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Research
Cite this article: Hardy SM, Smith CR,
Thurnherr AM. 2015 Can the source– sink
hypothesis explain macrofaunal abundance
patterns in the abyss? A modelling test.
Proc. R. Soc. B 282: 20150193.
http://dx.doi.org/10.1098/rspb.2015.0193
Received: 31 January 2015
Accepted: 9 April 2015
Subject Areas:
ecology
Keywords:
source – sink hypothesis, abyssal seafloor,
productivity, larval dispersal,
macrofaunal abundance
Author for correspondence:
Sarah M. Hardy
e-mail: [email protected]
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rspb.2015.0193 or
via http://rspb.royalsocietypublishing.org.
Can the source –sink hypothesis explain
macrofaunal abundance patterns in the
abyss? A modelling test
Sarah M. Hardy1, Craig R. Smith2 and Andreas M. Thurnherr3
1
School of Fisheries and Ocean Sciences, University of Alaska, Fairbanks, PO Box 757220, Fairbanks,
AK 99775, USA
2
Department of Oceanography, University of Hawaii, Manoa, 1000 Pope Road, Honolulu, HI 96822, USA
3
Lamont-Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, USA
Low food availability is a major structuring force in deep-sea benthic communities, sustaining only very low densities of organisms in parts of the abyss.
These low population densities may result in an Allee effect, whereby local
reproductive success is inhibited, and populations are maintained by larval
dispersal from bathyal slopes. This slope–abyss source–sink (SASS) hypothesis suggests that the abyssal seafloor constitutes a vast sink habitat with
macrofaunal populations sustained only by an influx of larval ‘refugees’
from source areas on continental slopes, where higher productivity sustains
greater population densities. Abyssal macrofaunal population densities
would thus be directly related to larval inputs from bathyal source populations. We evaluate three predictions derived from the SASS hypothesis:
(i) slope-derived larvae can be passively transported to central abyssal regions
within a single larval period, (ii) projected larval export from slopes to the
abyss reproduces global patterns of macrofaunal abundance and (iii) macrofaunal abundance decreases with distance from the continental slope. We
find that abyssal macrofaunal populations are unlikely to be sustained solely
through influx of larvae from slope sources. Rather, local reproduction probably sustains macrofaunal populations in relatively high-productivity
abyssal areas, which must also be considered as potential larval source areas
for more food-poor abyssal regions.
1. Introduction
The abyssal seafloor, encompassing ocean depths between 3000 and 6000 m, is
a vast habitat covering approximately 54% of the Earth’s surface (reviewed by
Thistle [1] and Smith et al. [2]). This habitat consists largely of plains and hills
covered by fine sediments, punctuated by manganese nodules, seamounts and
trenches. Sunlight is absent in abyssal ecosystems, which are overwhelmingly
dependent on the sinking flux of detrital organic material from primary production in overlying surface waters. However, only a small fraction of net
primary production reaches the abyssal seafloor (approx. 0.5–2%), with the
amount varying geographically according to levels of primary production
and export efficiency in overlying waters (e.g. [2]). Abyssal ecosystems are
thus characterized in large part as extremely ‘food limited’.
Food limitation is widely considered to be a major structuring force in
deep-sea benthic communities (reviewed by Smith et al. [2], Levin et al. [3] and
Snelgrove & Smith [4]). Variation in carbon flux at both local and regional scales
influences patterns of abundance, biomass, body size and levels of alpha-, betaand gamma-diversity, as well as a broad range of ecosystem functions [2]. Food
limitation in parts of the abyss can be so great that only extremely low macrofaunal population densities can be sustained [5]. Such circumstances could
generate an Allee effect, whereby low densities severely hamper reproductive
success and local population growth rates could reach zero, or even negative
values [6]. These low-quality ‘sink’ habitats, in which reproduction is insufficient
to balance mortality, occur in a variety of ecosystems [7]. ‘Source–sink theory’
& 2015 The Author(s) Published by the Royal Society. All rights reserved.
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(1) physical transport is sufficient for propagules from the
continental slope to reach the central abyssal regions of
the major ocean basins within the time frame of a
single pelagic larval period;
(2) projected larval export from continental slopes to the abyss
reproduces global patterns of macrofaunal abundance on
the abyssal seafloor; and
(3) benthic faunal abundance decreases with integrated
distance from the continental slope.
Rex et al. [5] argue that all three predictions hold true for
molluscs in the North Atlantic. Here we test these predictions
using additional datasets with broader taxonomic scope from
the abyssal Pacific Ocean, the largest abyssal region on the
planet. Lastly, we offer a reformulation of the SASS hypothesis
highlighting effects of productivity, propose appropriate tests
of the new hypothesis, and predict deep-sea regions and
faunal components in which source–sink dynamics are more
or less likely to affect community structure and diversity.
2. Testing predictions of the slope –abyss
source–sink hypothesis
Source–sink dynamics are inextricably linked to larval dispersal dynamics, particularly in the case of small, relatively
sessile marine invertebrates which rely on planktonic larvae
as their primary means of colonizing distant habitat patches.
The SASS hypothesis asserts that the abyssal seafloor constitutes a ‘marginal’ habitat (cf. [31]), wherein food is so scarce
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Proc. R. Soc. B 282: 20150193
composed of a limited subset of slope taxa with extended
bathymetric ranges. Subsequent references to the SASS
hypothesis by other authors have focused on this line of evidence, discussing whether the trends observed in molluscs
were typical of other taxa and/or regions. Moreno et al.
[22] attempted to test predictions of the SASS hypothesis by
applying nestedness analysis to polychaete species richness
data from the Pacific margin of South America, asking
whether the abyssal species were a subset of the shelf and
bathyal fauna. A significant pattern was detected, ostensibly
supporting the SASS hypothesis. However, the authors
reported only 11 polychaete species below depths of 3000 m,
and only one species below 4000 m. Other abyssal Pacific
studies report approximately 200 polychaete species within
relatively small areas at depths below 4000 m, with species
continuing to accumulate [23,24], suggesting the dataset of
Moreno et al. [22] severely under-sampled the polychaete
fauna and cannot be taken as support for the SASS hypothesis.
Evidence of high species turnover and low gene flow across
depth strata further contradicts the notion that abyssal taxa represent range extensions from slope areas (e.g. [17,18,25–30]).
Indeed, distinct benthic assemblages are found within relatively
limited depth zones, and numerous species are restricted to
abyssal depths.
