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Ecological Applications, 19(6), 2009, pp. 1492–1499
Ó 2009 by the Ecological Society of America
Improved water quality can ameliorate effects
of climate change on corals
SCOTT A. WOOLDRIDGE1
AND
TERENCE J. DONE
Australian Institute of Marine Science, PMB#3 Townsville MC, Queensland 4810 Australia
Abstract. The threats of wide-scale coral bleaching and reef demise associated with
anthropogenic climate change are widely known. Moreover, rates of genetic adaptation and/or
changes in the coral–zooxanthella partnerships are considered unlikely to be sufficiently fast
for corals to acquire increased physiological resistance to increasing sea temperatures and
declining pH. However, it has been suggested that coral reef resilience to climate change may
be improved by good local management of coral reefs, including management of water quality.
Here, using major data sets from the Great Barrier Reef (GBR), Australia, we investigate
geographic patterns of coral bleaching in 1998 and 2002 and outline a synergism between heat
stress and nutrient flux as a major causative mechanism for those patterns. The study provides
the first concrete evidence for the oft-expressed belief that improved coral reef management
will increase the regional-scale survival prospects of coral reefs to global climate change.
Key words: bleaching threshold; CO2 limitation; coral reef; dissolved inorganic nitrogen (DIN); Great
Barrier Reef, Australia; zooanthellae species.
INTRODUCTION
In favorable environmental conditions, the obligate
endosymbiosis between corals and dinoflagellate algae
of the genus Symbiodinium (‘‘zooxanthellae’’) is characterized by an excess translocation of fixed-carbon
photosynthetic products (photosynthates) from the
zooxanthellae to the coral host (Fig. 1a; Muscatine
1990). Breakdown of the symbiosis (coral bleaching)
occurs when a significant proportion of the zooxanthellae compliment is expelled from the coral animal (Brown
1997). Prolonged bleaching can be fatal to the coral
host, and can devastate entire reef-scapes over vast areas
of ocean (see, e.g., Sheppard 2003). The primary
triggering condition for large-scale mass bleaching
events is the combination of high solar irradiance and
anomalously warm sea surface temperatures (SSTs;
reviewed by Hoegh-Guldberg 1999). Such sensitivity
makes coral reefs vulnerable to future climate change,
with some scientists predicting that global warming
trends could see the majority of the world’s coral reefs
severely degraded or even transformed to non-coraldominated states by as early as 2030 (see, e.g., HoeghGuldberg et al. 2007). Perhaps more in hope than
expectation, the opinion has commonly been expressed
that improved coral reef management, by delivering
conditions that favor the recovery of coral reefs
following disturbance, could forestall the onset of such
a catastrophe (see, e.g., Marshall and Schuttenberg
2006). In particular, improved water quality (primarily
Manuscript received 27 May 2008; revised 11 December
2008; accepted 22 December 2008. Corresponding Editor: L. A.
Deegan.
1 E-mail: [email protected]
the regulation of input of dissolved inorganic nitrogen,
DIN) is an identified management goal for promoting a
reef’s ‘‘resilience’’ to disturbance (McCook et al. 2007).
Based on a new conceptual model for the warm-water
breakdown of the coral–algae symbiosis, Wooldridge
(2009a) recently raised the possibility that reduced DIN
in the seawater surrounding reefs could also directly
benefit corals by enhancing their resistance to heat
stress, i.e., raise the temperature thresholds that trigger
bleaching. In this paper, we consider the implications of
this suggestion at the scale of sea-scapes and regions on
the GBR, wherein the coastal waters are highly ‘‘DIN
enriched’’ as a consequence of a century and a half of
European settlement of north Queensland (Wooldridge
et al. 2006). However it is first necessary to briefly
summarize our current understanding of warm water
coral bleaching and DIN at organism, cellular and
subcellular scales. A detailed account of the work
summarized in the next paragraph is provided in
Wooldridge (2009a).
