
environmental measure of disturbance (W) was highest, or total coral cover was lowest.
Since the branched, oviparous corals are ecologically extinct from the Florida Keys
region (Precht and Aronson 2004), the massive oviparous corals represent the most
competitive coral group remaining. As such, the dominance of the MO group fits the
predictions of the AST model (Grime 1979).
Other functional groups of corals were predicted by the AST (Grime 1979) to peak in
biomass at some moderate position across the direct and indirect gradients. However,
only the MB functional group displayed a significant (p < 0.001) unimodal distribution,
which was observed in the indirect gradient analysis. The BV functional group did also
exhibit higher values in cover at moderate total coral cover and a downward facing
second-order polynomial relationship, but the polynomial section of the equation was not
significantly different from zero (Table 2.05). The best fit second-order polynomial
relationship of the FP and MO functional groups did not differ visually from the best fit
line of the linear regression for each functional groups. Additionally, while all functional
groups displayed significant linear relationships with total coral cover, only the FP and
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MO functional groups displayed a significant linear relationship with W. As such, the
distribution of the MO functional group across the direct and indirect gradients, and its
biomass dominance across reefs, fits the predictions of the AST model (Grime 1979).
The Ruderal and Competitive Ruderal functional groups of corals were predicted by
the AST (Grime 1979) to peak in biomass at some moderate position across the direct
and indirect gradients. For Caribbean corals, these adaptive strategies are represented by
the massive, viviparous corals and the branching, viviparous corals, respectively. The
MB functional group did display a significant (p < 0.001) unimodal distribution in
percent coral cover across the indirect gradient analysis. The BV functional group did
also exhibit higher values in cover at moderate total coral cover and a downward facing
second-order polynomial relationship, but the polynomial section of the equation was not
significantly different from zero (Table 2.05).
Another prediction of the AST (Grime 1979) was that all functional groups will
display lowest percent cover at highest levels of disturbance. This prediction was also
observed in the analysis of the direct gradient (Figure 2.04; Table 2.01).
Total species richness
According to both the IDH (Connell 1978; Huston 1994) and the AST (Grime 1979) a
peak in species richness is expected to appear at a location across either direct or indirect
gradients where rates of population growth and rates of recovery from disturbance are
both at moderate levels (Figure 2.16; 2.17). Total species richness was found to have a
highly significant unimodal relationship with W, and a very highly significant unimodal
relationship with total coral cover. Linear regression across the direct environmental
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gradient was not significantly different from a flat line. For species richness data
measured across a gradient of coral cover, examination of the residual plot determined
that linear regression, although significant, was not an appropriate model. It is interesting
to note that even at very low values of total coral cover, the species richness of a site was
greater than 20 species, which could be considered very high for the Florida region at this
depth, (Dustan and Halas 1987; Porter and Meier 1992; Aronson et al 1994). This high
species richness despite low coral cover is probably due to the inclusion of rare and
sparsely distributed species over the relatively large area (~200 m2) surveyed for species
at each site. It is worth noting here that the IDH as a theoretical model is specifically
intended to explain species richness and diversity at the patch scale, and that at regional
scales a linear relationship between biomass and species richness would be expected
(Chase and Leibold 2002). The results presented here demonstrate that the IDH also
applies at the meso-scale on the Florida Reef Tract.( i.e., between reefs separated by ~ 10
km across the 350-km long region), despite the large area encompassed.
Functional group richness.
Species belonging to all four functional groups were found on every reef site surveyed
in Florida, regardless of the position of reefs along either the direct or indirect gradients
of disturbance. As such, coral assemblage structure did not match neither the Gradient
Replacement pattern predicted by Grime (1977) nor the Nestedness pattern predicted by
Patterson (1987) at the level of functional groups. The lack of turnover of functional
groups across the reef sites indicates that at least one species within each functional group
is capable of surviving on all of the reefs surveyed. Sites that were not spur-and-groove
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reef were not considered in the analysis. The exclusion of marginal reef habitat no doubt
limited the degree of extreme environmental conditions encompassed by the gradient
analysis. Additional research that includes reef and non-reef habitats would be required
to examine whether environmental conditions can limit functional group presence on the
Florida Keys reefs.
Species richness within functional groups
Some species displayed a limited range of reefs across which they were present within
all functional groups. Meanwhile, other species within both functional groups were
present across all sites in both gradients. The nested pattern was most strongly displayed
by species within the FP functional group, with highest richness found in low disturbance
reefs and a linear decline in richness as total coral cover declined. The pattern exhibited
by the FP species was expected, as the FP functional group possesses a stress-tolerant
adaptive strategy that was predicted to be most affected by increased levels of
disturbance.
The species of the BV functional group also displayed a nested distribution pattern,
except in this case the peak in richness was found at a mid-point on the indirect gradient
and the same species were absent from both ends of the gradient. This pattern indicated
that some species within the BV functional group are tolerant of a wide range of
environmental conditions while others are not. Alternately it could be that environmental
conditions limited recruitment or colony survival at one end of the gradient and
competition or predation limited membership at the other end of the gradient (Menge and
Sutherland 1987). Examination of recruitment densities, partial mortality, competitive
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interactions and indicators of predation, such as fish bites, would be required to
determine the cause of the unimodal pattern exhibited by the BV functional group.
Some functional groups displayed significant changes in species richness across the
indirect gradient of total coral cover across the 20 reef sites, however. Both the BV and
FP functional groups displayed significantly fewer species on reefs characterized by low
coral cover. The foliose, plating and solitary corals of the FP functional group possess
many traits that promote the tolerance of stress, which Grime (1977) predicted would
restrict their ability to persist under conditions of high disturbance. Examination of the
sorted matrix of FP species shows that the four species most affected negatively by the
indirect gradient are Mycetophyllia lamarikiana, Mussa angulos, My. ferox and My.
danaana. These corals all possess larger polyps, thicker tissue and are the most
aggressive of the FP functional group (Budd et al. 2001; Lang 1972). The sensitivity of
the FP species, especially species from the Mycetophyllia genus, to disturbance indicates
that these K-selected and typically rare species may be most susceptible to degraded
water quality from Florida Bay.
The branched, viviparous corals that were excluded from reefs with low coral cover
include Porites divaricata, Madracis mirabilis and Madracis formosa. The same species
were also absent on reefs with the highest levels of total coral cover. These corals
possessed the smallest polyps and thinnest branches of the species within the BV
functional group (Budd et al. 2001). This pattern indicated that some species within the
BV functional group are tolerant of a wide range of environmental conditions while
others are not. Alternately it could be that environmental conditions limited recruitment
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or colony survival at one end of the gradient and competition or predation limited
membership at the other end of the gradient (Menge and Sutherland 1987). Examination
of recruitment densities, partial mortality, competitive interactions and indicators of
predation, such as fish bites, would be required to determine the cause of the unimodal
pattern exhibited by the BV functional group.
Both the MV and MO functional groups displayed very little change in species
richness across reefs, regardless of total coral cover. It was predicted that corals of the
MV functional group would be more tolerant of disturbance than species from other
functional groups, since the MV corals exhibit high levels of recruitment and a smaller
overall colony size, as described in Ch. 1, above. One or two species from the MO and
MV group did display a reduced range of sites across which they were found.
In the MV group Montastrea annularis was only found at four reef sites out of the 20
included in the analysis of the indirect gradient. M. annularis is known to dominate
shallow water habitats. It is probable that the limited distribution displayed by this
species on the deeper forereef was due to these sites being outside the range of its
environmental tolerance.
Three species were found to have a limited distribution across the indirect gradient of
20 reefs. Isophyllastrea rigida was only found at one site, while Isophylia sinuosa was
observed at six reef sites. The rarity of both species implies that the environmental
conditions of the deeper forereef sites are also outside the tolerances that they are adapted
too. The response of the MV coral Favia fragum is particularly worthy of note; it was
only found in sites with low total coral cover and not in sites with high total cover, and
had the lowest midpoint value of all corals regardless of functional group membership
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(Table 2.08). It may be that F. fragum selectively recruits to habitats characterized by
high disturbance, or that it is particularly susceptible to competitive exclusion by more
aggressive species.
The species richness of the MO functional group did decline as total coral cover
decreased, but the relationship was marginally insignificant. Perhaps the large scale at
which the surveys were taken allowed for the inclusion of less-disturbed microhabitats
which allowed for the persistence of this functional group. Alternately, the classification
of the MO functional group as Competitive–Stress-tolerant may need to be revised.
However, since coral cover of this functional group greatly exceeded that of all other
groups, it does conform to the competitive dominant strategy as proposed by Grime
(1977) in other ways.
CONCLUSIONS
In the introductory chapter I described how, when graphed, the percent cover data for
all corals surveyed (redrawn as Figure 2.20 below) on the Keyswide Coral Reef
Expedition produced a chaotic pattern in which each species appears to vary
independently. I used the confusing graph to demonstrate the need for techniques with
which to organize and simplify species-level data so that they can be interpreted in an
ecologically meaningful manner.
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Figure 2.20. Percent cover for each of the 38 species recorded on the 20 reefs surveyed
on the Keyswide Coral Reef Expedition.
The functional group framework that I developed in Chapter 1 was tested in this
chapter using data collected from the same corals as in the above example. described in
Chapter 1. As such we should now be able to re-organize the species data that produced
the chaotic graph above into functional groups, and expect to see meaningful pattern
where, in the figure above, there is none.
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Figure 2.21. Functional group cover for each of the four predominant functional groups
recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition.
As can be seen in Figure 2.21, the functional group framework provides a means for
interpreting the species data in a more ecologically meaning way. The MO functional
group, which dominates reefs with low levels of disturbance, can be seen to peak on reefs
opposite the islands of the Florida Keys. On reefs near passes through the islands,
however, the percent cover of the MO functional group declines dramatically.
The other three functional groups are not predicted to be as abundant or to produce as
much biomass as the MO functional group, and we can see that they remain at low
overall cover even on the reefs on which the MO functional group can accumulate high
levels of biomass. Figure 2.21 also indicates that since the species of the MO functional
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group are the predominant provider of coral cover in the Florida keys, management
action should focus on protecting these species or promoting their recovery. The other
functional groups are less affected by disturbance and stress than the MO functional
group, however, and it may be advantageous to determine what life-history strategies
allow these more tolerant corals to persist in the face of stress or disturbance so that all
coral species may be better protected from environmental change.
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CHAPTER 3. THE GEOGRAPHY AND ENVIRONMENTAL CHARACTERISTICS
OF THE NORTH LAGOON OF BERMUDA
INTRODUCTION
Bermuda, a United Kingdom Overseas Territory, is located on a 5560-hectare chain of
limestone islands located in the North Atlantic near 32oN 64oW (Figure 3.01). Although
Bermuda is north of the tropics, prevailing warm oceanic conditions support a limited
number of small mangrove forests, extensive seagrass beds and well-developed coral
reefs. The Bermuda reef platform encompasses a wide range of habitat types, from
small, enclosed bays and harbors to the broad lagoon, all of which are encircled by a
well-developed rim reef and large, exposed fore-reef zones. Bermuda is host to a reduced
suite of species relative to more southern reefs of the Caribbean, with only 22 species of
shallow-water hard coral recorded (Appendix 2.01; Sterrer 1998). The relatively small
number of local species aids in the search for biota - environment linkages, by reducing
the complexity of the coral assemblage. Additionally, there exists a library of climatic
and oceanographic data on Bermuda’s marine environment that dates back many decades
(Bermuda Weather Service; Bermuda Institute of Ocean Sciences [formerly the Bermuda
Biological Station for Research, Inc.]).
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It appears that acroporid corals were not present in Bermuda over the past several
hundred thousand years (Garrett et al. 1971). Repeated transplant experiments carried out
in the early 1970s at a site on the northern rim reef confirmed that acroporid corals are
currently prevented from establishment on Bermuda reefs by cold winter temperatures
(R. N. Ginsburg and E. A. Shinn personal communication). Consequently, unlike most of
Figure 3.01. A photomosaic map of the Bermuda Islands and surrounding reef platform.
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the western Atlantic (Aronson and Precht 2001), Bermuda’s reefs were not affected
by the loss of staghorn and elkhorn corals that occurred in the 1980s to early 1990s.
Instead, in most places the reef community appears to have changed little in the past 30
years when compared to the rest of the Caribbean, despite continued perturbation from
overfishing (Butler et al. 1993), ship groundings (Smith 1992), sedimentation (Dodge and
Vaisnys 1977), land reclamation (Flood et al. 2006), coral bleaching and coral disease
(Cook et al. 1990). Coral cover in Bermuda averages 50–90% on the terrace reef (Logan
1988), 20–26% at rim reef sites (Dodge et al. 1982, CARICOMP 1997; Murdoch et al.
unpublished data), 17% (with a range of 10–45%) on patch reefs (Dodge et al. 1982,
Garrett et al. 1971; Murdoch et al. unpublished data) and 13% inside the breaker line on
the South shore (Garrett et al. 1971; Murdoch et al. unpublished data).
Study Area
The area under study is centrally located within the north lagoon, and is bounded at
the southern extent by the north shore of the main island of Bermuda (Figure 3.02).
Roughly 1-km seaward of the shore runs the South Ships Channel, which is ~100-m
wide, 10–13 m deep, and which starts seaward of the island of St. Georges, at the east
end, and continues westward to Grassy Bay, where it branches and continues to three
locations. One branch of the channel extends to connect to the Royal Naval Dockyard,
while the other branch continues through the Great Sound and there splits again, with one
secondary channel continuing on to the anchorages on either side of Morgan’s Point and
the other secondary channel turning eastward and terminating at the docks in Hamilton
Harbour.
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Platform margin (fore) reefs and lagoonal reefs have been historically classified into
several different types, with some of the nomenclature specific to Bermuda (Figure 3.02;
Appendix A; Garrett et al. 1971; Logan 1988; Logan and Thomas 1992). Within the
lagoon, pinnacle reefs are characteristically steep-sided patch reefs measuring 10–150 m
in width and 6–20 m in height, and are typically found in the outer lagoon. Ring-shaped
patch reefs that are 50-m to 500-m wide are known as “mini-atolls”. Mini-atolls typically
have a raised rim of coral and algae encircling a sediment-filled mini-lagoon containing
only scattered coral knobs. When mini-atolls extend beyond 500 m in width they are
referred to as “faro” reefs (Stoddart and Scoffin 1979; Logan 1988). In Bermuda faro
reefs generally exhibit large central areas of shallow (~4-m depth) sandy seabed peppered
with very sparse coral knobs, fringed by a ~10-m wide ridge of well-developed coral reef
and surrounded by much deeper water (10 - 20-m depth).
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Figure 3.02. (below) An illustrated map of the islands and surrounding lagoonal patch
reefs of Bermuda, with important geographic features labeled (produced by
the author). The islands of Bermuda are clustered in a fishhook-like shape
on the southeast side of the atoll. The reef platform extends 15 km to the
northwest of the island. The rim reef reaches to within 2 m of the sea
surface and encloses the north lagoon and the tens of thousands of patch and
pinnacle reefs therein. The fore reef surrounds the island and platform and
extends down to a continuous field of loose rubble rhodoliths that rings the
platform at roughly 100-m depth. Below this field, the sides of the extinct
volcano on which Bermuda rests continue down without coral growth to the
Bermuda Rise, over 4000-m deep.
136
137
The study area is characterized by several large clusters of patch, pinnacle and faro
reefs that extend across the north lagoon (Figure 3.02). Baileys Flat (or Flats), which
form the eastern boundary of the study area, are a string of well-developed patch reefs
that runs in a roughly linear fashion for 9 km, from just offshore of Bailey’s Bay out to a
large shallow faro reef called The Crescent. A similar congregation of patch reefs, known
as Brackish Pond Flats, is found near the western edge of the study area. Brackish Pond
Flats extend in a north-south direction from Spanish Point out towards Devils Flats.
Brackish Pond Flats lies about 5 km west of Bailey’s Flats. Both of these linear reef
systems are thought to have formed on the tops of topographic highs that were once
aeolian dunes (windblown sand) formed during glacial periods, when sea levels were up
to 100-m lower than at present and the Bermuda platform was subaerially exposed
(Garrett and Scoffin 1977).
Connecting the northern end of the two reef flats is a network of faro reefs called
White Flats and The Crescent. These reefs possibly grew on top of massive wash-over
sand deposits that were created by the storm erosion of sand islands that are hypothesized
to have been in place along the northeast rim during the last rise in sea level, roughly
6000 years ago (Garrett and Scoffin 1977). Within the basin bound by Baileys Flats,
Brackish Pond Flats and White Flats are found scattered patch reefs. These patch reefs
tend to reach to very close to the surface and are generally conical in shape.
Seaward of White Flats and The Crescent lies a natural channel that is ~20-m deep,
and through which runs the North Ships Channel. Northward of the shipping channel are
located several lobe-shaped faro-reef formations, 1–2 km in length and up to 1-km in
width, and which also are hypothesized to have formed on top of wash-over deposits
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(Garrett et al, 1971). There is currently >20 m of coral accretion on top of the Pleistocene
deposits, which grew after submersion 6-8 thousand years ago (ka) (Garrett et al, 1971;
Garrett and Scoffin 1977). Many flat-topped pinnacle reefs, each roughly 50–100 m in
diameter, are scattered between the faros in this area. The faro reefs extend in a
northwesterly direction to adjoin at the landward side of a section of the rim reef locally
known as the Ledge Flats. Seaward of the rim lies the reef terrace, forereef, and then the
volcanic slope of the Bermuda seamount which continues down to the abyssal depths.