Our objective is to move beyond discussion of bathymetric trends to formulate and test predictions of the SASS
hypothesis concerning abyssal community structure and dispersal dynamics. Specifically, we focus on the prediction that
areas of the abyssal seafloor below 4000 m should constitute
sink habitats inhabited by populations of benthic organisms
that are sustained by the influx of larvae dispersing, in a
single generation, from more productive continental slope
areas. This idea suggests the following testable predictions:
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describes the export of offspring from high-quality habitats
(sources) to populations in sink habitats through dispersal
and/or emigration [8,9]. Sink populations are unsustainable
without this supplementation from source areas, such that
regional population structure may depend on connectivity
between these sources and sinks. In extreme cases, sink
populations in highly marginal habitats sustain no local reproduction, and rely solely on the immigration of each generation
of individuals from source populations.
Deep-sea biodiversity patterns and their underlying causes
are of increasing interest given links to ecosystem functioning,
and efforts to establish conservation guidelines for deep-sea
resource exploitation, including oil extraction, mining and
deep-sea fisheries [10–12]. Identification of source and sink
habitats has clear relevance to conservation efforts, in that protection of sink habitat is unlikely to preserve and/or revitalize
endangered populations, while protection of source habitats
may be disproportionately important [7]. Indeed, marine
conservation research—particularly efforts to design effective
marine protected areas (MPAs)—emphasizes dispersalmediated ‘connectivity’ to source populations or high-quality
habitat patches (e.g. [13]).
The role of source–sink dynamics in governing abyssal community structure has been suggested previously (e.g. [3,4]), and
Rex et al. [5] explicitly applied source–sink theory to explain
bathymetric species diversity gradients. The well-documented
decline in species diversity from mid-bathyal (i.e. mid-continental slope) to abyssal depths in the North Atlantic [14] may
primarily be driven by attenuation of particulate organic
carbon flux with depth [15]; however, the mechanisms underlying productivity-driven diversity clines continue to be a
topic of discussion in deep-sea ecology [3,16,17]. Rex et al. [5]
proposed the slope–abyss source–sink (SASS) hypothesis to
explain this trend, suggesting that extremely low input of
organic matter to abyssal sediments has created a source–sink
system between continental margins and the abyssal seafloor,
whereby abyssal populations are maintained only by larval
dispersal from more productive areas on the surrounding
continental slopes. As distance to productive coastal ecosystems
increases, source–sink dynamics are said to become increasingly important, because population densities on the foodlimited abyssal seafloor are so low as to be reproductively
non-viable (i.e. suffer from an Allee effect).
Based on analysis of depth ranges in North Atlantic gastropods and bivalve molluscs, Rex et al. [5, p. 164] note that the
abyssal fauna largely represents ‘sparsely occupied range extensions for a subset of bathyal species with high dispersal ability’,
arguing against the existence of a truly endemic abyssal fauna.
In this view, abyssal populations consist of non-reproductive
individuals having dispersed as larvae from slope ‘source’
populations. The SASS hypothesis essentially describes large
areas of the abyssal seafloor as a biodiversity sink, rather than
a high-diversity region and centre of evolutionary radiation
such as has been suggested by others (e.g. [18–21]). As such,
the SASS hypothesis implies that anthropogenic activities
restricted to the abyss (e.g. manganese nodule mining) are
much less likely to result in species extinctions than previously
expected, because the reproductively active populations of abyssal species actually lie at shallower depths on the continental
slope. Thus, the SASS hypothesis has clear implications for
both conservation efforts and evolution in the deep sea.
Rex et al. [5] reported that abyssal molluscs showed
depressed a-diversity relative to bathyal depths and were
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The potential spatial scales over which dispersal of deep-sea
larvae might occur depend on the speed and trajectory of
bottom currents, and the amount of time larvae spend in
the plankton (commonly referred to as planktonic larval duration, PLD). Measurements of PLD in individual abyssal taxa
are rare, but estimates range from a few days to a few months
[38,39]; conservatively, PLDs are likely to be less than 1 year
for most taxa. Thus, could dispersive larvae, in particular the
demersal forms characteristic of most deep-sea species that
produce planktonic larvae, be transported from the slope to
the centres of abyssal ocean basins in a single generation?
Deep-sea drifter and tracer-release studies, in which neutrally buoyant floats or chemical tracers are released and
tracked below 1500 m depth in the open ocean, provide
useful insights into potential transport distances for deepsea larvae. Numerous studies in the deep Pacific and Atlantic
Oceans indicate that over approximately 1-year time scales,
transport distances in most of the open ocean (i.e. away
from bathyal topography such as continental slopes and
mid-ocean ridges) are of the order of 10 to several hundred
kilometres per year, except in the equatorial zones and the
Southern Ocean [40 –45]. Considering that the distance from
the nearest slope to the centre of the Pacific Ocean basin is
up to 5000 km, and up to 3000 km in the South Atlantic
and Indian Ocean basins (e.g. see fig. 3b in [46], and values
of DMIN in electronic supplementary material S1), abyssal
benthic populations in these regions cannot be maintained
by the transport of planktonic larvae in a single hop from
slope populations. Shorter distances are required for slope-
(b) Modelling larval source –sink dynamics in the abyss
Given the spatio-temporal variability of the velocity field in the
deep ocean revealed by drifter trajectories (e.g. [41,42,44]),
horizontal dispersal on sufficiently large scales is expected to
be random-walk-like (e.g. [47]), implying that concentrations
of pelagic larvae originating on the continental slope should
decrease as roughly the square of the transport distance from
the slope. Thus, even if slope larvae were somehow transported
to the central ocean basins, larval densities in the basins would
be exceedingly low. True sink populations are recruitment
limited, so if abyssal communities are maintained predominantly by larval input from slope sources, abundance of
abyssal organisms should reflect the integrated larval input
from surrounding slopes. We modelled potential larval transport from the slope to the abyss in order to ask: does
projected larval export from continental slopes to the abyss
reproduce regional patterns of benthic invertebrate abundance
at the abyssal seafloor? Alternatively, are some abyssal areas
more likely than slopes to serve as source areas for larvae
dispersing to other abyssal sites?
To address these questions, we constructed a simple dispersal model which produces a larval slope source index
(LSSI). The LSSI is a relative estimate of the total larval
input to a given location on the seafloor from all slope sites
within a conceivable dispersal range. The model was initialized by setting the larval concentration of each ‘source
pixel’ (topographic pixel in the 2000–3000 m depth range)
to the product of the pixel surface area As and particulate
organic carbon (POC) flux [48]. The pixel surface area As
was calculated by dividing the horizontal area of the pixel
(based on latitude/longitude extents) by the cosine of the
topographic slope angle. We used 2000–3000 m as the
depth range for the source of slope-derived larvae because,
for the vast majority of species occurring below 4000 m for
which bathymetric ranges are known (including molluscs,
sea stars and holothurians), the upper limit of the range is
deeper than 2000 m [5,17]. Thus, for most abyssal species,
potential source populations on the slope lie below the
2000 m depth contour. For the first model run, the larval concentrations of all source pixels deeper than 4000 m and
shallower than 2000 were set to zero. After initialization,
the LSSI for each sink pixel was calculated by summing the
contributions to that location from all slope source pixels.
