Download Seamounts: centres of endemism or species richness for ophiuroids?

Global Ecology and Biogeography, (Global Ecol. Biogeogr.) (2007) 16, 720–732
Blackwell Publishing Ltd
RESEARCH
PAPER
Seamounts: centres of endemism or
species richness for ophiuroids?
Timothy D. O’Hara*
Museum Victoria, GPO Box 666, Melbourne
3001, Australia
ABSTRACT
Aim To test the hypotheses that seamounts exhibit high rates of endemism and/or
species richness compared to surrounding areas of the continental slope and oceanic
ridges.
Location The south-west Pacific Ocean from 19–57° S to 143–171° E.
Methods Presence/absence museum data were compiled for seamount and nonseamount areas at depths between 100 and 1500 m for the Ophiuroidea (brittle-stars),
an abundant and speciose group of benthic invertebrates. Large-scale biogeographical
gradients were examined through multivariate analyses at two spatial scales, at the
scale of seamounts (< 1° of latitude/longitude) and regions (5–9°). The robustness
of these patterns to spatially inconsistent sampling effort was tested using Monte
Carlo-style simulations. Levels of local endemism and species richness over numbers
of samples were compared for seamount and non-seamount areas using linear
regressions. Non-seamount populations were randomly generated from areas and
depth ranges that reflected the typical sampling profile of seamounts.
Results Seamount ophiuroid assemblages did not exhibit elevated levels of species
richness or narrow-range endemism compared with non-seamount areas. Seamounts
can exhibit high overall species richness for low numbers of samples, particularly on
seamounts supporting a dense coral matrix, but this does not increase with additional
sampling at the rates found in non-seamount areas. There were relatively few identifiable seamount specialists. In general, seamount faunas reflected those found at
similar depths in surrounding areas, including the continental slope. Seamount and
non-seamount faunas within the study area exhibited congruent latitudinal and
bathymetric species turnover.
Main conclusions Seamount faunas were variable for ophiuroid faunal composition, species richness and narrow-range endemism, reflecting their environmental
diversity and complex history. The continental slope was also variable, with some
areas being particularly species rich. Broad geomorphological habitat categories
such as ‘seamounts’ or ‘continental slope’ may be at the wrong scale to be useful for
conservation planning.
*Correspondence: T. O’Hara, Museum
Victoria, GPO Box 666, Melbourne 3001,
Australia.
E-mail: [email protected]
Keywords
Biogeography, deep sea, endemism, Monte Carlo simulations, null models,
Ophiuroidea, seamounts, species richness.
INTRODUCTION
Seamounts are an iconographic marine habitat and the focus of
much research effort. They provide topographical structure
across the continental slopes and abyssal plains of the deep sea,
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altering oceanic circulation patterns with local upwellings, turbulent
mixing and closed circulation cells. These hydrodynamic processes
in turn can raise productivity, and seamounts frequently support
dense aggregations of fauna around their summits (Rogers, 1994;
Beckmann & Mohn, 2002). A major conservation issue is the
DOI: 10.1111/j.1466-8238.2007.00329.x
© 2007 The Author
Journal compilation © 2007 Blackwell Publishing Ltd www.blackwellpublishing.com/geb
Seamount endemism and species richness
damage to these communities by anthropogenic activities, particularly bottom trawling for fish (Koslow et al., 2001; Anderson
& Clark, 2003), but potentially in the future from mining of rare
metals (United Nations, 2004).
Biogeographically, seamounts are of great interest. They can be
very old and geographically isolated (Hein, 2004; Kitchingman &
Lai, 2004), suggesting that they function as biogeographical
‘islands’, slowly accumulating a distinctive fauna through ancient
vicariant and rare dispersal events followed by accelerated evolution through genetic processes operating on isolated small populations (Samadi et al., 2006). This has been termed the ‘centres of
endemism’ model of seamount biogeography (Samadi et al.,
2006). Initial reports suggested that seamounts do in fact support
large numbers of locally endemic species (Wilson & Kaufmann,
1987; Richer de Forges et al., 2000).
An alternative explanation is that these apparently high levels
of endemism are artefacts of sampling species-rich communities
(Samadi et al., 2006). Most biotic communities have ‘right-skewed’
species-abundance profiles; most species are rare and only a few
very common (Gotelli & Graves, 1995; Gaston, 1996). Sampling
species-rich communities will result in the collection of more
rare species. Through chance some of these will only be detected
from seamounts and will thus appear to be endemic. Other sources
of bias for many analyses are uneven collection effort; seamounts
are often more intensively sampled than the surrounding continental slopes due to their scientific interest, and the inadequate
taxonomic knowledge of rare species (Samadi et al., 2006). This
reasoning does not downgrade the potential ecological importance of seamounts. Indeed, under this model seamounts are
characterized as having high species richness and abundance.
More prosaically, they have been termed ‘oases of productivity’ in
an otherwise oligotrophic deep-sea environment (Rogers, 1994,
Samadi et al., 2006).
In this paper, the distribution patterns of ophiuroids, a major
group of benthic invertebrates, were examined to see whether
they supported raised levels of endemism or species richness for
seamounts in the south-western Pacific Ocean. The seamounts in
this region are among the best known in the world (Richer de
Forges et al., 2000), having been extensively surveyed over the last
20 years by at least 25 French, New Zealand and Australian scientific
expeditions. They were spread from tropical to sub-Antarctic
latitudes, including three north–south chains in the Coral and
Tasman seas (19 –35° S), a cluster just south of Tasmania (44° S)
and a chain including Macquarie Island (54° S).
