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Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity. Here we synthesize current knowledge on temperature-diversity relationships in the deep sea. Our results from both present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible that temperature is important only when at relatively high and low levels but does not play a major role in the intermediate temperature range. Possible mechanisms explaining the temperature-biodiversity relationship include the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea temperatures due to human-induced climate change may have more adverse consequences than expected considering the sensitivity of deep-sea ecosystems to temperature changes. © 2014 Cambridge Philosophical Society.
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Biol. Rev. (2016), 91, pp. 275287. 275
doi: 10.1111/brv.12169
Temperature impacts on deep-sea biodiversity
Moriaki Yasuhara1,and Roberto Danovaro2,3
1School of Biological Sciences, Swire Institute of Marine Science, and Department of Earth Sciences, The University of Hong Kong, Hong Kong,
China
2Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
3Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Napoli, Italy
ABSTRACT
Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely
what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ
photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity.
Here we synthesize current knowledge on temperaturediversity relationships in the deep sea. Our results from both
present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is
considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible
that temperature is important only when at relatively high and low levels but does not play a major role in the
intermediate temperature range. Possible mechanisms explaining the temperaturebiodiversity relationship include
the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of
these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going
global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea
temperatures due to human-induced climate change may have more adverse consequences than expected considering
the sensitivity of deep-sea ecosystems to temperature changes.
Key words: deep-sea, temperature, diversity, global warming, climate change.
CONTENTS
I. Introduction .............................................................................................. 276
II. Potential Controlling Factors of Deep-sea Biodiversity ................................................... 276
III. Evidence for an Effect of Temperature on Deep-sea Biodiversity ........................................ 277
(1) Temporal patterns .................................................................................... 277
(2) Spatial patterns ....................................................................................... 278
IV. TemperatureDiversity Relationship .................................................................... 280
(1) Positive relationships ................................................................................. 280
(2) Negative relationships ................................................................................ 280
(3) A unified unimodal relationship? ..................................................................... 280
V. Potential Mechanisms of TemperatureDiversity Relationship .......................................... 281
VI. Rates of Temperature Change ........................................................................... 283
VII. Sensitivity to Temperature Changes ..................................................................... 283
VIII. Future Directions ......................................................................................... 283
IX. Conclusions .............................................................................................. 284
X. Acknowledgements ....................................................................................... 285
XI. References ................................................................................................ 285
XII. Supporting Information .................................................................................. 286
* Address for correspondence (Tel: +852-2299-0317; E-mail: moriakiyasuhara@gmail.com; yasuhara@hku.hk).
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
276 Moriaki Yasuhara and Roberto Danovaro
I. INTRODUCTION
Correlation between temperature and marine diversity is
one of the most pervasive ecological phenomena not only in
the present day (Tittensor et al., 2010) but also throughout
the last 3 million years (Yasuhara et al., 2012b), and many
ecological and evolutionary hypotheses have been proposed
to explain the underlying mechanism for this correlation.
However, available large-scale diversity patterns in relation
to temperature are still limited to several taxa with sufficient
records due to the vastness and inaccessibility of the deep
sea, as well as costs associated with technologies needed for
deep-sea exploration. Moreover, the different hypotheses
proposed so far are still largely controversial (Willig,
Kaufman & Stevens, 2003; Currie et al., 2004; Danovaro,
Dell’Anno & Pusceddu, 2004; Yasuhara et al., 2009,
2012a,b; Brown & Thatje, 2014), thus further testing and
investigations are needed. Since present Intergovernmental
Panel on Climate Change (IPCC) scenarios indicate that
the temperature of most oceanic regions will change rapidly
in coming decades, a better understanding of the potential
responses to these changes is one of the main priorities in
current ecological research.
Palaeoceanographic and oceanographic studies indicate
that deep-sea bottom-water temperature can change over
various time scales. For example, during the Cenozoic, the
deep sea cooled by more than 10C over the last 60 million
years (Lear, Elderfield & Wilson, 2000). During the Late
Quaternary glacial/interglacial cycles, deep-sea temperature
was 4C cooler in glacials than in interglacials (Dwyer et al.,
1995; Sosdian & Rosenthal, 2009). Even on millennial and
centennial time scales, palaeoceanographic records indicate
1–2C deep-sea temperature changes (Farmer et al., 2011;
Cronin et al., 2012). Furthermore, recent oceanographic
studies showed dynamic temperature changes even over
periods as short as decades or a few years. For example,
rapid deep-water warming (0.1C per decade) over the last
50 years is known in the western Mediterranean (Bethoux
et al., 1990). A recent study in this region also reported rapid
drops in temperature (0.3C cooling within a few years)
linked to climate-driven episodic events (Danovaro et al.,
2004). In the Labrador Sea, deep-water temperature has
shown dynamic decadal variation for the last 60 years at
rates of change up to 0.5C per decade (van Aken, de
Jong & Yashayaev, 2011). Abrupt changes in deep-water
temperature also have been observed in relation to dense
shelf water cascading events, which are able to influence
physical and biological processes down to bathyal depths
(Canals et al., 2006).
Deep-sea temperature shows substantial differences,
especially among oceans, depths, and water masses (Fig. 1).
For example, deep-sea temperature is 1C warmer in the
North Atlantic Ocean compared to the North Pacific Ocean
at abyssal depths and much warmer at bathyal depths. Some
marginal seas such as the Mediterranean, the Red and the
Sulu seas have extremely high deep-sea temperature (from
13C for the Mediterranean to >20CfortheRedSeaat
2000 m depth). Some deep waters at high latitudes are very
cold, with temperatures close to 2C (e.g. Antarctic Bottom
Water). Two deep-water masses in the Atlantic Ocean show
distinct temperatures: colder Antarctic Bottom Water and
warmer North Atlantic Deep Water. Temperature typically
decreases with increasing water depth, except for some
very warm intermediate water masses (e.g. Mediterranean
Overflow Water in the Atlantic Ocean).
