Modeling the effects of climate change and acidification on global coral reefs

Incorporating adaptive responses into future projectionsof coral bleachingCHERYL A . LOGAN* † , J OHN P . DUNNE ‡ , C . MARK EAK IN § and SIMON D. DONNER¶

*Division of Science and Environmental Policy, California State University, Monterey Bay, Seaside, CA, USA, †Atmospheric and

Oceanic Sciences, Princeton University, Princeton, NJ, USA, ‡Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, NJ,

USA, §Coral Reef Watch, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA, ¶Department of

Geography, University of British Columbia, Vancouver, BC V6T 1Z2, Canada

Abstract

Climate warming threatens to increase mass coral bleaching events, and several studies have projected the demise of

tropical coral reefs this century. However, recent evidence indicates corals may be able to respond to thermal stress

though adaptive processes (e.g., genetic adaptation, acclimatization, and symbiont shuffling). How these mechanisms

might influence warming-induced bleaching remains largely unknown. This study compared how different adaptive

processes could affect coral bleaching projections. We used the latest bias-corrected global sea surface temperature

(SST) output from the NOAA/GFDL Earth System Model 2 (ESM2M) for the preindustrial period through 2100 to

project coral bleaching trajectories. Initial results showed that, in the absence of adaptive processes, application of a

preindustrial climatology to the NOAA Coral Reef Watch bleaching prediction method overpredicts the present-day

bleaching frequency. This suggests that corals may have already responded adaptively to some warming over the

industrial period. We then modified the prediction method so that the bleaching threshold either permanently

increased in response to thermal history (e.g., simulating directional genetic selection) or temporarily increased for

2–10 years in response to a bleaching event (e.g., simulating symbiont shuffling). A bleaching threshold that changes

relative to the preceding 60 years of thermal history reduced the frequency of mass bleaching events by 20–80% com-

pared with the ‘no adaptive response’ prediction model by 2100, depending on the emissions scenario. When both

types of adaptive responses were applied, up to 14% more reef cells avoided high-frequency bleaching by 2100. How-

ever, temporary increases in bleaching thresholds alone only delayed the occurrence of high-frequency bleaching by

ca. 10 years in all but the lowest emissions scenario. Future research should test the rate and limit of different adap-

tive responses for coral species across latitudes and ocean basins to determine if and how much corals can respond to

increasing thermal stress.

Keywords: acclimatization, adaptation, climate change, coral bleaching, global climate models, sea surface temperature

Received 1 February 2013; revised version received 19 July 2013 and accepted 30 July 2013

Introduction

Climate change is projected to threaten global biodiver-

sity over this century, but accurate projections of

climate change impacts on ecosystem structure and

function have proven to be difficult (Dawson et al.,

2011). Many of the models used to make predictions

(e.g., empirical niche models) overlook the capacity of

organisms to adapt to a changing environment (Chown

et al., 2010; Dawson et al., 2011; Hoffmann & Sgr�o,

2011). The capacity of a species to cope with change

depends on both intrinsic factors (e.g., phenotypic plas-

ticity, microevolution, or dispersal to new habitat) and

extrinsic factors (e.g., rate, magnitude, and nature of cli-

matic change) (Dawson et al., 2011). Models that

include adaptive capacity may provide more accurate

predictions of the effects of climate change on

biodiversity, thus allowing policy makers, conservation

managers, and biologists to better allocate resources

toward monitoring at-risk populations and to make

appropriate plans for management (Cooke et al., 2013).

Tropical coral reefs are an important ecosystem in

which to investigate the impacts of climate change. Reef

ecosystems are among the most diverse in the world,

and provide economic and social stability to many

nations in the form of food security and economic

revenue. Ocean temperatures of 1–2 °C greater than

annual summertime maxima can lead to coral bleach-

ing, a loss of the symbiotic dinoflagellates (zooxanthel-

lae) living within the coral tissue (Hoegh-Guldberg,

1999). Because zooxanthellae supply the host with most

of its nutritional requirements, prolonged bleaching

and associated disease often lead to coral mortality.

Mass coral bleaching and mortality events around the

world over the past three decades have raised ques-

tions about the future of coral reef ecosystems (HughesCorrespondence: Cheryl A. Logan, tel. +831 582 4698,

fax + 831 582 4122, e-mail: [email protected]

© 2013 John Wiley & Sons Ltd 125

Global Change Biology (2014) 20, 125–139, doi: 10.1111/gcb.12390

et al., 2003; Hoegh-Guldberg et al., 2007). The fate of

global coral reefs under climate change has been esti-

mated in several previous studies (Hoegh-Guldberg,

1999; Sheppard, 2003; Donner et al., 2005; Donner, 2009;

Frieler et al., 2012; Teneva et al., 2012). These studies

suggest that mass coral bleaching will be a frequent

occurrence on most reefs worldwide by midcentury or

earlier, assuming that bleaching thresholds remains

static over time (Fig. 1; red line).

Evidence for the ability of individuals or communi-

ties to adaptively respond to thermal stress suggests

that bleaching thresholds may increase in response to

climate warming (Fig. 1; blue line), although the rate

and extent of this increase remains unknown (Hughes

et al., 2003). Corals and their associated endosymbiotic

communities can respond to changes in the local ther-

mal environment at ecological and evolutionary time-

scales (reviewed in Gates & Edmunds, 1999; Coles &

Brown, 2003; Edmunds & Gates, 2008; Weis, 2010).

Major research on corals’ adaptive capacity has focused

on four processes: (i) symbiont shuffling, or shifts in the

abundance of existing Symbiodinium toward more heat-

tolerant genotypes (Buddemeier & Fautin, 1993; Baker

et al., 2004; Berkelmans & van Oppen, 2006; Abrego

et al., 2008; Jones et al., 2008; Sampayo et al., 2008;

Coffroth et al., 2010; Silverstein et al., 2012); (ii) physio-

logical acclimatization of the coral host or the existing

zooxanthellae (e.g., increased expression of heat shock

proteins, photoprotective proteins, antioxidants, etc.)

making the coral holobiont more thermally tolerant

(Falkowski & LaRoche, 1991; Brown et al., 2002; Robison

& Warner, 2006; Desalvo et al., 2008; Middlebrook et al.,

2008; Bellantuono et al., 2012; Barshis et al., 2013); (iii)

natural selection acting on the coral host or symbiont

populations leading to more heat-tolerant genotypes

(directional selection) (Coles & Brown, 2003; Maynard

et al., 2008; Thompson & van Woesik, 2009; Van Woesik

et al., 2011; Voolstra et al., 2011); and (iv) community

shifts, resulting in changes to the coral community com-

position toward dominance by more heat-tolerant taxa

(Coles & Brown, 2003; Maynard et al., 2008; Sampayo

et al., 2008; Van Woesik et al., 2011). Symbiont shuffling

has been quantitatively shown to increase thermal toler-

ance by as much as 1–1.5 °C in one common Indo-Paci-

fic coral species (Berkelmans & van Oppen, 2006). The

adaptive capacity of the other processes and other spe-

cies, however, has yet to be quantified.

In previous modeling studies, the likelihood of coral

bleaching was predicted based on a simple fixed ther-

mal threshold (Hoegh-Guldberg, 1999; Sheppard, 2003;

Sheppard & Rioja-Nieto, 2005), a cumulative heat stress

index (Donner et al., 2005, 2009; Frieler et al., 2012;

Teneva et al., 2012; Liu et al., 2013; Van Hooidonk et al.,

2013), or a complex multivariate model approach that

includes multiple environmental variables in addition

to temperature (Maina et al., 2008). Some regional scale

models have also projected changes in coral cover due

to bleaching caused by temperature anomalies, and

included species interactions and evolutionary dynam-

ics (Baskett et al., 2009, 2010; Anthony et al., 2011). In

the absence of specific knowledge about regional envi-

ronmental variables, species’ tolerances, and commu-

nity-level interactions, the cumulative heat stress index

has been found to be the best model for roughly pre-

dicting bleaching at a global scale (Boylan & Kleypas,

2008; Donner, 2011; Logan et al., 2012). One clear draw-

back of the cumulative heat stress index is that it does

not take into account what is known about differences

in bleaching tolerances among species (e.g., massive

and encrusting corals tend to be more bleach resistant

compared with branching corals) (Loya et al., 2001;

Marshall & Baird, 2001). Despite this drawback, this

bleaching prediction model is currently employed by

NOAA’s Coral Reef Watch (CRW) Program to make

real-time global bleaching predictions (Liu et al., 2013)

and provides a good framework for simulating differ-

Fig. 1 A conceptual model of temperature thresholds for coral

bleaching to recent and future climate warming (based on

Hughes et al. (2003)). The gray area represents ocean tempera-

ture, encompassing variability and the range of temperatures

projected in future warming scenarios. A fixed threshold (red

line) is static in time and predicts a steady increase in bleaching

frequency until bleaching is nearly ubiquitous. A fixed threshold

model is used in no adaptation models such as Coral Reef Watch

(CRW) real-time global bleaching predictions and many future

projections. An increasing bleaching threshold (blue line) pre-

dicts that corals can respond adaptively to warming over some

range, and asymptotes when ocean temperature approaches the

absolute thermal limit beyond which adaptive responses are no

longer possible for corals. It would predict some increases in

bleaching through time, but the slope and limit of this threshold

are unknown (represented by the ?).

© 2013 John Wiley & Sons Ltd, Global Change Biology, 20, 125–139

126 C. A. LOGAN et al.

ent adaptive responses. The cumulative stress index is

called a degree heating week (DHW), and is based on

empirical data showing that corals begin to bleach

when ocean temperature reaches ca. 1 °C above their

summertime maximum (Jokiel & Coles, 1977, 1990;

Glynn & D’Croz, 1990; Glynn, 1993, 1996; Goreau &

Hayes, 1994; Goreau et al., 1997).