Eastward of Baileys Flat is a large expanse of flat sandy seabed at 13 m depth and
with no coral reefs, known as Murray’s Anchorage. Westward of Brackish Pond Flats is
the entrance to the Great Sound, and the western side of the North Shipping Channel, as
well as Dockyard. Further to the west continues the lagoon, across which are scattered
other reef flats and clusters of patch reefs.
All surveys were carried out within the study area extending from land out to the rim
reef across the middle of the North Lagoon. The study area was partitioned into six zones
representing different distances from shore (Figure 3.07). Sites were not surveyed on the
rim or fore reef as these areas are an ecologically and hydrographically a different kind of
habitat. The forereef habitat is exposed to oceanic water over at least half of the tidal
cycle and receives the full brunt of storm waves. In contrast, lagoonal waters are retained
on the platform for 4.2 days and have higher loads of suspended sediment, a greater range
of temperature and lower levels of nitrogen than offshore oceanic waters (see Morris et
al. 1977). In addition, lagoonal reefs are protected from the full strength of oceanic waves
emanating from the N, E and W quarters by the encircling rim reef, and from waves
originating from the S by the islands of Bermuda. Furthermore, the rim and fore-reef
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habitats are all interconnected and form one large ring-shaped reef, while the patch and
faro reefs are often separated from neighbors by expanses of relatively deep water and
sediment-covered basins.
Below I review the previously published information regarding the distributions of
marine environmental factors or reef corals across habitats in Bermuda. Subsequently I
describe three separate projects in which I quantified different aspects of the study area
for which information was lacking previously. In Project 1, I describe how the coral reefs
located within the study area was mapped into a Geographic Information System
application (Project 1). In Project 2 I describe the results of an effort to quantify light
availability across the study area. Project 3 details the results of an analysis that
determined how light varied in intensity over a range of depths and when measured
originating from different directions.
Previous research into the distribution of corals across the North Lagoon
The coral reefs of Bermuda have been the focus of interest for geologists and
biologists for over 100 years (Heilprin 1889; Agassiz 1895; Verrill 1902). Recent
research has focused on reefs within Castle Harbour (Dodge et al. 1982; Smith 1999;
Flood et al. 2006; Jones et al. 2007), along the nearshore zones off North Shore (Smith et
al. 1998; Jones et al. 2007), within the central lagoon at Three-Hill Shoals and Crescent
Reef (e.g. Logan 1988; Smith et al. 2003; Jones et al. 2007), and on the northern and
southern forereef terrace (Cook et al 1996; Jones et al. 2007). These previous surveys
found that coral cover across the study area of the current project increases with distance
from shore, with reefs near North Shore having the lowest cover (10-15 percent coral
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cover; Figure 3.02), lagoonal reefs at Crescent and Three Hill Shoals having higher cover
(25-35 percent coral cover), and forereefs in the area around North Rock having the
highest coral cover (35-45 percent coral cover; Jones et al. 2007). Nearshore sites were
hypothesized to have lower cover due to the water quality of the area limiting growth and
survivorship. Water quality was hypothesized to be poor nearshore due to the proximity
to the reefs to areas of high population density and to the southern shipping channel,
which is a source of increased sediment suspension (Jones et al. 2007).
However, prior to the research project described in this dissertation, no data existed
for the patch reefs at intermediate locations between North Shore and the Crescent and
Three-Hill Shoals area. Also, only two lagoonal patch reefs in the zone just shoreward of
the platform rim have ever been assessed. These two reefs were surveyed in the early
1970s (Garrett et al. 1971; Logan 1988), before overfishing drastically reduced the
densities of sharks and other carnivorous fish species such as rockfish (i.e. groupers) and
snappers (Butler et al. 1993). In Chapter 4, I investigate whether coral cover, coral
richness, and the relative contribution by different functional groups of corals do vary
with distance from shore in a linear fashion, as the previous research described above
indicates, or whether a different pattern really exists. I also compare sites that differ in
depth and aspect across patch reefs, which represents another level of analysis that was
not attempted by prior researchers.
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Predominant environmental factors in operation across the study area
The environmental factors generally considered to most strongly determine the
assemblage structure of reef corals in Bermuda are temperature (Cook et al. 1990; Smith
1999), light (Dodge and Vaisnys 1977; Fricke and Meischner 1985; Logan et al 1994),
wave energy (Upchurch 1970; Mills et al. 2004), and the amount of suspended sediments
in the water column (Smith 1999; Mills 2000; Mills et al. 2004). These four factors
interact over environmental gradients that occur across the area of study (Logan 1988).
Suspended Particulate Matter
High levels of suspended sediment, or particulate matter (SPM), which reduces light
transmission to depth, are generally found in nearshore areas and decrease in
concentration as one moves offshore (Upchurch 1970; Logan 1988; G. Toro Farmer
unpublished data). This gradient is most likely present because the nearshore reefs are
protected from the predominantly southwesterly winds over the year by the location of
the island along the southern side of the reef platform. The sheltering effect of land
reduces the yearly amount of wave energy, allowing the retention of finer-grained
sediments near the shore (Upchurch 1970). The nearshore waters of the north lagoon also
experience a dramatic increase in the traffic of ships through the south channel in the
summer (Figure 3.03). These ships typically re-suspend substantial amounts of sediment,
as seen in the long, wide sediment trails that remain along the entire length of the ships
channel for many hours (Figure 3.04). The southern shipping channel runs along the
north shore of the island at a distance of roughly 0.5 km from shore (Figure 3.06, below).
142
The lagoonal reefs far from shore are not as well protected by the island from waves
generated by high wind, although neighboring shallow (~2-m depth) reefs probably
reduce wave energy to some degree. Also, while there is a northern shipping channel that
passes through the offshore patch reefs, during the sampling period of this project (2000–
2005) ships only rarely traversed this passage (Bermuda Government, Dept. Marine and
Ports). For these reasons the reefs offshore experience higher wave energy (Mills et al.
2004), but also lower levels of suspended sediment. As I show below (Project 3), the
lower levels of suspended sediment offshore allows more light to reach a given depth on
offshore reefs than at a comparable depth on inshore reefs.
143
Figure 3.03. A graph charting the number of passages by ships traveling through the
southern shipping channel in 2004. Cruise ships carrying tourists only come
to Bermuda in the warm months of summer. Ships bringing cargo visit
Bermuda on a regular weekly schedule over the entire year. The data
presented is derived from the Bermuda 2004 Cruise Ship Schedule (Bermuda
Govt., Department of Tourism and Transport 2004).
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Figure 3.04. An aerial photograph of a cruise ship traversing the south shipping channel
of Bermuda in a westerly direction, and leaving a plume of sediment in its
wake. A portion of North Shore and Spanish Point can be seen behind the
ship. (© 2006 T.J.T.Murdoch)
Water Temperature
Temperature varies in a predictable gradient from nearshore to offshore across the
study area (CARICOMP 1997; de Putron 2003). Reefs near the rim are exposed to
oceanic waters, which exhibit a limited range in temperature relative to the seawater in
enclosed bays and harbors. For this reason the greatest range in temperature occurs in
inshore waters, which cool to below 17°C in the winter months (February-April) and
warm to 31°C in the summer months of August and September (Figure 3.05). Offshore
reefs, alternatively , reach 18 to 19°C in winter and 29°C in summer months. Outer
145
PLUME
lagoon reefs experience temperatures that lie between these two extremes (de Putron
2003).
Figure 3.05. Temperature record for 2 subsurface temperature data loggers located either
near North Shore (Inshore) or on the forereef at 30 ft depth (Offshore) for a
three year period from 1998 – 2000 (modified from de Putron 2003).
Solar Radiation
The Effect of Depth and Turbidity
The visible sunlight that we see is of the same general range of wavelengths as the
solar radiation that plants use for photosynthesis; technically referred to as
Photosynthetically Available Radiation (PAR; Kirk 1994). Sunlight is absorbed by water,
even when it contains little suspended sediment (Kirk 1994). Light intensity decreases
with depth in an exponential manner, the rate of which is dependant upon the turbidity of
146
the water and the wave-state of the surface (Kirk 1994). Corals at deeper sites are
expected to receive less light for growth than corals at shallower sites. Sites at a particular
depth in water with higher turbidity should likewise receive less light than sites at the
same depth in clearer water.
The Effect of Aspect
The coral reefs in Bermuda represent the most northerly coral reefs in the Atlantic. As
such, the angle of the sun in the southern sky is more acute here than on reefs located
closer to the equator (Figure 3.06). For this reason, the southern side of a patch reef in
Bermuda should be exposed to substantially more sunlight over the course of the year
relative to the northern side of the same patch reef. Below I describe a study (Project 2) to
determine the differences in light flux to a sensor facing a southerly vs a northerly
direction. In Chapter 4 I compare the differences in the coral assemblages located on the
north to those on the south sides of the same patch reef at the same depth.
147
Figure 3.06. A graph of the hourly positions and paths the sun appears to take as it
crosses the sky in Bermuda over the course of a day during the summer and
winter solstices, and either equinox. The numerals around the circumference
of the circle represent bearing, with 90° representing East. The numerals
within the circle represent the angle above the horizon, with 90 representing
the zenith point, directly overhead. The sun is at it’s apparent daily apogee in
Bermuda at 12.13 pm local standard time. Graph generated using the
shareware tool “Sol Path” (© C. Gronbeck 2002, 2006).
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Wave energy and currents
The island of Bermuda possesses a hilly topography with an average height of 30 m
above sea level (Morris et al. 1977), which acts to block the effects of the wind on marine
habitats located in a leeward direction. As the island is located along the south-east edge
of the lagoon, the island primarily blocks winds that originate from the east through to a
south-westerly direction from reaching lagoonal waters. The prevailing winds in
Bermuda are from a south-westerly direction throughout the summer (Appendix C,
below), which results in calmer waters being found near the northern shore and higher
waves occurring offshore. In the winter, the prevailing winds originate from the north-
westerly direction. As there are no islands to block the wind from the north-west, high
seas produced by winter storms affect all lagoonal reefs to a relatively equal degree
(Morris et al. 1977 ), and even the northern shore is subjected to large (>4-m) waves
(Thomas 1985). Additionally, wind-driven current flow declines with depth, at an
exponential rate (Ekman 1905).
Bermuda experiences a semi-diurnal tidal cycle with a range of 0.75 m on average
(Morris et al. 1977). As a result of the changing tides, strong currents occur in some areas
on the Bermuda platform, particularly at the entrances to enclosed bodies of water such
as Harrington Sound and the Great Sound (Figure 3.02; Morris et al. 1977). Strong tidal
currents can also be observed to flow over the lagoonal rim at all locations, although they
are strongest at the northeast and southwest ends of the lagoon, presumably due to the
position of the Bermuda islands. However, since the study area is located within the
central area of the Bermuda lagoon,, far from enclosed bodies of water and the NE and
SW parts of the lagoon, tidal currents have little strength.
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Project 1: Mapping of lagoonal reefs
Introduction and Methodology
When the project was first initiated there were no accurate maps available that delineated
the locations of the patch reefs found scattered within the lagoon. For this reason, many
of the sites I surveyed were selected based on the surprisingly inaccurate maps of reef
location available from the Hydrographic Office of the United Kingdom, as well as from
triangulation of terrestrial landmarks and extensive time spent out in the lagoon in boats
learning the “lay of the land”.
In order to aid in the scientific study of Bermuda’s lagoonal reefs henceforth, in
2003–2004 I produced the first accurate, geo-referenced digital map of the entire suite of
reefs visible within the study area, as part of a larger mapping effort I did as a member of
the Bermuda Zoological Society that included all lagoonal patch and pinnacle reefs. This
map was produced by referencing a mosaic set of georeferenced aerial photographs of the
islands and surrounding submerged platform that the Bermuda Zoological Society
commissioned in 1997 (Figure 3.01).
The aerial photographs of the Bermuda Islands and surrounding reef platform were
produced using a Zeiss Jena LMK photogrammetric survey camera with forward motion
compensation, which was mounted onto a small aircraft. In 2003 a composite raster
bitmap for the entire Bermuda platform was produced from the slides, with a final
resolution of 50 cm per pixel and a geo-referenced error of less than 2 m (Bermuda
Zoological Society 1997). A map of probable coral reef habitat was then created for the
entire Bermuda platform from the digital mosaic with the GIS package ESRI ArcMap 9.1
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(Figure 3.02). To create this map I manually digitized the boundaries of coral reef areas
as continuous closed polygons at a scale of 1:2500, using color (light to dark reddish-
brown) and the presence of sand halos around reefs as visual indicators of boundary edge.
Spatial referencing of the digital photographs was accurate to 2 m and, combined with a
pixel size of 50 cm, a spatial accuracy of about ±2.5 m was possible for visually mapped
reef boundaries. Over 34,000 separate reefs were mapped across the extent of the lagoon.
Once the boundaries of each reef within the lagoon was mapped to GIS, I delineated
the outer edges of the study area, as well as the margins between each of the six zones
within the electronic map. I then used the Hawth’s Analysis Tools extension for ESRI’s
ArcGIS (Beyer 2004) to generate the data which I compiled into Table 3.01, which
details the area enclosed by each zone, the number of reefs in each zone, the density of
reefs per km2, the total reef area per zone, the percentage of total zone area covered by
reefs, and the mean size of each reef.
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Figure 3.07. Zonal boundaries, locations of the north and south shipping channels, and
location of patch reefs distributed across the study area encompassing the
North Lagoon. The numbers allocated to each zone are written on the right
side of the map.
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Results and Discussion
The characteristics of the patch reefs within each of the six zones surveyed are listed
in Table 3.01. Zone 1 lies closest to shore and is bounded on the southern side by the
northern shore of the island. The northern boundary is delineated by the South Shipping
Channel which cuts across the study area. Zone 2 is located on the northern side of the
South Shipping Channel and extends 1-2 km to seaward. Zones 1 and 2 had the fewest
reefs per km2, but the mean reef size was larger than most other zones. Many of the
nearshore reefs in Zone 1 appear to be fringing reefs, which are large, linear structures
that are positioned with the long axis running parallel to shore. These reefs probably
formed on a basement of drowned shoreline and only formed in the past 4,000-6,000
years (Garrett et al. 1971; Garrett and Scoffin 1977).
The reefs in Zones 2 to 4 are mostly contained within the clusters of reefs known as
Baileys Flat and Brackish Pond Flat. These reef systems appear to have formed on
fossilized sand dunes that formed during glacial periods when the shallow platform was
subaerially exposed. Between these two large reef clusters is a deeper area of
approximately 12-m depth across which are scattered many smaller patch and pinnacle
reefs, which may contribute to the lower mean area of the reefs in the middle zones of the
platform.
The reefs in zones 5 and 6 are large faro reef complexes, formed on what are most
probably wash-over sediment deposits that formed 8000 to 6000 years ago when the
platform first flooded (Garrett et al, 1971; Garrett and Scoffin 1977). These reefs form
large clusters with large reefs surrounding a shallow inner sand-covered area speckled
with small patch reefs.
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Table 3.01. Characteristics of each zone of the survey area across the Bermuda Lagoon,
and the patch reefs contained therein.
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Project 2: Assessing the three-dimensional light field over a range of depths
Introduction and Methodology
Although light in oceanic waters can be accurately quantified as a one-dimensional
gradient of downwelling and upwelling flux, light in shallow coastal environments has a
three-dimensional character (reviewed in Kirk 1994; Ackleson 2003). Bermuda’s high
latitude further enhances the multidimensional character of the light field, in that the
angle of the sun in the sky is significantly sharper through much of the year than it is at
all other coral reef regions, which al lie further to the south.
To quantify the three-dimensional character of light in Bermudian waters, I assessed
the differences in light flux measured by a hemispherical sensor, representing a mound-
shaped coral colony, when it was positioned perpendicular to the directions North, East,
South, West, Up and Down (N, E, S, W, U, D). To do this I modified a standard scalar
Li-Cor light sensor, which is spherical and designed to measure light impinging from all
directions, by covering the bottom half of the sphere so that light could only be received
over the top half of the sphere (Figure 3.08). Light was blocked from the bottom half of
the sensor with the use of opaque adhesive tape, and the entire sensor was mounted at the
midpoint of an circular and opaque black plastic collar with a 25-cm diameter. The collar
was added to further prevent the reception of light by the sensor from sources located
below the exposed hemispherical sensor surface.
I measured light availability from the underwater light field emanating as
downwelling light, upwelling light, and light impinging from easterly, southerly, westerly
and northerly aspects. Average measurements from these six directions were recorded by
the data logger at 5-second intervals for 5 minutes each at 3-m depth intervals down to
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15-m depth. Data collection was done in clear oceanic water (Secchi disk depth >18 m) at
location 32.382°N, 64.648°W on the forereef east of Bermuda, on July 24th, 2002. A
second light sensor was placed at 9-m depth to control for the effects of clouds.
Concurrent measurements taken in air and at 9-m depth prior to the experiment were used
to convert recorded light flux to a percentage of the light hitting the surface of the ocean.
Both sensors were connected by transmission cables to a electronic data logger located on
the boat at the surface. The boat was not directly overhead of the area of data collection,
so as to avoid detection of the boat shadow. The mean light flux and standard error of
each collection period from each depth and aspect were subsequently graphed for visual
comparison. The data did not conform to the assumption of equal variances, and
transformations of the data were unable to resolve the problem. The results of ANOVA
on all forms of the transformed data produced the same significance values as did
individual Mann-Whitney U tests (a nonparametric test of differences), so the results
from the ANOVA using non-transformed data are presented.