Even though the above-mentioned deep-sea temperature
changes and differences in space and time are not subtle,
bottom-water temperature has been rather neglected as a
possible controlling factor of deep-sea diversity because of
its relative stability in space and time compared to shallow-
marine systems. However, there is increasing evidence for sig-
nificant temperaturediversity relationships in the deep sea
(Danovaro et al., 2004; Yasuhara et al., 2009, 2014; O’Hara
& Tittensor, 2010). Moreover, it is likely that deep-sea
organisms are sensitive even to small temperature changes
because they live under temperature conditions with much
less daily and seasonal variation compared to shallow-marine
organisms, although taxa that originated in shallow-marine
environments and then penetrated into the deep sea (Rau-
pach et al., 2009) may have stronger tolerance to temperature
changes compared to deep-sea taxa originating at depth.
In this review, we explore and analyse the relationships
between deep-sea benthic alpha (local) diversity and tem-
perature reported from the world’s oceans; compare present
spatial and past temporal deep-sea temperaturebiodiversity
patterns; and show that the deep-sea temperaturediversity
relationship is positive at low temperatures (<5C) and
negative at high temperatures (>1015C). When con-
sidered over a sufficiently broad temperature range, the
temperaturediversity relationship appears to be unimodal,
although temperature may be important only at relatively
high (>1015C) and low (<5C) values and may not
play major role at intermediate temperatures. Ecological
theories (Allen, Brown & Gillooly, 2002; Currie et al., 2004)
consistently suggest a positive temperaturediversity rela-
tionship, but climatic impact projections (Hughes et al., 2003;
Cheung et al., 2009; Mora et al., 2013) often suggest negative
biological consequences of warming. The unimodal relation-
ship may be one of the keys to solving this fundamental
controversy in ecological and climate change sciences.
II. POTENTIAL CONTROLLING FACTORS OF
DEEP-SEA BIODIVERSITY
Temperature is not the sole factor potentially affecting
deep-sea biodiversity. Thus before investigating the
temperaturediversity relationship in detail, we first
summarize the existing hypotheses on the factors controlling
deep-sea biodiversity.
Evolutionary dynamics (Jablonski, Roy & Valentine,
2006) operate over long time scales (Jablonski et al., 2006),
larger scale (such as beta, gamma, and latitudinally binned)
diversity measures (Roy et al., 1998), and to a greater extent
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 277
30
25
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15
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0
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15
10
10
8
6
4
2
0
5
0
10
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0
ABC
DEF
0 m 1000 m 2000 m
3000 m 4000 m 5000 m
Fig. 1. Global temperature (C) distributions at (A) 0 m, (B) 1000 m, (C) 2000 m, (D) 3000 m, (E) 4000 m, and (F) 5000 m water
depths. Data from World Ocean Atlas 2009 (http://www.nodc.noaa.gov/OC5/WOA09/pr_woa09.html) . The map was created
using Ocean Data View (http://odv.awi.de/).
on coastal taxa (Tittensor et al., 2010). This is because (i)
longer time scales should include more extinctions and
speciations; (ii) alpha (local) diversity may better reflect
species coexistence, but beta, gamma, and latitudinally
binned diversities reflect regional-scale diversity largely
formed by the long-term dynamics of extinction and
speciation; (iii) coastal taxa are influenced to a greater extent
by geological time-scale events (e.g. sea-level changes, plate
tectonics) (Renema et al., 2008; Irizuki et al., 2009) because
of their narrow distribution along (often complex) coastlines
in which isolation of local communities is easily induced by
geological events. However, evolutionary dynamics may be
less important in shaping present-day oceanic and deep-sea
alpha diversity patterns. A recent study suggested that the
deep-sea latitudinal species diversity gradient is steeper in
interglacial periods and weaker or absent in glacial periods,
indicating that the latitudinal species diversity gradient is
largely produced by orbital-scale climate change instead
of more gradual evolutionary process involving speciation
and extinction (Yasuhara et al., 2009). Furthermore, there is
growing evidence from marine ecosystems that environmen-
tal parameters, in particular temperature, may be the most
important factor shaping recent large-scale biodiversity pat-
terns at least at the alpha diversity level and in oceanic and
deep-sea taxa (Tittensor et al., 2010; Yasuhara et al., 2012b).
Although there are several potentially important factors
for deep-sea biodiversity (Levin et al., 2001; Willig et al.,
2003), including the quantity and quality of particulate
organic carbon (POC) flux (or surface productivity), habitat
heterogeneity, and biotic interactions (Levin et al., 2001),
bottom-water temperature is one of the leading candidates
(Yasuhara et al., 2009, 2012a; Rex & Etter, 2010; Tittensor
et al., 2011; McClain et al., 2012). In ecological theory,
speciesenergy relationships (in the form of either chemical,
thermal, or radiation energy) are considered a potentially
unifying determinant of large-scale diversity patterns. Radi-
ation energy can be excluded in the deep sea because there
is no light there. Food availability (i.e. POC flux or surface
productivity) and temperature are not mutually exclusive;
both could potentially control deep-sea biodiversity depend-
ing on region and/or taxonomic groups (Yasuhara et al.,
2012a,c). Since other reviews have examined the importance
of POC flux (or surface productivity) for deep-sea biodiver-
sity (Rex et al., 2005; Rex & Etter, 2010), here we focus on
the impact of temperature in deep-sea ecosystems.