Few studies have modeled the ability of corals to

adapt to rising temperatures. Adaptive responses have

previously been incorporated into cumulative heat

stress models by modifying the calculation of the

bleaching threshold or the SST climatology, which rep-

resents the coral’s thermal history (see Table 1). In one

approach, the bleaching threshold was increased to

determine the thermal tolerance necessary to prevent

widespread or frequent bleaching before some future

point in time (Donner et al., 2005, 2009; Frieler et al.,

2012). This approach determines how much the bleach-

ing threshold would have to change to allow for coral

survival. The bleaching threshold has also been modi-

fied to incorporate temperature variability (Boylan &

Kleypas, 2008; Donner, 2011; Logan et al., 2012; Teneva

et al., 2012) based on empirical evidence that some

corals living in more variable environments may be

more resistant to bleaching. This could be a result of

adaptation or acclimatization to recent thermal history

(Castillo & Helmuth, 2005; McClanahan et al., 2007;

Ateweberhan & McClanahan, 2010; Oliver & Palumbi,

2011a,b). Other studies have modified the duration and

calculation of the SST climatology (the period of time

that represents corals’ summertime maximum tempera-

ture in the model) (Van Hooidonk & Huber, 2009;

Donner, 2011; Teneva et al., 2012). For example, the cli-

matology timeframe has been modified to ‘roll’ forward

through time instead of using a fixed time period, sim-

ulating an adaptive response to the corals’ most recent

thermal history (Anthony et al., 2011; Teneva et al.,

2012).

In this study, we examine the sensitivity of proposed

adaptive processes on coral bleaching projections under

future climate change using the suite of representative

concentration pathways (RCPs) developed for the IPCC

AR5. We applied a cumulative stress bleaching model

with no adaptive response to SST output from the

Geophysical Fluid Dynamics Laboratory (GFDL) Earth

System Model 2 (ESM2M) though to 2100. We then

examined how implementing a preindustrial thermal

history into the model influenced these predictions.

Next, we evaluated three additional bleaching predic-

tion models that approximate different coral adaptive

responses (Table 1): (i) a thermal history window that

rolls forward through time, simulating an adaptive

response to recent thermal history (e.g., via genetic

adaptation); (ii) a bleaching threshold that temporarily

increases following a thermal stress event (e.g., simulat-

ing symbiont shuffling or transient community shifts

toward more heat-tolerant corals); and (iii) the additive

effect of combining a rolling thermal history and a

bleaching threshold that temporarily increases through

time. Finally, we compared results from each of our

adaptive models to the model with no adaptive

response to determine: (i) which adaptive processes

could potentially increase coral resistance to high fre-

quency mass bleaching events given projected warming

trends; (ii) how these compare to the limited bleaching

observations available; and (iii) the capacity to which

these processes must act to prevent high frequency

mass bleaching events by midcentury.

Materials and methods

Coral reef locations

Tropical coral reef locations were extracted from the Millen-

nium Coral Reef Mapping Project (UNEP-WCMC, 2010) and

adjusted in Matlab (MathWorks R2012a v.7.14.0) to the grid

used in the NOAA Geophysical Fluid Dynamics Laboratory

(GFDL) Earth System Model 2M (ESM2M, the latter M

denotes the use of a Modular Ocean Model) (Dunne et al.,

2012). This resulted in a total of 1925 reef containing grid

cells.

Bias-corrected ESM2M SST

We chose the NOAA GFDL ESM2M because it has moderate

climate sensitivity among coupled ocean–atmosphere general

circulation models (GCMs) developed for the Fifth IPCC

Assessment (AR5). Climate sensitivity is a commonly used

metric to compare GCMs, and is defined as the temperature

change that the GCM projects with a change in Earth’s atmo-

spheric concentration of CO2. It should be noted that the regio-

nal pattern of warming in ESM2M is such that the global air

temperature increase is approximately 14% stronger than the

tropical (30°S–30°N) SST increase. ESM2M captures regional

surface climate patterns (Reichler & Kim, 2008), modes of

interannual variability (Guilyardi et al., 2009), and historical

climate change (Hegerl et al., 2007). However, like many

GCMs, ESM2M overpredicts ENSO variability, which can also

lead to the overprediction of bleaching events in some regions.

Thus, we applied a bias correction to the ESM2M model so

that the mean and variance in the model gives peak tempera-

tures and ENSO statistics comparable with observations

(Dunne et al., 2013).

To correct ESM2M biases in the climatological monthly

maximum, we calculated a monthly climatology for both

ESM2M and the observational HadISST1 dataset from the UK

Meteorological Office Hadley Centre (Rayner et al., 2003), and

then calculated the difference between the maximum in each

climatology. The correction for ESM2M’s relative overpredic-

tion of decadal-scale variability and resulting extremes


PREDICTING CORAL BLEACHING UNDER ADAPTATION 127

involved several steps. The period since the mid-1900s, a time-

frame over which we have reasonable observational coverage,

contains considerable interannual variability as well as a long-

term trend. To isolate biases in variability on the decadal scale,

we binned HadISST1 and ESM2M data into six decades (i.e.,

1951–1960, 1961–1970, etc.). For each decade at each grid cell,

we calculated a monthly climatology and found the warmest

month within it for both HadISST (SSTobsmeanmaxdecadal) and

ESM2M (SSTmeanmaxdecadal). We also found each decadal

maximum (the warmest monthly temperature value in the

decade; SSTobsmaxdecadal, SSTmaxdecadal). We then calculated

the difference between each decadal maximum and the clima-

tological mean maximum for each decade (i.e., SSTobsmean-

maxdecadal and SSTmeanmaxdecadal), which gave an estimate of

historical decadal-scale departure from the warmest month of

the climatology for each of the six decades for both HadISST1

(Vobs = SSTobsmaxdecadal-SSTobsmeanmaxdecadal) and ESM2M

(Vmodel = SSTmaxdecadal-SSTmeanmaxdecadal). We then aver-

aged across the six decades to yield a single decadal-scale var-

iability estimate for each dataset. To normalize ESM2M

variability to the observations over the entire historical and

projection period, we first calculated the annual maximum

SST (SSTmaxannual), and then the moving decadal mean maxi-

mumSSTmovingmeanmaxdecadal as the 10 year box-car

smoothed values of SSTmaxannual (filling in the beginning and

ending decades with median values for those decades). We

then calculated the variance corrected SST as:

Variance Corrected SST ¼ M� ðSSTmaxannual

� SSTmovingmeanmaxdecadalÞ� ð1� Varobs=VarmodelÞ

Note that this correction was applied only when

Varobs < Varmodel to reduce model variability to levels found

in the observations and to avoid increasing variability where

observations have more variability than ESM2M.

Table 1 Summary of coral bleaching prediction models used in this study. Adaptive responses were simulated by modifying the

degree heating month (DHM) threshold or the climatological time period. A DHM threshold can be combined with either a fixed

climatology (e.g., a static time frame) or rolling climatology (e.g., a time frame that moves forward though time)

Model Adaptive response Empirical references

Degree heating month

(DHM) threshold

Climatology

window

Model

references

1 None Coles et al., 1976;

Jokiel & Coles,

1990; Glynn &

D’Croz, 1990;

Goreau & Hayes,

1994; Goreau

et al., 1997

2 °C DHM Fixed Donner et al.,

2005; Donner,

2009, 2011; Frieler

et al., 2012; Logan

et al., 2012; Teneva

et al., 2012; Van

Hooidonk et al.,

2013; This study

2 Adaptive response to recent

thermal history (e.g., via

genetic adaptation)

Brown et al.,

2002; Robison

& Warner, 2006;

Ulstrup et al., 2006

Smith-Keune &

van Oppen, 2006;

Desalvo et al., 2008;

Oliver & Palumbi,

2011a,b; Bellantuono

et al., 2012;

Barshis et al., 2013

2 °C DHM Rolling Anthony et al., 2011;

Teneva et al., 2012;

This study

3 Symbiont shuffling Baker et al., 2004;

Berkelmans & van

Oppen, 2006;

Abrego et al., 2008;

Sampayo et al. 2008;

Coffroth et al., 2010;

Silverstein et al., 2012

DHM threshold

increases by 1 °C after

a bleaching event and

reverts to original

threshold over

2 or 5 years

Fixed This study

Transient community shifts Coles & Brown, 2003;

Maynard et al., 2008;

Thompson & van

Woesik, 2009; Van

Woesik et al., 2011

Same as above but

reverts to original

threshold over

10 years



Model 1: ‘no adaptive response’ bleaching predictionmethod

We used a monthly modification of the widely employed

NOAA Coral Reef Watch Program (CRW) cumulative stress

index method (or the degree heating week index) as the ‘no

adaptive response’ bleaching prediction model. Cumulative

stress indices assume that bleaching is a function of cumula-

tive deviations above a maximum temperature baseline to

which corals are currently adapted or acclimatized (Goreau &

Hayes, 1994; Goreau et al., 1997). A SST climatology estimates

the corals’ historical summertime maximum temperature for

each grid cell in the model, typically calculated as the annual

maximum monthly mean (MMM, or warmest of the averages

for each month) over some recent time period (e.g., 20 years).

While CRW’s satellite monitoring uses a weekly index degree

heating week (DHW, Liu et al., 2013), predictive studies that

utilize monthly SST output from global climate models sum

monthly temperature anomalies of at least 1 °C above this

MMM climatology over a 3 month period to determine a

degree heating month (DHM) index (Donner et al., 2005; Don-

ner, 2009, 2011; Frieler et al., 2012; Teneva et al., 2012). A DHM

value of 1 °C-month or higher is indicative of a ‘likely bleach-

ing event’ and 2 °C-months or higher is indicative of ‘severe

bleaching and likely mortality’. Donner et al. (2005) found that

the monthly method agrees with 68% of bleaching events pre-

dicted using the Coral Reef Watch weekly method from 1985

to 2002, and predicted 8% more total bleaching events overall.