The warm-water bleaching syndrome of the coral–
algae endosymbiosis follows a sequence of algal photoinhibition, oxidative damage, and host cell membrane
disruption (e.g., Gates et al. 1992, Lesser 1996, Jones et
al. 1998, Warner et al. 1999). Wooldridge (2009a)
proposes that the onset of this sequence is linked with
a disruption to the ‘‘dark’’ photosynthetic reactions of
the algal endosymbionts, implicating limited availability
of CO2 substrate around the Rubisco enzyme (Fig. 1b).
In this way, biophysical factors that cause CO2 demand
to exceed CO2 supply within the coral’s intracellular
milieu are identified as bleaching risk factors (Fig. 2). In
terms of CO2 demand, an enlarged endosymbiont
population increases the likelihood of CO2 becoming a
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FIG. 1. (a) Schematic overview of the internal carbon cycling that is maintained by the coral–zooxanthellae symbiosis. (b)
Schematic representation of the breakdown of the symbiosis (¼zooxanthellae expulsion), as triggered by a limitation of CO2
substrate for the ‘‘dark’’ reactions of zooxanthellae photosynthesis. ‘‘Pi’’ indicates orthophosphate.
FIG. 2. Schematic overview of the biophysical factors that interact to determine the demand- and supply-side dynamics for CO2
substrate within the intracellular endosymbiont population. Factors that promote enlarged zooxanthellae densities increase CO2
demand, while factors that promote fast zooxanthellae growth rates ultimately decrease CO2 supply via ATP limitation of host
‘‘CO2-concentrating mechanisms’’ (CCMs). Factors that can forestall ATP limitation help to maintain the CCMs. The notation
f(factors) indicates a function of those factors; pCO2 is partial pressure of CO2.
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limiting internal substrate during periods of peak
photosynthesis (discussed by Dubinsky et al. 1990).
Several factors promote enlarged endosymbiont populations (particularly on a per host cell basis), including
DIN enrichment in the surrounding sea water (Muscatine et al. 1998), partial pressure of CO2, pCO2,
enrichment in the surrounding sea water (Reynaud et
al. 2003), and diffusive (i.e., branching) coral colony
morphologies (Helmuth et al. 1997, Muscatine et al.
1998). Experimental manipulations confirm the higher
number of zooxanthellae expelled during periods of high
irradiance in corals exposed to DIN enrichment
(Stimson and Kinzie 1991). However, since a coral’s
total photosynthetic demand for CO2 is determined by
the dynamic interplay between zooxanthellae population
density and solar irradiance levels, a decline in either
should return equilibrium and terminate the expulsion
process. The problem arises in circumstances where an
irradiance-driven reduction in zooxanthellae numbers
also triggers disruption in the CO2 supply for the
remnant zooxanthellae population. Underpinning the
bulk CO2 supply for the intracellular zooxanthellae is a
range of active host CO2-concentrating mechanisms
(CCMs) (Appendix A: Fig. A1). The cellular energy
(ATP) needed to activate the host CCMs is tightly
coupled to the transfer of excess photosynthates from
the zooxanthellae (Al-Horani et al. 2003). Subtly, this
means that the zooxanthellae indirectly play a role in
generating the CO2 that they themselves require for
photosynthesis. Therefore, should the flow of photosynthates from the zooxanthellae be disrupted, then the
capacity of the coral host to energize the CCMs becomes
limiting, leaving a proportion of the zooxanthellae
vulnerable to CO2 limitation (and expulsion); thereby
further enhancing the reduction in photosynthate flux.
Wooldridge (2009a) proposes that the potential onset of
this destructive self-enhancing feedback is ultimately
determined by the rate of (re)growth (mitotic index, MI
[%]) of the remnant zooxanthellae population following
an initial irradiance-driven expulsion event. When a
large number of zooxanthellae are expelled (per day)
and then subsequently produced (per day), the increased
respiratory cost of such turnover can lead to a negative
autotrophic balance (see, e.g., Hoogenboom et al. 2006)
where more carbon per day is directed into new cell
production than is transferred to the coral host. This
inverse relationship between photosynthate transfer and
symbiont MI has been documented in corals, sea
anemones, and jellyfish (Verde and McCloskey 1996,
McGuire and Szmant 1997, Sachs and Wilcox 2006).