Results and Discussion
At all depths the amount of light impacting the sensor when it faced a southerly
direction was substantially higher than when it faced a northerly direction (Figure 3.09).
Downwelling light was substantially higher than the amount of upwelling light (as
expected), and downwelling light was also significantly higher than light originating from
either a southerly direction or a northerly direction. Additionally, more downwelling light
was available in locations closer to the surface than at greater depths. The values for the
sensor placed in an easterly and westerly aspect were statistically indistinguishable from
156
each other and at levels between those obtained from the northerly and southerly aspects,
which is as would be expected (T. Murdoch unpublished data). For simplicity, the data
from these two “midpoint” directions have been omitted from further analysis in this
section. Two-way ANOVA of depth and aspect for all 5 depths and four directions (N, S,
U, D) found that the interaction between the depth and the direction that the sensor faced
was highly significant at p < 0.001 (Table 2.02). Tukey HSD post hoc comparisons of the
light data determined that all measurements were significantly different for each depth
and aspect except between all measurements taken at 12-m depth and at 15-m depth, and
between the measurements taken from the northerly aspect and of upwelling light at all
depths.
These results illustrate that the location of Bermuda at a high latitude results in more
light being available to an organism living on the south-facing side of an object, such as a
coral reef, than on the north side, due to a shading effect created by the bulk of the reef
itself. The survey was done in August, when the angle of the sun is more obtuse than it is
for eight months of the year. Thus, for most of the year the relative difference in light
availability between the north and south sides of a reef is greater than that observed.
However, since less light reaches the surface of the earth as the sun angle sharpens, the
absolute difference between the northern aspect and southern aspect would be less in
winter months.
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Figure 3.08. A diagram illustrating the modified Li-Cor scalar PAR sensor. Opaque
adhesive tape, an opaque plastic jar, and a black plastic collar constrained
the light quantified by the sensor to that impacting the upper, exposed
hemisphere.
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Figure 3.09. Mean proportion of surface light (± standard error) originating from four
directions at five depths, as measured by the hemispherical sensor.
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Table 3.02. Two-way analysis of variance of the effects of depth and aspect on the
proportion of surface light reaching a hemispherical sensor.
Source SS df MS F-ratio p
Depth 5382523.974 4 1345630.993 178.307 .000
Aspect 24710913.276 3 8236971.092 1091.466 .000
Depth *
Aspect5931307.572 12 494275.631 65.496 .000
Error 2867746.630 380 7546.702
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Project 3: Cross-platform differences in downwelling light availability
Introduction and Methodology
If turbidity is higher nearshore relative to offshore, as prior research (CARICOMP
1999; Jones 2007) indicate, then the amount of downwelling light impacting a point at a
particular depth should be lower nearshore than offshore. In order to assess cross-
platform differences in the availability of downwelling light, light flux was assessed at 8-
m depth at five equally-spaced locations that were at different distances from shore
(Figure 3.10), over a week-long interval in June 2004. Downwelling light intensity was
measured using a collection of miniaturized, submersible Onset Hobo® light sensors with
self-contained data loggers, following techniques described in Kirk (1994).
Each sensor recorded light flux at 5-min intervals over the 7-day period. The
maximum light flux readings taken over the 2 hr in the middle of each daylight period
were used to calculate differences between locations in light availability. Only data from
the first five days were used, as most sensors became fouled with fine sediment or
filamentous algae after that period of time. Transformed data did not conform to the
assumptions of homogeneity of variances; the results from ANOVA of the non-
transformed data are presented but should be interpreted with caution.
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Figure 3.10. Map of the five reef sites, indicated by the light-bulb symbol. At each site
luminance readings were taken concurrently, from 26 July 26 to 1 August
2004. All sensors were placed at exactly 8-m depth, with the sensor surface
facing straight upward. The boundaries of the study area, the six zones, and
the north and south shipping channels are also illustrated
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Results and Discussion
Figure 3.11 illustrates the continuous changes in light level over 5-min intervals over
the five days across the five sites. Light levels increase over the course of a day until
12:13 pm local standard time, and then decline again as the surface of the earth rotates
away from the sun. Sharp spikes in light above the daily maximum are characteristic of
peaks in light produced by the passage of waves. A surface wave can act as a lens, and
may either focus or diffuse light reaching a point below it (termed “wave focusing”; Kirk
1994; Schubert et al. 2001). This process of wave focusing is the source for the
meandrous patterns of brighter light observed on the sandy sea floor in shallow water, or
on the bottom of a swimming pool. The magnitude of the spike during wave focusing
events is dependent on the shape of the wave and the depth of the sensor, with the highest
spikes occurring when lens shape and sensor depth match and a large amount of the sun’s
light is focused on the spot. Sudden large drops in light intensity that one can see in the
daily light data are probably due to the occlusion of the sun by clouds (Kirk 1994). Drops
in light intensity that match across all sensors, such as the event recorded near noon on
the third day surveyed, indicate the passage of very large clouds that encompassed the
entire reef platform. Another source of reduced light across large areas is the occurrence
of sustained wind events with speeds greater than 28 km/hr (15 kts), which cause the
formation of frothing waves or “white caps” that reflect light away from the seabed (Kirk
1994).
Light levels were highest at the site located in the rim reef zone, and declined at sites
progressively nearer to shore (Figs. 3.11, 3.12). ANOVA determined that the overall
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pattern was highly significant (Table 3.03). Tukey’s HSD post hoc analysis (Table 3.04)
determined that only sites C and D were not significantly different in light intensity.
These results indicate that, for a given time period at a given depth, corals nearshore
are exposed to less light than those offshore. Since light is a critical resource for
hermatypic corals which host photosynthetic zooxanthellae (Rogers 1979; Achituv and
Dubinsky 1990), and since different coral species are adapted to cope with a range of
characteristic annual light budgets (Huston 1985a; Graus and Macintyre 1989), it is
expected that different corals will be found at the same depth but at different distances
from shore across the Bermuda platform.
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Figure 3.11. Light intensity readings taken over five days from sensors positioned at 8-m
depth at 5 reef sites located at different distances from shore across the area
of study. Instantaneous light intensity readings were taken at 5-second
intervals over five days.
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Figure 3.12. Average light intensity (Lumens ±SE) measured from 11 am to 1 pm local
standard time over the first of the five days of deployment, by light sensors
located at 8-m depth at five reef sites positioned at increasing distances from
the North Shore of Bermuda. The approximate distance from shore of the
boundaries between zones (which varied along the extent of each zone) are
also indicated.
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Table 3.03. ANOVA table of the differences in light intensity across the five locations
from the data illustrated in Figure 2.13.
Source SS df MS F ratio p
Distance 193031.858 4 48257.964 216.557 0.000
Error 25626.866 115 222.842
Table 3.04. Results of a Tukey’s post hoc analysis of the significance in the differences in
the amount of luminance at 8-m depth over the hours of 11 am to 1 pm
between the five locations across the reef platform. Only sites C and D did
not differ significantly in the amount of light measured at 8-m depth.
Tukey HSD
Distance A B C D E
A
B 0.000
C 0.000 0.009
D 0.000 0.000 0.596
E 0.000 0.000 0.000 0.000
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DISCUSSION
A review of the literature regarding Bermuda’s physical oceanographic conditions, as
well as novel research, indicates that the four critical environmental factors of
temperature, light, suspended particulate matter and current flow all covary with distance
from shore and with depth. As described in Chapter 1, these four factors can each affect
corals as stressors, disturbance agents and as factors promoting growth, depending on the
levels or intensities at which they occur (Figure 3.13).
The amount of variability in temperature is higher nearshore compared with offshore,
with colder winter temperatures and hotter summer temperatures experienced by sites
near land (Morris et al. 1977; du Putron 2003). Offshore sites, which are bathed in the
waters of the surrounding Sargasso Sea, experience less change in temperature over the
year. Temperatures also vary across depths in the summer, with warmer waters occurring
at the sea surface across the lagoon (Morris et al. 1977). Low temperatures inhibit
physiological functions, and as such act to inhibit growth and tissue repair. High
temperatures, alternatively, act as a disturbance agent, by inducing coral bleaching (Cook
et al. 1990; Brown 2004), inhibiting reproduction (Fraser and Currie 1996), promoting
the growth of coral diseases (Harvell et al. 1999), and the growth of competing
organisms such as macroalgae (Johannes et al. 1983). Accordingly, nearshore reefs are
predicted to have less coral cover and species relative to offshore reefs. Additionally,
competitively-dominant corals may be expected to dominate in areas of lower
temperature range found offshore, with disturbance-tolerant or stress-tolerant corals
dominating the nearshore areas with a high range of temperatures.
Light levels in Bermuda are highest in the shallowest waters offshore, and decline
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both with depth and with proximity to shore. Wave energy follows the same pattern. Both
light and wave energy act as damaging agents at high levels, promote growth at moderate
levels and inhibit productivity at very low levels. For that reason it may be expected that
ruderal corals dominate shallow sites, particularly on reefs offshore, while competitive-
dominate coral species dominate at some mid-point across the lagoon and at moderate
depths. Deep sites, particularly nearshore, are predicted to be dominated by stress-tolerant
coral species adapted to low levels of light and low rates of dissolved nutrient flux.
Suspended particulate matter (SPM) is in highest concentration nearshore, and
decreases in concentration as the distance from shore increases (Mills et al. 2004; G.
Toro-Farmer unpublished data). SPM can act as both a disturbance agent and as a source
of nutrients. Nearshore sites are predicted to possess more corals that are capable of
removing or surviving the smothering effects of SPM. Additionally, heterotrophic corals
that are able to utilize SPM instead of light as a source of carbohydrate nutrition may be
favored in nearshore habitats relative to those offshore.
In Chapter 4 I describe how I examined the manner that species and functional groups
of coral varied across sites that differed in distance from shore and depth, which serve as
simple proxy direct gradients for the co-varying physical gradients of temperature, light,
SPM and wave energy that were described in this chapter. Coral assemblages were
surveyed across sites located at a range of depths and distances from shore on patch and
pinnacle reefs within the North Lagoon of Bermuda, and the results compared to the
patterns predicted by the modified Adaptive Strategies Theory that I presented in Chapter
1.
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Figure 3.13. Representation of how varying levels of the four most important
environmental factors act to promote growth, or act as a stressor or
disturbance agent to corals.
170
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CHAPTER 4: THE DISTRIBUTION OF CORAL SPECIES AND FUNCTIONAL
GROUPS OVER PHYSICAL GRADIENTS ACROSS THE NORTH
LAGOON OF BERMUDA
INTRODUCTION
According to the Adaptive Strategies Theory (AST; Grime 1979), one can predict the
characteristics of the functional group of organisms that will dominate a particular habitat
by determining the levels of stress and disturbance that are found at that location (Figure
4.01). On coral reefs, the four environmental factors that predominantly affect the
amount of stress or disturbance which corals experience are: water temperature, solar
radiation (i.e. sunlight), suspended particulate matter (SPM) and water flow. In Chapter 3
I described how these four physical factors vary as gradients across the North Lagoon of
Bermuda. In this chapter I examine whether the modified AST that I described in Chapter
1 predicts how species and functional groups of coral are distributed across sites on reefs
in Bermuda that are located over these environmental gradients of stress and disturbance.
The sites I surveyed in Bermuda can be thought of as representing the range of
environmental conditions enclosed within the nested square illustrated in the AST (CSR)
diagram below (Figure 4.01).
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The four critical environmental factors of temperature, light, suspended particulate
matter and current flow all vary with distance from shore and with depth (Chapter 3). As
described in Chapter 1, these four factors can each act on corals as either stressors,
disturbance agents and in the promotion of growth, depending on the levels or intensities
at which they occur (Figure 1.06).
Sea water temperature exhibits a wider range within the surveyed area at nearshore
sites compared with locations offshore, with colder winter temperatures and hotter
summer temperatures experienced by sites near land (Morris et al. 1977; de Putron 2003).
Since corals suffer physiological disturbance when they experience temperatures too far
outside their average range, nearshore reefs are predicted to have less coral cover and
species relative to offshore reefs. due to high disturbance levels (strong annual seasonal
temp fluctuations) restricting the growth of stress-tolerant corals and limiting the number
of species capable of surviving on these nearshore reefs. Additionally, competitively-
dominant corals may be expected to dominate in the areas of lower temperature range
found offshore.
Light levels in Bermuda are highest in the shallowest waters offshore, and decline
both with depth and with proximity to shore, due to the re-suspension of sediments. Wave
energy follows the same distribution pattern. Light and wave energy both damage corals
when at high levels . At moderate levels light and water flow both promote coral growth.
At low levels of both light and water flow corals experience limited productivity .
Accordingly, ruderal corals are predicted to dominate shallow sites, particularly on reefs
offshore, while competitive-dominate coral species are predicted to dominate at some
mid-point across the lagoon and at moderate depths. Deep sites, particularly offshore, are
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predicted to be dominated by stress-tolerant coral species adapted to low levels of light
and low rates of dissolved nutrient flux due to reduced rates of water flow. Nearshore
reefs may see high nutrient fluxes due to the presence of nitrogen-rich ground water.
Suspended particulate matter (SPM) is in highest concentration nearshore, and
decreases in concentration as the distance from shore increases (von Bodungen et al
1982; Mills et al. 2004; G. Toro-Farmer unpublished data). SPM can act as both a
disturbance agent and as a source of nutrients Nearshore sites are predicted to possess
more corals that are capable of removing or surviving the smothering effects of SPM.
Additionally, heterotrophic corals that are able to utilize SPM instead of light as a source
of carbohydrate nutrition may be favored in nearshore habitats relative to those offshore.
OBJECTIVES
With the use of direct gradient analysis I tested the following hypotheses regarding
how species and functional groups of coral varies across the sites surveyed in the
Bermuda lagoon:
Similarities in the distribution of species and functional groups
Irrespective of the manner in which stress or disturbance agents are distributed across
sites, species within functional groups are hypothesized to have similar functional
responses to the environment. If this is so, then species belonging to the same functional
group should differ little in their distributions across sites, due to the shared responses to
environmental and biological conditions (Steneck and Dethier 1994; Gitay and Noble
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1997; Hooper et al. 2002). Conversely, the distribution patterns of species belonging to
different functional groups should be substantially different from each other, due to
disparate environmental tolerances. Chapter 1 details how these differences in site fidelity
should appear when distributional data is graphed in a variety of ways.
Despite my best attempts to do otherwise, it may be that the traits I selected to use in
the categorization of species into functional groups are those indicative of functional
mechanisms by which species acquire resources, and not those which are used to cope
with differing environmental disturbances. If this is so, then species within functional
groups may overlap greatly in their nutritional needs and therefore compete strongly
amongst other members for resources Species that belong to the same resource-based
functional group (also known as “guild”) should tend to occur in different
environmentally-defined habitats (reviewed in Fox 1999). Also species that are members
of different guilds should be able to coexist within a location to a greater degree than
species from the same guild.
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Figure 4.01. A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)
generalized two-dimensional AST model of FG dominance within habitat
types, incorporating the concession that biota can only survive in habitats
within which the rate or amount of resource acquisition (resource
abundance) is greater than the rate or amount of resource loss (or
disturbance). The boundary between the white and grey areas is the zero net
growth intercept (ZNGI) of the assemblage as a whole. The nested square
within the AST diagram of state space represents the hypothetical range within
the AST model that was represented by the sites surveyed within the north
lagoon of the Bermuda Reef Platform. Letter designations are:
C – Competitive Dominant;
R – Ruderal;
S – Stress tolerant.
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Similarity among sites in species assemblages
Sites were compared according to the degree to which they shared coral species. Sites
that differed in aspect, depth and distance from shore were evaluated so that the species
composition of each site could be interpreted accordingly. Sites that shared
environmental characteristics, regardless of zone or depth, were expected to cluster
together in multidimensional species-abundance space. Sites at a similar depth and
distance from shore were expected to cluster together in multidimensional state space (i.e.
have similar assemblages of corals on them) because the shared environmental conditions
of each site should filter coral species membership in the same way.
Percent cover and abundance per functional group
The percent cover for corals overall, and for the group of species that are members of
the most competitive functional group, are both predicted to peak on reefs where the
levels of disturbance and stress are lowest. In the north lagoon light and wave energy are
highest at shallow, offshore sites and lowest at nearshore, deep sites. Conversely, SPM
and temperature are most damaging to corals at nearshore locations regardless of depth,
and decline with distance from shore. Accordingly, moderate levels of all four variables
are expected to occur at mid-depth and roughly in the centre of the lagoon. Since
moderate levels of the four variables are the least limiting to corals, the average coral
cover of all species, as well as of the competitive species should peak at sites located in
the middle of the lagoon as well. Members of the Branched, Oviparous (BO) functional
group (i.e. the acroporids) are not found in Bermuda. With the BO group absent, either
the Competitive-Ruderal or Competitve - Stress-tolerant functional groups may plausibly
177
occupy its environmental niche, and thus dominate habitats characterized by low levels of
stress and disturbance in Bermuda. Branched Viviparous (BV) species represent the
Competitive-Ruderal group. Species of the Massive Oviparous (MO) functional group
belong to the Competitive-Stress-tolerant group.