Model 1 differed slightly from the CRW DHW in three

ways. We used a monthly DHM threshold to match the

monthly SST output from the GFDL ESM2M, as opposed to

biweekly near-real-time SST satellite data. Second, DHMs

were accumulated as soon as the temperature exceeded the

MMM for a particular grid cell, rather than only for weekly

temperatures of 1 °C or more above the MMM. Both of these

are standard departures from the CRW method that have been

used when applying the prediction method to monthly resolu-

tion data (Donner et al., 2005; Van Hooidonk & Huber, 2009;

Donner, 2011; Logan et al., 2012; Van Hooidonk et al., 2013).

Third, we used an MMMmax climatology instead of a MMM

climatology. The MMMmax is calculated as the mean of the

maximum monthly SST of each year during the climatological

period (1985–2004) (Donner, 2009). Unlike the MMM,

MMMmax does not assume 1 month is always the warmest

each year. We chose this alternate climatology based on previ-

ous studies showing that it provides higher predictive power

(1–b) when normalized to the false positive rate (a) in compar-

ison with ReefBase bleaching observations, especially in the

tropical Pacific (Donner, 2011; Logan et al., 2012). We did not

use the variability-based DHM threshold proposed in previ-

ous studies, because although that method may have higher

overall predictive power than the standard DHM method, it

also resulted in far greater false positives (Donner, 2011). The

method employed here has a higher ‘power to false positive’

ratio compared with the variability-based DHM threshold in

both studies (Logan et al., 2012).

In our implementation of Model 1, we tested two different

20 year climatological periods. The first started in 1985, mark-

ing the beginning of the satellite era, a typical timeframe used

by CRW and found in other projections studies (e.g., Donner

et al., 2005; Frieler et al., 2012; Liu et al., 2013; Van Hooidonk

et al., 2013). The second started in 1900, early in the Industrial

period, to evaluate if there are signs adaptive responses have

already occurred.

High-frequency bleaching metric

We present results for global bleaching frequency in terms of

the percentage of reef cells (out of 1925 total reef grid cells)

undergoing heat stress sufficient to cause ‘severe’ bleaching

(DHM ≥2 °C months) more than twice that in the previous

10 years (P > 0.2). We chose this ‘high-frequency bleaching’

metric as a conservative qualitative estimate for the maximum

bleaching frequency that would prevent reef recovery, follow-

ing previous studies (Donner, 2009). Considerable variation in

recovery time is known to occur depending on community

composition, diversity, and thermal history, and recovery of

coral cover does not imply recovery to the pre-bleaching com-

munity composition (Baker et al., 2008; Van Woesik et al.,

2011). The twice in 10 years metric was used in previous stud-

ies to reflect the most rapid observed recovery of hard coral

cover to pre-bleaching coral cover (Donner, 2009). The use of

this specific metric is not intended to imply certainty with

respect to the actual rate of recovery. Rather, by employing

this arbitrary definition of ‘high-frequency bleaching’ used by

previous studies, we seek only to assess the sensitivity of pre-

vious conclusions to our representation of adaptive responses.

Implementation of adaptive responses into the bleachingprediction model

We implemented three basic models to account for corals’

ability to respond adaptively to rising temperatures, as

summarized in Table 1.

Model 2: Rolling climatology. The goal of this model was to

simulate corals’ ability to adaptively respond to recent thermal

history (e.g., via directional genetic selection) over different

timescales. In this general model, we used a climatological

window that rolls forward through time so that the bleaching

threshold increases relative to recent thermal history. The

climatology duration represents the ‘average summertime

maximum’ over the previous 40, 60, 80, or 100 years (model

simulations indicated rolling climatologies of <40 years pro-

duced unrealistically low frequencies of bleaching in modern

times). Windows of 40–100 years may represent timeframes

over which genetic adaptation could occur in Symbiodinium

and faster growing corals (e.g., acroporids) (Csaszar et al.,

2010). Additional research, however, would be required to

determine whether these rates are realistic. The rolling clima-

tology is calculated as the MMMmax, in the same way as

described for Model 1, but in this model the climatological

period rolls forward through time (Ware et al., 1996; Anthony

et al., 2011; Teneva et al., 2012). For example, using a 60 year

rolling climatology, in 2050 the MMMmax climatology was cal-

culated between 1990 and 2050; in 2100 the MMMmax climatol-

ogy was calculated between 2040 and 2100. The window



length represents the rate of the adaptive response; a very

short window (e.g., <10 years) represents a rapid response on

pace with projected rates of warming, while a very long per-

iod (>200 years) approaches a fixed threshold (Fig. 1; red line).

Intermediate periods represent varying rates of an adaptive

response (i.e., slope of blue line in Fig. 1). We chose not to

impose an absolute limit on the extent to which corals could

adapt in this model because the limit remains unknown for

most coral species. Arabian/Persian Gulf corals are known to

survive at summer temperatures of up to 36 °C (Riegl et al.,

2011). Applying our shortest climatology window (40 years)

combined with the highest RCP (8.5) resulted in only <1% (9/

1925) of reef cells with a climatology value of ≥36 °C by 2100

(the highest value was 37.7 °C). Thus, imposing an upper ther-

mal limit near 36 °C would not significantly influence the

results.

Model 3: Temporary increase in bleaching threshold. The

primary goal of this model was intended to simulate symbiont

shuffling (corals’ ability to temporarily shuffle their zooxan-

thellae population to a more heat-tolerant symbiont type

following a heat stress event) (Baker et al., 2013) but it could

also represent shifts in community composition toward more

heat-tolerant taxa followed by a return of heat susceptible cor-

als in the absence of continued thermal stress (e.g., Van Woe-

sik et al., 2011). In this model, the DHM threshold increases by

1 °C following a severe bleaching event. The threshold then

returns to its original value over a period of 2, 5, or 10 years

using a linear decay function: f(t) = C–t/r, where t is time in

months after a severe bleaching event, C is a constant (1 °C),and r is the return time to the original threshold in months.

We chose a conservative 1 °C threshold increase based on

Berkelmans & van Oppen (2006) study showing that acroporid

corals on the Great Barrier Reef increased their tolerance by

1–1.5 °C by shuffling their dominant symbiont type to a more

heat-resistant clade. The threshold increase is temporary

because symbiont communities are known to revert back to

their pre-bleaching composition within 2–5 years in the

absence of continued heat stress events (Thornhill et al., 2005;

Sampayo et al., 2008; LaJeunesse et al., 2009; Coffroth et al.,

2010; Silverstein et al., 2012; Baker et al., 2013). We also chose a

10 year-return time because it might better approximate tran-

sient community shifts following a thermal stress event (May-

nard et al., 2008; Thompson & van Woesik, 2009; LaJeunesse

et al., 2010; Van Woesik et al., 2011). In this case, an increased

DHM threshold represents the death of bleaching-susceptible

species within a community (i.e., increasing the ‘average’

bleaching threshold of the community). The bleaching thresh-

old linearly returns back to the pre-bleaching value over

10 years as bleaching-susceptible corals begin to repopulate

the community.

Model 4: Rolling climatology and temporary increase in

bleaching threshold. The goal of this model was to simulate

corals’ potential to respond adaptively to recent thermal his-

tory and temporarily increase thermal tolerance following a

thermal stress event (Table 1). For example, this might occur if

corals were able to increase thermal tolerance via acclimatiza-

tion of the coral host and simultaneously increase tolerance

via symbiont shuffling (Fitt et al., 2009). We implemented this

model by using the rolling climatology values from Model 2

and the linear decay function from Model 3.

Summary of model runs

We projected the occurrence of high-frequency bleaching

through 2100 for all IPCC AR5 representative concentration

pathways (RCPs 2.6, 4.5, 6.0, 8.5) for all bleaching prediction

models (Models 1–4). The number associated with each RCP

relates to the final radiative forcing in Watts per square meter

(W m�2) by year 2100, with larger numbers resulting in higher

globally averaged temperature (Moss et al., 2010). RCPs are

not intended to represent specific ‘business as usual’ or other

specific decisions (or lack of decisions), but to represent gen-

eral pathways consistent with a range of possible decisions.

RCP 2.6 results in the lowest radiative forcings by 2100, a sce-

nario that would be consistent with strong reductions in

greenhouse gas emissions. RCP 4.5 and 6.0 are driven by emis-

sions scenarios that result in CO2 stabilization, with stabiliza-

tion in RCP 4.5 happening sooner than in RCP 6.0. RCP 8.5

has the highest emissions baseline that is used in combination

with no emissions stabilization and aggressive emissions

growth. Observed CO2 emissions have been tracked at or

above those used in RCP 8.5 with few current programs or

treaties to stabilize CO2 (Peters et al., 2013). For this reason, we

primarily present results for RCP 6.0 and 8.5 in the main text,

and those for RCP 4.5 and 2.6 in the Supplement. We will refer

the four RCPs using the following terminology: ‘lowest’,

‘moderately low’, ‘moderately high’, and ‘highest’ radiative

forcings (W m�2) at 2100.