Hot water and high irradiance drive high zooxanthellae
MI (Goldman and Carpenter 1974, Strychar et al. 2004)
but only so long as DIN is not limiting to cell
multiplication (Fitt 2000).
In this way, it is understood that upper thermal
bleaching thresholds are not static, but rather, are
directly related to the growth dynamic of the endosymbiont population. Thermal (kinetic) increases in MI are
Ecological Applications
Vol. 19, No. 6
exacerbated by a surfeit of external seawater DIN,
which leads to the entire bleaching syndrome at a lower
temperature than would be the case in the absence of
excess DIN. With that as our premise, we now consider
its implications for populations, communities and reefscapes. First, we explore the hypotheses that, compared
to analyses based on temperature alone, inclusion of
DIN as a causative factor substantially increases the
explained variability in complex patterns of coral
bleaching documented on the GBR in 1998 and 2002.
Second, we develop the proposition that substantial
reduction of coastal DIN, as is currently being pursued
for GBR waters, will have a serendipitous benefit of
increasing the tolerance of corals to temperatures they
currently find intolerable.
METHODS
We used a spatially explicit Bayesian belief network
(BBN) model (Pearl 1988, Wooldridge and Done 2004)
to investigate the benefits of inclusion of DIN in
explaining and predicting variability in complex patterns
of coral bleaching documented on the GBR in 1998 and
2002. The data set included (1) geographic patterns of
coral bleaching observed during aerial surveys of ;1300
reefs (Berkelmans et al. 2004), (2) the maximum SST
occurring at each reef over any three-day period
(max3d) in those bleaching periods as a proxy for heat
stress (Fig. 3c), (3) decadal average summer SST at each
reef as a proxy for thermal history (Fig. 3a), and (4) an
index of water quality at each reef based on the inverse
risk of exposure to DIN-rich terrestrial runoff (Fig. 3b).
Further description of the methods of data collection,
analysis, and proxy justification is provided as supplementary material (see Appendix B).
We used the Netica software package (Norsys
Software, Vancouver, British Columbia, Canada) to
build a BBN that describes how measurable attributes at
each reef (max3d, water quality index, mean summer
maximum SST), and inferred (bleaching resistance) reef
attributes combine to influence bleaching status (i.e.
presence/absence; Fig. 3e). The BBN visualizes the
dependency relationships as arcs between our proxy
indicator variables, which are represented in the BBN as
multi-state nodes. The arcs connecting the nodes are
directional and point from parent nodes to child nodes,
i.e., the intuitive meaning of a directed link is that the
parent node has a direct influence on the child node. The
absence of a link between two variables indicates
conditional independence between them. The strength
(i.e., certainty) of the dependency link between a child
and its parent node(s) is summarized through a
conditional probability table (CPT). The CPT specifies
the conditional probability of the child node being in a
particular state, given the states of all of its parents (i.e.,
P[child j parent1, parent2, ... parentN]) and aims to reflect
the fact that some states in the model domain will tend
to occur more frequently when other states are also
present.
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FIG. 3. Data sets, tools, and predictions along the Great Barrier Reef (GBR). (a) Thermal history index based on the typical
maximum summer sea surface temperature (SST). (b) Water quality index based on the inverse risk of exposure to terrestrial runoff
that is rich in dissolved inorganic nitrogen (DIN). (c) Heat stress index based on maximum SST occurring over any three-day
period (max3d) during summer of 1998. (d) Predicted areas of low resistance to coral bleaching (in red). (e) Bayesian belief network
showing how (a), (b), and (c), were used to predict (d). (f ) Temperature-dependent probability of coral bleaching in the ‘‘low
resistance’’ (red) and ‘‘not low resistance’’ area (green) in (d). For any given temperature, improved water quality reduces the
probability of bleaching (Pbleaching ).