Massive, viviparous (MV) corals, which I classified as Ruderal according to the
modified AST, are predicted to dominate at offshore reef sites in shallow water where
disturbance levels are predicted to be the highest. Stress-tolerant corals of the Foliose and
Plating (FP) functional group are predicted to be intolerant of disturbance at all but the
lowest levels. Since temperature variability and SPM, which are both forms of
disturbance, are higher nearshore compared with offshore over all depths, stress-tolerant
corals should dominate only deep sites located in the zones furthest from shore.
Species distributions across sites
In addition to providing information regarding the percent cover and relative
abundance of each functional group across all sites, as I did in Chapter 2, I also
determined the distribution patterns of each species. This species-specific data allows one
to see the degree to which species within functional groups share distributional patterns,
if at all. I also present this data for a pragmatic reason. This project represents the most
intensive survey of reef sites across Bermuda’s north lagoon to date, and the only survey
of how coral assemblages change with depth and distance from the shore across patch
reefs across the lagoon. For this reason, species distribution data are provided in order to
aid in management and conservation of the corals, as well to guide future scientific
research.
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Species richness of all corals
According to the predictions of the productivity-diversity hypothesis, which lead to
CSR theory (Grime 1973; 1979), and the intermediate disturbance hypothesis (Connell
1978; Aronson and Precht 1994; Huston 1996), the habitat types with intermediate levels
of stress and disturbance should display greater species richness than either the habitats
with low levels of stress or disturbance and the habitats with high levels of stress or
disturbance. Sites located in the middle of the lagoon and at mid-depth are thus predicted
to possess the highest number of species, with lower numbers of species found at the
extremes of distance and depth.
Functional group richness
Grime (1977) predicts that the richness of functional groups will be low across sites,
as he predicts each functional group will be replaced by another from site to site due to
the combined effects of environmental filtering and competitive exclusion between
functional groups. Alternatively, if competition does not operate between groups, then
all functional groups are predicted to occur at mid-depths on reefs centrally located
within the lagoon, as these reefs are characterized by moderate levels of the four
environmental factors. Shallow sites offshore and all sites inshore are predicted to not
possess the stress-tolerant functional groups, and deeper sites should not possess the
ruderal nor competitive-ruderal species, according to the AST.
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METHODOLOGY
Data collection
The tops of three replicate patch reefs (designated E, C and M), and the sides of two
of the three patch reefs (E and C), separated by at least 1-km, were sampled within each
of the 6 zones (Figs. 4.02, 4.03; Table 4.01). Zones differed in distance from the North
Shore of Bermuda and were within the lagoonal area bounded by the rim reef to the
north. At each reef, transects were videotaped following the procedures described in
Aronson et al. (1994), Aronson and Swanson (1997), for fore-reef habitats, but with
modifications that were needed in order to cope with the different geomorphology of
patch reefs. Since variation in the size of reefs may have affected the composition of the
coral assemblage in unintended ways (Keough 1984), all of the reefs surveyed were of
similar area and overall shape. Each patch reef was oval in shape, roughly 60-m long,
40-m wide, and with the long-axis lying in an east-west direction. The top of each patch
reef was assessed using eight 10-m long transects, placed haphazardly and so as to
encompass as much of the top of the patch reef as possible Only eight transects were
used as no more could be surveyed without overlap. . Additionally, four 10-m long
transects were haphazardly placed horizontally along consecutive ~2- to 3-m depth
contours on the southern and northern sides of the reefs.. Only four 10-m transects were
filmed on each flank; this representing the maximum number of transects that could fit
along the ~ 50-m long flank of each patch reef at each depth, while still allowing for the
haphazard placement of the transects. Since the four transects encompassed most of the
surface of the reef at each depth it seemed probable that the sampled population
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represented most or all of the total population of corals found at each site, which is to say
that most or nearly all of the statistical universe was recorded.
All transects were videotaped along a 0.4-m wide x 10-m long swath of the reef with a
high-resolution digital video camera enclosed in an underwater housing. An aluminum
bar projecting forward from the camera housing was used to maintain a 40-cm distance
between the camera lens and the reef surface. A depth gauge mounted on the end of the
bar displayed the depth of the reef substrate on each video frame, providing a measure of
the rugosity of the reef surface when filming the tops of reefs. The depth gauge also (1)
aided the videographer in maintaining a set depth while filming transects on the steeply
sloped sites of pinnacle reefs, (2) provided scale in the videotaped images, and (3)
provided a record of the depths surveyed on each reef.
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Figure 4.02. General design of the study, in which survey sites (circles) were surveyed at
a range of depths on the north, south and top sides of replicate patch reefs
within each of six zones located at increasing distances from shore. Not
shown are the replicate reefs within each zone.
182
Figure 4.03. A map of the lagoonal reefs located within and around the research area and
the 18 patch reef sites surveyed in the videographic analyses. Horizontal
lines indicate the six zone boundaries. Grey lines represent the location of
the north and south shipping channels. A portion of the island of Bermuda is
represented by the area in darker gray at the bottom of the image.
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Table 4.01. Details of the 18 surveyed reefs surveyed across the North Lagoon, also
mapped on Figure 4.03. Replicates labeled M were only videographically
sampled on the top of the reef, whereas replicates E and C were surveyed on
the tops as well as across a range of depths on the north and south sides of
each reef.
Zone Replicate Name Site Lat Long
Reef Top
Depth (m)
1 E Baileys Bay Patch E1 32.3520 -64.7250 7
1 M Shelly Bay Patch M1 32.3290 -64.7440 7
1 C Robbie’s Reef C1 32.3170 -64.7520 7
2 E Inner Baileys Flat E2 32.3530 -64.7480 5
2 M Shelly Bay Shoals M2 32.3360 -64.7570 5
2 C Finger Coral Patch C2 32.3356 -64.7765 7
3 E Martello Patch E3 32.3720 -64.7430 6
3 M Judie's Awakening M3 32.3700 -64.7620 6
3 C Gaeroid’s Reef C3 32.3550 -64.7820 7
4 E Angel Reef E4 32.3808 -64.7660 4
4 M Jeannette's Reef M4 32.3750 -64.7830 4
4 C Sascha’s Reef C4 32.3643 -64.8062 4
5 E 8A Hole Reef E5 32.4066 -64.7830 4
5 M S. Crescent 3 Patch M5 32.3870 -64.7990 3
5 C Pawlik’s Reef C5 32.3940 -64.7890 2
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6 E Pretty Bumpy Reef E6 32.4180 -64.8193 2
6 M Lisa's Reef M6 32.3961 -64.8605 2
6 C Claire's Reef C6 32.4094 -64.8410 3
Data analysis
Different hypotheses were tested using different types of data derived from the
videotaped transects. Relative Frequency of occurrence (RF) data for corals was used for
the analysis of the similarity in species distributions, the similarity of sites in species
composition, and the frequency of occurrence of each species across all reefs, as well as
species richness and functional group richness data. RF data was used for these analyses
instead of point-count data as it included rare or small species that may be missed in the
assessment of randomly placed points on transects. The RF data were collected in the
following manner. 20 non-overlapping video frames were digitally captured from each of
the 10-m long transects. Following image capture, the presence or absence of each
species in each of the 20 frames was recorded. The proportion of frames over which each
species occurred in each transect was then calculated by dividing the number of times
each species was present in each of the 20 frames.
Point-count data was assessed from each video transect following a computer-
automated version of the procedures described in Aronson et al. (1994), Aronson and
Swanson (1997) and Murdoch and Aronson (1999) that were developed by the author for
a different project (Appendix 4B). The video transects from the tops of three replicate
reefs, and the tops and southern flanks over a range of depths for two replicate reefs for
each of the six zones were assessed for the percent cover of individual coral species by
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point-counts Twenty-five random points positioned on each adjacent digital image
captured from the videographic tape. The alternate (odd-numbered) frames were captured
to provide other views of the same substrate and as an aid for visual analysis of point
count locations but were otherwise not analyzed. . The results of each analyzed frame
were summed for the entire transect, and the average of the four or eight transects was
used to calculate the average percent cover for each of the sites on a reef.
The following variables were calculated for each reef site from the videographic data:
Species coexistence among habitats
The frequency of occurrence (RF) data were used to calculate a similarity matrix for
the suite of species, based on the proportion data from each transect and separately based
on the proportion data averaged at each site. Transect-level and site-level results were
alike, so the less complicated site-level analysis is described. A Bray-Curtis similarity
metric was calculated for each species pair from square-root transformed proportional
data. Since frequency of occurrence data exhibits a smaller range of values than biomass
data, it need only be square root transformed, instead of fourth-root transformed, when
used to generate similarity matrices (Clarke and Gorley 2006). Using the Bray-Curtis
metric, species that exactly shared the same distribution pattern were assigned the highest
percent similarity (i.e. 100%), and species with distribution patterns that did not overlap
at all were assigned very low similarity values. The benefit of looking at the coexistence
of species within and among functional groups in this way is that knowledge of the actual
186
environmental and biological conditions of each site was not needed, as long as sites
were sampled across a broad range of habitats.
Similarity among sites in species assemblages
Sites were also compared according to the degree to which they shared coral species
using the same frequency of occurrence data as described above. Sites that differed in
aspect, depth and distance from shore were compared so that the species composition of
each site could be interpreted accordingly. Sites that shared zone and depth were
expected to cluster together in multidimensional species-abundance space, because sites
with similar depth and distance from shore shared environmental conditions and therefore
should affect coral species membership in a similar manner.
Species distributions across sites
In order to see how member species of each functional group were distributed across
sites in the four dimensions surveyed (i.e. RF x depth x aspect x replicate reef), I graphed
the frequency of occurrence data for each species. These data were averaged for each of
the four or eight transects for each site and the results graphically presented in three
ways. An MDS diagram was generated for all sites, and the average RF of each species
and functional group plotted as a circle, with differing sized representing differences in
occurrence. Additionally average (±SE) RF was plotted as points on a line graph for each
replicated site, aspect, depth and reef. The same data were also plotted onto a bubble
diagram for each depth and reef (but not aspect). Bubble diagrams present the relative
abundance for each species across sites and depths in a two-dimensional manner that is
187
analogous to the actual distribution of sites across real space. These three disparate
graphical techniques were concurrently used for the identical data so that the reader could
better comprehend the 4D manner in which each species and functional group was
distributed across sites.
Percent cover data for each species at each sites was also used to determine the
distributional patterns of each species across the tops of three replicate reefs and tops plus
south sides of two replicate reefs in each zone. The method by which these analyses were
done is described below.
Standard measures
Percent cover, species richness and functional group richness measures of the coral
assemblage were also collected across sites from video transects. This data was collected
from video transects filmed on the tops of three replicate reefs and on the tops and south
sides of two replicate reefs located in each of the six zones. The information from the
tops and south sides was collected for two reasons: (1) to test the hypotheses of the
modified AST using the kind of information usually collected by coral-reef scientists in
the habitats where research is generally focused (i.e. the tops of reefs and not the sides);
and (2) to accurately determine the manner in which coral parameters vary across the
North Lagoon. The data from the north sides were ignored so as to reduce the complexity
of the analysis by ignoring the effect of aspect.
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Statistical analyses
Codes for species and functional groups
The acronyms used in the graphs to follow for each functional group are:
BV: Branched Viviparous; FP: Foliose and Plating viviparous
MV: Massive Viviparous; MO: Massive Oviparous;
Functional group membership used in the graphs to follow, and the letter designations for
each species are as follows:
Functional Group Species Abbreviation
BV Madracis decactis MDEC
BV Madracis mirabilis MMIR
BV Porites porites PPOR
FP Agaricia fragilis AFRAG
MO Diploria labyrinthiformis DLAB
MO Diploria strigosa DSTRIG
MO Montastraea cavernosa MCAV
MO Montastraea faveolata MFAV
MO Montastraea franksi MFRANK
MO Stephanocoenia intersepta STEPH
MV Favia fragum FAV
MV Porites astreoides PAST
MV Siderastrea radians SRAD
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A Bray-Curtis similarity matrix was generated for all observed coral species, based on
their distributions across all reef sites. The results of the matrix was graphically
displayed, as both a dendrogram and a multidimensional scaling (MDS) diagram (Figs.
2.19-2.23) An analysis of similarity was calculated in order to determine whether
functional groups of species formed significantly distinct clusters.
A two-way analysis of variance was calculated for each of the standard univariate
measures assessed.
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RESULTS
Depths per reef
Figure 4.04 illustrates the number of sites per reef and the depths at which each site
was surveyed on each patch reef. The number of sites per reef was limited by the size of
the flanks (i.e. sides) of each reef, and reefs in different zones had flanks of different
heights. Reefs in Zones 1 and 2 were small and deep and therefore only one depth could
be surveyed per side. Reefs in Zones 3 and 4 were in shallower water, but reached closer
to the surface and as a result two could be surveyed per side. Reefs in the outer two
zones were in deeper water, but reached the shallowest depths as well. As a result, three
depths could be surveyed on the reefs in zone 5 and five depths surveyed down each
flank on reefs in Zone 6. The reefs in most zones were patch reefs with sloping sides.
Reefs in Zones 1 and 2 did not contain deeper central basins of sediment. Reefs in Zones
3 –5 were better developed and did contain a deeper central “mini-lagoon” containing
sediment and limited coral development, These central areas were avoided in the
transects. The reefs in Zone 6 were well-developed pinnacle reefs, with shallow, flat tops
without central mini-lagoons, and had very steep or overhanging sides reaching to 12-m
depth.
The limited height that characterizes the reefs in Zones 1 and 2 may be indicative of a
highly disturbed and stressed environment to corals. These two zones are separated by the
southern shipping channel, in which light levels are reduced and suspended sediment
loads are high due to the passage of container and passenger ships throughout the year.
191
Figure 4.04 should be referred to when examining the graphs to follow, as the manner
in which sites graphically arranged on each reef are the same manner throughout. In each
matching graph, the site located at the top of each reef is within the central white band for
each zone, while south-facing sites are illustrated within the light gray band in each zone,
and the sites with a northern aspect are illustrated within the darker gray band in each
zone.
192
Figure 4.04. Diagram illustrating the average depths of each site on patch reefs located
on different sides (aspects) and at varying distances from shore. Two
replicate reefs were sampled in each zone across all depths and on all sides.
The depths of the reefs in zone 1 completely overlapped. S: Southern
aspect; T: Top of reef; N: Northern aspect. C = Central replicate; E: Eastern
replicate.
193
Similarity in species distributions across sites on each reef
A Bray-Curtis similarity matrix was generated for all observed coral species, based on
their distributions across all reef sites. The results of the matrix was graphically displayed
using both a dendrogram and a multidimensional scaling (MDS) diagram (Figs. 2.05,
2.06). Species that shared phylogeny and functional group membership tended to cluster
together, both when plotted in a dendrogram and in multidimensionally scaled space.
Coral species that fit this pattern included Madracis mirabilis and Madracis decactis;
Diploria strigosa and Diploria labyrinthiformis; and Montastraea franksii and
cavernosa. Species that did not fit the pattern of phylogenetic nor functional-group
clustering are Porites astreoides [MV] grouping with Montastraea faveolata [MO], and
the three species group of Favia fragum [MO], Siderastrea radians [MO] and
Stephanocoenia intercepta [MV]. The two species Agaricia fragilis and Porites porites
did not cluster with any species.
Analysis of similarity (ANOSIM; Table 2.02) determined that the BV and MO
functional groups were not significantly dissimilar in their distribution patterns in
multidimensional space, but only marginally so (p = 0.06). The clusters formed by the
MO and MV functional groups were not significantly dissimilar, at p = 0.1.
194
Figure 4.05. Dendrogram of Bray-Curtis similarities of species and functional groups
clustered according by group-averaging. Similarities per pair of species were
based on square-root transformed relative abundance data averaged across
sites located on replicate reefs and over different aspects, depths and
distances from shore.
195
Figure 4.06. Multidimensional scaling diagram (MDS) of square-root transformed
relative abundance data for coral species averaged across sites located on
replicate reefs and over different aspects, depths and distances from shore.
The symbol used for each species indicates its functional group membership.
196
Table 4.02. Results of an ANOSIM analysis of the distinctness in clustering of each
functional group.
One-Way Analysis
Global Test
Sample statistic (Global R): 0.395
Significance level of sample statistic: 2.5%
Number of permutations: 999 (Random sample from 120120)
Number of permuted statistics greater than or equal to Global R: 24
Pairwise Tests
R Significance Possible Actual Number >=
Groups Statistic Level % Permutations Permutations Observed
MV, PV 0.111 50.0 4 4 2
MV, MO 0.290 10.7 84 84 9
MV, BV -0.222 100.0 10 10 10
PV, MO 1.000 14.3 7 7 1
PV, BV -0.333 100.0 4 4 4
MO, BV 0.420 6.0 84 84 5
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Similarity among sites in species assemblages
The 60 sites surveyed across aspects, depths and zones were grouped according to
how similar they were in terms of shared species, based on the relative abundance data.
Sites were compared in order to see whether sites that shared aspect, depth or zone also
shared species assemblage structure. The resultant matrix of Bray-Curtis site similarities,
based on square-root-transformed relative abundance data for species, was graphed into
both a dendrogram (not shown due to its complexity) and MDS. Linear boundaries of
equal similarity were produced, enclosing similar sites within the two-dimensional
graphic of multidimensional species state-space. Only the 58% iso-similarity boundary is
illustrated, for clarity and because the site clusters generated by this one iso-similarity
boundary were the most meaningful, as determined below.