III. EVIDENCE FOR AN EFFECT OF
TEMPERATURE ON DEEP-SEA BIODIVERSITY
(1) Temporal patterns
Significant temperaturediversity relationships have been
found for various time scales of 101–104years (Figs 2 and
3). Cronin & Raymo (1997) first discovered a significant
temperaturediversity relationship in glacialinterglacial
climatic cycles. Cronin et al. (1999) showed the same
relationship over a millennial time scale. Subsequently, a
decadal biological monitoring study showed a significant
temperaturediversity relationship and identified temper-
ature as a primary driver of deep-sea diversity (Danovaro
et al., 2004). Because temperature may covary with POC
flux (an indicator of food availability), Hunt, Cronin & Roy
(2005) and Yasuhara et al. (2009) used multiple regression
modelling considering both temperature and POC flux, and
showed that temperature but not POC flux was a significant
predictor of deep-sea biodiversity in their palaeoecological
records of benthic ostracodes and foraminifera. Since most
of these studies were conducted in the North Atlantic
Ocean, Yasuhara et al. (2012a) investigated this pattern in
the Pacific Ocean, finding contrasting results between taxa.
Foraminiferal diversity showed a weak relationship with
temperature, but ostracode diversity showed a significant
unimodal relationship with POC flux. Thus, the dominant
driver may be taxon or region dependent. A recent North
Atlantic deep-sea palaeoecological study (Yasuhara et al.,
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
278 Moriaki Yasuhara and Roberto Danovaro
101
102
103
104
>105
Modern
ab
c
d
g
h
h
k
i
j
Temperature (°C)
0 5 10 15 20
f
Time scale (years)
NA
NA
e
Fig. 2. Summary of known deep-sea temperature – diversity relationships. Time scales and temperature ranges in studies investigating
this relationship are shown. Orange line: significant positive temperaturediversity relationship. Blue line: significant negative
temperaturediversity relationship. Black line: no significant relationship with temperature. a, Corliss et al. (2009) on benthic
foraminifera (see text and Tables 1 and 2 for our re-analysis); b, O’Hara & Tittensor (2010) on ophiuroids; c, McClain et al. (2012)
on gastropods and bivalves; d, Tittensor et al. (2011) on gastropods and bivalves; e, Yasuhara et al. (2012c) on benthic foraminifera
and ostracodes; f, Danovaro et al. (2004) on nematodes; g, Cronin et al. (1999) on benthic ostracodes; h, Hunt et al. (2005) on benthic
foraminifera; i, Yasuhara et al. (2009) on benthic ostracodes; j, Yasuhara et al. (2012a) on benthic foraminifera; k, Cronin & Raymo
(1997) on benthic ostracodes. NA, no data available.
2014) found a significant temperaturediversity relationship
even over multi-decadal and centennial time scales.
These results together suggest the presence of consistent
temperaturediversity relationships over time scales ranging
from 101to 104years.
These temporal patterns are derived mostly from palaeoe-
cological time series, and as such may lack information for
environmental parameters that do not have reliable geologi-
cal proxy records. However, most important environmental
parameters (temperature, POC flux, and seasonality of
surface productivity) usually considered in present-day
deep-sea biological studies (Tittensor et al., 2011; McClain
et al., 2012) are available as palaeo-proxies (Hunt et al.,
2005; Yasuhara et al., 2009, 2012a). Thus palaeoecological
time-series studies are reasonably comparable to present-day
deep-sea biological studies.
(2) Spatial patterns
Until recently, all studies on temperaturediversity
relationships used time-series data from either living or
fossil faunas; there was no work based on a present-day,
large-geographical-scale spatial dataset. Tittensor et al. (2011)
first attempted to test the speciesenergy hypothesis using
regression models and a large present-day faunal dataset
from the North Atlantic Ocean. Their results showed that
POC flux was a more important factor than temperature
for mollusc diversity. McClain et al. (2012) confirmed their
findings using a larger dataset covering the whole Atlantic
Ocean. However, O’Hara & Tittensor (2010) used a similar
modelling framework to demonstrate that temperature was
the strongest correlate of diversity for ophiuroids from
southwestern Pacific seamounts. In the Arctic Ocean, neither
temperature nor POC flux showed a significant relationship
with diversity (Yasuhara et al., 2012c).
To date, no temperaturediversity relationships have
been reported from the deep North Atlantic Ocean
based on present-day spatial data. Corliss et al.’s (2009)
benthic foraminifera study showed a significant correlation
between species diversity and seasonality of productivity,
but not surface productivity. Because they did not consider
bottom-water temperature, here we reanalyse their data
[foraminiferal diversity E(S200) (expected species richness
rarefied to 200 individuals; calculated from census data)
and environmental data for bottom-water temperature,
POC flux (calculated from surface productivity data; see
online supporting information Appendix S1 for details), and
seasonality of surface productivity (from Sun et al., 2006;
Corliss et al., 2009); see online Table S1] using regression
models and model-averaged parameter estimates (see online
Appendix S1 for the full methods). This re-analysis showed
a significant effect of temperature (Tables 1 and 2). All of
the best five models consistently indicated that bottom-water
temperature is a significant predictor of species diversity, and
model-averaging results showed that the coefficient for the
temperature term is significantly different from zero.
Present-day spatial faunal data show weaker support
for a temperaturediversity relationship compared to
temporal faunal data, although spatial (i.e. macroe-
cological) and temporal (i.e. time-series and palaeo-)
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 279
–2 –1 0 1 2 3 4
5
10
15
20
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35
Temperature (°C)
Species diversity E(S51)
Species diversity E(S51)
2 4 6 8 10 12 14
0
10
20
30
40
Temperature (°C)
Species diversity E(S51)
13.8 14.0 14.2
5
10
15
20
25
30
35
Temperature (°C)
AB
C
Fig. 3. Examples of deep-sea temperature diversity relationships. (A) Positive relationship from North Atlantic palaeo-time-series
dataset (Yasuhara et al., 2009). (B) Negative relationship from Mediterranean Sea biological time-series dataset (Danovaro et al.,
2004). (C) Unified unimodal relationship from present-day Atlantic Ocean and Mediterranean Sea spatial dataset (Danovaro et al.,
2009; Bongiorni et al., 2010; Bianchelli et al., 2013; Pusceddu et al., 2013; R. Danovaro, unpublished data; see online Table S2) (we
used the data from 1000 to 4000 m water depth only: see online Fig. S1). Species diversity shown as E(S51 ), species richness rarefied
to 51 individuals.