First, we compared results from Model 1 (‘no adaptive

response’) with and without the ESM2M SST bias correc-

tion. All subsequent bleaching prediction models were run

using the bias-corrected SST ESM2M output because of its

better representation of SST variability and ENSO. Second,

we compared Model 1 results using a 1900–1919 climatolog-

ical period to those using a 1985–2004 period to ask what

present-day bleaching would look like if present-day coral

bleaching thresholds were applied with the climatology

prior to anthropogenic warming, and if there is any sign

that adaptive responses have already been exhibited by cor-

als. Third, we ran each of the adaptive bleaching models

(Models 2–4; summarized in Table 1) and compared them

to the predictions from Model 1. Finally, we calculated the

increase in MMMmax climatology value between 1960 and

2100 for each reef cell to estimate the adaptive thermal tol-

erance that would be required under each window length

and RCP scenario. For example, the difference between the

40 year rolling climatology in 1960 (calculated by averaging

the maximum monthly SST each year between 1920 and

1960) and the 40 year rolling climatology in 2100 (calculated

by averaging the maximum monthly SST each year between

2160 and 2100) provides a basis for understanding the

extent to which corals’ have adapted by 2100 in that model.

All bleaching models were coded and run in Matlab (Math-

Works R2012a v.7.14.0).



Results

Model 1 (1985–2004 climatology): ‘no adaptive response’results in high-frequency bleaching by midcentury

The ‘no adaptive response’ model applied to SSTs from

the ESM2M model and calibrated to a 1985–2004 clima-

tology projects ‘high-frequency bleaching’ in >50% of

reef cells by 2030–2050 in all RCPs (Fig. 2 for the moder-

ately high RCP 6.0; S1 for all other RCPs; black lines).

Under these assumptions, the ‘best case’ future scenario

(the lowest RCP 2.6) leads to less than 50% of global reef

cells experiencing high-frequency bleaching by 2050

using a 1985-2004 climatology (Fig. S1a, black lines),

with the higher scenarios all resulting in more than 50%

of global reef cells experiencing high-frequency bleach-

ing by 2050 (Fig. 2, S1c-d, black lines). The bias-cor-

rected version of the ESM2M predicted less severe

ENSO events and typically resulted in a ca. 5–10 year

delay in the percent of global reef cells that would expe-

rience ‘high-frequency bleaching’ in all scenarios

(Fig. 2, S1; dotted vs. solid lines). The spatial distribu-

tions of bleaching frequencies in decadal snapshots for

the moderately high RCP 6.0 scenario, corresponding to

Fig. 2, are shown in Fig. S2. The differences between

two datasets show that raw ESM2M output predicts

high-frequency bleaching events sooner than the bias-

corrected ESM2M output (green in Fig. S1). Regions

with the strongest impact by 2030 included the south-

ern Caribbean and parts of the equatorial Pacific and

Coral Triangle regions (Fig. S2b) where ENSO signals

are especially strong. By 2050, the entire Caribbean was

predicted to experience high-frequency bleaching,

along with most of the equatorial Pacific, the Coral Tri-

angle region, the Red Sea, and Madagascar (Fig. S2c).

By 2070, the only regions predicted to be spared from

high-frequency bleaching included the Southeastern

Pacific and a few small regions within the southern end

of the South China Sea. All future comparisons employ

the bias-corrected ESM2M as we believe it more accu-

rately reflects future ENSO variability.

Model 1 (1900–1919 climatology): using an historicalthermal history results in high-frequency bleaching inpresent day

When the Model 1 (‘no adaptive response’) was cali-

brated to a climatology period between 1900 and 1919,

warming over the last century results in high-frequencybleaching by 1990 (Fig. 2 for the moderately high RCP

6.0; S1 for all other RCPs; solid gray lines). The 1900–1919 climatological period resulted in high-frequencybleaching >50% of reef cells by 2010 in all emissions

scenarios (Fig. 2, S1).

Model 2 shows potential for reduced coral bleaching ifadaptive responses are possible

Results from the rolling climatologies (solid lines) are

compared with those from the Model 1 (‘no adaptive

response’) (dashed lines) in Fig. 3a and b (RCP 6.0 and

8.5) and Fig. S3a and b (RCP 2.6 and 4.5). In all RCPs,

the rolling climatology strongly increased predicted

bleaching between 2000 and ca. 2030, and then dimin-

ished the impact of warming on bleaching between 2040

and 2100. This shift occurred because rolling climatolo-

gies included temperatures lower than those during the

1985–2004 climatology period used in Model 1 due to

inclusion of years earlier in the time series, and added

warmer temperatures thereafter. When a 100 year roll-

ing climatology was applied, the prediction algorithm

resulted in fewer than 50% of global corals experiencing

high-frequency bleaching in RCP 2.6 and 4.5 (Fig. S3a

and b) throughout the 21st century. Application of a

60 year rolling climatology resulted in fewer than 50%

of corals worldwide experiencing high-frequencybleaching in all RCPs except 8.5 (Fig. 3a and b). The

60 year rolling climatology applied to the moderately

high RCP (6.0) (Fig. 3a; medium gray solid line) gave

similar bleaching rates as the lowest RCP (2.6) under the

assumption of a fixed 1985–2004 climatology (Fig. S3a;

Fig. 2 Percent of global reef cells predicted to experience ‘high-

frequency bleaching’ under the moderately high RCP,

6.0 W m�2 by 2100, using from the GFDL Earth System Model

(ESM2M) with (black) and without (gray) a bias correction in

the climatological maximum that reduces the frequency of

ENSO events (Model 1). ‘High-frequency bleaching’ is defined

as a reef cell that experiences two or more severe coral bleaching

events (DHM ≥2 °C-months) in a decade. An historical climatol-

ogy (1900–1919) predicts over 50% of global reef cells experienc-

ing severe coral bleaching (more than two bleaching events in

10 years) before the year 2000. A satellite-era climatology (1985–

2004) predicts over 50% of global reef cells experiencing high-

frequency bleaching by ca. 2030. Results for all other RCPs can

be found in Fig. S1.



dotted black line). The 40 year rolling climatology was

the only run that resulted in fewer than 50% of global

corals experiencing high-frequency bleaching by 2100 in

all RCPs (Fig. 3, S3a and b). Model predictions included

only rare high-frequency bleaching (<4% global reef

cells) in the three lowest RCPs (2.6, 4.5, and 6.0) (Fig. 3a,

S3a and b; light gray lines) and fewer than 25% of global

reef cells in highest RCP (8.5) by 2100 (Fig. 3b; light gray

line). The difference in MMMmax between 1960 and 2100

ranged from 0.9 °C (29.0–29.9 °C) in the lowest RCP

(2.6) with a 40 year climatology to 2.5 °C (29.0–31.4 °C)in highest RCP (8.5) with a 40 year climatology

(Table 2). Although we do not present model results

with climatological periods of <40 years, we found that

periods of 20 and 30 years predicted high-frequencybleaching in <5% of global reef cells through 2100.

Model 3 shows limited potential for symbiont shufflingand transient community shifts to reduce coral bleaching

Application of a bleaching threshold that temporarily

increases following a bleaching event (Fig. 3c and d,

S3c and d; solid lines) predicted less frequent bleaching

in all RCPs when compared with Model 1 (‘no adaptive

response’) (Fig. 3c and d, S3c and d; dashed lines). In

the lowest RCP (2.6), ca. 24–30% of global reef cells

experienced high-frequency bleaching through the end

of the century as compared with 48% in Model 1 (Fig.

S3c). In the higher emissions scenarios, the bleaching

threshold that temporarily increases delayed bleaching

trajectories by approximately 5–10 years (Fig. 3c and d).

The 2 year return time resulted in ca. 5 year delay,

whereas the 5 and 10 year return times resulted in nearly

(a) (b)

(c) (d)

Fig. 3 Percent of global reef cells predicted to experience high-frequency bleaching using the adaptive response models. Model 2

(a and b) employs a rolling climatological period, representative of an adaptive response to recent thermal history over the previous 40,

60, 80, or 100 years. Model 3 (c and d) employs a temporary increase in the bleaching threshold of 1 °C after a bleaching event, which

may be representative of a temporary increase in thermal tolerance due to symbiont shuffling or transient community shifts toward

more heat-tolerant taxa. Both bleaching models use SST output from the GFDL ESM2M bias-corrected model for the moderately high

RCP 6.0 (a and c) and highest RCP 8.5 (b and d). For comparison, dashed lines in all panels represent the corresponding results from

the ‘no adaptive response’ (Model 1) using the 1985–2004 climatology. Results for RCPs 2.6 and 4.5 can be found in Fig. S3.



identical predictions of a ca. 10 year delay, as compared

with Model 1.

Model 4 shows potential for additive effects in reducingfuture coral bleaching

Combining the 60 and 100 year rolling climatology

windows with a temporary increase in bleaching

threshold led to greatly reduced bleaching in both

the moderately high and highest RCPs (6.0 and 8.5)

(Fig. S4). Relative to the rolling climatology alone

(dashed lines are replotted from solid lines in

Fig. 3a and b), the addition of a temporary increase

in bleaching threshold led to a reduction the mod-

el’s prediction of present-day bleaching. The combi-

nation of models also eliminated high-frequencybleaching in the moderately high and highest RCPs

(6.0 and 8.5), except with the 100 year rolling clima-

tology window under the highest RCP (8.5) (Fig.

S4b). Simulations using lower emissions RCPs and

shorter climatological window periods produced

unrealistically low frequencies of bleaching events in

modern times. In the lowest and moderately low

RCPs (2.6 and 4.5), the combined assumptions led

to fewer than 10% of global reef cells undergoing

high-frequency bleaching (data not shown).