Ophiuroids (commonly called brittlestars, snake stars or basket
stars) have emerged as a key group for furthering our understanding of patterns of seamount biodiversity in this region.
They are one of the dominant components of the deep-sea benthic
fauna on both hard and soft sediment habitats, allowing faunal
comparisons to be made between seamounts, continental margins
and oceanic islands. They are common associates of key benthic
structural elements such as corals and sponges. They are generally
abundant and diverse enough to permit statistical analysis but
not too diverse to become impossible to identify over typical
project timelines. They have a reasonably well-understood taxonomy. Finally, they have a variety of dispersal strategies including
planktotrophy, lecithotrophy, viviparity and asexual fissiparous
reproduction (Byrne & Selvakumaraswamy, 2002).
This study tested two hypotheses: (1) that seamounts have
more narrow-range ophiuroid species than equivalent areas on
the continental slope (a prediction of the ‘centre of endemism’
model); and (2) that seamounts have more species than equivalent
areas on the continental slope. Data for a direct test of the ‘oases
of productivity’ model were not available. An initial community
analysis was undertaken in order to identify the important largescale biogeographical gradients and stratify the test data sets
appropriately.
METHODS
Data collection
Ophiuroid data used in this study were part of a larger data set
that includes records from throughout the Indian and Pacific
Oceans assembled over 5 years from museum and historical
records. This includes approximately 32,000 records from all
Australian museums, New Zealand’s National Institute of Water
and Atmospheric Research (NIWA), the Muséum National
D’Histoire Naturelle Paris and historical records from the great
scientific expeditions of the 19th and 20th centuries (see O’Hara &
Stöhr, 2006, for details). The data were inherently messy, collected
over many surveys using different collection gear with varying
success. Abundance data were not consistently available as large
hauls were sometimes sub-sampled on board ship and tow-times
varied considerably. However, the enormous cost and difficult
collection conditions involved in sampling seamounts over large
spatial scales preclude more sophisticated experimental designs.
Consequently, only species-sample presence data were analysed.
All data were stored in a purpose-built taxonomic, distributional
and modelling data base (Fleet v1.0) developed using Microsoft
Access.
The study area for this project was confined to the Coral and
Tasman seas in the south-western Pacific Ocean. This area extended
from the northern tip of New Caledonia and the Chesterfield
bank (19° S) to the southern section of the Macquarie Ridge (56° S),
including the Australian continental margin, Lord Howe Rise
and Norfolk Ridge (140–171° E) (Fig. 1). It excluded the New
Zealand continental margin and the abyssal plain of the southern
Tasman Sea. The principal sources of data were the numerous
French expeditions around the New Caledonian Exclusive Economic Zone, material from Australian scientific and fishing voyages along the Australian continental margin and around Lord
Howe and Norfolk islands, and material collected by the New
Zealand Oceanographic Institute (NZOI, now NIWA) from
throughout the Coral and Tasman seas. The bathymetric range
was restricted to 100–1500 m to ensure a consistent bathymetric
spread of samples throughout the study area. Only samples from
trawls, dredges and epibenthic sleds were included. Other collection methods such as cores, grabs and traps were too irregularly
distributed to be useful. Only records identified to species were
retained for analysis. This included records for 73 undescribed species
which were consistently identified by the author and are being
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
721
T. D. O’Hara
Figure 1 Map of the Tasman and Coral Seas
showing the 2000 m depth contour, location
of samples (blue = seamount, purple = non
seamount) and regions defined for this study:
A = NE Australia, B = N Lord Howe, C = N
Norfolk, D = E Australia, E = S Lord Howe,
F = S Norfolk, G = Tasmania, H = Macquarie.
progressively described (e.g. O’Hara & Stöhr, 2006). These have
been given unique taxa number in the data bases at Museum Victoria, e.g. Stegophiura sp MoV 5229. The resulting data set included
318 species from 16 of the 18 recognized families of ophiuroids.
For the purposes of this study, a wide definition of seamount
was adopted, which included cones, flat-topped guyots, pinnacles
and other topographic ‘hill’ elevations (Rowden et al., 2005).
Oceanic islands were treated as a special case. They were included
in the seamount list to assess their contribution to the overall
biogeographical patterns. In many cases they have been formed
by similar processes to neighbouring submarine seamounts and
are likely to have been subject to similar biogeographical processes. For example, Chesterfield and Lord Howe islands are the
oldest and youngest volcanic structures in a north–south chain
of seamounts along the western Lord Howe Rise (Quilty, 1993).
Macquarie Island is on the same ridge of elevated oceanic crust that
forms seamounts to the north and south of the island (Williamson,
1988). Many seamounts have protruded above sea level in the
past (e.g. Quilty, 2001).
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Samples were available from 70 seamounts and oceanic islands
(see Appendix S1 in Supplementary Material). The locations of
all samples were confirmed by plotting them on modern GIS
bathymetric data layers (National Oceans Office, 2005). No records
within the study depth were available for the large Cascade
seamount on the Eastern Tasman Plateau, the atolls and seamounts
in the western Coral Sea (Wreck, Kenn, Cato Reefs) or the
northernmost Tasmantid seamounts (Recorder, Moreton). Nonseamount habitat within the target area and depth range included
the continental slopes and outer shelves around Australia and
New Caledonia, and the fragments of continental crust that form
the base of the Lord Howe Rise, Norfolk Ridge and Loyalty Ridge.