faunal data available to test the temperaturediversity
relationship are still limited (Fig. 2). This discrepancy
despite the ‘space-for-time’ substitution (Blois et al., 2013)
could arise because (i) the present-day spatial pattern is a
‘snapshot’, i.e. a composite of not only ecological-time-scale
consequences (including temperature control of coexistence
of species), but also evolutionary-time-scale consequences
(including speciation and extinction), and differences
between ecological and evolutionary responses could
obscure the relationship; (ii) rates of temperature change that
can not be examined using spatial data may be important;
(iii) present-day spatial studies tend to cover very broad
POC flux ranges (Tittensor et al., 2011; McClain et al.,
2012) that may overwhelm temperature effects; and (iv)the
temperaturediversity relationship is consistently significant
at a relatively low temperature range (0–5C), regardless
of the use of palaeo or present-day data (Fig. 2). In addition,
the dominant driver may be different at different time and
spatial scales (Gambi et al., 2014), for example a temperature
effectmaybestrongeroverlongertimescalesbuta
POC-flux effect may be stronger over shorter time scales.
However this is less plausible because the time-series studies
shown in Fig. 2 indicate consistency of the temperature
effect among different time scales. Significant temperature
effects are known even over short, decadal– centennial time
scales (Danovaro et al., 2004; Yasuhara et al., 2014).
Many environmental and biological factors covary
with water depth. But the fact that the temperature
diversity relationship is supported more strongly in
time-series studies than in present-day spatial studies strongly
implies that temperature, rather than other factors covarying
with water depth, has a primary effect on diversity because
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
280 Moriaki Yasuhara and Roberto Danovaro
Table 1. Best five regression models of present-day North Atlantic deep-sea foraminiferal species diversity E(S200 ) as a function of
temperature, POC flux, and seasonality of surface productivity. Several other models are shown for comparison. Geographic region
term is included in all models (see online Appendix S1 for full modelling methods)
Model T Coef. P Coef. P2Coef. SP Coef. r2AICcAW
Foraminiferal E(S200) models with the Lutz et al. (2007) POC flux as P
16.880 0.56 250.6 0.451
27.694 ——21.887 0.57 252.4 0.187
37.950 4.619 0.57 253.2 0.127
47.142 1.706 19.471 0.60 253.2 0.124
56.500 6.371 22.440 33.610 0.62 254.8 0.056
SP 16.817 0.36 265.8 0.000
P—13.573 0.43 260.9 0.003
P2+P— 15.019 26.459 0.50 259.2 0.006
Null 0.35 263.6 0.001
Foraminiferal E(S200) models with the Pace et al. (1987) POC flux as P
16.880 0.56 250.6 0.489
27.694 ——21.887 0.57 252.4 0.202
36.759 0.208 0.56 253.6 0.112
46.222 0.126 4.480 0.59 254.0 0.092
56.955 1.627 27.406 0.58 255.2 0.050
SP 16.817 0.36 265.8 0.000
P—5.575 0.45 259.6 0.006
P2+P— 4.929 5.692 0.50 258.9 0.008
Null 0.35 263.6 0.001
T, temperature; SP, seasonality of surface productivity; P, particulate organic carbon (POC) flux; P2, quadratic term of POC flux.
The table shows the coefficient for each term (T Coef., P Coef., P2Coef., SP Coef.), r2, the Akaike information criterion corrected for small
sample size (AICc), and the Akaike weight (AW).
Bold denotes significance at P<0.05.
time-series studies do not involve water-depth change.
Glacial– interglacial sea-level changes of 120 m (Yokoyama
et al., 2000) have an almost negligible effect in palaeoe-
cological time-series studies in sites >1000– 2000 m water
depths.
IV. TEMPERATUREDIVERSITY
RELATIONSHIP
As discussed above, evidence is accumulating for a
relationship between temperature and diversity. However,
studies have identified two apparently opposite relationships,
i.e. positive and negative.
(1) Positive relationships
Most temperaturediversity relationships reported previ-
ously are positive, meaning that species diversity increases
with increasing temperature (Fig. 2). All fossil evidence shows
a positive temperaturediversity relationship (Cronin &
Raymo, 1997; Cronin et al., 1999; Hunt et al., 2005; Yasuhara
& Cronin, 2008; Yasuhara et al., 2012b, 2014). Our reanal-
ysis of present-day North Atlantic deep-sea foraminiferal
diversity also shows this positive relationship (Tables 1 and 2).
(2) Negative relationships
Negative temperaturediversity relationships are known
from nematode time series records from the deep
Mediterranean Sea (Danovaro et al., 2004) and from present-
day ophiuroid data from southwestern Pacific seamounts
(O’Hara & Tittensor, 2010) (Fig. 2).
(3) A unified unimodal relationship?
The negative relationships reported previously were from
relatively warm deep seas including the warm marginal sea of
the Mediterranean (Fig. 3B) and relatively shallow (and thus
warmer) seamounts. By contrast, the positive relationships
are typically reported from colder deep-sea systems (<5C;
Fig. 3A). Thus, over a broad range of temperatures, the
temperaturediversity relationship could be unimodal
with a peak, for deep-sea organisms, at around 510C
(Model 1 in Fig. 4). According to Schulte, Healy & Fangue
(2011), the thermal performance of organisms increases as
temperature increases, reaches a maximum at intermediate
temperatures, and then rapidly decreases. This pattern may
be applicable also to species diversity, as a lower biological
performance of many species can result in lower biodiversity
and vice versa. Accordingly, if diversity patterns are controlled
by the physiological tolerance of deep-sea organisms (as
discussed in Section V), the unimodal temperaturediversity
curve may be ‘right skewed’, following the thermal
performance curve of biological rate processes (Schulte
et al., 2011), characterized by a gradual diversity increase at
low temperatures (<10C), a maximum at intermediate
temperatures (1015C), and then a rapid decrease at high
temperatures (>15C) (Model 2 in Fig. 4). If a majority
of species have similar thermal performance curves, they
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 281
Table 2. Model-averaged parameter estimates and confidence
intervals of present-day North Atlantic deep-sea foraminiferal
species diversity E(S200)
Term RI Coefficient Lower CI Upper CI
Foraminiferal E(S200) models with the Lutz et al.