Examination of change in SST through 2100

To illustrate the implications of an assumed adaptive

response to recent thermal history in our rolling clima-

tology model, we compared the SST changes and corre-

sponding rates of change at global coral reef cells

projected from ESM2M through 2100 (Fig. 4). The abso-

lute change in SST over time under all RCP scenarios in

the bias-corrected ESM2M (Fig. 4a; 10 year rolling

climatology mean for all reef cells) shows the global

average warming trajectory for each RCP. The corre-

sponding decadal rate of warming for this 10 year roll-

ing climatology (Fig. 4b) illustrates that in all RCPs

except the highest (8.5), the inferred rates of warming

reach their peaks near the present day, and thus would

correspond to the most vulnerable period for corals if

adaptive responses are at work on decadal timescales.

The decadal rate of warming for the ‘slowest’ rolling

climatology window that we modeled (100 years;

Fig. 4c), illustrates a scenario in which bleaching pres-

sure on corals continues to increase under all RCPs to

the present day and only stabilizes after 2040 in the

lowest RCP (2.6), late 21st century in RCP 4.5 and RCP

6.0, and never in highest RCP (8.5). Although most

apparent in lowest RCP (2.6), all scenarios show accel-

erated warming around 2040 as a result of the assumed

decrease in aerosol emissions and associated lessening

of their cooling influence built into the RCPs (Chalmers

et al., 2012).

Summary of model results

The overall results of our models are summarized in

Table 3, which provides global rates of high-frequencybleaching in various decadal snapshots between 1970

and 2100 under RCP 6.0. None of these models pre-

dicted high-frequency bleaching in 1970. By 2010, using

a historical climatology with Model 1 predicted high-frequency bleaching in 50% of reef cells whereas all

other models predicted high-frequency bleaching in

≤10% of reef cells. In 2100, the only models in which

high-frequency bleaching of >95% of reef cells was not

predicted were those that incorporated a rolling

climatology. Only limited reduction in bleaching was

seen in models with a temporary increase in the

bleaching threshold when not combined with a rolling

climatology.

Discussion

Our results suggest that corals may have already adap-

tively responded to at least some of the temperature

change since the preindustrial period, providing

support for a bleaching threshold model that increases

in response to climate warming (Fig. 1; blue line). The

extent to which adaptive responses may have already

occurred, however, cannot be determined at present

Table 2 Temperature increase (°C) in the MMMmax climatology between 1960 and 2100 for all IPCC AR5 representative concentra-

tion pathways (RCPs) and climatology window lengths from Model 2. Values represent the median of all 1925 reef cells

RCP (W m�2 by 2100)

Rolling climatology window

40 years 60 years 80 years 100 years

2.6 0.9 (29.0–29.9) 1.0 (28.9–29.9) 1.0 (28.8–29.8) 1.0 (28.8–29.8)

4.5 1.4 (29.0–30.4) 1.4 (28.9–30.3) 1.4 (28.8–30.2) 1.3 (28.8–30.1)

6.0 1.6 (29.0–30.6) 1.5 (28.9–30.4) 1.5 (28.8–30.3) 1.3 (28.8–30.1)

8.5 2.4 (29.0–31.4) 2.2 (28.9–31.1) 2.0 (28.8–30.8) 1.8 (28.8–30.6)



due to limitations of long-term bleaching observations

(Oliver et al., 2009; Donner, 2011). When our ‘no adap-

tive response’ model was applied to SSTs from the

ESM2M model, it predicted that high-frequency bleach-

ing would be a frequent occurrence on most reefs

worldwide by midcentury or earlier, similar to recent

modeling efforts (Donner et al., 2005; Donner, 2009;

Frieler et al., 2012; Teneva et al., 2012; Van Hooidonk

et al., 2013). Of our simulated adaptive responses, only

combinations of the rolling climatology model with cer-

tain RCPs predicted a significant reduction in high-fre-quency bleaching by 2100. Overall, our results

highlight the importance of considering multiple adap-

tive processes in projections of climate warming on

coral reefs.

We used SST output from a single general circulation

model because our goal was to compare different adap-

tive processes, rather than to make precise predictions.

We did, however, choose a moderate sensitivity model

and corrected the model output for known biases in

SST variability that might overpredict or underpredict

bleaching. In all RCP scenarios, we found that bias-cor-

recting ESM2M output to agree with SST observations

and reduce the severity of ENSO events and other

(a)

(b)

(c)

Fig. 4 (a) Global average warming trajectory for each scenario using 10 year rolling MMMmax climatology averaged for global reef cells

between 1960 and 2100. Decadal rate of change in a (b) 10 year and (c) 100 year rolling MMMmax climatology averaged for global reef

cells between 1960 and 2100 for all climate change scenarios.



modes of high climatic variability resulted in approxi-

mately a 10 year delay in bleaching projections. This

result provides an important caveat in terms of the lim-

itations of 5th IPCC Coupled Model Intercomparison

Project (CMIP5) climate models when applied to ther-

mal stress on marine organisms. In the case of ESM2M,

the correction was necessary to reduce variability.

Hypothetically, the situation would be reversed for

models that uniformly underestimate variability. The

actual situation is far more complex, as the individual

models in CMIP5 each have differing strengths and

weaknesses in their abilities to capture climatic variabil-

ity (Guilyardi et al., 2009 and references therein). This

particularly raises questions of studies using multi-

model ensembles, which must assume the mean of all

biases among the models to be near zero.

Although we have only limited knowledge of the

‘correct’ frequency of bleaching at different reefs

around the world, we can make some constrained

assumptions as to whether our model results gener-

ally match observed bleaching. For example, evidence

from the few long-term observational time series

available for the Great Barrier Reef, Caribbean, South-

east Asia, Moorea, and Palau suggests that those

reefs had a 3–10% per year frequency of bleaching

over the past 15 years (Eakin et al., 2010; Burke et al.,

2011; De’ath et al., 2012; Guest et al., 2012), whereas

from 1876 to 1979, only six events have been reported

worldwide (S.D. Donner, unpublished data). In none

of our models did high-frequency bleaching occur by

1970, in rough agreement with observations. How-

ever, use of a fixed 1900–1919 climatology resulted in

50% of global reef cells experiencing high-frequencybleaching by 2010 (Table 3), which is five times

higher than rates reported at the aforementioned

locations. Of the adaptive models we tested, the roll-

ing climatology windows of between 60 and

100 years aligned with the limited datasets of empiri-

cal bleaching observations, with the 100 year window

predicting the highest bleaching frequency of 10% in

2010 (Table 3). A temporary increase in the bleaching

threshold alone and in combination with the rolling

climatology predicted bleaching rates below this

range, with only 1–2% of global coral reef cells expe-

riencing high-frequency bleaching by 2010. Thus, of

all our models, the rolling climatologies appear to be

most consistent with the highly limited time series of

bleaching observations. We emphasize the need here

for more long-term observational bleaching studies

worldwide because empirical validation studies are

necessary to test the predictive power provided by

each adaptive process. The limitations in existing da-

tabases of global bleaching observations are explained

in depth in Donner (2011).

The possible overprediction of bleaching events

resulting when using the 1900–1919 climatology in the

‘no adaptive response’ model suggests that corals

may have already adaptively responded to at least

some of the ocean warming during the preindustrial

period. An alternative explanation would be that cor-

als are now living closer to an absolute bleaching

threshold than they were a century ago. This presup-

poses that the early satellite era coincidentally began

just as peak summer SST was reaching corals’ thermal

thresholds (Fig. 1; red line). Certainly, corals must

have some absolute temperature threshold, but that

does not preclude a threshold that increases in

response to climate warming (Fig. 1; blue line). The

absolute temperature limit beyond which metazoans

can no longer survive is thought to be ca. 45–47 °C(Schmidt-Nielsen, 1997), but the absolute bleaching

threshold for tropical scleractinian corals remains

unknown. Corals in the Arabian/Arabian Gulf are

known to regularly experience mean summer maxi-

mum temperatures of up to 36 °C without bleaching

(Riegl et al., 2011), although bleaching events have

Table 3 Summary of bleaching prediction model results under the moderately high RCP 6.0 in decadal snapshots of historical and

future model run years using the bias-corrected model. ‘High-frequency bleaching’ is defined as reef cells that experience high

frequency bleaching (DHM ≥ 2 °C-month) more than twice per decade

Model

% Global reefs experiencing high-frequency bleaching

1970 2000 2010 2020 2050 2100

Model 1: ‘No adaptive response’ (1985–2004 climatology) 0 0 1 3 45 99

Model 1: ‘No adaptive response’ (1900–1919 climatology) 0 9 50 67 99 100

Model 2: Rolling climatology (60 years window) 0 2 5 5 2 3

Model 2: Rolling climatology (100 years window) 0 3 10 11 25 43

Model 3: Temporary threshold increase (2 years return time) 0 0 1 2 33 99

Model 3: Temporary threshold increase (10 years return time) 0 0 1 2 7 98

Model 4: Rolling climatology (100 years window) & Temporary

threshold increase (10 years return time)

0 1 2 2 3 29



been occurring with increasing frequency there as

well. Thus, it is unlikely that all corals have reached

an absolute limit at present. Given empirical evidence

that corals and symbionts can increase thermal toler-

ance via phenotypic responses to rising temperature

(e.g., Bellantuono et al., 2012, Middlebrook et al.,

2008), it is likely that some adaptive processes have

already occurred and that there is an as yet unknown

absolute maximum beyond which corals cannot sur-

vive (e.g., Fig. 1; blue line). However, the rate and

extent of adaptive responses will vary by species,

depth, location, etc., which is not considered in the

conceptual model (Fig. 1) or in our ‘generic’ bleaching

models. Therefore, coral diversity will likely decline

as temperatures rise and species with less adaptive

capacity are eliminated (Somero, 2010). This may

cause the extinction of some coral species and bring

with it other costs to reef ecosystems.