The available data set for the entire study area consisted of 318
species from 1108 samples. Of these, 380 samples from seamounts
contained 212 species, and 729 samples from non-seamount
locations (i.e. continental slopes and rises) contained 253 species.
Of the 1108 samples, 589 were collected by trawls and 519 by
dredges and epibenthic sleds, with comparatively fewer trawls on
seamounts (30%) than on non-seamounts (65%).
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
Seamount endemism and species richness
Table 1 Regional/habitat groups of samples defined for biogeographical analyses. Depth parameters refer to samples not the actual topography.
Region
Habitat
Latitude
Longitude
North-east Australia
North Lord Howe
Slope
Slope
Seamount
Slope
Seamount
Slope
Seamount
Slope
Seamount
Slope
Seamount
Slope
Seamount
Seamount
19 –28° S
148 –157° E
157–164° E
North Norfolk
East Australia
South Lord Howe
South Norfolk
Tasmania
Macquarie
164 –171° E
28–37° S
148 –157° E
157–164° E
164–171° E
37–45° S
143 –152° E
52–57° S
158 –161° E
The study area was divided into regions in order to examine
biogeographical relationships (Table 1). Longitudinally, the area was
divided into three segments based broadly on: (1) the Australian
continental margin (including the offshore Tasmantid seamount
chain); (2) the Lord Howe Rise; and (3) the Norfolk Ridge. For
the purposes of this study, the Norfolk Ridge was considered to
include the Norfolk Ridge proper, the Loyalty Ridge and the
seamounts south of the Isle de Pins, the Western Norfolk Ridge
and Wanganella Bank. The Lord Howe Rise included the Coriolis,
Lansdowne and Fairway Banks. The Macquarie Ridge fell into
the same longitudinal span as the Lord Howe Rise. Latitudinally,
the area was divided into four segments corresponding to: (1) the
northern section of the Lord Howe and Norfolk Ridges (dividing
the ridges roughly in half) and the equivalent section of northeastern Australia from 19 to 28° S; (2) the southern section of
the Lord Howe and Norfolk Ridges, Tasmantid seamounts and the
eastern coast of Australia to 37° S; (3) Tasmania, including the
seamounts to the east and south to 45° S; and (4) the Macquarie
Ridge.
The preferred microhabitat for each species was determined
from ship-board experience, published information, photos of
the seafloor and museum collection data. This information was
categorized into three broad microhabitat classes: epizoic (living
semi-permanently on arborescent cnidarians or sponges), cryptozoic (living in the interstices of rock or biogenic substrates) and
soft sediment (infaunal or epifaunal).
Multivariate analyses
Multivariate community analyses were performed by consolidating individual sample-species data into presence/absence species
lists or groups at two spatial scales: (1) individual seamounts;
and (2) regions (see above). The seamount analysis contained
samples from seamounts (including islands) only. The regional
analysis contained samples from seamount and non-seamount
Min.
depth
Max.
depth
Mean
depth
No. of
samples
No. of
species
135
970
150
110
190
102
131
784
183
691
110
102
700
100
606
1423
1400
1490
1133
1500
1050
1342
1210
1488
1451
1500
1400
1280
355
1150
384
493
496
576
320
965
645
1077
546
414
1115
383
16
7
106
221
110
174
14
24
19
6
68
279
33
32
17
14
55
150
106
80
19
26
45
16
82
92
44
17
habitats within each region for comparison. The Bray–Curtis
similarity coefficient was used to generate similarity matrices.
Bray–Curtis is equivalent to the Sorensen coefficient when used
on presence/absence data (Clarke & Warwick, 2001). Ordinations
were produced from the similarity matrices using the multidimensional scaling (MDS) functions in the software primer v5.2
(Clarke & Warwick, 2001).
Collection effort differed considerably between seamounts
(see Appendix S1) and between regions (Table 1). This can produce
artefacts in multivariate analyses, as collection effort can influence species richness which in turn affects Bray–Curtis distances,
particularly for presence/absence data. One such artefact is that
species-poor samples become outliers on ordinations (Clarke
et al., 2006). Two techniques were used to minimize artefacts from
variable collection effort. First, species-poor groups (≤ 5 species)
were excluded from the analysis as they were unlikely to contribute
significantly to biogeographical patterns. Sample-poor groups
were retained if they contained enough species. Secondly, the
resulting patterns were compared with simulated data sets created
by artificially limiting the number of samples included from each
seamount to the median number of samples overall. Samples
were randomly selected without replacement from each group
up to the number required, and the resulting species lists were
analysed as before. The similarity matrices derived from these
simulations were correlated with the original using both the
parametric Pearson and non-parametric Spearman methods.
Correlating similarity matrices is a preferable method of determining how closely multivariate patterns ‘match’ than direct
comparison of ordinations or cluster diagrams (Clarke &
Warwick, 2001). This comparison was repeated 20 times with
different sets of randomly selected samples. Consistently high
correlation coefficients (high mean and low standard deviation
over the 20 runs) were used as an indication that the overall multivariate pattern was broadly similar and that variable collection
effort had not unduly biased the results.
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
723
T. D. O’Hara
A series of analysis of similarities (anosim) (Clarke & Warwick,
2001) were performed using the classificatory factors: (1) latitude
at four levels: 19–28° S, 28–37° S, 37–45° S, 52–56° S; (2) longitude at three levels: 143–157° E, 157–164° E, 164–171° E;
(3) mean sample depth at three levels: 100–500 m, 501–1000 m,
1001–1500 m); (4) minimum sample depth at three levels:
100–500 m, 501–1000 m, 1001–1500 m; (5) emergence (seamounts
only) at two levels: islands and submerged seamounts; and (6)
habitat (regions only) at two levels: seamount (including islands)
and non-seamount. One-way analyses were performed first.