In order to determine whether there were meaningful patterns in the manner that the
species relative abundance data clustered sites, three separate one-way and two-way
analyses of similarity (ANOSIM) of sites were carried out. Sites were compared
according to:
1. Aspect within depth and zone
2. Depth
3. Zone
Sites were also graphed onto the three separate MDS diagrams using symbols that
represented either aspect, depth or zone of each site. These three graphs are illustrated
below.
198
1) Aspect
Figure 4.07 illustrates the MDS of sites illustrated with icons that indicate Aspect. All
of the sites located on the Tops of patch reefs (grey squares) are grouped in the upper
cluster (A), along with sites with other aspects (the two triangle icons). Conversely, only
sites that had either a Northern or Southern aspect are within the lower two clusters (B
and C). There are no apparent clusters of northern vs. southern-facing sites. A series of
Analyses of Similarity (ANOSIMs) of the factor Aspect across each depth within each
zone confirmed this visual interpretation of the data. The tops of patch reefs possessed
significantly different assemblages of coral species than either side of the same reef. The
north and south sides of each patch reef, however, were only found to differ significantly
in assemblage structure in Zone 1 and Zone 3 (Table 4.03 this table does not show the
differences existed between sides in Zone 1 and 3 Table 4.04 shows that Zones 1 2 and
3D had differences between the sides I think the lack of a consistent pattern of
differences will allow you to pool the north and south data
The finding that coral assemblages were not dissimilar on opposite sides of patch
reefs across most zones was unexpected. An analysis comparing the amount of light
reaching surfaces with a southern or northern aspect found that significantly more light
should be available to corals on the southern side of a patch reef in Bermuda than on the
northern side of the same reef. It may be that the availability of diffuse light is sufficient
to prevent the occurrence of differences between the two sides of patch reefs in most
zones. On the other hand, it may be that the lagoonal corals are obtaining the majority of
their energy via heterotrophy instead of autotrophy, and thus the coral assemblages on
each site are not structured by light availability or the zoox are sufficiently adapted (more
199
pigments per cell) or more abundant (cells per mL or cm2 of coral tissue) that the coral is
not penalized for the reduced light levels. Just have to be above saturating light levels,
which may be only about 1/3- ½ incoming radiance for some zoox. Get some refs on this.
As a third alternative, perhaps the metric of relative abundance that was used resulted in
data that were not powerful enough (you needed more transects per “site”). for the
detection of differences in the assemblage structure between the north and southern
flanks of reefs. However, since tops of reefs in each zone were consistently found to
differ significantly from that of both flanks but you had 8 transects compared to 4 on
either flank, it seems likely that the relative abundance data should provide sufficient
power for the complete analysis.
200
Figure 4.07. MDS of square-root transformed relative abundance data of species for all
sites. Sites are represented by one of three icons depending upon the aspect
which characterized that site. S: Southern aspect; T: Top of reef (i.e. vertical
aspect); N: Northern aspect.
201
Table 4.03. ANOSIM table for the factor Aspect across all sites, including the results of
pairwise post-hoc tests.
Global Test for Aspect
Sample statistic (Global R): 0.098
Significance level of sample statistic: 0.1%
Number of permutations: 999 (Random sample from a large number)
Number of permuted statistics greater than or equal to Global R: 0
Pairwise Tests
R Significance Possible Actual Number >=
Groups Statistic Level % Permutations Permutations Observed
S, T 0.181 0.1 Very large 999 0
S, N -0.001 43.6 Very large 999 435
T, N 0.198 0.1 Very large 999 0
202
Table 4.04. Significance levels of separate ANOSIM tests comparing similarities between
reef sites located on the south versus north sides of reefs in each zone and at
different depths. Sites on the sides of reefs are labeled as follows: S: Shallow;
M: Mid-depth; D: Deep.
Zone and
Depth p
1 0.009
2 0.046
3S 0.591
3D 0.008
4S 0.103
4D 0.349
5S 0.263
5D 0.288
6S 0.119
6M 0.417
6D 0.834
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2) Depth
Figure 4.08 shows the MDS of sites illustrated with icons that indicate Depth. An
obvious pattern can be seen in which sites are sorted by depth in the MDS diagram,
(which is derived solely from species abundance data). ANOSIM revealed that globally
sites clustered to a significant manner when categorized according to the factor Depth
Pairwise comparisons indicate that sites categorized by virtually all depths were
significantly clustered (Table 4.06). Only the species assemblages at depths 2 to 4 m, and
5 to 7m depths were not grouped significantly (Table 4.05). Light and wave energy both
decline with water depth, and these two physical factors are probably responsible for the
strong zonation patterns across depths in the coral species.
204
Figure 4.08. MDS of square-root transformed relative abundance data of species for all
sites depths on all reefs. Sites are represented by one of ten icons that
indicate the average depth in meters of that site. Darker icons represent
deeper sites. The number in the legend next to each icon is the average depth
in meters of that site.
205
Table 4.05. ANOSIM table for the factor Depth, calculated from data at each depth from
across all sites.
Global Test for Depth
Sample statistic (Global R): 0.382
Significance level of sample statistic: 0.1%
Number of permutations: 999 (Random sample from a large number)
Number of permuted statistics greater than or equal to Global R: 0
Table 4.06. Significance levels of pair-wise tests comparing similarities between reef
sites located on different depths.
Pairwise tests: Significance Level
2 3 4 5 6 7 8 9 12
2
3 0.002
4 0.321 0.627
5 0.001 0.001 0.001
6 0.001 0.001 0.001 0.065
7 0.001 0.001 0.001 0.171 0.003
8 0.001 0.001 0.001 0.001 0.001 0.036
206
9 0.002 0.001 0.78 0.001 0.001 0.001 0.001
12 0.001 0.002 0.001 0.001 0.001 0.001 0.001 0.096
207
3) Zone
There is also an obvious pattern in which sites are sorted consecutively by zone across
the field of points in the MDS diagram (Figure 4.09), which is derived solely from
species abundance data. Sites from Zones 1 and 2 are chiefly located in the lower right
cluster, sites from Zone 3 and 4 are predominantly located in the upper cluster, and sites
from Zones 5 and 6 are located in either the upper or lower left cluster. An ANOSIM of
Zone (Table 4.07), regardless of aspect or depth of each site, determined that all zones
were significantly different in terms of coral assemblage composition, except pairwise
comparisons between Zones 1 and 2, and Zones 1 and 3. Zones 2 and 3 were significantly
different, however.
Table 4.08 displays the results of a SIMPER similarity analysis for each zone.
SIMPER analysis examines the contribution of each species to the average resemblances
between zones (Clarke et al. 2006). Generally it can be seen that the two Madracis
species (which are in the Branched Viviparous functional group) dominate inshore zones,
whereas the Massive Viviparous species Porites astreoides and the Massive Oviparous
species Montastraea faveolata, Diploria strigosa and Diploria labyrinthiformis dominate
offshore zones. One adaptive mechanism by which these five massive corals can coexist
is examined in Section B, below.
208
Figure 4.09. MDS of square-root transformed relative abundance data of species for all
sites. Sites are represented by one of six icons depending upon the zone that
site was located within. Darker icons represent sites further from shore. The
number in the legend next to each icon represents the zone the site was in,
with Zone 1 being closest to shore and Zone 6 furthest from shore.
209
Table 4.07. ANOSIM table for the factor Zone across all sites.
Global Test
Sample statistic (Global R): 0.622
Significance level of sample statistic: 0.1%
Number of permutations: 999 (Random sample from a large number)
Number of permuted statistics greater than or equal to Global R: 0
Pairwise Tests
R Significance Possible Actual Number >=
Groups Statistic Level % Permutations Permutations Observed
1, 2 1.000 10.0 10 10 1
1, 3 1.000 6.7 15 15 1
1, 4 0.818 4.8 21 21 1
1, 5 0.929 2.8 36 36 1
1, 6 0.833 3.6 28 28 1
2, 3 0.722 2.9 35 35 1
2, 4 0.549 1.8 56 56 1
2, 5 0.895 0.8 120 120 1
2, 6 0.821 1.2 84 84 1
3, 4 0.35 4.8 126 126 6
3, 5 0.763 0.3 330 330 1
210
3, 6 0.792 0.5 210 210 1
4, 5 0.589 0.1 792 792 1
4, 6 0.617 0.2 462 462 1
5, 6 0.522 0.1 1716 999 0
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Table 4.08. SIMPER analysis of the dominant species that differ between zones across
the Bermuda Platform.
Zone 1Average similarity: 71.57
Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MDEC 2.65 25.70 3.73 35.91 35.91MMIR 2.13 17.96 3.49 25.10 61.01SRAD 0.99 8.73 10.06 12.19 73.20FAV 1.12 7.07 2.59 9.88 83.08MFAV 0.78 4.61 1.02 6.43 89.52MCAV 0.66 2.13 0.80 2.98 92.49
Zone 2Average similarity: 68.78Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 3.38 20.96 2.13 30.48 30.48MDEC 2.47 17.48 2.93 25.41 55.89PAST 1.82 10.65 3.72 15.49 71.37MFAV 1.48 8.03 2.47 11.68 83.05DSTRIG 0.77 4.01 1.48 5.83 88.88MCAV 0.75 2.48 0.76 3.60 92.49
Zone 3Average similarity: 84.82Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 3.79 24.55 10.50 28.94 28.94MDEC 2.79 17.20 3.31 20.28 49.22PAST 2.91 16.80 3.30 19.80 69.02MFAV 2.30 9.98 2.72 11.76 80.78MCAV 1.27 5.74 158.50 6.77 87.55AFRAG 0.67 4.74 1.80 5.59 93.14
Zone 4Average similarity: 81.88Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 2.94 17.31 5.97 21.14 21.14PAST 2.78 14.40 3.28 17.59 38.73MDEC 2.47 12.86 2.11 15.70 54.43MFAV 2.49 12.11 3.29 14.79 69.22DSTRIG 1.65 7.92 2.75 9.68 78.90MCAV 1.23 6.43 3.17 7.85 86.75MFRANK 1.12 4.18 1.39 5.10 91.85
212
Table 4.08 continued.
Zone 5Average similarity: 74.30Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%PAST 2.17 13.18 1.50 17.74 17.74MFAV 2.05 13.01 7.51 17.51 35.25MDEC 2.25 12.37 1.55 16.65 51.90MCAV 1.58 6.89 1.86 9.27 61.18MFRANK 1.37 6.68 1.71 8.99 70.16DSTRIG 1.13 6.42 1.23 8.64 78.81DLAB 0.98 5.91 1.58 7.96 86.77MMIR 0.86 4.16 1.17 5.60 92.37
Zone 6Average similarity: 73.62Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%PAST 2.01 14.07 3.17 19.11 19.11MDEC 1.31 11.11 6.28 15.09 34.20MCAV 1.28 10.00 1.99 13.58 47.78MFAV 1.58 9.43 2.27 12.81 60.59MFRANK 1.37 7.82 1.17 10.63 71.22DLAB 1.06 6.16 1.55 8.37 79.59DSTRIG 0.95 5.46 1.16 7.41 87.00STEPH 0.65 4.41 1.04 5.99 92.99
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Aspect, Zone and Depth
The aspect, depth and zone of a site interact to generate the cluster pattern Figs 4.07 –
4.09). The tops of sites from all zones are in the upper cluster (Figure 4.10). The sites
located on the sides of reefs in Zones 1 through 4 are located in the lower right cluster
(Figure 4.10), and sites located on the deeper sides of reefs in Zones 5 and 6 are located
in the lower left cluster (Figure 4.10). Light and wave energy is higher on the tops of the
lagoonal reefs, while deeper sites are darker and have slower current flow. Reefs
nearshore have higher sediment than reefs offshore. Thus B sites are darker but with
higher suspended sediment than A, and C sites are darker, deeper and with less suspended
sediment than both A and B.
214
Figure 4.10. The sites surveyed across the Bermuda platform cluster into three groups
with different coral species composition, which also match three different
environmental conditions. The three groups are (A) Tops of all reefs, (B)
deeper sites in zones 1-4 and (C) deeper sites in zones 5-6.
215
Distribution patterns of coral species
Frequency of occurrence
All corals as a group
The average frequency of occurrence (RF) of any coral at each site is plotted as dot
size onto the same MDS graph used above (Figure 4.11) The same data was also plotted
using the standard format for a line graph (Figure 4.12A) and also as a “bubble” graph
(Figure 4.12B). These three graphs allow one to examine how corals overall were
distributed across the patch reefs located over the lagoon. All three graphs illustrate that
corals occurred frequently on many shallow sites across most zones. The smaller sized
circles in the lower left cluster indicate that corals occurred less frequently at sites that
were located on the sides of patch reefs far from shore.
216
Figure 4.11. MDS of square-root transformed frequency of occurrence data of all coral
species for all sites, as in the three figures above. In this and all following
MDS diagrams throughout this section, the size of each circle represents the
number of frames containing any coral, averaged across transects per site,
according to the scale in the legend.
217
A,
B.
218
Figure 4.12. The average proportion of frames with any coral present across all sites,
illustrated as a line graph per site per reef (A) and as a bubble graph per
depth and zone (B).
Branched Viviparous Corals
The frequency of occurrence of all branching viviparous corals as a group, and of
each species of BV coral separately, are plotted in Figs 4.13 to 4.17 below. As a group,
the BV corals occur most frequently on the sides of the reefs in zones 1 and 2, and occur
less often on reefs further from shore. The two species of Madracis each separately share
this basic distribution pattern, with a much greater likelihood of occurring in frames
sampled on the sides of patch reefs rather than on the tops, and greater numbers of
occurrences observed nearshore compared with offshore (Figs 4.13 B, 4.13C, 4.15, 4.16).
In comparison, the species Porites porites differs from the Madracis species in its
distribution, and was only observed to occur on the tops of reefs and never on the sides.
Porites porites was also much rarer than the Madracis species across all reef sites overall
(Figs. 4.13D, 4.17).
219
Figure 4.13. Four MDS graphs of square-root transformed frequency of occurrence data
of Branched Viviparous species as a group, and for M. decactis, M. mirabilis
and P. porites corals separately for all sites.
220
Branched Viviparous Functional Group
A.
B.
221
Figure 4.14. The average proportion of frames with corals of the Viviparous Branching
(VB) functional group present across all sites, illustrated as a line graph per
site per reef (top) and as a bubble graph per depth and zone (bottom).
Madracis decactis
A.
B.
222
Figure 4.15. The average proportion of frames with corals of the species Madracis
decactis present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Madracis mirabilis
A.
223
B.
Figure 4.16. The average proportion of frames with corals of the species Madracis
mirabilis present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Porites porites
A.
224
B.
Figure 4.17. The average proportion of frames with corals of the species Porites porites
present across all sites, illustrated as a line graph per site per reef (top) and as
a bubble graph per depth and zone (bottom).
225
Foliose and Plating Viviparous Corals
The only coral in the foliose and plating (FP) functional group that was observed
within the lagoon was the species Agaricia fragilis. The distribution of A. fragilis was
found to have little similarity to the distribution of the other corals assessed using Bray-
Curtis similarity analysis (Figs 4.18, 4.19). A. fragilis was observed primarily on the
deeper flanks of patch reefs in Zones 1–3. Its predominance in low light environments
fits the prediction for A. fragilis as a stress-tolerant species adapted to areas of low
current flow, low light availability and also low total coral cover.
226
Figure 4.18. MDS graph of square-root transformed frequency of occurrence data of the
coral species Agaricia fragilis, the only member of the Foliose and Plating
Viviparous (FP) functional group observed in the North lagoon in Bermuda
in this study. Circles size represents the average number of frames
containing A. fragilis per site out of 20, as in the legend on the side of each
MDS graph. Note the different scale used in this MDS for A. fragilis
compared with the other MDS diagrams in this section.
227
Agaricia fragilis
A.
B.
228
Figure 4.19. The average occurrence frequency of the species Agaricia fragilis across all
sites, illustrated as a line graph per site and reef (top) and as a bubble graph
per depth and zone (bottom).
Massive Viviparous corals
When the frequency of occurrence of all species of the Massive Viviparous functional
group, and each member species, Favia fragum, Porites astreoides and Siderastrea
radians, are plotted at each site across the MDS diagram (Figure 4.20) we can see that the
distribution pattern of the MV group (Figure 4.20) is primarily driven by the distribution
of P. astreoides (Figure 4.20C; 4.22). P. astreoides is most abundant in the upper cluster,
which represents the tops and shallow sides of reefs. Sites in the lower two clusters,
which are derived from reef sites located on the deeper sides of patch reefs, are
characterized by much less P. astreoides.
Favia fragum is less abundant and is also primarily found on the tops of reefs (Figs.
4.20B; 4.22). Alternatively, S. radians appears equally distributed across reef sites across
the three clusters (Figure 4.20D; 4.24), with no obvious pattern related to depth, zonation
or aspect.
229
Figure 4.20. Four MDS graphs of square-root transformed data of occurrence frequency
by Massive Viviparous species as a group, and for F. fragum, P. astreoides
and S. radians corals separately, for all sites. Circle size represents the
average number of frames containing each species or functional group per
transect per site out of 20, as in the legend on the side of each MDS graph.
230
Massive Viviparous functional group
A.
B.
Figure 4.21. The average proportion of occupied frames per transect with corals
belonging to the Massive Viviparous functional group present across all
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sites, illustrated as a line graph per site per reef (top) and as a bubble graph
per depth and zone (bottom).