Of all our simulated adaptive processes, only combi-

nations of the rolling climatology model with low CO2

RCPs predicted high-frequency bleaching in <50% of

global reef cells by 2100 (Table 3). These predictions

resulted in largely different outcomes depending on

the length of the climatological window. Under the

moderately high RCP 6.0, using the most conservative

rolling climatology window of 100 years, the model

predicted that 43% of global coral reef cells will experi-

ence high-frequency bleaching by 2100, vs. only 3%

using a 60 year window (Table 3). This corresponds to

a 1.0–2.2 °C temperature increase in the thermal history

(MMMmax climatology) between 1960 and 2100

depending on RCP (Table 2). The extent to which corals

can respond adaptively to a thermal history of

60–100 years is uncertain. There are theoretical limits to

the rate and absolute amount of warming to which cor-

als can respond adaptively, but there is little evidence

to constrain these parameters at present. For example,

there is only one study that has estimated the heritabil-

ity of thermal tolerance, using one species of coral

(Acropora millepora) and two types of Symbiodinium

(Csaszar et al., 2010). Using a heritability value in the

range of those measured by Csaszar et al. (2010), Bask-

ett et al. (2009) modeled the evolution of a heat-tolerant

symbiont under the IPCC AR4 A1b scenario and

showed a potential 2 °C increase in holobiont tolerance

from 2000 to 2100. As more estimates of rates and abso-

lute capacity for genetic adaptation become available

for corals and their symbionts, we can better assess the

realism of the rolling climatology model. In addition,

further development of techniques to assess past

bleaching events over the last century using paleocli-

matic proxies (Lough, 2010) would be helpful for gener-

ating empirical evidence necessary to validate the

fidelity of the various climatological time periods.

Under the rolling climatology models, change in

bleaching susceptibility over time is a function of the

rate of warming and frequency of warming events

rather than the absolute amount of warming, although

a theoretical limit to the amount of warming tolerable

by corals undoubtedly exists. If corals do respond more

to the rate of change, it would have very encouraging

implications for the future of coral reefs. It would sug-

gest that the presumed increase in bleaching events (Ea-

kin et al., 2009) would not be indicative of a monotonic

increase in bleaching severity through this century, but

rather a multi-decadal increase as corals respond adap-

tively to the recent temperature increase. This level of

adaptive capacity would stabilize bleaching frequency

at current levels through midcentury in all but the high-

est scenario, in which the warming accelerates dramati-

cally (Fig. 4). However, we cannot assert that corals

will be able to adaptively respond at this rate or to this

extent (Table 2). Furthermore, the steep increase and

decline in high-frequency bleaching predicted during

midcentury would likely result in community shifts

toward more tolerant genotypes (Fig. 3a and b), reduc-

ing biodiversity on reefs.

Prediction models with temporary increases in the

bleaching threshold following bleaching events only

delayed high-frequency bleaching by between 2 and

10 years compared with the ‘no adaptive response’

model and the general trajectory was the same (Fig. 3b

and c). If this type of model represents symbiont shuf-

fling or transient community shifts, these processes

may not provide a large delay in the occurrence of

high-frequency bleaching. Symbiont shuffling is not

likely to have a major impact until the frequency of

severe bleaching events exceeds the rate at which sym-

bionts have been shown to switch back to their pre-

bleaching abundance (Sampayo et al., 2008; LaJeunesse

et al., 2009; Coffroth et al., 2010; Silverstein et al., 2012),

although there could be fitness trade-offs to maintain-

ing a population of more heat-tolerant symbionts

(Mieog et al., 2009; Jones & Berkelmans, 2011). How-

ever, the additive effect of a 10 year increase in bleach-

ing tolerance combined with the 100 year rolling

climatology resulted in 29% of global reef cells experi-

encing high-frequency bleaching by 2100 vs. 43% in the

rolling climatology-only scenario in the moderately

high RCP (6.0) (Table 3). Thus, in certain combinations

of assumptions, our model shows that a 10 year

increase in tolerance (e.g., due to transient community

shifts) could have a strong additive effect that would

greatly reduce bleaching by 2100. However, communi-

tiesmay only partially return to their pre-bleaching com-

position or remain permanently changed (Van Woesik

et al., 2011), so it remains unclear how often longer term

increases in tolerance might occur. Nevertheless, even



short-term increases in bleaching tolerance could poten-

tially help protect against sporadic high thermal stress

events resulting from stochastic climatic variability. Of

course, not all species will respond in the same way to

warming, so these mechanisms may be observed differ-

ently in different regions of the ocean. Taxonomic varia-

tions in the type, rate, magnitude, and permanence of

adaptive responses will influence the overall impact of

warmingwill have on coral reef ecosystems.

This study highlights the importance of considering

different representations of adaptive responses in pro-

jections of climate change impacts on coral reefs. Our

models showed that long-term steady increases in ther-

mal tolerance (e.g., simulating genetic adaptation or

permanent shifts in community composition) decrease

bleaching rates by the end of the century much more so

than temporary increases (e.g., simulating symbiont

shuffling or transient community shifts). Although the

necessary observations are not yet available to validate

the models presented here, the results of our sensitivity

experiments illustrate the extent to which adaptation

and acclimatization mechanisms proposed in the litera-

ture could alter future projections. The possible over-

prediction of present-day bleaching events using an

early-Industrial climatology indicates that corals and

their symbionts may have already adaptively

responded to climate warming. The ability of the roll-

ing climatology model to more roughly capture the

present-day bleaching frequency supports the use of a

bleaching prediction model that employs a threshold

that increases with rising temperatures on a multi-deca-

dal scale (e.g., Fig. 1; blue line). Our projections showed

that half as many reef cells are predicted to experience

high-frequency bleaching by 2100 if a 100 year rolling

climatology is employed in place of a fixed threshold.

This is equivalent to a globally averaged 1.0–1.8 °Cincrease in thermal history (MMMmax) between 1960

and 2100, similar in magnitude to the adaptation tests

(using 1–1.5 °C) conducted in previous studies (e.g.,

Donner, 2009). A temporary increase in the bleaching

threshold, proposed to simulate symbiont shuffling or

transient species shifts, however, did little to delay

high-frequency bleaching by 2100. Due to the differ-

ential rate and capacity of coral species to respond

adaptively to thermal history, even the more hopeful

projections would likely result in a loss in biodiver-

sity through a shift toward stress tolerant species or

genotypes (Van Woesik et al., 2011) and may not

reduce the extinction risk faced by many coral species

(Brainard et al., 2012). In combination with reduced

calcification rates projected under ocean acidification

(Anthony et al., 2011), the extent of future reefs will

likely be greatly reduced even if adaptive rates to

thermal stress are found to occur at the high end of

our models (e.g., a 40 year rolling climatology). Vali-

dating these models requires effort to expand global

bleaching datasets and observation networks, as well

as empirical validation of the different proposed

mechanisms as more comprehensive bleaching obser-

vations become available. In addition, continued labo-

ratory and field studies are needed to investigate the

rate and extent to which acclimatization and adapta-

tion to increasing thermal stress might be possible as

the climate warms. Finally, quantifying the role of

fixed vs. plastic or temporary mechanisms (e.g.,

genetic vs. acclimatory) that lead to increases in ther-

mal tolerance for a variety of species across latitudes

and ocean basins will help pave the way for more

sophisticated predictive models.

Acknowledgements

We thank S. Jorgensen, K. Kroeker, and K. Mach for helpful dis-cussion and comments on this manuscript. The NOAA CoralReef Conservation Program and the Cooperative Institute ofClimate Science Postdoctoral Program at Princeton Universityfunded this study. The contents in this manuscript are solely theopinions of the authors and do not constitute a statement ofpolicy, decision, or position on behalf of NOAA or the USGovernment.

References

Abrego D, Ulstrup KE, Willis BL, van Oppen MJH (2008) Species–specific interactions

between algal endosymbionts and coral hosts define their bleaching response to

heat and light stress. Proceedings of the Royal Society B: Biological Sciences, 275, 2273–

2282.

Anthony K, Maynard JA, Diaz-Pulido G, Mumby PJ, Marshall PA, Cao L, Hoegh-

Guldberg O (2011) Ocean acidification and warming will lower coral reef resil-

ience. Global Change Biology, 17, 1798–1808.

Ateweberhan M, McClanahan TR (2010) Relationship between historical sea-surface

temperature variability and climate change-induced coral mortality in the western

Indian Ocean. Marine Pollution Bulletin, 60, 964–970.

Baker AC, Starger CJ, McClanahan TR, Glynn PW (2004) Coral reefs: corals’ adaptive

response to climate change. Nature, 430, 741.

Baker AC, Glynn PW, Riegl B (2008) Climate change and coral reef bleaching: an

ecological assessment of long-term impacts, recovery trends and future outlook.

Estuarine, Coastal and Shelf Science, 80, 435–471.

Baker AC, McClanahan TR, Starger CJ, Boonstra RK (2013) Long-term monitoring of

algal symbiont communities in corals reveals stability is taxon dependent and

driven by site-specific thermal regime. Marine Ecology Progress Series, 479, 85–97.

Barshis DJ, Ladner JT, Oliver T, Seneca F, Traylor-Knowles N, Palumbi SR (2013) A

genomic basis for coral resilience to climate change. Proceedings of the National

Academy of Sciences, 110, 1387–1392.

Baskett ML, Gaines SD, Nisbet RM (2009) Symbiont diversity may help coral reefs

survive moderate climate change. Ecological Applications, 19, 3–17.

Baskett ML, Nisbet RM, Kappel CV, Mumby PJ, Gaines SD (2010) Conservation man-

agement approaches to protecting the capacity for corals to respond to climate

change: a theoretical comparison. Global Change Biology, 16, 1229–1246.