(2007) POC flux as P
R-SPA 1 4.13 13.73 5.48
R-TEA 1 1.18 8.14 5.79
R-TWA 1 6.98 1.67 12.29
T 0.98 7.21 3.01 11.42
P 0.36 0.28 20.75 20.20
SP 0.29 24.94 75.59 25.70
P20.19 20.91 4.06 45.87
Foraminiferal E(S200) models with the Pace et al. (1987)
POC flux as P
R-SPA 1 4.20 13.53 5.13
R-TEA 1 1.33 8.30 5.63
R-TWA 1 7.15 1.91 12.40
T 0.98 6.96 2.98 10.94
P 0.31 0.87 5.27 7.00
SP 0.29 23.28 69.00 22.44
P20.14 4.53 1.49 10.55
T, temperature; SP, seasonality of surface productivity; P,
particulate organic carbon (POC) flux; P2, quadratic term of POC
flux; R, geographic regions (SPA, subpolar North Atlantic; TEA,
tropical eastern North Atlantic; TWA, tropical western North
Atlantic); RI, relative importance; CI, confidence interval.
Bold denotes CIs that exclude zero.
will have optimum habitat ranges at similar midhigh
temperatures, and thus species diversity will be higher at
these temperatures. This prediction is supported by a nema-
tode dataset (Danovaro et al., 2009; Bongiorni et al., 2010;
Bianchelli et al., 2013; Pusceddu et al., 2013; R. Danovaro,
unpublished data) covering a broad temperature range
which shows a significant, unimodal, temperaturediversity
relationship and also a rapid diversity decrease at the highest
temperatures (Fig. 3C; see online Table S2).
The third model (Model 3 in Fig. 4) describes the case
in which temperature is important only at relatively high
(negative relationship), i.e. >1015C, and low (positive
relationship), i.e. <5C, temperatures but does not play
major role at intermediate temperatures, where another
factor such as POC flux instead may play a major role
(Tittensor et al., 2011; McClain et al., 2012). This model may
be consistent with the absence of a significant relationship
in studies covering a broad temperature range (Tittensor
et al., 2011; McClain et al., 2012). However, studies based
on present-day spatial data covering a broad temperature
range are still very limited (Fig. 2); further studies are needed
to test these three models rigorously.
V. POTENTIAL MECHANISMS OF
TEMPERATUREDIVERSITY RELATIONSHIP
There are several possible hypotheses explaining the
temperaturediversity relationship, including the physio-
logical tolerance hypothesis (Currie et al., 2004), metabolic
hypothesis (Allen et al., 2002), and island biogeography the-
ory (MacArthur & Wilson, 1967; Boucher-Lalonde, Kerr &
Currie, 2014). The physiological tolerance hypothesis sug-
gests that species richness in a particular area is limited by
the number of species that can tolerate the local conditions
(Currie et al., 2004). Currie et al. (2004) originally suggested
that richness and climate may covary simply because fewer
species can physiologically tolerate conditions in colder places
a
b
g
h
k
i
j
Temperature (°C)
0 5 10 15 20
f
Diversity
High
Low
Model 1
Model 2
Model 3
Fig. 4. Conceptual diagram showing potential relationship between temperature and deep-sea biodiversity. The deep-sea
temperaturediversity relationship may be unimodal (Model 1, black curve), ‘right-skewed’ unimodal (Model 2, grey curve), or
present only at relatively high and low temperature ranges (Model 3, dotted lines). See text for further details. Lines labelled a, b,
fk are known deep-sea temperaturediversity relationships (see Fig. 2 for details).
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
282 Moriaki Yasuhara and Roberto Danovaro
than in warmer places. This proposal could be modified and
applied to the unimodal relationship suggested here: fewer
species can physiologically tolerate conditions in extremely
cold or warm places than in other sites and, as a result,
diversity shows a peak at intermediate temperatures. This
is reasonable because it is obvious that not only relatively
cold but also relatively hot conditions are detrimental, espe-
cially for deep-sea organisms that typically are adapted to
low temperatures (Bouchet & Taviani, 1992; Carney, 2005).
Some (perhaps stenotherm) species can be at the upper limit
of their thermal tolerance in relatively warm deep sea such
as the deep Mediterranean [e.g. deep-water coral Lophelia
pertusa (Brooke et al., 2013)], so that further temperature
increases can reduce their biotic potential and long-term sur-
vival, and resulting biodiversity. This physiological-tolerance
explanation is also consistent with well-known unimodal
depthdiversity relationships (Rex, 1981; Rex & Etter, 2010;
Yasuhara et al., 2012c), in which diversity is lower both
in very shallow (i.e. high-temperature) and very deep (i.e.
low-temperature) zones. Furthermore, the spatial limits of
many marine species are known to be affected by thermal
gradients (Sunday, Bates & Dulvy, 2012).