Global R values from one-way analyses were then ranked to assess
the relative contribution of each factor to the overall pattern. The
factor with the highest R value (in this case latitude) was then
used as the primary factor in two-way crossed anosim analyses
with each of the other factors, in order to assess their relative
contribution to the pattern within each latitude group. P values in
all cases were calculated using 4999 permutations. The unbalanced
study design (e.g. the varying number of seamounts per region)
precludes the use of more sophisticated manova style analyses
using the software such as permanova (Anderson, 2001). However, the anosim results were confirmed by using a bioenv procedure, which correlates similarity matrices of environmental
variables with faunal similarity matrices to see which combination
of variables best match the faunal pattern (Clarke & Warwick,
2001). The variables were the mean latitude, longitude and depth
of samples in each group, habitat (0, 1) and emergence (0, 1).
The environmental matrices were calculated using normalized
Euclidean distance and correlated with the faunal matrices using
the Spearman coefficient. anosim and bioenv procedures were
performed using the primer v5.2 software.
Univariate analyses
The null hypothesis of no significant difference between species
richness for seamount and non-seamount samples was tested
with a series of anovas and ancovas using the software statistica
v7.1 (StatSoft, 2005). Samples were separated into separate data
sets on the basis of collection method (dredge/sled and trawl) for
analysis due to the significant interaction between this factor and
habitat. Loge(x + 1)-transformed latitude and depth were used in
some analyses as covariates. Unequal sample sizes between groups
required the use of Type III SS calculations (Quinn & Keough, 2002).
Null models
Observed levels of seamount endemism were compared with a
null model that assumed that the distribution of narrow-range
species is random with respect to the location and depth of
samples. Endemism is inherently scale dependent, so to compare
seamounts with unbounded areas of the continental slope,
species with a geographical range of less than 1° of latitude were
used. The null model was constructed from 25,000 species lists
derived from randomly selecting without replacement between 1
and 50 samples from seamounts and non-seamounts throughout
the study area and depth range (100–1500 m). A line of best fit
was determined by linear regression and 95% prediction interval
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calculated from the formula μ y ± t n−2 (Sμ 2 + s 2 ), where μy is the
mean of the estimate, t is the t value at 95%, s is the standard
error of the estimate and Sμ the standard error of the predicted
value, using the software statistica version 7.1 (StatSoft, 2005).
Null models were also developed for comparing the species
richness found on seamounts with comparable areas on the continental slope. For these null models, the selection of random
samples was constrained to a 50-km radius and ± 250 m bathymetric range around an initial randomly selected sample (50 km
being the mean radius and 500 m the mean depth range of
samples from seamounts). Finally, additional null models were
developed for: (1) smaller constraint areas (10 km radius); (2)
samples collected using specific collection gear, trawls only and
dredges/epibenthic sleds; and (3) different microhabitat groups
(epizoic, cryptozoic and benthic) and specific regions (Tasmania,
northern Norfolk). A line of best fit was determined by linear
regression as above. Previous studies had reported a linear relationship between sample and species number (Richer de Forges
et al., 2000). Polynomial fits were attempted but in general the x2
coefficient was very low and linear models were retained for ease
of comparison. Species rarefaction curves were not calculated
due to lack of consistent species-sample abundance data.
RESULTS
Community analyses
The Global 1-way anosim analyses of species lists for each
seamount produced significant results for latitude, longitude,
mean and minimum depth of each seamount, with latitude having
the highest R value (Table 2). Emergence (island versus submerged
Table 2 anosim results for species lists at two spatial scales grouped
by latitude (19 –28° S, 28 –37° S, 37– 45° S, 52–57° S), longitude
(143 –157° E, 157–164° E, 164 –171° E), depth (100 –500, 501–1000,
1001–1500 m), emergence (island versus submerged) and habitat
(seamount versus non-seamount).
2-way crossed
anosim averaged
across latitude groups
1-way anosim
Global R
Seamount
Latitude
Longitude
Mean depth
Min. depth
Emergence
Region
Latitude
Longitude
Mean depth
Min. depth
Habitat
P
Global R
P
0.574
0.417
0.342
0.174
0.071
0.000*
0.000*
0.000*
0.000*
0.188
−0.051
0.413
0.147
− 0.073
0.638
0.000*
0.087
0.635
0.387
0.024
− 0.044
0.236
− 0.022
0.007*
0.397
0.599
0.090
0.568
− 0.049
0.794
0.548
− 0.143
0.591
0.013*
0.040*
0.790
*Significant result ( P < 0.05).
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
Seamount endemism and species richness
Figure 2 Multidimensional scaling of species occurrence for individual seamounts (a–c) and regions (d) using the Bray–Curtis similarity
coefficient. Ordination points superimposed by (a) seamount name, (b) region, (c) mean depth of samples and (d) regional groups.
seamounts) was not significant. Two-way crossed anosim analyses
with latitude as the primary factor and each other variable as
the secondary factor produced significant results only for mean
depth (Table 2). The best match using all variables in a bioenv
analysis was latitude alone (ρ = 0.600), followed by latitude/
longitude (ρ = 0.582) and latitude/mean depth (ρ = 0.578).