Favia fragum
A.
B.
232
Figure 4.22. The average proportion of frames with corals of the species Favia fragum
present across all sites, illustrated as a line graph per site per reef (top) and as
a bubble graph per depth and zone (bottom).
233
Porites astreoides
A.
B.
234
Figure 4.23. The average proportion of frames with corals of the species Favia fragum
present across all sites, illustrated as a line graph per site per reef (top) and
as a bubble graph per depth and zone (bottom).
Siderastrea radians
A.
B.
235
Figure 4.24. The average proportion of frames with corals of the species Siderasterea
radians present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Massive Oviparous corals
As a group, massive oviparous corals were most abundant on the tops of reefs (upper
cluster) and on the sides of the reefs in Zones 5 and 6 (left cluster; Figs. 4.25A, 4.26).
Only the species M. faveolata (Figs. 4.25C, 4.27) displayed a similar distribution pattern
to the pattern displayed by the functional group overall, however. The two species M.
cavernosa and M. franksi, which were found to be similar at a 75% level using Bray-
Curtis analysis, did display obvious differences in distribution when graphed. M.
cavernosa was most abundant on the sides of nearshore reefs (right cluster) and on the
tops of reefs (top cluster; Figs. 4.25B, 4.26), while M. franksi was most abundant on the
sides of the offshore reefs (Cluster C; Figs 4.25D, 4.28).
The two Diploria species exhibit similar patterns of abundance (Figs 4.25E, 4.25F,
4.29, 4.30), with most corals occurring on the tops of reefs in the upper cluster, and few
species on the flanks in the other two habitat clusters. Some differences in distribution
between the two Diploria species are apparent, however. D. labyrinthiformis is less
abundant than D. strigosa overall, and appeared to be more common on the sides of reefs
offshore (left cluster) relative to D. strigosa.
Stephanocoenia intersepta displayed the most distinct pattern of abundance relative to
the other MO corals (Figs. 4.25G; 4.31). Its highest abundance was not on the tops of
reefs in Zones 3 and 4 like most MO coral species, but instead on the sides of reefs in
zones 5 and 6.
236
Figure 4.25 . Seven MDS graphs of square-root transformed relative abundance data of
(a) Massive Oviparous species as a group, and for (b) M. cavernosa, (c) M.
faveolata, (d) M. frankesi, (e) D. labyrinthiformis, (f) D. stigosa and (g) S.
intersepta separately for all sites.
237
Massive Oviparous functional group
A.
B.
238
Figure 4.26. The average proportion of frames with corals of the Massive Oviparous
(MO) functional group present across all sites, illustrated as a line graph per
site per reef (top) and as a bubble graph per depth and zone (bottom).
239
Montastraea cavernosa
A.
B.
240
Figure 4.27. The average proportion of frames with corals of the species Montastraea
cavernosa present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Montastraea faveolata
A.
B.
241
Figure 4.28. The average proportion of frames with corals of the species Montastraea
faveolata present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Montastraea franksi
A.
242
B.
Figure 4.29. The average proportion of frames with corals of the species Montastraea
franksi present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Diploria labyrinthiformis
A.
243
B.
Figure 4.30. The average proportion of frames with corals of the species Diploria
labyrithiformis present across all sites, illustrated as a line graph per site per
reef (top) and as a bubble graph per depth and zone (bottom).
Diploria strigosa
244
A.
B.
Figure 4.31. The average proportion of frames with corals of the species Diploria
strigosa present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
245
Stephanocoenia intersepta
A.
B.
246
Figure 4.32. The average proportion of frames with corals of the species Stephanocoenia
intersepta present across all sites, illustrated as a line graph per site per reef
(top) and as a bubble graph per depth and zone (bottom).
Standard measures for coral reefs
In the section below I examine how average percent cover of the entire coral
assemblage, and each functional group separately, as well as species richness and
functional group richness vary over the six zones. Due to time constraints only the tops of
three replicate reefs in each zone were surveyed. The data from these three surveys are
presented first. On two of the three replicate reefs, both the tops and south sides were
surveyed for the six factors. The data that includes the change in coral assemblages
across the sides of patch reefs are described in the section following the one below.
Section 1: Tops of Reefs Only
A. Average Percent Coral Cover
The average percent coral cover for all corals as a group (which I term “Total Coral
Cover” or TCC below) peaked in the middle of the north lagoon in Zone 3 (Figure
4.33A). TCC appeared substantially lower in Zone 1, nearshore. TTC also declined
progressively with distance from shore across Zones 4 to 6. Additionally there appeared
to be substantial variability in TCC among reefs within each region. Two-way ANOVA
confirmed that the interaction between zone placement and replicate reefs was highly
significant, at p < 0.001 (Table 4.09A). Since wave energy has been shown to be higher
offshore (Mills et al. 2004), and suspended sediment load higher nearshore (Toro Farmer,
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unpublished data) it may be that the central reefs have higher TCC because the corals
there are exposed to less levels of disturbance or stress than corals on reefs either
offshore or nearshore.
B. Species Richness
The number of coral species on the top of reefs peaked in Zone 2 (Figure 4.33B). The
variability in species richness between sites was highest in Zone 1 and declined on sites
further from shore. Two-way ANOVA confirmed that the interaction of zone placement
and replicate was highly significant, at p = 0.006 (Table 4.09B). This pattern, in which
nearshore sites display higher variability than offshore sites, was hypothesized by
Murdoch and Aronson (1999), and reiterated by Pandolfi (2002). Zone 2 represents an
area in close proximity to the south shipping channel, as well as near the island of
Bermuda. It may be that disturbances are more frequent in this area and that the
mechanisms of the Intermediate Disturbance Hypothesis (Grime 1977; Connell 1978) are
operating to promote coral richness there.
C. Functional Group Richness
Functional group richness (Figure 4.33C)for the three predominant functional groups
was lowest offshore, reached a plateau across sites 2–4, and then declined again in Zone
1. Two-way ANOVA confirmed that the interaction of zone placement and replicate was
highly significant, at p = 0.005 (Table 4.09C).The analysis of each species in the section
above and for percent cover of each functional group illustrates that the decline in FG
richness offshore is due to a decline in the abundance and biomass of the Branched
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Viviparous functional group. The decline in Zone 1, alternatively, is due to a decline in
the abundance and biomass of the two mound-shaped or massive functional groups.
D. Percent cover of the Branched Viviparous Functional Group
Branched viviparous corals are predicted to be both competitive and ruderal (C-R),
following the AST model of Grime (1977). As such they should be capable of tolerating
disturbance to at least a moderate degree, and also capable of dominating habitats when
released from competition (See Ch. 1). Branched viviparous corals peaked in abundance
on some of the reefs in Zone 2 in this analysis (Figure 4.33D). Sites in all other zones
exhibited substantially lower cover of the BV functional group, with virtually zero cover
in Zones 5 and 6. Two-way ANOVA (Table 4.09D) confirmed that the interaction of
zone placement and replicate was highly significant, at p < 0.001. Zone 2 is nearest the
southern shipping channel, which is a source of suspended sediment during summer
months. Others have noted that the branched corals dominate nearshore habitats off North
Shore (i.e. Logan 1988; Mills et al. 2004). It may be that the BV functional group is more
tolerant of suspended sediment than the massive corals in the other functional groups, and
that this tolerance, combined with a lack of competition with the other groups allows the
branched viviparous corals to dominate reefs in Zone 2.
E. Percent cover of the Massive Viviparous functional group
The massive viviparous corals are predicted to be the most tolerant of disturbance. As
such the cover of the MV group was expected to show little variation across sites
regardless of zone. As illustrated in Figure 4.33E, however, the average percent cover of
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this functional group peaked in Zone 4, with lower cover values in zones nearer or further
from shore. Two-way ANOVA confirmed that the interaction of zone placement and
replicate was highly significant, at p < 0.001 for the MV functional group (Table 4.09E).
F. Percent cover of the Massive Oviparous functional group
The massive oviparous corals are predicted to be relatively tolerant to stress but also
to be able to dominate reefs through competitive interactions when resources are
abundant and disturbance levels are low. The MO functional group is predicted to display
low cover on reefs exposed to higher disturbance. In the analysis of percent cover on the
three reefs across the six zones across the North Lagoon of Bermuda, the MO functional
group displayed similarly high values across reefs in zones 3 through 6, with a decline in
cover on reefs in Zones 2 and 1 (Figure 4.33F). Variability between reefs within zones
was minimal in Zone 4, with more variability evident in zones closer or further from
shore. Two-way ANOVA (Table 4.09F) confirmed that the interaction of zone placement
and replicate was highly significant, at p < 0.001.
It may be that the higher levels of turbidity and lower current flow speeds nearshore
caused a decline in survivorship for the large mound-shaped corals in the MO functional
group. Reefs offshore, however, are exposed to much lower levels of sediment, but
higher wave energy. The MO corals should be able to withstand wave energy due to their
morphology, so it is unclear why the percent cover of the MV functional group would not
be highest on reefs furthest from shore
250
Figure 4.33. (next page). Average percent coral cover for (A), (B) species richness, (C)
functional group richness as well as (D – F) the average percent cover for
each functional group on the tops of each of three replicate reef sites in each
of the six zones. The data for each site was based on eight transects of 10-m
length. The tops of the reefs of each zone differed in depth, and light
availability at a given depth was reduced nearshore relative to offshore, as
described above.
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A. Total Coral Cover
B. Species Richness
C. Functional Group Richness
D. Branched Viviparous Coral Cover
E. Massive Viviparous Coral Cover
F. Massive Oviparous Coral Cover
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Table 4.09. Results of the 2-way ANOVAs of the six parameters across the 18 reef sites
located on the tops of patch reefs located in three replicate “legs” across six
zones located across the north lagoon in Bermuda.
A. Total Coral CoverSource SS df MS F-ratio p-value ZONE 1.760 5 0.352 50.501 0.000LEG 0.023 2 0.012 1.670 0.192ZONE*LEG 0.612 10 0.061 8.779 0.000Error 0.878 126 0.007
B. Species RichnessSource SS df MS F-ratio p-value ZONE 109.285 5 21.857 15.839 0.000LEG 29.056 2 14.528 10.528 0.000ZONE*LEG 36.111 10 3.611 2.617 0.006Error 173.875 126 1.380
C. FG richnessSource SS df MS F-ratio p-value ZONE 19.951 5 3.990 18.535 0.000 LEG 0.722 2 0.361 1.677 0.191ZONE*LEG 5.861 10 0.586 2.723 0.005Error 27.125 126 0.215
D. Branched Viviparous Coral CoverSource SS df MS F-ratio p-value ZONE 1.518 5 0.304 59.148 0.000LEG 0.065 2 0.032 6.320 0.002ZONE*LEG 0.640 10 0.064 12.466 0.000Error 0.647 126 0.005
E. Massive Viviparous CoverSource SS df MS F-ratio p-value ZONE 0.788 5 0.158 58.255 0.000LEG 0.003 2 0.001 0.553 0.576ZONE*LEG 0.240 10 0.024 8.860 0.000Error 0.341 126 0.003
F. Massive Oviparous CoverSource SS df MS F-ratio p-value ZONE 1.249 5 0.250 29.632 0.000LEG 0.197 2 0.098 11.663 0.000ZONE*LEG 0.544 10 0.054 6.451 0.000Error 1.062 126 0.008
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Standard measures for coral reefs
Section 2: Tops and South Sides of Reefs
A. Average Percent Coral Cover
As in the section above, the average percent cover of the entire coral assemblage (i.e.
TCC; Figure 4.34A) can be seen to vary substantially both across zones and across
replicates within zones. Depth also clearly plays a factor in the total coral cover at a site,
and appears to interact in a complex manner with distance from shore. Coral reefs
nearshore in Zones 1 to 3 display higher cover on the sides of reefs than on the tops of
reefs, while reefs in the zones further from shore display higher cover on the tops of reefs
than on the sides. TCC is highest on the flank of one of the 2 reefs samples in Zone 2.
TCC was found to be lowest on the top of reefs in Zone 1, and at the deepest sites on the
reefs in Zone 6.
Historically researchers in Bermuda have only surveyed the tops of patch reefs found
in the lagoon. As can be seen by comparing Figs. 4.34 and 4.35 to Figure 4.33 from the
last section, surveying only the tops of reefs fails to account for a substantial proportion
of the average percent cover that occurs on these lagoonal reefs. Instead, to truly
represent the condition of Bermuda’s lagoonal reefs, surveys should encompass the full
range of depths that occur across each reef, and over the entire extent of the lagoon.
B. Species Richness
On the reefs surveyed in this project, species richness (Figure 4.34B) can be seen to
vary with depth as well as zone and across replicates within zones in a complicated
manner. Species richness appeared to peak in Zone 3, was found to be lowest on the
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deepest sites in Zone 6. Surveys that only encompass the tops of reefs, as in Section 2
above, fail to uncover these complexities in species richness that occur across the flanks
of lagoonal reefs in Bermuda.
C. Functional Group Richness
The number of functional groups within a site also appears (Figure 4.34C) to be due
to factors that interact across zones, replicates and depths. Functional group richness
appears higher on deeper sites on reefs nearshore than on the tops of reefs. Alternatively,
functional group richness is lower on the tops of reefs offshore than it is on the sides of
the same reefs. Functional group richness peaks in Zones 3 and 4, and is lowest on the
deepest sites in Zone 6. Again, ecologically important patterns in functional group
richness are apparent on the sides of these lagoonal patch reefs that standard survey
techniques would have missed.
D. Percent cover of the Branched Viviparous functional group
The percent cover of the coral species belonging to the Branched Viviparous
functional group was found to peak in Zone 2 (Figure 4.35A). Moreover, percent cover of
this group was consistently higher on the deeper sites than on the tops of reefs in Zone 1
through to Zone 4. The BV functional group displayed low percent cover in Zones 5 and
6 across all depths. Since the BV corals were consistently higher on the sides of patch
reefs than on the tops, it is apparent that standard surveys which only consider the tops of
patch reefs will misrepresent the contribution of the BV coral species to the assemblage
structure of lagoonal corals.
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When the percent cover of each of the member species of the BV functional group are
presented separately (Figure 4.36), it is apparent that the species Madracis mirabilis
contributed the greatest percentage of biomass and thus was responsible for the general
pattern in percent cover that characterized the functional group as a whole. Madracis
mirabilis peaked in Zones 2 with a decline in cover both closer and further from shore. It
also displayed higher cover on the flanks of patch reefs versus on the tops. The sibling
species to Madracis mirabilis, Madracis decactis, displayed a similar distribution and
pattern of biomass, but with lower values overall (Figure 4.36B). Conversely the third
BV coral, Porites porites (Figure 4.36C), displayed a completely different pattern in
terms of percent coral cover. It was found to exhibit the highest percent cover values on
the tops of reefs instead of the flanks like the other BV species. P. porites also displayed
very low values in percent cover, generally being represented by only one point per site.
The species-specific patterns apparent in the percent cover data of these BV coral species
match the patterns displayed by the same species in the MDS analysis described above,
which were based on measures of relative abundance data instead.
E. Percent cover of the Massive Viviparous functional group
The coral species of the Massive Viviparous functional group consistently peaked in
cover on the tops of reefs and was lower on the flanks of the same reefs, regardless of
zone (Figure 4.35). The percent cover of the MV functional group peaked in Zone 3, and
was found to be lower on reefs closer to shore and further from shore. Surveying the tops
of reefs for this functional group would provide meaningful estimates of its functional
role across the lagoon.
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Comparison of the component species of the MV functional group (Figure 4.38)
illustrates that the species P. astreoides is responsible for the general pattern in percent
cover across the lagoon that characterizes the group. P. astreoides peaks in abundance in
Zones 3 and 4, and exhibits higher percent cover on the tops of reefs versus on the deeper
flanks. Favia fragum and Siderastrea radians, alternatively, present very low percent
cover values of 1 or 2 points per site, and appear to occur across depths and zones. These
patterns concur with the patterns apparent in the MDS analysis based on relative
abundance data described in Section 1 above.
F. Percent cover of the Massive Viviparous functional group
The corals that comprise the Massive Viviparous functional group were found to peak
in percent cover on the tops of reefs in Zones 3 to 6, with lower values apparent in Zones
1 and 2, nearer to shore (Figure 4.35). The cover of the MV functional group generally
declined with depth across all zones, but with an alternate pattern occurring on one of the
two replicate reefs in some zones.
The two Diploria species peaked in percent cover on the tops of patch reefs and
displayed lower cover on the sides, across all zones (Figure 4.38). The species Diploria
strigosa exhibited higher cover than D. labyrinthiformis, although both species peaked at
roughly 5% cover on the lagoonal reefs. These co-occurrence patterns of these two
species were found to be very similar, based on relative abundance data (section 1
above), and the percent cover data appears to confirm that these two sister species also
share habitats when biomass is used as a measure.
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The percent cover data for the two species Montastraea frankesi and M. faveolata was
grouped into one variable after it was decided that the discrimination between the two
species in the point count analysis may have been compromised. The M. annularis spp.
category displayed the highest percent cover across reefs, with high variability in cover
apparent across depths, replicate reefs and zones. The congener M. cavernosa was found
to contribute lower percent cover across the region overall. It peaked in cover on the sides
of patch reefs in the middle of the lagoon, with lower values on reefs in Zones 1, 2 and 6.
The species Stephanocoenia intersepta was rarely sampled by point count analysis.