Deep-sea alpha diversity may be maintained by
across-depth and across-region migrations as permitted by
species’ physiological tolerances (Carney, 2005). Bathymetric
(i.e. down-slope and up-slope) migrations during warming
and cooling periods tracking temperature tolerances have
indeed been hypothesized as one of the mechanisms
controlling temporal shifts in deep-sea species diversity
(Rodriguez-Lazaro & Cronin, 1999; Yasuhara et al., 2008,
2009). In marginal seas of the North Atlantic Ocean,
geographical migration of ‘Atlantic species groups’ is known
to be a crucial driver of deep-sea biodiversity. In relatively
cold Nordic seas, deep-sea foraminiferal species diversity
increased during warmer periods by migration of diverse
‘Atlantic species groups’ from warmer North Atlantic proper
during the late Quaternary (Rasmussen et al., 2003). In the
warm deep Mediterranean Sea, it is known that the intrusion
of diverse Atlantic nematode species following an abrupt
temperature decrease enhanced deep-sea nematode species
diversity (Danovaro et al., 2004). Thus, both upper and lower
tolerance limits control depth and geographical migrations
of deep-sea species, and resulting alpha diversity.
The original version of the metabolic hypothesis predicts
that higher temperatures enhance metabolic efficiency and
thus reproduction and that these enhancements potentially
result in an increased speciation rate and species diversity
(Allen et al., 2002). However, there is increasing evidence
that modern-day alpha species diversity patterns can be
shaped over ecological time scales without considerable
speciation or extinction in many ecosystems (Yasuhara et al.,
2009, 2012b; Boucher-Lalonde et al., 2014). Furthermore,
many time-series studies using biological and palaeonto-
logical data showed temperaturediversity relationships
to be present over ecological time scales (Danovaro et al.,
2004; Hunt et al., 2005; Yasuhara et al., 2009). As a con-
sequence, these temperaturediversity relationships must
be explained by ecological processes and/or interactions
(Storch, 2003; Hunt et al., 2005; McClain et al., 2012)
rather than by speciation rates (Allen et al., 2002; Currie
et al., 2004; Brown & Thatje, 2014). Recent studies have
suggested that temperature-induced metabolic changes
could affect ecological interactions between species (Storch,
2003; Hunt et al., 2005; McClain et al., 2012). Such
ecological interactions may include Allee effects, guild
interactions, species coexistence, and niche overlap.
All these factors may affect biodiversity, as suggested
with chemical-energy-induced (i.e. carbon-flux-induced)
metabolic changes (McClain et al., 2012). However, the
certain mechanisms are still largely unknown and further
empirical and mechanistic studies are needed. In addition,
the descending arm of the unimodal temperaturediversity
relationship is difficult to explain using the metabolic
hypothesis because the metabolic hypothesis posits a
positive temperaturediversity relationship. Moreover, the
descending arm occurs at temperatures >10C, for which
enzymatic activities are known to be generally favoured;
most enzymatic systems typically decrease their performance
only at temperatures higher than 30C (Childress, 1995;
Cavicchioli et al., 2002). Furthermore, it has been suggested
that the metabolic theory of ecology is poor predictor for
diversity-level phenomena (Hawkins et al., 2007).
Island biogeography theory proposes that richness
depends upon an equilibrium between colonization
and extinction rates (MacArthur & Wilson, 1967;
Boucher-Lalonde et al., 2014). Deep-sea alpha diversity may
be controlled by immigration from a regional species pool
(that is much larger than local diversity) and local extinction
rate, and both may be modulated by temperature (Boucher-
Lalonde et al., 2014), although the underlying mechanisms
are largely unknown. The importance of regional processes
themselves on alpha diversity (known as regional enrichment)
is becoming increasingly well understood in various ecosys-
tems including deep sea (Ricklefs, 1987; Rex & Etter, 2010).
In fact, the size of the regional species pool (i.e. regional
diversity) controls deep-sea alpha diversity (Stuart & Rex,
1994; Rex & Etter, 2010). However regional enrichment
cannot explain the temperaturediversity relationship in
the time-series records reviewed herein, because the size of
the regional species pool would not change over ecological
time scales, given no speciation and extinction. Thus,
immigration and local extinction (i.e. island biogeography
theory) may be more important than the size of the regional
species pool itself (i.e. regional enrichment), at least in terms
of the temperaturediversity relationship.
The last possibility is that the ascending and descending
arms of the curve may be explained by different combinations
of the physiological tolerance hypothesis (Currie et al.,
2004), metabolic hypothesis (Allen et al., 2002), or island
biogeography theory (MacArthur & Wilson, 1967; Boucher-
Lalonde et al., 2014). A positive relationship at low
temperatures and a negative relationship at high
temperatures may not necessarily be caused by a single
mechanism.
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 283
VI. RATES OF TEMPERATURE CHANGE
We know little about the impact of rates of
temperature change on deep-sea biodiversity. Among
the biological and palaeoecological time-series studies
reviewed herein, the shortest (i.e. months to years) time-scale
study (Danovaro et al., 2004) is the only one to show a
negative temperaturediversity relationship with all other
time-series studies showing a positive relationship, suggesting
that the rate of temperature change may be significant in
deep-sea biodiversity. The extent to which the negative
relationship observed by Danovaro et al. (2004) was due
to the rapid rate of temperature change rather than due
to the higher temperature itself is not clear, but it may be
hypothesized that this response depends, at least partially, on
the body size and generation time of the investigated taxa.
Smaller organisms have a higher surface area relative to body
volume and thus may be more sensitive to rapid temperature
change (although this may be less relevant to poikilotherms),
and shorter generation times may allow more rapid responses
or adaptation. Small species such as nematodes, that typically
display generation times between a few days and several
months (Heip, Vincx & Vranken, 1985), will react strongly
and rapidly to temperature changes but also may adapt to
such changes through generations. Conversely large-biomass
taxa with much longer generation times (often >5–10years;
such as molluscs, deep-sea solitary corals, brachiopods, and
echinoderms; Gage & Tyler, 1991) will be more resistant to
the effects of rapid changes, but then may be unable to adapt
over short time scales. We argue that rates of temperature
change in the deep sea are potentially important in selecting
winner and loser species in the deep sea. Understanding
this aspect could become one of the future priorities for a
better comprehension of the effects of temperature change
on deep-sea biodiversity. However, we do not know the
temperature tolerance of most (if not almost all) deep-sea
species, and it remains the case that temperature itself could
be the most important controlling factor of deep-sea species
diversity. In fact, our findings could be simply explained by
the unimodal temperaturediversity relationship without
considering rates of temperature change.