Each source pixel contribution was calculated by dividing
the larval concentration by the squared dispersal distance.
Normalizing larval input with the square of dispersal distance is consistent with the type of random-walk dispersal
patterns that are suggested by drifter studies, which show
convoluted, swirling trajectories.
Here we define dispersal distance as the length of the
shortest connection between the source and destination
pixels along great-circle segments that are not blocked by
topography shallower than 1500 m. The dispersal distance
p
of a source pixel to itself was set to 14 As, which is an approximation of the mean distance of any location within the pixel
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Proc. R. Soc. B 282: 20150193
(a) Deep-sea larval dispersal distances estimated
from drifter data
to-abyss larval transport in the North Atlantic relative to
the Pacific, but even here, many central abyssal areas are
more than 1000 km from the nearest slope. Thus, we conclude
that physical transport is very likely to be insufficient for propagules from the continental slopes to reach the central ocean
abyssal regions within a single pelagic larval period.
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that organisms are unable to reproduce, creating a demographic sink dependent on influx of larvae that were
produced in more productive bathyal source regions. This
prediction assumes the majority of abyssal taxa disperse via
planktonic larval stages, and that larvae are capable of reaching distant abyssal sink regions by means of transport in
deep-sea currents [5].
Evidence of reproductive activity in the abyss is extensive
[32 –34], suggesting many taxa are capable of allocating
resources to gamete production. More importantly, diverse
groups of macrofaunal invertebrates (approx. 300 –1000 mm)
and the vast majority of metazoan meiofauna (45 mm) are
exclusively direct developers (i.e. they do not produce intermediate larval stages at all), yet these groups dominate the
abundance, biomass and diversity of the abyssal benthos
[35,36]. Other dominant macrofauna such as the polychaete
worms exhibit brooding in many species, producing nondispersive larval stages [34]. Most notably, the Peracarida
(amphipods, isopods, tanaids and cumaceans)—which are
among the most speciose groups in the abyss, with an estimated several thousand species [37]—are exclusively
brooding taxa; yet some groups exhibit strong evidence
of adaptive radiations in situ at abyssal depths [18,19]. Such
adaptive radiation is impossible in non-reproductive sink
populations [8,31], and, combined with high local diversity,
suggests that at least some highly diverse, ecologically important clades are not subject to SASS dynamics. Nonetheless, we
consider below the dispersal dynamics of those taxa that do
produce planktonic larval stages, and thus could conceivably
be subject to source–sink dynamics.
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The SASS hypothesis predicts larval source areas on the
continental slope based on the observation that biomass and
standing stock decline with depth, presumably due to
decreased input of POC [5]. However, the abyssal seafloor is
not uniformly low in POC flux. Areas that underlie productive
surface waters, such as the Pacific equatorial upwelling zone,
receive elevated levels of flux, and thus support elevated biomass and abundance of benthic organisms [52]. We predicted
that these high-flux regions not associated with continental
margins may also serve as larval source areas for dispersal
into the oligotrophic central basins. We thus modified the
LSSI model to allow scaling of larval production with seafloor
(c) Trends in benthic faunal abundance with distance
from slope
Source–sink theory describes sink habitats as having a carrying capacity of zero, such that species abundance in these
low-quality habitats will decline in the absence of immigration
[7,8]. Moreover, abundance within a sink habitat is a function
of productivity in the source habitat, and resulting rate of dispersal to the sink. Thus, the abundance of abyssal species
would be expected to decline with distance from the productive source habitat, because habitat quality decreases due
to low productivity, and populations become increasingly dispersal-limited with distance to the source population [5]. Here
we ask: Does macrofaunal standing stock, or the standing stock
of predominant macrofaunal taxa, decrease with the distance
from the nearest continental slope?
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Proc. R. Soc. B 282: 20150193
(i) Effect of particulate organic carbon flux on larval supply
POC flux from Lutz et al. [48]. Model runs with a zonalto-meridional dispersal distance anisotropy factor of 3 show
interesting trends in the LSSI (figure 1). In particular, highproductivity regions associated with both coastal and
equatorial upwelling zones impact the LSSI, indicating these
regions may account for a disproportionately large part of
larval export relative to other slope areas (figure 1b). More
interestingly, additional model runs relaxed the depth restriction for larval source areas and considered the entire abyss
as a potential larval source, scaled again with POC flux,
which is an important predictor of benthic biomass [53].
In this scenario, both POC flux and distance from slope can
influence larval supply to a given abyssal location, yet largescale patterns in the LSSI closely resemble POC flux patterns
(figure 1c). This result is consistent with our prediction that local
productivity plays an important role in governing larval supply.
Indeed, the importance of POC flux as a driver is enhanced by
considering abyssal regions as potential larval sources.
The results of our LSSI modelling are striking. The models
based solely on slope larval sources (figure 1a,b) produce
macrofaunal abundance patterns dramatically different
from those documented in the deep sea (figure 1d ). In particular, vast regions of the northeast and equatorial North
Pacific abyss exhibit very weak larval input. If the supply
of larvae from continental slopes is limiting abyssal macrobenthic abundance, these areas should have macrofaunal
abundance approximately two orders of magnitude lower
than abyssal areas near continental margins. In fact, these
are regions of high abundance [53] (figure 1d). Thus, the prediction that projected larval export from slopes to the abyss
reproduces regional patterns of macrofaunal abundance at
the abyssal seafloor can be rejected. By contrast, when abyssal
depths of more than 4000 m are included as potential larval
sources (larval source strength varying with seafloor POC
flux as in earlier runs), modelled larval inputs reproduce
most regional patterns in abyssal macrofaunal abundance
(figure 1c,d). Thus, if source –sink dynamics are important
in controlling abyssal macrofaunal abundance, some abyssal
regions are likely to be important source habitats. In this
model, large regions of the abyssal seafloor emerge as potential larval sources (figure 1c), including areas underlying
productive surface waters such as the equatorial Pacific
upwelling zone. Source–sink processes controlling population
densities are thus likely to be influenced by regional productivity patterns, rather than resulting solely from dispersal
of larvae from distant slopes.