The species was absent from the two sampled reefs in Zone 4, and it peaked in cover in
Zones 1 and 6. It also tended to display higher percent cover on deeper sites on a reef
than on the tops of reefs. The pattern of cover presented by the species Stephanocoenia
intercepta appears substantially different to that of the other species of the MO functional
group. The patterns generated by the percent cover data for all species in the MO
functional group matches the patterns determined by relative abundance data as described
in Section 1 above.
G. Percent cover of the Foliose and Plating Viviparous functional group
The one species of the FP functional group that was sampled across the lagoon was
the plating species Agaricia fragilis (Figure 4.35). It was only represented in the percent
cover data by a few points or less per site, and always on the deeper sites on inshore reefs
located in Zones 1 to 3. Observations while diving found that, while not represented by
point count data, the species A. fragilis was only observed on the tops of patch reefs in
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Zones 1 and 2, and elsewhere generally within caves and in the shadows of overhanging
ledges.
Figure 4.34. (Below) Percent cover, species richness and functional group richness of
corals surveyed on sites located on the tops and southern flanks of patch
reefs. Two replicate reefs were sampled across six zones. T: Tops; S: Sides.
Numbers represent depths in feet [and will be converted to meters and make
larger!].
Figure 4.35. (Below) Percent cover of the Branched Viviparous, Massive Viviparous and
Massive Oviparous functional groups of corals surveyed on sites located on
the tops and southern flanks of patch reefs. Two replicate reefs were
sampled across six zones. T: Tops; S: Sides. Numbers represent depths in
feet [and will be converted to meters].
260
261
262
Figure 4.36. Percent cover of the three species of Branched Viviparous functional group.
263
Figure 4.37. Percent cover of Agaricia fragilis, the one species of the Foliose and Plating
functional group found within the lagoonal sites surveyed.
264
Figure 4.38. Percent cover of the three species of Massive Viviparous functional group.
265
Figure 4.39 A-B Percent cover of the two of the five species of Massive Oviparous
functional group.
266
Figure 4.39 C-E. Percent cover of the three other species of Massive Oviparous
functional group.
267
DISCUSSION
Species and functional group distributions across sites
In the investigation regarding whether species that were members of the same
functional groups shared distribution patterns in terms of occurrence, the MDS of coral
species based on relative abundances across sites fit a pattern indicating nested functional
groups across habitat types, (Figure 1.07). This mixed pattern was generated because
some, but not all, species within each functional groups shared similar distribution
patterns across sites. In each functional groups there was a group of species that shared
habitats, with a small number of species displaying low coverage, relative abundance and
no clear preference or occurrence within particular habitats. For instance, the BV coral
Porites porites differed from the other species of Branched Viviparous corals in both
habitat and biomass. In a similar manner, the MO corals Favia fragum and Siderastrea
radians were most similar to the MV coral Stephanocoenia intersepta, in that all three
species were relatively rare, exhibited low coverage , and did not show a clear preference
for either the tops of reefs nor the deeper sites. Nor did these three species show a
preference for reefs inshore nor offshore.
Of the species within functional groups that did share distribution patterns, and thus
high levels of Bray-Curtis similarity, most pairs were composed of congeneric species.
This pattern in which species that share phylogenetic heritage also share habitats implies
that the environmental tolerances of the sibling species act to control their distribution to
a greater degree than intergeneric competition. One mechanism by which sister species
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could co-occur within habitats include a priority effect in which each species has an equal
likelihood of occurring within a small patch and each can prevent its congener from
removing it (Brown et al. 2002) . Alternatively it may be that, since coral cover on many
of the sites surveyed is less than 50%, competitive interactions are rare and the effects of
competition weak across the lagoon and that environmental conditions limit the longevity
of all colonies. If so then continual recruitment by all species would allow persistence
across the lagoon despite short life spans among individuals of each species. Statistical
tests that can check for the pattern in which species share habitats at a larger scale, while
rarely sharing patches within habitats could be used to determine whether intergeneric
competition operates in the species that showed shared distributions in the Bermuda
lagoon.
The occurrence of species within functional groups that possessed disparate
distribution patterns represents a result that is contrary to the predictions of the AST
(Grime 1979). Within all three functional groups there were some inter-group
distributional differences between species that indicate that the AST theory has some
limitations in its ability to predict species distributions. Within the MO functional group,
the two Diploria species appeared to dominate the tops of reefs, while Montastraea
species were abundant on both the tops and sides of reefs. Conversely Stephanocoenia
intersepta was primarily found at the deepest parts of offshore reefs. Similarly the BV
coral P. porites was located on the tops of reefs while the two Madracis species were
found on the flanks of patch reefs. Porites astreoides also dominated the tops of reef
while S. radians, another MV coral, typically occurred at the base of reefs. In all three
functional groups it appears as if each functional group has member species that fulfill
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their functional role within a particular depth, with different species representing each
functional group at a different depth. Such a distribution pattern may be indicative of the
role of inter-group competition in limiting the membership of species within a functional
group to the same depth habitat, while shared physiological traits concurrently result in
shared life-history traits and functional responses across depths by members of the same
functional group.
Percent coral cover per functional group
In the North Lagoon of Bermuda, different functional groups of corals varied in
relative abundance, percent cover and in occurrence across a range of habitats in a
manner that supports some of the hypotheses of the modifies AST presented in Chapter 1.
The Massive Oviparous (MO) and Branched Viviparous (BV) functional groups were
characterized in Ch. 1 as stress-tolerant–competitive and ruderal–competitive,
respectively. As such both groups were predicted to dominate particular habitats in the
absence of the BO functional group, which is predicted to be the most competitive, but
which is not found in Bermuda. Alternatively, the Massive Viviaparous (MV) and FP
(Foliose and Plating) functional groups were predicted to be ruderal and stress-tolerant,
respectively. Both of these groups are predicted to not dominate habitats in terms of
abundance or biomass, although for different functional reasons. The MV functional
group is predicted to allocate resources to reproduction over biomass accumulation as a
means of surviving the effects of competition and disturbance. Conversely the FP
functional group is predicted to occur in habitats characterized by low levels of light
where disturbances and competitive interactions are rare.
270
Management issues
Previous research on cross-lagoonal patterns of coral species distributions has been
limited to only four locales: the nearshore patch reefs, the outer lagoonal reefs at Crescent
and Three Hill Shoals, the rim reefs around North Rock and the 30-ft forereef (Logan
1988; Smith et al. 2003; Jones 2007). The previous interpretations of the data from these
locations paint the picture that coral cover and diversity increases in a fairly linear
manner from nearshore to offshore. This simple gradient in biomass and diversity is
hypothesized to be due to the negative influence of factors created by the island, such as
sediment or temperature extremes. However, the previously surveyed areas are separated
by large expanses of reef that have never been assessed scientifically. As such, the
precision of this historical research is rather coarse, and more complex patterns of
abundance, biomass and diversity may in fact exist across the North Lagoon. Since I
surveyed replicate reefs over six consecutive zones across the lagoon, the intensive
sampling represented by the current study should provide a more accurate depiction of
the condition of the coral assemblages in question.
In terms of functional effects, both the MO and BV functional groups provide the
most coral cover across the Bermuda lagoon, although in different zones. All functional
groups of corals possess a range of different characteristics, and management actions that
promote the survivorship of one functional group may inhibit the survival of species
belonging to other groups. In the same manner that botanists farm or garden trees in a
different way than they tend grasses or herbs, coral reef managers and scientists need to
consider the functional responses of each functional type of coral, and not treat all corals
as functionally equivalent in response or effect.
271
While the species of the MV functional group does not provide much coral cover, its
component species are highly fecund and are the most likely to recruit to newly created
habitat, if water quality and other conditions are appropriate. The BV and MO corals
recruit more rarely but may rely on similar cues as the MV functional group. As such the
MV functional group may be a useful species for indicating the relative intensity of
disturbance within a habitat, and also the relative suitability of the area for recruitment by
species belonging to all functional groups of coral.
The highest percent cover, diversity and relative abundance of corals was observed to
be within Zones 3 and 4, which have been neglected by previous researchers. These reefs
are located with the North Coral Reef Preserve and so are legally protected,. The reefs are
also in close proximity to the south shipping channel, however, and as such are at a
greater risk to environmental impact compared with most reefs in Bermuda.
This project also determined that the coral assemblages found on the flanks of the
lagoonal patch reefs possess higher coral cover and diversity than the tops of the reefs.
Most coral research focuses on the tops of patch reefs, due to the historical focus on
forereef sites in which flanks do not exist. Research and management of the lagoonal
reefs in Bermuda, and presumably elsewhere, may be driven by erroneous data unless the
sides of the reefs are considered.
The deeper reef sites in Zone 6 were characterized by low coral abundance and
percent cover, despite the proximity to the open ocean, the higher availability to light
compared to sites at the same depth nearshore, and a lower range of temperature
variability. The cause for the low biomass and species richness in this habitat is not
272
obvious, and may have been due to some form of disease or anthropogenic disturbance
heretofore unrecorded.
273
274
CHAPTER 5: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
In this dissertation I modified the Adaptive Strategies Theory, originally developed by
Grime (1977) for terrestrial plants, by removing confounding variables from the visual
model. The original Adaptive Strategies Theory relied strongly on a ternary model
showing the range of habitat characteristics across which species could adapt. However,
this ternary model confounded the independent variables of resource availability and
disturbance with the dependent variable of competition. I restructured the model as a two-
dimensional box across which only the two independent variables of resource availability
and disturbance were plotted. By modifying the model in this way, I was better able to
consider the varying levels of resource gain and loss, and thus use resource economics
theory to predict adaptive strategies. I then illustrated how the necessary trade-offs
required to cope with differing rates of resource gain and loss determine the range of
physiological and behavioral responses exhibited by an organism across habitat types.
I applied the refined theory to Caribbean reef corals. Corals were sorted into
functional groups based on their morphologies and reproductive modes. These two
functional attributes are indicative of the following adaptive strategies:
Branched oviparous corals [BO]: Competitive dominant,
Branched, viviparous corals [BV]: Competitive-Ruderal,
275
Massive, viviparous corals [MV]: Ruderal,
Massive, oviparous corals [MO]: Competitive – Stress-Tolerant,
Plating, foliose & solitary corals [FP], (which are only viviparous in the
Caribbean): Stress-Tolerant
In both Florida and Bermuda, these functional groups of corals responded to gradients of
disturbance and stress in predictably different ways.
In Florida, despite the chaotic patterns in biomass displayed by each assemblage of
coral species when separately plotted across reefs, each functional group of corals
responded to direct and indirect gradients of disturbance in a orderly and group-specific
manner. The replacement pattern predicted by Grime (1977), in which each functional
group dominated a particular region of the gradient, was not observed (Figure 5.01A).
Instead, functional groups displayed a nested distributional pattern (Figs. 5.01B; 5.02;
5.03), indicating that negative interactions between functional groups are probably weak .
In Bermuda as well, functional groups displayed a nested pattern across sites located
over a range of depths and geomorphological reef zones (Figs 5.01B; 5.03). As predicted
by the modified Adaptive Strategies theory for nested functional groups (Figs. 5.03;
5.04), branched viviparous corals dominating mid-depth sites inshore which were
characterized by low disturbance by waves and high resource availability from light and
suspended particulate matter. The massive viviparous corals, which were predicted to be
ruderal and thus limited to high resource habitats regardless of disturbance level,
primarily occurring in shallow sites from mid-shelf to offshore. The massive oviparous
corals, which were predicted to be more stress-tolerant and thus occur across a greater
276
depth gradient, but a more limited disturbance gradient, dominating both shallow and
deep sites from mid-shelf to offshore.
277
Figure 5.01. Diagrams depicting the differing ways in which the abundances of
competitive (C), stress-tolerant (S) and ruderal (R) functional groups of
corals are predicted to vary across habitats located across the range of stress
and disturbance gradients encompassed by the AST model, and depending
on the degree of niche overlap exhibited by each functional group. In all
graphs X and Y represent graphs of abundance relative to levels of
disturbance (X) or stress (Y). Z represents the modified CSR square
diagram, with the zero net growth intercept (ZNGI) illustrated for each
functional group. Graph A matches Grime’s original predictions in which
functional groups are limited to specific regions of adaptive niche phase
space with no overlap in niche boundaries. Graph B represents an alternate
model in which competitive species do not negatively interact with stress-
tolerant or ruderal species. In graph B the functional groups exhibit maximal
overlap in niche boundary. In all models C, S an R functional groups
maintain dominance under differing environmental conditions.
278
Figure 5.02. A diagram illustrating how the Zero Net Growth Intercepts (ZNGI) of each
of the predominant functional groups of Caribbean coral found in Florida
and Bermuda are dispersed across the Adaptive Strategies Theory model.
For clarity, the inset shows the distribution for each functional group
separately. The functional groups are distributed in a nested pattern across
habitat types defined by varying rates of resource gain and loss. Letters
represent the functional group occupying each patch as described in the text
above. The dark gray field on the lower right side of the diagram represents
279
the range of habitats in which high relative rates of resource loss limit
biomass.
Figure 5.03. The bounded area laid over the modified Adaptive Strategies Theory shown
in Figure 5.02 represents the range of habitat types surveyed in Florida.
280
Figure 5.04. The bounded area laid over the modified Adaptive Strategies Theory shown
in Figure 5.02 represents the range of habitat types surveyed in Bermuda.
Numbers represent zones, with 2 closer to shore and 6 furthest offshore.
Letters represent relative depths, as follows: S: Shallow; D: Deep.
In Florida the functional-group approach provided new insights into the manner in
which varying levels of disturbance affected species richness across sites. Massive
281
oviparous corals represented approximately 85% of the percent coverage of all corals on
a reef regardless of overall coral cover at a site, whereas other kinds of coral represented
a much smaller proportion of overall coral cover. Despite the small proportions in overall
cover, there were dramatic changes in species presence patterns across sites by the
subordinate functional groups. By categorizing species into functional groups, and then
tabulating the presence or absence of species across reefs ranked according to water
quality or overall coral cover, it was apparent that only the branched viviparous (BV) and
the Foliose and Plating (FP) functional groups lost species across the gradient. The BV
functional group lost species at both high and low total coral cover, whereas the FP
functional group had progressively fewer species as coral cover declined across reefs.
The loss of stress-tolerant species such as those in the FP group was predicted by the
modified Adaptive Strategies Theory.
When species were aggregated according to shared habitat in Bermuda, species from
the same genus co-occurred in almost every case. This implies that these closely related
species also share many functional traits and yet still coexist in many habitats. There are a
number of strategies by which these closely related species may coexist, including:
1. The related species may have either evolved means of avoiding competition,
are ruderal, or are stress tolerant and therefore are probably located within a (neutral;
Hubbell 2001) habitat where competition is so slow as to be negligible.
2. The species compete heavily at the colony scale but are able to mitigate
competition on a smaller or larger scale.
3. The species are so similar that at the population level there is competitive
equilibrium.
282
4. The species have slight differences in the location of source and sink
populations across the reef platform.
Each of the above points is a testable hypothesis worthy of further inquiry.
Coral cover on the lagoonal reefs in Bermuda and on the fore-reefs in the Florida
Keys (which were all offshore reefs) did not exceed 30%, and therefore the level of
interaction between coral colonies may have been fairly low. Percolation theory predicts
that randomly distributed, equally-shaped objects will contact a large network of
neighbors as the overall percent cover of the area approaches 60% (With et al. 1997).
This implies that corals in habitats with greater than 60% coral cover should have at least
one contacting neighbor (Figure 5.05), and probably more. Fore-reef sites at 15-m depth
in Bermuda generally have over 75% coral cover (Murdoch unpublished data), and
although the experiments have yet to be done, it may be that competitive exclusion
structures coral assemblages in these high-density coral habitats.
283
Figure 5.05. A network of interacting corals on the Bermuda fore reef.
A functional-group approach also provided insight into the manner in which species
were either dominant, subordinate or rare (e.g. Grime et al. 2001) across sites. The fact
that species from one functional group dominate reefs under particular environmental
conditions is contrary to the predictions of the unified neutral theory of Hubbell (2001),
which predicts that all corals are equally likely to dominate any patch. The unified neutral
theory was formulated for plant species within single functional groups and located
within uniform habitats, such as species of hardwood trees within a flat area of tropical
forest, and not for all of the plants that could coexist in the same forest. A key assumption
of this dissertation is that corals as a group are like plants as a group, and furthermore that
the functional groups of corals can be thought of as different “kinds” of corals the same
way we think of trees, shrubs and weeds as different kinds of plants. If branched
oviparous corals are functionally different from branched viviparous corals or any other
284
coral group, then it is inappropriate to assume that all corals will act in the same manner
under the same conditions, just as we would not expect species of trees and grasses to
share functional responses to the same environmental conditions.
As originally proposed by Grime (1977) the Adaptive Strategies Theory focuses
attention to the corners of the a triangular state-space model where each point of the
triangle represents an extreme habitat and corresponding adapted functional group. IN
this triangular model, intermediate habitats are predicted to be occupied by intermediate
functional groups. If this is the case then functional groups will replace each other from
habitat type to habitat type and the functional diversity across habitats will either be one
(1) or none (0). Contrary to prediction, functional groups of corals showed a nested
pattern of distribution, in which more than one functional group tended to exist within a
habitat. It seems, based on this information, that the C, S and R strategies are
complementary, not exclusionary. Species within the “Competitive Dominant” functional
group may compete heavily with each other, but the effect of competition between
functional groups appears to be reduced by trade-offs in the relative degree to which each
functional group displays the three primary traits of growth, reproduction and defense. If
so, the “Competitive Dominant” functional group appears to be badly named, and should
instead be called the “Growth” functional group.