VII. SENSITIVITY TO TEMPERATURE CHANGES
Besides the importance of the direction of the relationship
(positive versus negative) between temperature and deep-sea
biodiversity, another crucial factor is the sensitivity of
different taxa to changes in temperature. Deep-sea taxa
are likely to be more sensitive to temperature changes
than coastal taxa in general, because deep-sea temperature
is relatively stable, especially over daily and seasonal
time scales, compared to shallow-marine environments.
In addition, benthic components of the biota are likely
to be more sensitive to temperature changes than
pelagic components (especially piezotolerant organisms and
those migrating within the water column) for the same
reason (i.e. bottom-water temperature is relatively stable
compared to surface-water temperature). Thermal tolerance
of deep-sea species will clearly be higher for species showing a
wide bathymetric distribution, such as some cold-water corals
belonging to the genera Dendrophyllia and Desmophyllum,whose
distribution spans 8 to >4000 m water depth (Naumann,
Orejas & Ferrier-Pages, 2013). Information on deep-sea taxa
is extremely limited but a temporal analysis conducted in the
deep Mediterranean Sea indicates that minor temperature
shifts in the order of 0.1C or less are sufficient to
cause significant changes in biodiversity and community
structure of deep-sea nematode assemblages (Danovaro et al.,
2004). Nematodes are the numerically dominant component
of marine sediments accounting for more than 90% of
the abundance of all benthic organisms in the deep sea
(Lambshead, 2004; Danovaro et al., 2009). Since nematodes
are direct developers (i.e. lack a planktonic larval stage), they
do not experience variations in temperature through their
short life (often in the order of weeks), meaning that they are
an example of a stenothermic deep-sea organism.
VIII. FUTURE DIRECTIONS
To better understand the temperaturediversity relationship
in the deep sea, we need to focus future studies in six main
directions.
(1) We need more information on short (101
102year) time scales using either biological time-series
data or exceptionally highly resolved microfossil
records, because these time scales are directly
relevant to on-going global warming as recent
climate projections show deep-water warming by
2100 (Mora et al., 2013). The available biological and
palaeontological evidence from these time scales is
still very limited (Cannariato, Kennett & Behl, 1999;
Danovaro et al., 2004; Wollenburg, Mackensen &
Kuhnt, 2007; Yasuhara et al., 2008, 2014).
(2) We need more large-spatial-scale data on deep-sea
biodiversity, covering wide geographic and tempera-
ture ranges, to determine which model best fits the
data. It may be important to use a dataset from
an intermediate water depth range (e.g. focusing
on the bathymetric range 10004000 m) as applied
in many large-geographical-scale studies (Culver &
Buzas, 2000; Rex, Stuart & Coyne, 2000; Lambshead
et al., 2002; Corliss et al., 2009), because, for example,
shallower uppermost bathyal sites have unusually high
POC fluxes compared to ordinary deep-sea sites that
may overwhelm the effects of temperature and make
it undetectable. Very deep sites (>5000 m) below lyso-
cline or carbonate compensation depth are under
the influence of corrosive bottom waters that result
in unusually severe conditions for organisms with
calcareous shells or parts. Such studies will help to
understand the role of temperature in food-limited
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
284 Moriaki Yasuhara and Roberto Danovaro
deep-sea ecosystems. In fact, our nematode dataset
shows a much noisier temperaturediversity relation-
ship (r2=0.094, P<0.001) when we include all data
(i.e. not only the data from 1000 to 4000 m but also the
data from <1000 to >4000 m water depth) than for the
1000– 4000 m depth data only (r2=0.300, P<0.001;
see online Fig. S1). If sufficient large-spatial-scale data
were available, it would be possible to use statistical
modelling not only for the entire dataset but also for
low-temperature and high-temperature ranges sepa-
rately. Model 1 would be supported if all of these
approaches show a significant temperaturediversity
relationship (i.e. unimodal for the entire dataset, pos-
itive for the low-temperature range, and negative for
the high-temperature range) and if the slopes of the
temperaturediversity relationships in the low- and
high-temperature ranges were similar. Model 2 will
be supported if the slope of the temperaturediversity
relationship over the high-temperature range is signifi-
cantly steeper than that in the low-temperature range.
Model 3 will be supported if the entire dataset shows a
much weaker temperaturediversity relationship than
for separately constructed relationships in low- and
high-temperature ranges.
(3) We need comprehensive data from other oceans than
the North Atlantic. The majority of the data reviewed
herein are from the North Atlantic Ocean; additional
data from other oceans are needed to test our models of
the temperaturediversity relationship rigorously. For
example, the recent discovery of unexpectedly high
Southern Ocean deep-sea biodiversity (Brandt et al.,
2007) strongly suggests that more research is needed
especially in the southern hemisphere, where deep-sea
biology data are limited (Rex & Etter, 2010). We also
need more data from warm deep oceans, such as the
Mediterranean, the Red and the Sulu seas.