Bellantuono AJ, Hoegh-Guldberg O, Rodriguez-Lanetty M (2012) Resistance to ther-

mal stress in corals without changes in symbiont composition. Proceedings of the

Royal Society B: Biological Sciences, 279, 1100–1107.

Berkelmans R, van Oppen MJH (2006) The role of zooxanthellae in the thermal toler-

ance of corals: a “nugget of hope” for coral reefs in an era of climate change.

Proceedings of the Royal Society B: Biological Sciences, 273, 2305–2312.

Boylan P, Kleypas J (2008) New insights into the exposure and sensitivity of coral

reefs to ocean warming. In: Proceedings of the 11th International Coral Reef Sympo-

sium, pp. 854–858. Ft. Lauderdale, FL.



Brainard RE, Birkeland C, Eakin CM, Mcelhany P, Miller MW, Patterson M, Piniak

GA (2012) Status Review Report of 82 Candidate Coral Species Petitioned Under the US

Endangered Species Act. US Dep. Commerce. NOAA Tech. Memo., NOAA-

TMNMFS-PIFSC-27, Honolulu, HI. 530 p.+ 1 Appendix.

Brown BE, Downs CA, Dunne RP, Gibb SW (2002) Exploring the basis of thermotoler-

ance in the reef coral Goniastrea aspera.Marine Ecology Progress Series, 242, 119–129.

Buddemeier RW, Fautin DG (1993) Coral bleaching as an adaptive mechanism. Bio-

Science, 43, 320–326.

Burke LM, Reytar K, Spalding M, Perry A (2011) Reefs at Risk Revisited. World

Resources Institute, Washington, DC.

Castillo KD, Helmuth BST (2005) Influence of thermal history on the response of Mon-

tastraea annularis to short-term temperature exposure.Marine Biology, 148, 261–270.

Chalmers N, Highwood EJ, Hawkins E, Sutton R, Wilcox LJ (2012) Aerosol contribu-

tion to the rapid warming of near-term climate under RCP 2.6. Geophysical Research

Letters, 39, L18709.

Chown SL, Hoffmann AA, Kristensen TN, Angilletta MJ Jr, Stenseth NC, Pertoldi C

(2010) Adapting to climate change: a perspective from evolutionary physiology.

Climate Research, 43, 3–15.

Coffroth MA, Poland DM, Petrou EL, Brazeau DA, Holmberg JC (2010) Environmen-

tal symbiont acquisition may not be the solution to warming seas for reef-building

corals. PLoS ONE, 5, e13258.

Coles S, Brown BE (2003) Coral bleaching—capacity for acclimatization and adapta-

tion. Advances in Marine Biology, 46, 183–223.

Coles SL, Jokiel PL, Lewis CR (1976) Thermal tolerance in tropical vs. subtropical reef

corals. Pacific Science, 30, 159–166.

Cooke SJ, Sack L, Franklin CE, Farrell AP, Beardall J, Wikelski M, Chown SL (2013)

What is conservation physiology? Perspectives on an increasingly integrated and

essential science†. Conservation Physiology, 1, 1–23.

Csaszar N, Ralph P, Madelleine R, Berkelmans R, Van Oppen M (2010) Estimating

the potential for adaptation of corals to climate warming. PLoS ONE, 5, e9751.

Dawson TP, Jackson ST, House JI, Prentice IC, Mace GM (2011) Beyond predictions:

biodiversity conservation in a changing climate. Science, 332, 53–58.

De’ath G, Fabricius KE, Sweatman H, Puotinen M (2012) The 27–year decline of coral

cover on the Great Barrier Reef and its causes. Proceedings of the National Academy

of Sciences, 109, 17995–17999.

Desalvo MK, Voolstra CR, Sunagawa S et al. (2008) Differential gene expression dur-

ing thermal stress and bleaching in the Caribbean coral Montastraea faveolata.

Molecular Ecology, 17, 3952–3971.

Donner SD (2009) Coping with commitment: projected thermal stress on coral reefs

under different future scenarios. PLoS ONE, 4, e5712.

Donner SD (2011) An evaluation of the effect of recent temperature variability on the

prediction of coral bleaching events. Ecological Applications, 21, 1718–1730.

Donner SD, Skirving WJ, Little CM, Oppenheimer M, Hoegh-Guldberg O (2005) Glo-

bal assessment of coral bleaching and required rates of adaptation under climate

change. Global Change Biology, 11, 2251–2265.

Donner SD, Heron SF, Skirving WJ (2009) Future scenarios: a review of modelling

efforts to predict the future of coral reefs in an era of climate change. In: Coral

Bleaching, (eds van Oppen MJH, Lough JM), 159–173. Springer, Berlin.

Dunne JP, John JG, Adcroft AJ et al. (2012) GFDL’s ESM2 global coupled climate-car-

bon Earth System Models Part I: physical formulation and baseline simulation

characteristics. Journal of Climate, 25, 6646–6665.

Dunne JP, Stouffer RJ, John JG (2013) Reductions in labour capacity from heat stress

under climate warming. Nature Climate Change, 3, 563–566.

Eakin CM, Lough JM, Heron SF (2009) Climate variability and change: monitoring

data and evidence for increased coral bleaching stress. In: Coral Bleaching (eds

Oppen MJH, Lough JM), pp. 41–67. Springer, Berlin, Heidelberg.

Eakin CM, Morgan JA, Heron SF et al. (2010) Caribbean corals in crisis: record ther-

mal stress, bleaching, and mortality in 2005. PLoS ONE, 5, e13969.

Edmunds PJ, Gates RD (2008) As we see it: acclimatization in tropical reef corals.

Marine Ecology Progress Series, 361, 307–310.

Falkowski PG, LaRoche J (1991) Acclimation to spectral irradiance in algae. Journal of

Phycology, 27, 8–14.

Fitt WK, Gates RD, Hoegh-Guldberg O et al. (2009) Response of two species of Indo-

Pacific corals, Porites cylindrica and Stylophora pistillata, to short-term thermal

stress: the host does matter in determining the tolerance of corals to bleaching.

Journal of Experimental Marine Biology and Ecology, 373, 102–110.

Frieler K, Meinshausen M, Golly A, Mengel M, Lebek K, Donner SD, Hoegh-Guld-

berg O (2012) Limiting global warming to 2°C is unlikely to save most coral reefs.

Nature Climate Change, 3, 165–170.

Gates RD, Edmunds PJ (1999) The physiological mechanisms of acclimatization in

tropical reef corals. American Zoologist, 39, 30–43.

Glynn PW (1993) Coral reef bleaching: ecological perspectives. Coral Reefs, 12, 1–17.

Glynn PW (1996) Coral reef bleaching: facts, hypotheses and implications. Global

Change Biology, 2, 495–509.

Glynn PW, D’Croz L (1990) Experimental evidence for high temperature stress as the

cause of El Nino-coincident coral mortality. Coral Reefs, 8, 181–191.

Goreau TJ, Hayes RL (1994) Coral bleaching and ocean “hot spots”. Ambio-Journal of

Human Environment Research and Management, 23, 176–180.

Goreau TJ, Hayes RM, Strong AE (1997) Tracking South Pacific coral reef bleaching

by satellite and field observations. In: Proceedings of the 8th International Coral Reef

Symposium pp. 1491–1494. Panama City, Panama.

Guest JR, Baird AH, Maynard JA et al. (2012) Contrasting patterns of coral bleaching

susceptibility in 2010 suggest an adaptive response to thermal stress. PLoS ONE, 7,

e33353.

Guilyardi E, Wittenberg A, Fedorov A et al. (2009) Understanding El Ni~no in ocean–

atmosphere general circulation models. Bulletin of the American Meteorological Soci-

ety, 90, 325–340.

Hegerl G, Braconnot P, Allen M (2007) Understanding and attributing climate

change. In: Climate Change 2007: The Physical Science Basis (eds Solomon S, Qin D,

Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Tignor M, Miller HL), pp.

663–745. Cambridge University Press, Cambridge.

Hoegh-Guldberg O (1999) Climate change, coral bleaching and the future of the

world’s coral reefs. Marine and Freshwater Research, 50, 839–866.

Hoegh-Guldberg O, Mumby PJ, Hooten AJ et al. (2007) Coral reefs under rapid

climate change and ocean acidification. Science, 318, 1737–1742.

Hoffmann AA, Sgr�o CM (2011) Climate change and evolutionary adaptation. Nature,

470, 479–485.

Hughes TP, Baird AH, Bellwood DR et al. (2003) Climate change, human impacts,

and the resilience of coral reefs. Science, 301, 929–933.

Jokiel P, Coles S (1977) Effects of temperature on the mortality and growth of Hawai-

ian reef corals. Marine Biology, 43, 201–208.

Jokiel P, Coles S (1990) Response of Hawaiian and other Indo-Pacific reef corals to

elevated temperature. Coral Reefs, 8, 155–162.

Jones AM, Berkelmans R (2011) Tradeoffs to thermal acclimation: energetics and

reproduction of a reef coral with heat tolerant Symbiodinium type-D. Journal of

Marine Biology, 2011, 1–12.

Jones AM, Berkelmans R, van Oppen MJH, Mieog JC, Sinclair W (2008) A community

change in the algal endosymbionts of a scleractinian coral following a natural

bleaching event: field evidence of acclimatization. Proceedings of the Royal Society B:

Biological Sciences, 275, 1359–1365.

LaJeunesse TC, Smith RT, Finney J, Oxenford H (2009) Outbreak and persistence of

opportunistic symbiotic dinoflagellates during the 2005 Caribbean mass coral

“bleaching” event. Proceedings of the Royal Society B: Biological Sciences, 276, 4139–

4148.