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to the pixel centre. Our simple dispersal model does not
explicitly resolve time, and thus cannot be used to evaluate
dispersal distances achievable within a time frame approximating PLD. We initially limited dispersal distances to less
than or equal to 2000 km in order to keep computation tractable. This limitation creates an underlying assumption
that larval PLDs are sufficient for dispersal across such long
distances. However, as discussed above, drifter studies indicate PLDs of 4– 5 years would be required for slope larvae
to travel such distances (i.e. much longer than published estimates of PLD). The 2000 km dispersal distance used in our
model is thus a very generous estimate such that we are
probably overestimating the potential recruitment to abyssal
populations from slope source areas. Nonetheless, as long
as the dispersal distance is sufficiently large to allow flux to
all locations on the abyssal seafloor, the model solution is
not sensitively dependent on its value, because larval input
is normalized to the square of the distance to the source.
The closest source areas will thus dominate the spatial patterns of the LSSI. We tested this expectation with additional
model runs at low spatial resolution using different dispersal
distance limits and confirmed that patterns were similar
across runs (results not shown).
Drifter and tracer data from the abyssal Atlantic [44,49]
indicate significantly greater zonal than meridional displacement from deployment locations (i.e. ‘dispersal’) on
time scales of 2–3 years, except near topography. Zonal
tracer tongues occur in all major ocean basins [50],
suggesting greater zonal than meridional dispersal may be
typical. We thus modified our model to simulate zonal-tomeridional dispersal anisotropy (z) by multiplying zonal
p
p
and meridional distances by 1/ z and z, respectively,
ensuring that the horizontal surface area of each pixel is
conserved.
Initial model construction was based on a reduced topographic dataset derived by pre-averaging the Smith &
Sandwell V12.1 topography [51] with a nominal resolution
of 10 into 9 9 pixels. To test the effect of this topographic filtering, a run was carried out with the domain limited to the
Pacific but with approximately doubled resolution (5 5
pixel pre-averaging). Results from the standard- and highresolution runs are very similar, except near the open
boundaries (Drake Passage and a region south of Australia).
The main effect of the increased horizontal resolution is that
there are more potential larval source areas on seamounts
and small islands. However, since the slope area associated
with these small-scale topographic features is small, they do
not significantly affect large-scale patterns.
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(a)
(b)
50
100 200 500 1000 2000 5000
larval slope source index
50
20
50
100 200 500 1000 2000 5000
larval slope source index
Proc. R. Soc. B 282: 20150193
(c)
20
(d)
20
50
100 200 500 1000 2000 5000
larval slope source index
100
200 500 1000 2000 5000
individuals m–2
Figure 1. (a– c) Dispersal distance normalized larval input calculated with zonal-to-meridional dispersal distance anisotropy factor of 3. Because larval input is a
relative quantity, the data in each of the three panels were scaled with a constant factor into a common range (20– 5000) and are reported without units.
(a) Constant larval source strength, accounting only for distance to slope. (b) Source strength scaled to POC flux, with larval supply from continental slope
only. (c) Source strength scaled to POC flux, allowing entire abyss to serve as a larval source area. (d) Estimated abundance of benthic macrofauna at the
deep seafloor smoothed to 0.1 degree resolution and displayed in logarithm scale (base 10). Adapted from [53].
We used existing datasets for macrofaunal abundance in
the abyssal North Pacific [23,52,54– 60] (electronic supplementary material, S1 and S2) to test the prediction that
benthic faunal abundances are inversely related to distance
from the continental slope (i.e. that standing stock declines
with distance to slope). Two metrics were calculated for
each abundance data point in order to quantify the range
of dispersal distances required for colonization of abyssal
sediments from the continental slope. These metrics were
based on the approximate position of the 2000 m isobath
along the continental slope (commonly used to delineate
slope from abyssal seafloor), north of 158 S, and include the
shortest linear distance to the isobath (DMIN) and the inteP
grated distance ( (1/r 2)) from 868 equally spaced points
along the isobath (DSUM) to account for dispersal from multiple locations along the slope (electronic supplementary
material S1). If faunal abundance is inversely related to distance to the continental slope, then we would expect a
negative relationship between faunal abundance and both
DMIN and DSUM.
We conducted a stepwise multiple regression using latitude, longitude, depth, DMIN, DSUM and POC flux to the
seafloor (derived from Lutz et al. [48]) as predictor variables,
to evaluate potential predictors of macrofaunal abundance.
Latitude and longitude were initially included to account
for spatial correlations among sampling locations. However,
evaluation of variance inflation factors for predictor variables
indicated problems with colinearity between longitude and
depth, and between DMIN and DSUM. Thus, DMIN and
longitude, which had the highest variance inflation factors,
were excluded from the regression analysis. Separate analyses
were conducted using abundance data for total macrofauna
and for dominant macrofaunal taxa including polychaetes,
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20
5
bivalves, gastropods, total molluscs, tanaids and isopods
(table 1). Examination of diagnostics indicated that all datasets met the assumptions of normality and equal variances,
so all analyses were conducted using untransformed data
with the software SPSS STATISTICS v. 22.
Regression analysis revealed significant relationships to
DSUM only for total macrofauna and Tanaidacea. In both
cases, abundance was negatively related to DSUM, indicating
an increase in abundance with distance to the slope, in contrast to predictions of the SASS hypothesis. For all other
taxa, only POC flux was retained in the regression model
as a significant predictor of abundance. For all categories,
abundance showed a positive trend with increasing POC
flux. These results suggest that dispersal from shelf and
slope populations alone is not the limiting factor controlling
macrofaunal densities observed in Pacific abyssal habitats,
and that productivity is more likely to be driving patterns
of macrofaunal abundance.
3. Suggested revision of the slope– abyss
source–sink hypothesis: the oligotrophic
sink hypothesis
Source–sink population dynamics ultimately arise from differences in ‘habitat quality’ that can occur over a variety of spatial
scales [9]. At the abyssal seafloor, some environmental parameters typically used to characterize habitat quality, such as
temperature, flow regime and substrate type, can be relatively
uniform over tens to thousands of kilometres. However, food
availability in the form of surface-derived POC flux has long
been known to exhibit spatial and temporal heterogeneity in
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taxonomic group
partial correlation coeff
adj R 2
s.e.
t-value
p-value
2651.243
805.977
211.292
99.636
23.082
8.089
0.003
,0.001
0.683
0.516***
24.308
1.740
22.476
0.016
20.275
0.547***
2471.397
76.247
26.182
,0.001
POC flux
Bivalvia
409.018
46.805
8.739
,0.001
0.713
0.501***
intercept
244.304
11.504
23.851
,0.001
POC flux
Gastropoda
39.141
7.062
5.543
,0.001
0.542
0.284***
intercept
POC flux
27.576
8.897
5.779
3.548
21.311
2.508
0.194
0.014
0.280
0.066**
251.880
14.367
23.611
0.001
POC flux
48.038
8.819
5.447
,0.001
0.535
0.277***
Tanaidacea
intercept
2137.814
26.435
25.213
,0.001
POC flux
DSUM
151.806
20.864
12.479
0.217
12.165
23.982
,0.001
,0.001
0.818
20.422
0.691***
0.742***
2114.111
93.758
18.844
11.567
26.056
8.105
,0.001
,0.001
0.686
0.463***
total macrofauna
intercept
POC flux
DSUM
Polychaeta
intercept
total Mollusca
intercept
Isopoda
intercept
POC flux
**p , 0.05, ***p , 0.001.
the deep sea, from the landscape scale of abyssal hills and valleys to the regional scales of oligotrophic gyres and upwelling
zones [2]. Direct measurements of POC flux at abyssal depths
are relatively rare, but recent modelling efforts estimate
fluxes for the global ocean that clearly demonstrate this variability in food availability (e.g. [48]). Heterogeneous POC flux
could thus produce areas of higher or lower habitat quality
over spatial scales relevant to larval dispersal.