These results were reflected in the MDS ordination (Fig. 2a–c),
which showed a broad latitudinal gradient, with seamounts from
the northern regions to the left and those from off Tasmania and
along the Macquarie Ridge to the right. The oceanic islands were
scattered throughout the ordination, generally adjacent to
seamounts from the same region. Elizabeth Reef and Lord Howe
Island are a little displaced from the N7 and N9 seamounts also
on the southern Lord Howe Rise. Norfolk Island is adjacent to
N11 and N4 from the southern Norfolk Ridge. Chesterfield is
adjacent to the Nova and Capel seamounts on the northern Lord
Howe Rise, and Macquarie Island sits a little apart from the
northern Macquarie seamount. Depth was important within
some regional groups; for example, explaining some of the dispersion of northern Norfolk seamounts (Fig. 2c).
At a larger spatial scale, the Global 1-way anosim analyses for
regional seamount/non-seamount species lists produced significant results for latitude only (Table 2). Longitude, mean depth,
minimum depth and habitat (seamount versus non-seamount)
were not significant. Two-way crossed anosim analyses with
latitude as the primary factor and each other variable as the
secondary factor produced significant results for mean and
minimum depth (Table 2). The bioenv correlations were all
relatively poor. The best match using all variables in a bioenv
analysis was minimum depth (ρ = 0.138), followed by minimum
depth/latitude (ρ = 0.131) and minimum depth/latitude /habitat
(ρ = 0.127).
The ordination of seamount and non-seamount species groups
from each region also shows a broad latitudinal gradient (Fig. 2d).
The northern regions are to the top left, the southern Lord Howe,
Norfolk and eastern Australian regions are in the middle, and the
Tasmanian and Macquarie regions to the lower right. There was
an almost complete latitudinal turnover of species across the
study region, with only 6 of 318 species in common between the
Macquarie group and all the northernmost groups combined.
Generally, seamount groups were close to the non-seamount
groups from the same region with a few exceptions. The northern Lord Howe region with few, relatively-deep, samples (see
Table 1) sat as an outlier to the lower left. The eastern Australian
seamounts group, with few, relatively shallow, samples, also sat as
an outlier to the upper right, adjacent to the northern Lord Howe
seamounts. There was no single cluster of seamount groups.
Collection effort differed considerably at both spatial scales
(Tables 1 & 2). Consequently, the multivariate patterns were
compared to a series of 20 simulated analyses that limited the
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
725
T. D. O’Hara
Figure 3 The relationship between the number
of species and number of samples for seamounts
and non-seamount areas. Dots represent each of
the 70 seamounts (many overlap). Crosses
represent 25,000 randomly selected populations
of between 1 and 50 samples from areas of the
continental slope of 50-km radius and 500-m
depth range, and the solid and dotted lines show
the linear regression and 95% prediction limits.
The arrows indicate seamounts that emerge to
form oceanic islands.
collection effort for each group to up to four (for the seamount
analysis) and 33 (regional analysis) randomly selected samples.
All resulting similarity matrices were significantly correlated
with the original, for both the seamount (mean Pearson R = 0.91
± 0.01, Spearman ρ = 0.78 ± 0.03) and regional analyses (mean
Pearson R = 0.92 ± 0.01, Spearman ρ = 0.88 ± 0.02), suggesting
that the original patterns were not significantly affected by
collection effort.
Species richness
Species richness for individual seamounts ranged from 1 to 37
species from 1 to 43 samples (Appendix S1). The most speciesrich samples from seamounts were collected from Blackbourne
(25 species, south Norfolk), V (23, Tasmania), K1 (22, Tasmania),
Mont K (20, north Norfolk) and Sister 1 (20, Tasmania). However, some samples from the continental slope were also rich,
including several from eastern Bass Strait (27 and 26 species),
south of New Caledonia (24, 23, 20 and 20) and the Loyalty
Ridge (21 and 18).
The majority of seamounts fell within the 95% prediction
limits for simulated populations based on areas of radius 50 km
and depth range 500 m on the continental slope (Fig. 3). A few of
the larger seamounts with numerous samples (Chesterfield,
Macquarie Island, Nova, Capel) tended to have fewer species
than predicted from equivalent non-seamount areas. Confining
the comparison to subsets of the data (Fig. 4) resulted in broadly
similar patterns for gear type (dredge/epibenthic sleds and trawls)
and microhabitat groups (epizoic, cryptozoic and soft sediment),
although three seamounts (B1, J1 and 38 from Tasmania) had
more cryptozoic species than predicted from continental slope
samples. Finally, regional variation was examined. The regional
analysis was restricted to the two regions with the highest number
of samples: Tasmania and north Norfolk. As the seamounts in
these areas were generally small (Appendix S1), the area of slope
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for non-seamount samples was also reduced to a 10-km radius.
The majority of seamounts from around Tasmania were above
the non-seamount regression line, and three above the 95% prediction. In contrast, most of the seamounts from northern Norfolk
were below the non-seamount regression line. One seamount
was above the 95% prediction (Mont K) and one below (Kaimon
Maru). Emergent seamounts (oceanic islands) were either within
or lower than that predicted from the slope (Fig. 3).