A bigger problem with the Adaptive Strategies Theory is in defining the degree of
resource availability and disturbance that a habitat possesses without tautologically
referencing the biota about which one is attempting to make predictions. Also, the
assumption that all sources of disturbance or resources can be delimited to one axis is
probably false. In Bermuda each kind of disturbance affected each functional group
285
differently: the kinds of corals that can tolerate wave damage are different from those that
can tolerate high levels of suspended sediment. Despite this problem, however, the
Adaptive Strategy Theory does accurately predict that a ruderal strategy is required to
persist under both kinds of disturbance, and also that the functional group with a
competitive-dominant strategy would not be able to persist under either form of
disturbance.
The Adaptive Strategy Theory is typically used to predict the assemblage structure of
only one upper-level taxon of organisms, such as plants, macroalgae or reef corals,
ignoring all the other sessile organisms. It seems likely that species from multiple phyla,
or even different kingdoms (i.e. sponges, soft corals, algae, hard corals etc), share
membership in the same environmental functional group. Organisms adapted to the same
habitat type should share functional traits. These larger taxonomic groupings may have
had a long evolutionary history of interphyletic interaction, and, therefore such should be
considered together.
In the end, the weakness of the Adaptive Strategies Theory is that in simplifying
complex ecological data, it also reduces the accuracy of the resulting information. This is
of course also its strength. The Adaptive Strategies Theory provides a series of simple,
testable hypotheses that can be used to guide ecological research in an iterative and
informative manner. To fully test all of the predictions of Adaptive Strategies Theory,
one would have to measure a very large number of traits in many species, as well as a
broad range of physical, chemical, geological and biological characteristics across many
habitats. The Adaptive Strategies Theory is not so much an accurate model of reality as it
286
is a powerful theoretical framework, which can be modified to give it great heuristic
value for guiding ecological research.
287
288
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APPENDICES
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APPENDIX A: Digital Video Image Capture Methodology
•Introduction
The following methodologies allow image capture, image manipulation and data analysis
transects of spur-and-groove reef habitats that were filmed with a digital video camera in
an underwater housing. While the methods were developed using Macintosh computers
and associated hardware and software, the same or similar products exist for the PC, and
most of the methods in this document can be accomplished with either platform.
• Hardware RequiredSony DCR-VX1000 Digital Video Camera
Amphibico VX1000 U/W Housing
Macintosh Power Mac G3/266 Desktop Computer
Radius Digital Video Card With Firewire Port
• Software Required
Microsoft Excel 98
Adobe Photoshop 5.0
Radius PhotoDV plugin for Photoshop
Applescript Script Editor 1.1.2.
IMPORTANT: Macros such as Applescript are programs that automate applications including the “Finder” application. As such it is possible to create, alter or delete files stored on any hard drive or unlocked disk attached to the computer while running a Macro. The manner in which Applescript macros work,
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and the function of the macrosprovided should be understood before running them. The authors assume no responsibility for any type of loss, or any other damages, including, but not limited to special, incidental, consequential, or other damages.• Make Folder of Random Dot Files (Excel and Photoshop)
Turn on computer.
Make new folder named “NewDots” on the startup HD.
This is to hold the 99 random-dot image files.
Open Excel File named: random dot maker98
Open Adobe Photoshop 5.0
Open Applescript program: Random-dot Image Generator
Run Applescript program: Random-dot Image Generator
Once this program has run – there should be 99 image files of random dot images with 10
random dots – lettered – in the folder named “NewDots” on your startup HD.
• Capture DV reef frames
If the digital video camera or cassette recorder is not attached to the computer – then shut
down the Mac and connect the digital video cassette player to the Radius digital video
card that is inside the Mac Power PC G3 via the Firewire ports.
Turn on the Mac and the DV cassette player.
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If the digital cassette recorder is attached to the computer – quit Applescript and open the
applications Adobe Photoshop 5.0 with the Radius plugin, and Microsoft Excel
Locate the correct video tape and place it in the digital video cassette player.
In Photoshop, open the Radius digital video plugin via the following path -
File: Import: Radius PhotoDV…
In the Radius control window play the videotape and record the start and stop times for
each transect in the Excel spreadsheet named: Tape Gap Calculator
Rewind the tape and cue it to the first frame of the first transect.
Select the following options (see below) while still in the Radius Plugin:
Capture Mode: Autocapture
Every [XXX} frames
i.e. Number of frames per time-gap between frame grabs – as prescribed by the
Tape Gap Calculator
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Until [52] are captured (give or take a couple)
Capture as[Yr-Si-D-Tr-Qu} - 2 digit yr, 2-5 letter site designation, 1 letter depth designation, 2 digit transect, 2 digit frame – starting at “00”
i.e. 98-Pel-D-04-00 = Year 1998, Pelican Reef, Deep Site, 4th Transect, 1st frame
Capture size: [720x480 (raw)]
De-interlace: [None]
Format:: [NTSC 4:3]
Once this is all in order – press start and wait for the 53 frames to be captured.
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• Clean up video frames
Once the 53 frames have been captured – they can all be adjusted to the correct size,
color adjusted and saved by running the Photoshop action “DO PING 52 TIMES” ***
*** NB – it is important to re-record the sub-action “SAVE” within this action so that the
files are saved to the correct folder.
The entire process of capturing and cleaning up the frames can then be repeated for the
other 9 transects on the 3 digital video tapes per site.
Be sure to save all of the files from each transect in a unique folder nested within another
folder holding all of the transects of a site– so that all of the files can be batch processed
in the next step. Folders should be named in the following manner –
HARD DRIVE: SITE FOLDER:
containing:
HARD DRIVE: SITE FOLDER: TRANSECT FOLDER
i.e. MyHardDrive: 98-Pel-D 01-10 containing 98 Pel D 01 : 98 Pel D 10
• Paste dots to images
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Once all of the frames are captured, cleaned up and saved into folders corresponding to
site and transect – run the Applescript “Paste Random Dots” to paste the dots from
randomly selected images to each of the 500+ frames of each site. This program will
lead you through the selection of the folder containing the random-dot files, as well
through to the selection of the first image file in the first of the 10 folders within the
folder corresponding to the site currently under analysis.
• Analyze Video Frames
Data can be either entered directly into an Excel spreadsheet on the computer – or entered
onto a paper spreadsheet. The user records the sessile biota or substrate underneath the
center point of the hollow square dots located on each image. The user also needs to
record the depth of each frame.
If a randomly positioned dot falls on the depth gauge present in the image – the user can
rotate the layer containing the dots 180° - this usually moves the dots to a position over
the substrate.
Several Photoshop actions are included that facilitate in the analysis of the video images.
The quick-keys corresponding to these actions are:
F1 – Select Background Layer
F2 – Select Layer 1
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F3 – Toggle Brightness/Contrast manipulation control
�-F4 – Flatten layers down to background
F5 – Rotate currently selected layer 180°
F15 – “PING” – a suite of actions that manipulate the raw video image so it is
the correct size and of improved resolution and color balance.
�-L - Levels control – a very useful tool for color-adjusting underwater images
-L - Auto Levels adjust
Once all the images have been analyzed all of the images in each folder nested in the
folder for each site can be flattened using the Batch command and the “flatten” action in
Photoshop:
The menu commands are as follows:
File: Automate: Batch…
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• Burn to CD
(E) Once an entire reef site has been analyzed, the digital video frames and the Excel spreadsheets and other statistical data can be stored in a folder and subsequently copied onto a CD using CD recording software such as Adaptec Toast 3.5.3
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APPENDIX B: Applescript computer program for using Microsoft Excel® and
Adobe Photoshop® software to place dots on frames
-- the list of file types which will be processed
-- eg: {"PICT", "JPEG", "TIFF", "GIF"}
property type_list : {"8BPS", "PICT", "JPEG", "TIFF", "GIF"}
-- since file types are optional in Mac OS X,
-- check the name extension if there is no file type
-- NOTE: do not use periods (.) with the items in the name extensions list
-- eg: {"txt", "text", "jpg", "jpeg"}, NOT: {".txt", ".text", ".jpg", ".jpeg"}
property extension_list : {}
property timerRoutine : ""
-- This droplet processes both files or folders of files dropped onto the applet
on open these_items
----the below checks to ensure needed Excel files and Photoshop Actions are in
place
tell application "Finder"
activate
set ButtonChoice to display dialog " ••••WARNING••••
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This program will modify
ALL Photoshop files contained
within the files or folders dragged
over its icon.
Do you wish to continue?" buttons ¬
{"STOP!", "OK"} default button "STOP!" with icon caution
set button_name to button returned of ButtonChoice
if button_name is "STOP!" then
return
end if
set ButtonChoice to display dialog "This program requires that you have
the included Microsoft Excel file random dot maker (25) open, and
the included Photoshop Action file
placed in the Photoshop Extensions Folder on your HD.
Have you done this?" buttons ¬
{"NO! Quit so I can do it", "OK"} default button "OK" with icon note
end tell
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set button_name to button returned of ButtonChoice
if button_name is "NO! Quit so I can do it" then
return
end if
repeat with i from 1 to the count of these_items
set this_item to (item i of these_items)
set the item_info to info for this_item
if folder of the item_info is true then
process_folder(this_item)
else if (alias of the item_info is false) and ¬
(the file type of the item_info is in the type_list) then
process_item(this_item)
else
tell application "Finder"
activate
display dialog "The files or folders did not contain Photoshop
files." buttons {"Quit"} ¬
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default button "Quit" with icon stop
end tell
return
end if
end repeat
tell application "Finder"
activate
display dialog "The session has finished." buttons {"Quit"} ¬
default button "Quit" with icon stop
end tell
end open
-- this sub-routine processes folders
on process_folder(this_folder)
set these_items to list folder this_folder without invisibles
repeat with i from 1 to the count of these_items
set this_item to alias ((this_folder as text) & (item i of these_items))
set the item_info to info for this_item
if folder of the item_info is true then
process_folder(this_item)
else if (alias of the item_info is false) and ¬
(the file type of the item_info is in the type_list) then -- or ¬
324
--the name extension of the item_info is in the extension_list) then
process_item(this_item)
end if
end repeat
end process_folder
-- this sub-routine processes files
on process_item(this_item)
-- NOTE that the variable this_item is a file reference in alias format
-- FILE PROCESSING STATEMENTS GOES HERE
tell application "Microsoft Excel"
Activate
(*set Visible of ActiveWindow to false*)
Activate Window "random dot maker FGB (25)"
Select Range "R1C1"
CopyObject Selection
Paste
Activate ChartObject "Chart 13" of ActiveSheet
Select ChartArea of ActiveChart
set CutCopyMode to false
CopyObject ChartArea of ActiveChart
end tell
325
(* this part is not needed
tell application "Adobe® Photoshop® 6.0.1"
activate
do script "Dot Grabber" -- an Adobe Photoshop 6.0 action - see attached
end tell *)
-- this selects the next photoshop file
tell application "Finder"
activate
select file (this_item)
open selection
end tell
-- this pastes the NewDots onto a new layer on the video frame, saves the file and
closes it
tell application "Adobe® Photoshop® 6.0.1"
activate
do script "Dot Paster"
end tell
end process_item
326
Appendix C: A list of coral species observed in Bermuda
The following is a list of the species of scleractinian hard corals that have been observed
in Bermuda by the author. Just list the ones seen at your sites
Branched Oviparous
1. Oculina diffusa
2. Oculina robusta ???
Branched Viviparous
1. Madracis decactis
2. Madracis formosa (New possible record: S. R. Smith)
3. Madracis mirabilis
4. Porites furcata (New record: T.J.T. Murdoch: unpublished confirmation)
5. Porites porites
Massive Viviparous
1. Agaricia agaricites (T.J.T. Murdoch, A. Venn: possible sighting)
2. Dichocoenia stokesii
3. Favia fragum
4. Isophyllia sinuosa
5. Meandrina meandrites
6. Porites astreoides
7. Siderastrea radians
Massive Oviparous
1. Diploria labyrinthiformis
327
2. Diploria strigosa
3. Montastraea cavernosa
4. Montastraea faveolata
5. Montastraea franksi
6. Montastraea species A (The majority of M. annularis spp. appear to be a hybrid
between M. faveolata and M. franksi in BDA)
7. Siderastrea siderea (T.J.T. Murdoch, S. du Putron: possibly regionally extinct?)
8. Stephanocoenia intersepta
Foliose, Plating and Solitary
1. Agaricia fragilis
2. Scolymia cubensis (W. Sterrer: potentially more than one species)
328
Appendix D: Bermuda climatology
Climatology of Bermuda from 1949-1999, as published online by the Bermuda Weather
Service (http://www.weather.bm/data/climatology.html)
329
Appendix E: Logistic regression of rank abundances; Florida data
Logistic regression of rank abundances versus total abundance per transect for each
functional group
Logistic Fit of BV By TCA
BV
0.00
0.25
0.50
0.75
1.00
-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130
SUM
1
2
3
4
5
Whole Model Test
Model -LogLikelihood DF ChiSquare Prob>ChiSq
Difference 6.34659 1 12.69318 0.0004
Full 238.99612
Reduced 245.34271
RSquare (U) 0.0259
Observations (or Sum 200
330
Wgts)
Converged by Objective
Parameter Estimates
Term Estimate Std Error ChiSquare Prob>ChiSq
Intercept -2.4993419 0.3709632 45.39 <.0001
Intercept -0.1303332 0.2248103 0.34 0.5621
Intercept 2.07864736 0.2772554 56.21 <.0001
Intercept 4.94687655 0.6259174 62.46 <.0001
TCA -0.0150532 0.0042367 12.62 0.0004
Logistic Fit of FP By TCA
FP
0.00
0.25
0.50
0.75
1.00
-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130
SUM
12
3
4
5
331
Whole Model Test
Model -LogLikelihood DF ChiSquare Prob>ChiSq
Difference 7.21570 1 14.4314 0.0001
Full 217.89041
Reduced 225.10611
RSquare (U) 0.0321
Observations (or Sum
Wgts)
200
Converged by Objective
Parameter Estimates
Term Estimate Std Error ChiSquare Prob>ChiSq
Intercept -3.3128101 0.5286694 39.27 <.0001
Intercept -1.3570022 0.2650898 26.20 <.0001
Intercept 1.05681986 0.2432521 18.88 <.0001
Intercept 4.49707184 0.5152874 76.17 <.0001
TCA -0.0164569 0.0043939 14.03 0.0002
332
Logistic Fit of MV By TCA
MV
0.00
0.25
0.50
0.75
1.00
-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130
SUM
1
2
3
45
Whole Model Test
Model -LogLikelihood DF ChiSquare Prob>ChiSq
Difference 10.41441 1 20.82881 <.0001
Full 166.38296
Reduced 176.79736
RSquare (U) 0.0589
Observations (or Sum
Wgts)
200
Converged by Gradient
333
Parameter Estimates
Term Estimate Std Error ChiSquare Prob>ChiSq
Intercept -1.254137 0.2738426 20.97 <.0001
Intercept 2.70655809 0.3465647 60.99 <.0001
Intercept 4.91549566 0.5580352 77.59 <.0001
Intercept 5.85518535 0.7797963 56.38 <.0001
TCA -0.0227229 0.0050557 20.20 <.0001
Logistic Fit of MO By TCA
MO
0.00
0.25
0.50
0.75
1.00
-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130
SUM
1
234
Whole Model Test
Model -LogLikelihood DF ChiSquare Prob>ChiSq
Difference 21.677679 1 43.35536 <.0001
Full 55.428898
Reduced 77.106577
334
RSquare (U) 0.2811
Observations (or Sum
Wgts)
200
Converged by Objective
Parameter Estimates
Term Estimate Std Error ChiSquare Prob>ChiSq
Intercept -0.251108 0.4552401 0.30 0.5812
Intercept 1.39009666 0.5633292 6.09 0.0136
Intercept 2.36232842 0.7768345 9.25 0.0024
TCA 0.12926131 0.0333187 15.05 0.0001
335
336
BIOGRAPHICAL SKETCH
Name of Author: Thaddeus James Thomas Murdoch
Place of Birth: Somerset Village, Sandy’s Parish, BERMUDA
Date of Birth: April 18, 1966
Graduate and Undergraduate Schools Attended:
University of South Alabama, Mobile, Alabama, USA
Dalhousie University, Halifax, Nova Scotia, CANADA
Degrees Awarded:
1995 – 1998 Master of Science in Marine Science,University of South Alabama, Mobile, Alabama, USAand the Dauphin Island Sea Lab, Dauphin Island, Alabama, USA.
1988 - 1991 Bachelor of Arts, Honors in Psychology (Neuroendocrinology), Dalhousie University, Halifax, N.S. CND
1984 - 1988 Bachelor of Science in Biology, Dalhousie University, Halifax, N.S. CND
Awards and Honors:
Bermuda Biological Station for Research, Inc. - Grant in Aid: 2003
PADI Foundation: 2000
Ph.D. Fellowship, Marine Science Dept., U. South Alabama: 1999 to 2002
Nelson Award for Outstanding Masters Student, U. South Alabama: 1998
Marine Science Dept. Student Assistantship, U. South Alabama: 1995 to 1998