LaJeunesse TC, Smith R, Walther M et al. (2010) Host–symbiont recombination

versus natural selection in the response of coral–dinoflagellate symbioses to

environmental disturbance. Proceedings of the Royal Society B: Biological Sciences,

277, 2925–2934.

Liu G, Rauenzahn J, Heron SF et al. (2013) NOAA Coral Reef Watch 50 km Satellite Sea

Surface Temperature-Based Decision Support System for Coral Bleaching Management.

NOAA/NESDIS, Silver Spring, MD.

Logan CA, Dunne JP, Eakin CM, Donner SD (2012) A framework for comparing coral

bleaching thresholds. In: Proceedings of the 12th International Coral Reef Symposium

(ed. Yellowlees D, Hughes TP), pp. 10A3. Townsville.

Lough JM (2010) Climate records from corals. Wiley Interdisciplinary Reviews: Climate

Change, 1, 318–331.

Loya Y, Sakai K, Yamazato K, Nakano Y, Sambali H, van Woesik R (2001) Coral

bleaching: the winners and the losers. Ecology Letters, 4, 122–131.

Maina J, Venus V, McClanahan TR, Ateweberhan M (2008) Modelling susceptibility

of coral reefs to environmental stress using remote sensing data and GIS models.

Ecological Modelling, 212, 180–199.

Marshall P, Baird A (2001) Bleaching of corals on the Great Barrier Reef: differential

susceptibilities among taxa. Coral Reefs, 19, 155–163.

Maynard JA, Anthony KRN, Marshall PA, Masiri I (2008) Major bleaching

events can lead to increased thermal tolerance in corals. Marine Biology, 155,

173–182.

McClanahan TR, Ateweberhan M, Muhando CA, Maina J, Mohammed MS (2007)

Effects of climate and seawater temperature variation on coral bleaching and mor-

tality. Ecological Monographs, 77, 503–525.

Middlebrook R, Hoegh-Guldberg O, Leggat W (2008) The effect of thermal history on

the susceptibility of reef-building corals to thermal stress. Journal of Experimental

Biology, 211, 1050–1056.



Mieog JC, Olsen JL, Berkelmans R, Bleuler-Martinez SA, Willis BL, van Oppen MJH

(2009) The roles and interactions of symbiont, host and environment in defining

coral fitness. PLoS ONE, 4, e6364.

Moss RH, Edmonds JA, Hibbard KA et al. (2010) The next generation of scenarios for

climate change research and assessment. Nature, 463, 747–756.

Oliver T, Palumbi S (2011a) Do fluctuating temperature environments elevate coral

thermal tolerance? Coral Reefs, 30, 429–440.

Oliver T, Palumbi S (2011b) Many corals host thermally resistant symbionts in high-

temperature habitat. Coral Reefs, 30, 1–10.

Oliver JK, Berkelmans R, Eakin CM (2009) Coral Bleaching in Space and Time. In:

Coral Bleaching (eds Oppen MJH, Lough JM), pp. 21–39. Heidelberg, Springer, Ber-

lin Heidelberg, Berlin.

Peters GP, Andrew RM, Boden T et al. (2013) The challenge to keep global warming

below two degrees. Nature Climate Change, 3, 4–6.

Rayner NA, Parker DE, Horton EB et al. (2003) Global analyses of sea surface temper-

ature, sea ice, and night marine air temperature since the late nineteenth century.

Journal of Geophysical Research: Atmospheres, 108, 4407.

Reichler T, Kim J (2008) How well do coupled models simulate today’s climate. Bulle-

tin-American Meteorological Society, 89, 303.

Riegl BM, Purkis SJ, Al-Cibahy AS, Abdel-Moati MA, Hoegh-Guldberg O (2011) Pres-

ent limits to heat-adaptability in corals and population-level responses to climate

extremes. PLoS ONE, 6, e24802.

Robison JD, Warner ME (2006) Differential impacts of photoacclimation and thermal

stress on the photobiology of four different phylotypes of Symbiodinium

(pyrrhophyta). Journal of Phycology, 42, 568–579.

Sampayo EM, Ridgway T, Bongaerts P, Hoegh-Guldberg O (2008) Bleaching suscepti-

bility and mortality of corals are determined by fine-scale differences in symbiont

type. Proceedings of the National Academy of Sciences, 105, 10444–10449.

Schmidt-Nielsen K (1997) Animal Physiology: Adaptation and Environment. Cambridge

University Press, Cambridge.

Sheppard CRC (2003) Predicted recurrences of mass coral mortality in the Indian

Ocean. Nature, 425, 294–297.

Sheppard C, Rioja-Nieto R (2005) Sea surface temperature 1871–2099 in 38 cells in the

Caribbean region. Marine environmental research, 60, 389–396.

Silverstein RN, Correa AMS, Baker AC (2012) Specificity is rarely absolute in coral–

algal symbiosis: implications for coral response to climate change. Proceedings of

the Royal Society B: Biological Sciences, 279, 2609–2618.

Smith-Keune C, van Oppen M (2006) Genetic structure of a reef-building coral

from thermally distinct environments on the Great Barrier Reef. Coral Reefs, 25,

493–502.

Somero GN (2010) The physiology of climate change: how potentials for acclimatiza-

tion and genetic adaptation will determine ‘winners’ and ‘losers’. Journal of Experi-

mental Biology, 213, 912–920.

Teneva L, Karnauskas M, Logan CA, Bianucci L, Currie JC, Kleypas JA (2012) Predict-

ing coral bleaching hotspots: the role of regional variability in thermal stress and

potential adaptation rates. Coral Reefs, 31, 1–12.

Thompson DM, van Woesik R (2009) Corals escape bleaching in regions that recently

and historically experienced frequent thermal stress. Proceedings of the Royal Society

B, 276, 2893–2901.

Thornhill DJ, LaJeunesse TC, Kemp DW, Fitt WK, Schmidt GW (2005) Multi-year,

seasonal genotypic surveys of coral-algal symbioses reveal prevalent stability or

post-bleaching reversion. Marine Biology, 148, 711–722.

Ulstrup KE, Berkelmans R, Ralph PJ, van Oppen M (2006) Variation in bleaching sen-

sitivity of two coral species across a latitudinal gradient on the Great Barrier Reef:

the role of zooxanthellae.Marine Ecology Progress Series, 314, 135–148.

Van Hooidonk R, Huber M (2009) Quantifying the quality of coral bleaching predic-

tions. Coral Reefs, 28, 579–587.

Van Hooidonk R, Maynard JA, Planes S (2013) Temporary refugia for coral reefs in a

warming world. Nature Climate Change, 3, 508–511.

Van Woesik R, Sakai K, Ganase A, Loya Y (2011) Revisiting the winners and the losers

a decade after coral bleaching.Marine Ecology Progress Series, 434, 67–76.

Voolstra CR, Sunagawa S, Matz MV et al. (2011) Rapid evolution of coral proteins

responsible for interaction with the environment. PLoS ONE, 6, e20392.

Ware JR, Fautin DG, Buddemeier RW (1996) Patterns of coral bleaching: modeling

the adaptive bleaching hypothesis. Ecological Modelling, 84, 199–214.

Weis VM (2010) The susceptibility and resilience of corals to thermal stress: adapta-

tion, acclimatization or both? Molecular Ecology, 19, 1515–1517.

Supporting Information

Additional Supporting Information may be found in the online version of this article:

Figure S1. Percent of global reef cells predicted to experience high-frequency bleaching under RCPs 2.6, 4.5 and 8.5, using the GFDLESM2Mmodel with (black) and without (gray) a bias correction in the climatological maximum that reduces the frequency of ENSOevents in the model (Model 1). An historical climatology (1900–1919) predicts over 50% of global reef cells experiencing severe coralbleaching (more than two bleaching events in 10 years) before the year 2000. A satellite-era climatology (1985–2004) predicts over50% of global reef cells experiencing high-frequency bleaching by ca. 2030. Results for RCP 6.0 can be found in Fig. 2.Figure S2. Maps of high-frequency bleaching predictions in model years 2010, 2030, 2050, and 2070 with a 1985–2004 climatologyunder the moderately high RCP, 6.0 W m�2 by 2100 (black lines in Fig. 1c). Blue represents a reef location without severe bleaching.Green represents a severe bleaching prediction using the GFDL ESM2M model. Red represents a severe bleaching prediction usingbias-corrected ESM2M.Figure S3. Percent of global reef cells predicted to experience high-frequency bleaching in the adaptive response models. Model 2(a and b) uses a rolling climatological period representative of an adaptive response to recent thermal history over the previous 40,60, 80, or 100 years. Model 3 (c and d) employs a temporary increase in the bleaching threshold of 1 °C after a bleaching event,which may be representative of a temporary increase in thermal tolerance due to symbiont shuffling or transient community shiftstoward more heat-tolerant taxa. Both bleaching models use SST output from the GFDL ESM2M bias-corrected model for the lowestRCP 2.6 (a and c) and moderately low RCP 4.5 (b and d). For comparison, dashed lines in all panels represent the correspondingresults from the ‘no adaptive response’ (Model 1) using the 1985–2004 climatology. Results for RCPs 6.0 and 8.5 can be found inFig. 3.Figure S4. Percent of global reef cells predicted to experience high-frequency bleaching for the moderately high RCP (6.0 W m�2 by2100) using the GFDL ESM2M bias-corrected model with a temporary increase in the Degree Heating Month threshold of 1 °C aftera bleaching event and four differing rolling climatology windows (Model 4). For example, this model might represent the additiveeffect of genetic adaptation to recent thermal history and temporary increases in thermal tolerance due to symbiont shuffling.



Date post:	24-Apr-2023
Category:	Documents
Upload:	independent
View:	0 times
Download:	0 times

Modeling the effects of climate change and acidification on global coral reefs

Documents