The null hypothesis for no difference between species richness
in seamount and non-seamount samples was not rejected in a
one-way anova for trawl samples (P = 0.142) but was for dredge
samples (P = 0.002), although the amount of variation explained
was very small (R2 = 0.018). The null hypothesis for both sets of
samples was rejected when latitude and depth were used as covariates in an ancova , which marginally improved the variation
explained (dredge: P = 0.000, R2 = 0.110; trawl P = 0.000, R2 =
0.043). However, the trend for both sets of samples was reversed,
with group means higher for slope (5.5 species) over seamount
(4.1) for dredge samples and seamount (3.8) over slope (2.9) for
trawl samples. Where they could be made, results from intraregional comparisons were mixed, with higher mean samplespecies richness for seamount over slope dredge samples from
Tasmania (9.2/5.5) but lower from north Norfolk (3.5/5.1),
south Norfolk (3.0/3.3) and eastern Australia (3.2/4.5), and
higher for trawl samples from south Lord Howe (4.2/3.2) and
south Norfolk (5.1/2.8) and lower from north Lord Howe (2.3/
4.0) and north Norfolk (6.9/3.5).
Endemism
Eighty-two species were endemic to the study area, of which 28
(34%) were found only in seamount samples (seamount specialists)
and 54 only in non-seamount samples or in both seamount and
non-seamount samples (generalists). The majority of seamount
specialists (n = 23 or 82%) were limited to a single degree of
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
Seamount endemism and species richness
Figure 4 The relationship between the number of species and the number of samples for data subsets from seamounts and non-seamount areas.
Dots represent each of the seamounts (many overlap). The solid and dotted lines show the linear regression and 95% prediction limits for the number
of species found in 25,000 random selections of samples from non-seamount areas (the data points are hidden for clarity). Unless stated, the nonseamount regressions are constrained to all species from a 50-km radius and 500-m depth range in all regions. The arrows indicate oceanic islands.
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
727
T. D. O’Hara
Figure 5 Histogram of latitudinal span of
species endemic to the study area.
latitude (defined here as ‘narrow-range’) compared with n = 16
(30%) for generalists (Fig. 5). Fifteen species were apparently
endemic to a single seamount (Appendix S1). Although narrowrange seamount specialists were located in the Norfolk/Lord
Howe and Tasmanian regions, there were no seamount endemics
from Tasmania, where most seamounts were geographically
proximate. There were no narrow-range seamount species from
the eastern Australian (Tasmantid) or Macquarie seamounts,
although they were among the most geographically isolated.
When the number of narrow-range seamount specialists was
compared to a null model that assumed the distribution of narrowrange species was random with respect to geographical position
(not shown), only one seamount fell outside the 95% prediction
intervals of the model (number of species = 0.0563 + 0.0809 ×
number of samples). The exception was the Chesterfield Bank at
the northern end of the Lord Howe Rise, which had fewer (n = 0)
narrow-range species than predicted for the sampling intensity
(43 samples). Even the seamounts with two endemics fell well
within the prediction intervals. If the null model was restricted to
non-seamount samples only (Fig. 6), all seamounts fell within
the 95% prediction interval.
DISCUSSION
Seamount species richness and endemism
Seamount species richness for ophiuroids tended to be consistent
with, or lower than, prediction limits for equivalent areas on the
continental slope, regardless of the area in question (10–50 km
radius), collection gear or species habitat preference. This was
a surprising finding, inconsistent with previous reports that
emphasized the species richness of seamounts (Samadi et al.,
2006). It does emphasize that other deep-sea habitats can also be
species rich. The majority of non-seamount samples for this
728
study came from the continental slope around south-eastern
Australia and New Caledonia. High continental slope species
richness has been noted previously for both regions (Richer de
Forges, 1990; Poore et al., 1994). Moreover, individual seamount
samples can be relatively species rich but they do not increase in
species richness with additional sampling as rapidly as nonseamount areas. This could be a species–area effect: larger areas
have been reported to have higher species richness (Gaston,
2000), a fact attributed to various causes, including the greater
habitat diversity of larger areas, the larger populations or the
larger regional species pool (Gotelli & Graves, 1995; Koleff &
Gaston, 2002).
Species richness is known to be positively correlated with
abundance (Gotelli & Graves, 1995). The lack of abundance data
in this study is regrettable, but it is unlikely to alter the conclusions of the study. The ‘oases of productivity’ model predicts that
seamounts should support a high abundance of animals (Samadi
et al., 2006) and therefore higher species richness than nonseamount areas, the opposite of what is being reported here.
There was regional variation (Fig. 4). Some Tasmanian
seamounts had a high species richness for one to three samples,
more than expected from equivalent numbers of samples on the
continental slope, in part because of the large numbers of cryptozoic
animals that were found in the dense matrix of the deep-water
coral, Solenosmilia variabilis (Koslow et al., 2001). In contrast,
seamounts from the northern Norfolk Ridge were more variable.
Mont K and Mont J had relatively high species per sample ratios,
while others such as Kaimon Maru had relatively low species
richness for the number of samples collected. Surprisingly, the
number of epizoic species (on arborescent cnidarians) was not
enhanced on seamounts. Smith et al. (2004a) noted that, contrary to assumptions, many bamboo coral specimens from
around New Zealand had been collected from flat areas as well as
seamounts.
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
Seamount endemism and species richness
support some locally endemic echinoderm species (Hoggett &
Rowe, 1988; Rowe, 1989; O’Hara, 1998).
The level of endemism may be understated for ophiuroids.