Biomass and diversity are generally elevated in high-flux
areas of the deep sea (e.g. [23,35,61]) distant from slope or
shelf areas, suggesting these regions constitute high-quality
habitat relative to areas underlying oligotrophic central
gyres. These areas (e.g. the equatorial Pacific upwelling
zone) are just as likely to function as ‘sources’ of dispersive
larvae as are productive areas along the continental margins.
Considering higher-flux abyssal regions as potential larval
source areas greatly increases both the effective population
size and the geographical area from which to draw the pool
of potential colonists for abyssal sediments. Moreover, potential distances larvae must travel to reach low-productivity
regions are significantly reduced. Considering source –sink
dynamics as a eutrophic –oligotrophic phenomenon encompassing the entire deep seafloor thus overcomes limitations
of the strict slope –abyss interpretation. Nonetheless, for
species lacking long-distance (approx. 1000 km) dispersal
abilities (such as diverse groups of direct developers and
brooders), even the oligotrophic central gyres are very
unlikely to contain pure sink populations.
(a) Identifying abyssal source and sink habitats
According to classic definitions of source and sink habitats (cf.
[9,31]), demographic sinks are areas in which local population
growth rates are less than 0; thus, sub-optimal habitats are
often demographic sinks, while source areas are found in
areas of high-quality habitat. For the food-poor abyssal
seafloor, productivity is likely to be the most effective predictor
of habitat quality for many soft-sediment organisms. Analyses
presented above add additional support to the body of evidence that benthic standing stock in the abyss is best
predicted by POC flux, suggesting that the abyssal equatorial
Pacific Ocean and Southern Ocean may serve as source areas
of diversity for taxa with long-distance dispersal that can
enhance the regional species pool. Productivity patterns may
further distinguish areas where slope–abyss source–sink
dynamics are particularly unlikely to occur. For example, the
abyssal Southern Ocean is within reach of the Antarctic continental shelf and is also characterized by relatively high levels
of POC flux [48]. Thus, any effects of dispersal from the
slope on abyssal populations are likely to be masked by effects
Proc. R. Soc. B 282: 20150193
beta coeff
6
rspb.royalsocietypublishing.org
Table 1. Summary of multiple linear regressions of abundance (no. individuals m22) against depth, latitude, DSUM and POC flux to the seafloor. Only those
variables that were retained in the regression models are listed below. For the best-fit model (i.e. including all predictor variables retained), the adjusted R 2
values (adj R 2) are given in bold, preceded by the values for other models containing fewer predictor variables where p , 0.05.
Downloaded from http://rspb.royalsocietypublishing.org/ on June 17, 2017
Some have suggested that the only true test of whether an area
functions as a sink habitat is to isolate it from dispersal and then
to monitor it to see if purported ‘sink’ populations disappear
[31,67]; this is not a tractable scenario for abyssal seafloor
studies. Nonetheless, two key pieces of information may indicate whether source–sink dynamics exist between two habitat
patches: detailed demographic data to confirm that local population growth rates are less than 0 in the sink habitat, and
information on directional movement or dispersal between
sources and sinks [67]. Demographic data could be used to
distinguish a true demographic sink from what is simply a
lower-quality habitat with reduced carrying capacity. Alternatively, indicators of habitat quality (e.g. food availability) may
be evaluated with respect to their effects on population dynamics, reproduction rates or individual fitness. For example,
measurements of fitness such as fecundity or proportions of
Data accessibility. Source code for the LSSI model has been deposited to
Dryad Digital Repository http://dx.doi.org/10.5061/dryad.1s445.
The dataset used for regression analysis was compiled from multiple
sources, as described in the text, and uploaded as electronic
supplementary material.
Acknowledgements. We thank M. Rex and C. McClain for thoughtful and
lively discussions that helped shape the ideas presented here. We also
thank C. Morgan and D. Tittensor for assistance with data processing.
We thank the ABYSSLINE Project (Seabed Resources Development
Ltd) for their support of CRS, resulting in insights into the structure
of abyssal communities that shaped this manuscript.
Funding statement. The International Seabed Authority supported the
compilation of abundance data used in the modelling effort through
an award to C.R.S.
Authors’ contributions. S.M.H. compiled the macrofaunal abundance data
from the abyssal Pacific and conducted the regression analysis. A.M.T.
and C.R.S. designed and constructed the LSSI model, conducted
model runs and produced figure 1. S.M.H. drafted the manuscript.
All authors collaborated in design of the study, contributed towards
manuscript writing and gave final approval for publication.
Conflict of interests. The authors have no competing interests.
References
1.
2.
3.
Thistle D. 2003 The deep-sea floor: an overview. In
Ecosystems of the deep oceans (ed. PA Tyler), pp. 5–
37. Amsterdam, The Netherlands: Elsevier Science.
Smith CR, De Leo FC, Bernardino AF, Sweetman AK,
Arbizu PM. 2008 Abyssal food limitation, ecosystem
structure and climate change. Trends Ecol. Evol. 23,
518–528. (doi:10.1016/j.tree.2008.05.002)
Levin LA, Etter RJ, Rex MA, Gooday AJ, Smith CR, Pineda
J, Stuart CT, Hessler RR, Pawson DL. 2001 Environmental
influences on regional deep-sea species diversity. Annu.
4.
5.
Rev. Ecol. Syst. 32, 51–93. (doi:10.1146/annurev.
ecolsys.32.081501.114002)
Snelgrove PV, Smith CR. 2002 A riot of species in an
environmental calm: the paradox of the species-rich
deep-sea floor. Oceanogr. Mar. Biol. Annu. Rev. 40,
311 –342.