(4) The underlying mechanisms explaining the
temperaturediversity models are still uncertain,
although several hypotheses are available: the physio-
logical tolerance hypothesis, metabolic hypothesis, and
island biogeography theory. Future research should
test these hypotheses by inter-region comparisons or
mesocosm experiments. ‘Top-down’ hypotheses (i.e.
metabolic hypothesis and island biogeography theory)
predict that the environment (temperature in this
case) imposes top-down limits on species diversity,
regardless of species identity (Boucher-Lalonde et al.,
2014). Thus, temperaturediversity relationships will
be the same globally. By contrast, in ‘bottom-up’
hypotheses (i.e. the physiological tolerance hypothesis),
the environment (temperature in this case) controls
species diversity bottom-up by constraining individual
species’ physiological tolerance ranges, and so
temperaturediversity relationships will differ among
oceanic regions with different species. Future research
could differentiate between these two hypothesis
groups by comparing temperaturediversity relation-
ships among different oceans (e.g. Atlantic, Pacific,
Arctic, and Southern Oceans). If the ‘shapes’ of
temperaturediversity relationships (e.g. slope of
ascending and descending arms and position of peak)
are similar or the same among different oceans then
‘top-down’ hypotheses are plausible, and vice versa.
Mesocosm or in situ experiments using nematodes,
foraminifera or even larger organisms may be one
avenue to test these hypotheses.
(5) We need to increase our understanding of physiolog-
ical responses and other ecological characteristics of
individual deep-sea species, which are largely unknown
for most deep-sea species, including their tolerance
to changing temperature conditions as well as their
metabolic responses (e.g. Brooke et al., 2013; Brown
& Thatje, 2014; Naumann, Orejas & Ferrier-Pages,
2014).
(6) Finally, longer (i.e. >105year) time-scale dynamics
are needed to understand the evolutionary dynamics
of deep-sea biodiversity. Such studies are essential to
establish the role of evolutionary dynamics in shaping
global biodiversity patterns in the deep sea. Even
though evolutionary dynamics have been investigated
in shallow-marine fossil records (Jablonski et al., 2006),
deep-sea studies investigating biodiversity dynamics
over evolutionary time scales are very limited (e.g.
Thomas & Gooday, 1996; Yamaguchi & Norris,
2012). Further research is needed to take advantage
of the rich microfossil records of benthic ostracodes
and foraminifera in deep-sea sediment cores, perhaps
complemented by ancient DNA approaches now
developing rapidly (Lejzerowicz et al., 2013), to
estimate biodiversity in the deep past and to elucidate
whether deep-sea evolutionary dynamics could be
driven by temperature, perhaps through changes in
metabolic rate and resulting speciation rate (Allen et al.,
2002; Brown & Thatje, 2014).
IX. CONCLUSIONS
(1) Despite notable technological advances in the last two
decades, the deep sea is still a remote environment difficult
to access, and thus biological and palaeoecological data are
limited. We compiled all published spatial (i.e. present-day)
and time-series (both biological and palaeoecological) data
on deep-sea temperaturediversity relationships, and used
the integration of different temperaturediversity patterns
covering a wide range of temperatures to create three possible
models: a unimodal (hump-shaped) model, a ‘right-skewed’
unimodal model, and a model in which temperature is
important only at relatively high (negatively) and low
(positively) temperatures.
(2) There are several hypotheses (physiological tolerance
hypothesis, metabolic hypothesis, island biogeography
theory, or combinations of these) to explain these three
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 285
models. The metabolic hypothesis may be less plausible
and the physiological tolerance hypothesis may best explain
the observed patterns discussed herein. However, further
research is needed to differentiate between these models.
(3) These results provide important baseline information
for the present and future management of deep-sea
ecosystems in this rapidly warming Anthropocene era.
X. ACKNOWLEDGEMENTS
We thank C. L. Wei for help with POC flux calculation,
G. Hunt, M. A. Rex, and an anonymous reviewer
for valuable comments, the Editor W. Foster, and the
Assistant Editor A. Cooper. R.D. was supported by
the National Flagship Programme RITMARE (Ricerca
Italiana in Mare) and the European Union project MIDAS
(Managing Impacts of Deep-seA reSource exploitation.
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XII. SUPPORTING INFORMATION
Additional supporting information may be found in the
online version of this article.
Fig. S1. Comparison of temperaturediversity relationships
between (A) 10004000 m dataset and (B) whole dataset
(including <1000 and >4000 m data) of present-day North
Atlantic Ocean and Mediterranean Sea nematode species
diversity (Danovaro et al., 2009; Bongiorni et al., 2010;
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
Temperature impacts on deep-sea biodiversity 287
Bianchelli et al., 2013; Pusceddu et al., 2013; R. Danovaro,
unpublished data; see online Table S2). Quadratic regression
lines are shown. The whole dataset (B; r2=0.094, P<0.001)
is much noisier than the 1000 –4000 m dataset (A; r2=0.300,
P<0.001).
Table S1. North Atlantic deep-sea foraminiferal dataset
used for regression modelling in the present study. Faunal
and environmental data from Sun et al. (2006) and Corliss
et al. (2009). See Appendix S1 for Lutz et al.’s (2007) and
Pace et al.’s (1987) particulate organic carbon (POC) flux
calculation. TEA, tropical eastern North Atlantic; TWA,
tropical western North Atlantic; MA, middle North Atlantic;
SPA, subpolar North Atlantic.
Table S2. Present-day North Atlantic Ocean and
Mediterranean Sea nematode species diversity dataset used
to construct Fig. 3C and Fig. S1. Data from Danovaro
et al. (2009), Bongiorni et al. (2010), Bianchelli et al. (2013),
Pusceddu et al. (2013), and R. Danovaro (unpublished
data).
Appendix S1. Methods for regression modelling using the
North Atlantic deep-sea foraminiferal dataset.
(Received 9 July 2014; revised 19 November 2014; accepted 21 November 2014; published online 18 December 2014)
Biological Reviews 91 (2016) 275– 287 ©2014 Cambridge Philosophical Society
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Tools for performing model selection and model averaging. Automated model selection through subsetting the maximum model, with optional constraints for model inclusion. Model parameter and prediction averaging based on model weights derived from information criteria (AICc and alike) or custom model weighting schemes. [Please do not request the full text - it is an R package. The up-to-date manual is available from CRAN].
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