Some shallow-water forms have proven to be suites of similar
cryptic species that are genetically divergent but morphologically
conserved (e.g. O’Hara et al., 2004). Morphological stasis is a feature of ophiuroids, with some extant species being identified
from the Miocene (e.g. Ishida, 2003) and some genera from the
Mesozoic (e.g. Jagt, 2000). There is a need for additional molecular
studies on deep-sea species. Nevertheless, the limited genetic
data from other phyla within the study area is equivocal for the
‘centres of endemism’ paradigm. There was little genetic structure between populations of corals, galatheid crustaceans and
planktotrophic molluscs, some hundreds of kilometres apart
(Smith et al., 2004a; Samadi et al. 2006). This mirrors the situation
for many animals found around hydrothermal vents which are also
known to be able to disperse over long distances (Won et al.,
2003, Hurtado et al., 2004; Miyazaki et al., 2004). Other molluscs
showed more population structure attributed to poor dispersal
capabilities of the species concerned or unusual oceanography of
the seamounts (Smith et al., 2004b; Samadi et al., 2006).
Figure 6 The relationship between the number of narrow-range
species (< 1° of latitude) and number of samples. Dots represent each
of the 70 seamounts (many overlap). The solid and dashed lines
show the linear regression and 95% prediction limits for the number
of narrow-range species found in 25 000 random selections of
between 1 and 50 samples from non-seamount samples throughout
the study area and depth range (data points are omitted for clarity).
Arrow indicates Norfolk Island, the only emergent seamount studied
with narrow-range species.
Regional patterns
This study found that 15 of the 318 species were apparently
endemic to a single seamount. Three seamounts contained two
endemics. A further eight seamount specialists were narrowrange species, restricted to seamounts within 1° of latitude. Many
of these species were rare (i.e. not abundant), collected in one or
two samples. This level of endemism was within that expected by
chance from all samples and for the subset of samples found on
the continental slope (Fig. 6).
Within the study area, Samadi et al. (2006) found that all 62
galatheid shrimps reported from the northern Norfolk seamounts
had previously been found elsewhere. In contrast, Richer de
Forges et al. (2000) reported high rates of local endemism (29–
34%) for seamounts throughout the south-west Pacific Ocean.
The discrepancy may lie in the differing taxonomic composition
of these studies or simply from inadequate taxonomy and sampling artefacts. The Richer de Forges et al. (2000) study included
a large range of macro-invertebrates (but not ophiuroids), some
of which may have poor dispersal abilities compared with
ophiuroids and galatheids. Equally, expeditions to unexplored
regions or habitats will almost always discover new species.
Adequate sampling is required before it can be ascertained with
certainty whether these species are narrow-range endemics or
just rarely found.
There is little evidence that geographical isolation influenced
community composition within the study depth range (100–1500
m). No narrow-range species were found on the most isolated
seamounts such as Gascoyne or Macquarie. Instead, these species
were scattered on a variety of seamounts throughout the Coral
and northern Tasman seas. This is in contrast to shallow water
(0–20 m) around oceanic islands within the study area, such as
Lord Howe, Norfolk and Macquarie, which are known to
The major macroecological gradients evident in the analysis of
seamount assemblages were related to latitude and mean sample
depth (Fig. 2b,c). The same macroecological gradients were
evident when regional faunas were analysed for both seamount
and non-seamount samples (Fig. 2d & Table 2). There was a clear
biogeographical gradient from the tropics to the sub-Antarctic,
with only 6 of 318 species common between the northernmost
and southernmost regions. Longitude and emergence (to form
islands) were not emphasized (Table 2). Diverse faunas were
collected from the seamounts of the northern Lord Howe and
Norfolk Ridges but they did not form separate regional groups
(Fig. 2b), a result that differs from previous findings from the
region (Richer de Forges et al., 2000) albeit using a different
methodology.
Although, the latitudinal gradient does reflect the geological
age of seamounts in the south-west Pacific Ocean (the oldest
seamounts to the north and the youngest to the south; see Quilty,
1993; Sutherland, 1994), it is worth emphasizing that the gradient was evident for both seamount and non-seamount faunas,
and thus not necessarily a consequence of biogeographical
processes peculiar to seamounts as suggested by Richer de Forges
et al. (2000). Indeed, for shelf and slope depths (100 –1500 m) the
gradient mirrors that found in shallow water (0–100 m) (O’Hara
& Poore, 2000). This was surprising as environmental gradients
in deeper water are much weaker. For example at 1500 m, water
temperature only differs by 0.15 °C between New Caledonia and
Macquarie Island (CSIRO, 2006).
Seamount faunas did not group together over the entire study
area (Fig. 2d). There was no widespread ‘seamount fauna’ as such.
Instead the fauna found on seamounts tended to be broadly similar (although not identical) to that found on neighbouring areas
(including other seamounts) at similar depths. This was consistent
© 2007 The Author
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729
T. D. O’Hara
with the findings of the last global review of seamount faunas
(Wilson & Kaufmann, 1987). In order words, seamount faunas
consisted largely of a selection of species available from the
regional species pool, although species abundances can vary
markedly (Koslow et al., 2001).
Seamounts as habitat
Seamounts within the study area had a great diversity of form,
size, depth and position, altering local environmental conditions
and consequently faunal composition (Rowden et al., 2005). The
flat-topped structures on the northern Lord Howe Rise have
considerable areas of soft sediments, while volcanic cones are
more likely to provide hard substrata, benefiting species that are
epizoic on corals (Stocks, 2004). Summit assemblages can differ
from those along their sides and at the base, because of different
ecological and hydrological conditions. Koslow et al. (2001) found
that the greatest cover of the habitat-forming coral Solenosmilia
variabilis on the Tasmanian seamounts was at mid-height, with
mud covering much of the summits and bases. In summary,
seamounts are not a uniform habitat and do not support uniform
assemblages.