Rex MA, McClain CR, Johnson NA, Etter RJ, Allen JA,
Bouchet P, Waren A. 2005 A source–sink
hypothesis for abyssal biodiversity. Am. Nat. 165,
163 –178. (doi:10.1086/427226)
6.
7.
8.
Courchamp F, Clutton-Brock T, Grenfell B.
1999 Inverse density dependence and
the Allee effect. Trends Ecol. Evol.
14, 405 –410. (doi:10.1016/S0169-5347(99)
01683-3)
Pulliam HR. 1988 Sources, sinks, and
population regulation. Am. Nat. 132, 652–661.
(doi:10.1086/284880)
Dias PC. 1996 Sources and sinks in
population biology. Trends Ecol. Evol. 11,
7
Proc. R. Soc. B 282: 20150193
(b) Testing the ‘oligotrophic sink hypothesis’ in the
deep sea: directions for future research
reproductive individuals could be compared between proposed
source and sink habitats.
Directional dispersal between abyssal habitat patches
may be more challenging to quantify. Modelling may be
needed to estimate transport rates of small particles in
abyssal currents. However, empirical observations are also
needed to constrain such models, and these observations
are still rare at abyssal depths. Genetic tests of population
differentiation are frequently applied in marine dispersal
studies and can yield some evidence of the distances over
which dispersal is likely to be acting (e.g. [68,69]), and/or
the presence of potential sink populations (genetic diversity
is often depressed in marginal or sink populations due to
small effective population size [31]). However, genetic studies
provide limited information on directionality of dispersal,
and are particularly poorly suited to examining processes
occurring over ecological time scales, such as single dispersal
events. For example, immigration rates required to maintain
genetic connectivity (often taken to be one individual per
entire population per generation) can be orders of magnitude
lower than those required to maintain a non-reproducing
sink population (equivalent to at least the average population
density per unit area per generation) [70]. Ultimately, identifying the directions and rates of abyssal larval dispersal
to maintain potential sink populations will require studies
of abyssal hydrodynamics, as well as larval distribution
and behaviour, and may require innovative larval tracking and modelling techniques such as those recently
applied in shallow-water ecosystems (e.g. [71,72]).
rspb.royalsocietypublishing.org
of high local productivity [62]. In fact, the abyssal Southern
Ocean may have provided a source of propagules to recolonize the Antarctic slope and shelf following species
extinctions during glacial periods [62,63].
Particular taxa may be more or less susceptible to source–
sink dynamics based on life-history patterns. In particular,
populations of species lacking dispersive larval stages will be
largely unaffected by source–sink dynamics [64,65], and as
mentioned above, these groups represent the most abundant
and diverse taxa found in the abyss. However, adaptive evolution in sink habitats can lead to increased survival and
reproduction, to the degree that the habitat no longer functions
as a sink [31]. In particular, sink populations that are unsustainable without dispersal or immigration and do receive a supply
of immigrants may experience high rates of niche evolution
[66]. These populations may, following lengthy periods of
maladaptation to the sink habitat, shift rapidly into an adapted
state in which stable population size no longer depends on
immigration. In this scenario, extreme oligotrophy may have
led to new adaptations and adaptive radiation. Currently
stable abyssal populations may well have functioned as sinks
in the past, especially if they evolved from slope species. In
short, many species-rich, poorly dispersing taxa appear to be
well adapted to abyssal oligotrophic conditions, whereas taxa
with widely dispersing larvae (e.g. gastropods and bivalves)
may be poorly adapted, but persist as sink populations in
areas of the oligotrophic abyss.
Downloaded from http://rspb.royalsocietypublishing.org/ on June 17, 2017
10.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
sciences, 1776–1976. Acad. Natl Sci. Spec. Publ. 12,
223–243.
Poore GCB, Wilson GDF. 1993 Marine species
richness. Nature 361, 597– 598. (doi:10.1038/
361597a0)
McClain CR, Hardy SM. 2010 The dynamics of
biogeographic ranges in the deep sea. Proc. R. Soc.
B 277, 3533 –3546. (doi:10.1098/rspb.2010.1057)
Hilário A, Metaxas A, Gaudron S, Howell K,
Mercier A, Mestre N, Ross RE, Thurnherr A,
Young C. 2015 Estimating dispersal distance in the
deep sea: challenges and applications to marine
reserves. Front. Mar. Sci. 2, 6. (doi:10.3389/fmars.
2015.00006)
Davis RE. 1998 Preliminary results from directly
measuring middepth circulation in the tropical
and South Pacific. J. Geophys. Res. Oceans 103,
24 619 –24 639. (doi:10.1029/98JC01913)
Ledwell JR, Montgomery ET, Polzin KL, St. Laurent
LC, Schmitt RW, Toole JM. 2000 Evidence for
enhanced mixing over rough topography in the
abyssal ocean. Nature 403, 179–182. (doi:10.1038/
35003164)
Bower AS, Lozier MS, Gary SF, Boning CW. 2009
Interior pathways of the North Atlantic meridional
overturning circulation. Nature 459, 243–247.
(doi:10.1038/nature07979)
Wijffels SE, Toole JM, Davis R. 2001 Revisiting the
South Pacific subtropical circulation: a synthesis of
World Ocean Circulation Experiment observations
along 328S. J. Geophys. Res. Oceans 106, 19 481–
19 513. (doi:10.1029/1999JC000118)
Hogg NG, Brechner Owens W. 1999 Direct
measurement of the deep circulation within the
Brazil Basin. Deep-Sea Res. II 46, 335–353. (doi:10.
1016/S0967-0645(98)00097-6)
Hautala SL, Riser SC. 1993 A nonconservative
b-spiral determination of the deep circulation in
the Eastern South Pacific. J. Phys. Oceanogr. 23,
1975– 2000. (doi:10.1175/1520-0485(1993)
023,1975:ANSDOT.2.0.CO;2)
Kallmeyer J, Pockalny R, Adhikari RR, Smith DC,
D’Hondt S. 2012 Global distribution of microbial
abundance and biomass in subseafloor sediment.
Proc. Natl Acad. Sci. USA 109, 16 213–16 216.
(doi:10.1073/pnas.1203849109)
Siegel DA, Kinlan BP, Gaylord B, Gaines SD. 2003
Lagrangian descriptions of marine larval dispersion.
Mar. Ecol. Prog. Ser. 260, 83 –96. (doi:10.3354/
meps260083)
Lutz MJ, Caldeira K, Dunbar RB, Behrenfeld MJ.
2007 Seasonal rhythms of net primary production
and particulate organic carbon flux describe
biological pump efficiency in the global ocean.
J. Geophys. Res. Oceans 112, C10011. (doi:10.1029/
2006JC003706)
Thurnherr AM, Speer KG. 2004 Representativeness
of meridional hydrographic sections in the western
South Atlantic. J. Mar. Res. 62, 37 –65. (doi:10.
1357/00222400460744618)
Talley LD, Johnson GC. 1994 Deep, zonal
subequatorial currents. Science 263, 1125–1128.
(doi:10.1126/science.263.5150.1125)
8
Proc. R. Soc. B 282: 20150193
11.
24.
diversity in the central Pacific abyss: local and
regional patterns, and relationships with
productivity. Mar. Ecol. Prog. Ser. 240, 157 –170.
(doi:10.3354/meps240157)
Neal L, Hardy SM, Smith CR, Glover AG. 2011
Polychaete species diversity on the West Antarctic
Peninsula deep continental shelf. Mar. Ecol. Prog.
Ser. 428, 119 –134. (doi:10.3354/meps09012)
Aldea C, Olabarria C, Troncoso JS. 2008 Bathymetric
zonation and diversity gradient of gastropods and
bivalves in West Antarctica from the South Shetland
Islands to the Bellingshausen Sea. Deep-Sea Res. 55,
350 –368. (doi:10.1016/j.dsr.2007.12.002)
Olabarria C. 2006 Faunal change and bathymetric
diversity gradient in deep-sea prosobranchs from
Northeastern Atlantic. Biodivers. Conserv. 15,
3685 –3702. (doi:10.1007/s10531-005-1344-9)
France SC, Kocher TD. 1996 Geographic and
bathymetric patterns of mitochondrial 16S rRNA
sequence divergence among deep-sea amphipods,
Eurythenes gryllus. Mar. Biol. 126, 633–643.
(doi:10.1007/BF00351330)
Zardus JD, Etter RJ, Chase MR, Rex MA, Boyle EE.
2006 Bathymetric and geographic population
structure in the pan-Atlantic deep-sea bivalve
Deminucula atacellana (Schenck, 1939). Mol. Ecol.
15, 639– 651. (doi:10.1111/j.1365-294X.2005.
02832.x)
Wagstaff MC, Howell KL, Bett BJ, Billett DSM, Brault
S, Stuart CT, Rex MA. 2014 b-diversity of deep-sea
holothurians and asteroids along a bathymetric
gradient (NE Atlantic). Mar. Ecol. Prog. Ser. 508,
177 –185. (doi:10.3354/meps10877)
Howell KL, Billett DSM, Tyler PA. 2002 Depthrelated distribution and abundance of seastars
(Echinodermata: Asteroidea) in the Porcupine
Seabight and Porcupine Abyssal Plain, NE Atlantic.
Deep-Sea Res. 49, 1901 –1920. (doi:10.1016/S09670637(02)00090-0)
Kawecki TJ. 2008 Adaptation to marginal habitats.
Annu. Rev. Ecol. Evol. Syst. 39, 321–342. (doi:10.
1146/annurev.ecolsys.38.091206.095622)
Tyler PA, Gage JD, Billett DSM. 1992 Reproduction
and recruitment in deep-sea invertebrate
populations in the NE Atlantic Ocean: a review of
the options. In Marine eutrophication and
population dynamics (eds G Colombo, I Ferrari,
VU Ceccherelli, R Rossi), pp. 257 –262. Fredensborg,
Denmark: Olsen & Olsen.
Tyler PA, Young CM. 1992 Reproduction in marine
invertebrates in ‘stable’ environments: the deep sea
model. Invertebr. Reprod. Dev. 22, 185 –192.
(doi:10.1080/07924259.1992.9672271)
Young CM. 2004 Reproduction, development and
life-history traits. In Ecosystems of the deep oceans
(ed. PA Tyler), pp. 381–426. Amsterdam, The
Netherlands: Elsevier Science.
Rex MA et al. 2006 Global bathymetric patterns of
standing stock and body size in the deep-sea
benthos. Mar. Ecol. Prog. Ser. 317, 1–8. (doi:10.
3354/meps317001)
Sanders HL. 1977 Evolutionary ecology and the
deep-sea benthos: the changing scene in natural
rspb.royalsocietypublishing.org
9.
326–330. (doi:10.1016/0169-5347(96)
10037-9)
Kawecki TJ. 2004 Ecological and evolutionary
consequences of source –sink population dynamics.
In Ecology, genetics, and evolution of
metapopulations (eds I Hanski, OE Gaggiotti), pp.
387–414. Burlington, MA: Elsevier.
Wedding LM, Friedlander AM, Kittinger JN, Watling
L, Gaines SD, Bennett M, Hardy SM, Smith CR. 2013
From principles to practice: a spatial approach to
systematic conservation planning in the deep sea.
Proc. R. Soc. B 280, 20131684. (doi:10.1098/rspb.
2013.1684)
Mengerink KJ et al. 2014 A call for deep-ocean
stewardship. Science 344, 696 –698. (doi:10.1126/
science.1251458)
Danovaro R, Gambi C, Dell’Anno A, Corinaldesi C,
Fraschetti S, Vanreusel A, Vincx M, Gooday AJ. 2008
Exponential decline of deep-sea ecosystem
functioning linked to benthic biodiversity loss. Curr.
Biol. 18, 1–8. (doi:10.1016/j.cub.2007.11.056)
Palumbi SR. 2003 Population genetics, demographic
connectivity, and the design of marine reserves.
Ecol. Appl. 13, S146 –S158. (doi:10.1890/10510761(2003)013[0146:PGDCAT]2.0.CO;2)
Rex MA. 1981 Community structure in the deep-sea
benthos. Annu. Rev. Ecol. Syst. 12, 331–353.
(doi:10.1146/annurev.es.12.110181.001555)
Tittensor DP, Rex MA, Stuart CT, McClain CR, Smith
CR. 2011 Species–energy relationships in deep-sea
molluscs. Biol. Lett. 7, 718–722. (doi:10.1098/rsbl.
2010.1174)
Stuart C, Rex M, Etter R. 2003 Large-scale spatial
and temporal patterns of deep-sea biodiversity. In
Ecosystems of the deep ocean (ed. PA Tyler), pp.
295–311. Amsterdam, The Netherlands: Elsevier.
Carney RS. 2005 Zonation of deep biota on
continental margins. Oceanogr. Mar. Biol. Annu.
Rev. 43, 211–278. (doi:10.1201/9781420
037449.ch6)
Hessler RR, Wilson GD, Thistle D. 1979 The deep-sea
isopods: a biogeographic and phylogenetic
overview. Sarsia 64, 67– 75.
Wilson GDF, Hessler RR. 1987 Speciation in the deep
sea. Annu. Rev. Ecol. Syst. 18, 185–207. (doi:10.