The continental slope also contains a variety of habitats, ranging from gentle slopes covered in thick mud to canyons and fracture zones with steep rock-covered sides. Much of the southern
Norfolk Ridge is covered by hard basalt without sediment, supporting little visible animal life (Williams et al., 2006). The rim of
the Horseshoe Canyon off the eastern Bass Strait has extensive
filter-feeding communities, while the canyon floor is covered in
mud (A. Williams, pers. comm.).
Most species found on seamounts within the study area were
also found in suitable habitat on continental slopes. Relatively
few (28 of 318) species were only found on seamounts. Unlike
other fragmented deep-sea habitats such as hot vents and cold
hydrocarbon seeps (Stöhr & Segonzac, 2005), there appeared to
be few seamount specialists. The conclusion to be drawn from
this is that ‘seamounts’ appear to be at the wrong scale to be
considered a useful seafloor habitat. They have been a convenient
mappable geopolitical entity, and may have some usefulness
when considered from a fisheries management perspective, but
do not show the consistency and specialization of seafloor assemblages to be considered a single unit for other management purposes such as marine park planning. Until we understand more
about the ecological and historical factors that structure seafloor
assemblages, ‘seamounts’ should be evaluated independently to
ascertain their conservation status.
Seamount biogeographical processes
Understanding the biogeographical processes that affect seamounts
is complicated by their complex geological and ecological history.
Lateral movement can be induced by tectonic forces; subsidence
can occur after the active volcanism ceases; and climatic cycles can
alter oceanographic conditions (for examples in the south-west
Pacific; see Quilty, 1993, 2001). The predominant biogeographical
processes that drive the assembly of marine faunal communities
730
are vicariance and dispersal (Poore & O’Hara, 2007). If seamount
communities were formed largely through tectonic-driven vicariance events then they would be expected to consist mainly of
species derived from the surrounding continental or oceanic
crust. For example, on seamounts rising from the abyssal plain,
one would expect a (possibly depauperate) assemblage based on
abyssal species that have become adapted to shallow-water conditions. Such a strong gradient could generate new species over
time (Gavrilets et al., 2000). However, this study has found that
seamounts support a similar suite of species to that found on
neighbouring seamounts or continental crust within strata of the
same depth.
The ophiuroid data presented here, and the limited available
genetic evidence from other phyla (see above), suggest that
seamount summit faunas have been assembled through dispersal.
Many marine species are capable of long-distance dispersal
and there are many shallow-water examples of species that are
genetically similar across the Tasman Sea from Australia to New
Zealand (Poore & O’Hara, 2007). Seamounts may accumulate
species at different rates depending on their location. The ability
of species to disperse to and from seamounts will also vary over
time depending on the prevailing environmental conditions and
will differ for species with different life histories. Seamounts may
be isolated for some time, causing a form of climatically driven
intermittent vicariance (Poore & O’Hara, 2007). However, there
is little evidence that this has led to many speciation events for
ophiuroids in the south-west Pacific Ocean. Potentially, seamounts
have other important evolutionary roles besides facilitating speciation, including providing abundant source populations for
surrounding regions, as a refuge habitat during adverse climatic
conditions and acting as ‘stepping stones’ facilitating the longdistance dispersal of species across oceans (Wilson & Kaufmann,
1987; Richer de Forges et al., 2000).
ACKNOWLEDGEMENTS
I would like to thank the Data Analysis Working Group of CenSeam (Global Census of Marine Life on Seamounts) for aiding
this research; the many museum curators and collection mangers
who have granted access to their collections of seamount
ophiuroids, particularly Nadia Ameziane and Marc Eleaume
(Muséum National d’Historie Naturelle, Paris), Dr Penny Berents
(Australian Museum, Sydney) and Anne-Nina Lörz (National
Institute of Water & Atmospheric Research, Wellington); the
leaders of scientific voyages in the region, particularly Alan
Williams (Commonwealth Scientific and Industrial Research
Organisation, CSIRO) and Bertrand Richer de Forges (l’Institut
de Recherche pour le Développement, Noumea); the International Seabed Authority (ISA) and Tony Koslow (CSIRO) for
facilitating my attendance at the workshop on ‘Deep Seabed
Cobalt-Crusts and Diversity and Distribution Patterns of
Seamount Fauna’ held in Jamaica in March 2006, where many of
the ideas in this paper germinated; to Richard Marchant
(Museum Victoria) for his statistical advice; and finally to Robin
Wilson, Gary Poore (Museum Victoria) and two anonymous
reviewers for commenting on draft manuscripts.
© 2007 The Author
Global Ecology and Biogeography, 16, 720–732, Journal compilation © 2007 Blackwell Publishing Ltd
Seamount endemism and species richness
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BIOSKETCH
Tim O’Hara, a senior curator of Marine Invertebrates at
Museum Victoria, has research interests in the fields of
biogeography, macroecology, conservation biology and
the evolution and taxonomy of echinoderms.
Editor: Julian Olden
SUPPLEMENTARY MATERIAL
The following supplementary material is available for this article:
Appendix S1 List of seamounts used in this analysis.
This material is available as part of the online article from:
http://www.blackwell-synergy.com/doi/abs/10.1111/
j.1466-8238.2007.00329.x
(This link will take you to the article abstract).
Please note: Blackwell Publishing is not responsible for the content or functionality of any supplementary materials supplied by
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