1146/annurev.es.18.110187.001153)
Allen JA, Sanders HL. 1996 The zoogeography,
diversity and origin of the deep-sea protobranch
bivalves of the Atlantic: the epilogue. Prog.
Oceanogr. 38, 95 –153. (doi:10.1016/S00796611(96)00011-0)
Hansen B. 1975 Systematics and biology of the
deep-sea holothurians. Part I: Elasipoda. Galathea
Rep. 13, 1 –262.
Moreno RA, Rivadeneira MM, Hernandez CE,
Sampertegui S, Rozbaczylo N. 2008 Do Rapoport’s
rule, the mid-domain effect or the source–sink
hypotheses predict bathymetric patterns of
polychaete richness on the Pacific coast of South
America? Glob. Ecol. Biogeogr. 17, 415 –423.
(doi:10.1111/j.1466-8238.2007.00372.x)
Glover AG, Smith CR, Patterson GLJ, Wilson GDF,
Hawkins L, Sheader M. 2002 Polychaete species
Downloaded from http://rspb.royalsocietypublishing.org/ on June 17, 2017
58.
59.
60.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
Biol. Ecol. 330, 327 –341. (doi:10.1016/j.jembe.
2005.12.037)
Ellingsen KE, Brandt A, Ebbe B, Linse K. 2007
Diversity and species distribution of polychaetes,
isopods and bivalves in the Atlantic sector of the
deep Southern Ocean. Polar Biol. 30, 1265 –1273.
(doi:10.1007/s00300-007-0287-x)
Holt RD, Gomulkiewicz R, Barfield M. 2003 The
phenomenology of nich evolution via quantitative
traits in a ’black-hole’ sink. Proc. R. Soc. Lond. B
270, 215–224. (doi:10.1098/rspb.2002.2219)
Diffendorfer JE. 1998 Testing models of source–sink
dynamics and balanced dispersal. Oikos 81,
417–433. (doi:10.2307/3546763)
Weersing K, Toonen R. 2009 Population genetics, larval
dispersal, and connectivity in marine systems. Mar. Ecol.
Prog. Ser. 393, 1–12. (doi:10.3354/meps08287)
Sotka EE, Palumbi SR. 2006 The use of genetic
clines to estimate dispersal distances of marine
larvae. Ecology 87, 1094– 1103. (doi:10.1890/00129658(2006)87[1094:TUOGCT]2.0.CO;2)
Levin LA. 2006 Recent progress in understanding larval
dispersal: new directions and digressions. Integr. Comp.
Biol. 46, 282–297. (doi:10.1093/icb/icj024)
Becker BJ, Levin LA, Fodrie FJ, McMillan PA.
2007 Complex larval connectivity patterns among
marine invertebrate populations. Proc. Natl Acad. Sci.
USA 104, 3267–3272. (doi:10.1073/pnas.0611651104)
Cowen RK, Sponaugle S. 2009 Larval dispersal and
marine population connectivity. Annu. Rev. Mar. Sci.
1, 443 –466. (doi:10.1146/annurev.marine.010908.
163757)
9
Proc. R. Soc. B 282: 20150193
61.
pp. 24– 86. La Jolla, CA: Scripps Institution of
Oceanography.
Wilson GDF. 1992 Biological evaluation of a
preservational reserve area: faunal data and comparative
analysis. Sydney, Australia: Australian Museum.
Smith CR, Demopoulos AWJ. 2003 The Deep Pacific
Ocean Floor. In Ecosystems of the deep oceans (ed.
PA Tyler), pp. 179 –218. Amsterdam, The
Netherlands: Elsevier Science.
International Seabed Authority. 2008 Biodiversity,
species ranges, and gene flow in the abyssal Pacific
nodule province: predicting and managing the
impacts of deep seabed mining. Technical study no.
3. Kingston, Jamaica: ISA.
Smith CR, Hoover DJ, Doan SE, Pope RH, DeMaster
KJ, Dobbs FC, Altabet MA. 1996 Phytodetritus at the
abyssal seafloor across 10 of latitude in the central
equatorial Pacific. Deep-Sea Res. II 43, 1309–1338.
(doi:10.1016/0967-0645(96)00015-X)
Brandt A, De Broyer C, De Mesel I, Ellingsen KE,
Gooday AJ, Hilbig B, Linse K, Thomson MRA, Tyler
PA. 2007 The biodiversity of the deep Southern
Ocean benthos. Phil. Trans. R. Soc. B 362, 39 –66.
(doi:10.1098/rstb.2006.1952)
Thatje S, Hillenbrand C-D, Mackensen A, Larter R.
2008 Life hung by a thread: endurance of Antarctic
fauna in glacial periods. Ecology 89, 682–692.
(doi:10.1890/07-0498.1)
Baguley JG, Montagna PA, Lee W, Hyde LJ, Rowe GI.
2006 Spatial and bathymetric trends in
Harpacticoida (Copepoda) community structure in
the Northern Gulf of Mexico deep-sea. J. Exp. Mar.
rspb.royalsocietypublishing.org
51. Smith WHF, Sandwell DT. 1997 Global seafloor
topography from satellite altimetry and ship depth
soundings. Science 277, 1956– 1962. (doi:10.1126/
science.277.5334.1956)
52. Smith CR, Berelson W, DeMaster DJ, Dobbs FC,
Hammond D, Hoover DJ, Pope RH, Stephens M.
1997 Latitudinal variations in benthic processes in
the abyssal equatorial Pacific: control by biogenic
particle flux. Deep-Sea Res. II 44, 2295 –2317.
(doi:10.1016/S0967-0645(97)00022-2)
53. Wei C-L et al. 2010 Global patterns and
predictions of seafloor biomass using random
forests. PLoS ONE 5, e15323. (doi:10.1371/journal.
pone.0015323)
54. Hessler RR, Jumars PA. 1974 Abyssal community
analysis from replicate box cores in the central
North Pacific. Deep-Sea Res. 21, 185 –209.
55. Snider LJ, Burnett BR, Hessler RR. 1984 The
composition and distribution of meiofauna and
nanobiota in a central North Pacific deep-sea area.
Deep-Sea Res. 31, 1225 –1249. (doi:10.1016/01980149(84)90059-1)
56. Smith KLJ. 1987 Food energy supply and demand: A
discrepancy between particulate organic carbon flux
and sediment oxygen consumption in the deep
ocean. Limnol. Oceanogr. 32, 201 –220. (doi:10.
4319/lo.1987.32.1.0201)
57. Wilson GDF, Hessler R. 1987 The effects of
manganese nodule test mining on the benthic
fauna in the North Equatorial Pacific. In
Environmental effects of deep sea dredging (eds
FN Speiss, R Hessler, G Wilson, M Weydert),