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We populated the CPTs based on the ;1300 reef
(bleaching) responses observed during 1998 and 2002
bleaching events on the GBR, and the measurable proxy
variables of water quality, thermal history, and heat
stress at each of those reefs. Bleaching resistance (Fig.
3e) is an ‘‘unobservable’’ attribute generated by the
model using the expectation maximization (EM) algorithm (Dempster et al. 1977). Its bimodal behavior (high
resistance; low resistance) was learned based on the
conditional interactions between the measurable proxy
variables and ‘‘bleaching’’ response, i.e., the EM
algorithm searched over the CPTs to maximize the
probability of the data (bleaching response) given the
dependence-structured network. The calibrated BBN
allowed our site-specific observations (i.e., parent states)
to be propagated throughout the network via a
probabilistic inference algorithm (Lauritzen and Spiegelhalter 1988), the key output being the likelihood of
different states in our ‘‘bleaching’’ node (Fig. 3e).
Finally, the bidirectional reasoning feature of the BBN
was used to diagnose the most likely states of water
quality and thermal history that lead to high or low
bleaching resistance.
RESULTS
Previous analysis of the aerial survey data (Berkelmans et al. 2004) had shown that the max3d indicator of
short-term heat stress alone was an excellent predictor of
bleaching likelihood (presence or absence), with a
predictive accuracy of 73% (SD ¼ 2.0%). We improved
this predictive capacity to 84% (SD ¼ 1.41%) by
inclusion in the BBN of water quality (Fig. 2b) and
thermal history (Fig. 2a), the former of which is
potentially amenable to local reef management. Within
the BBN, the system states of water quality explained
68% of the (relative) belief variance of resistance while
thermal history explained only 32%. The higher
predictive significance of water quality is reflected in
the spatially interpolated pattern of the bleaching
resistance states. For example, zones with high probability (.0.55) of being classified low resistance (i.e., high
sensitivity to heat stress) display strong spatial coherence with the low water quality state (Fig. 3d). However,
back propagation of the BBN confirmed the subtle
(conditional) importance of thermal history for classifying bleaching resistance, despite its relatively low
explanatory power (32%) as a stand alone parent. For
example, low resistance was found to be most probable
at low water quality and high thermal history sites,
whereas high resistance was most probable at high water
quality and low thermal history sites. Spatial interrogation of the original (observed) bleaching response data
from within (and outside) the zone of low resistance was
used to generate functions of differential susceptibility to
heat stress (Fig. 3f ). These two-parameter Weibull
functions show that the onset of bleaching occurs at a
temperature ;1.08–1.58C higher for reefs in the high
Ecological Applications
Vol. 19, No. 6
resistance domain than those in the low resistance
domain.
DISCUSSION
The coral–zooxanthellae endosymbiosis is highly
adapted to clear, nutrient-poor (oligotrophic) waters,
where the rate of proliferation of in hospite zooxanthellae populations is nitrogen limited (Hallock 2001).
Nitrogen limitation ensures that photosynthetic carbon
assimilation and its retention for zooxanthellae growth
are sufficiently out of balance that there is a vitally
important transfer of (excess) energy-rich photosynthates to the coral host, fueling its production of tissues,
skeleton, and gametes (Dubinsky and Jokiel 1994,
Dubinsky and Berman-Frank 2001). Moreover, the
continuity in supply of metabolically cheap photosynthate represents a crucial element in forestalling the
bleaching syndrome (Wooldridge 2009a). The progressive (self-enhancing) reduction in photosynthate transfer
caused by temperature- and irradiance-driven zooxanthellae turnover (i.e., expulsion and regrowth) is
exacerbated by any surfeit of external seawater DIN
that releases the zooxanthellae from their growth-limited
state, and leads to the entire bleaching syndrome at a
lower temperature than would be the case in the absence
of excess DIN.
In our analysis, we showed that corals bathed in
nutrient-rich coastal waters had a decreased bleaching
resistance (per degree of heating) during the 1998 and
2002 bleaching events compared to reefs in oligotrophic
oceanic waters, effectively lowering the upper thermal
bleaching threshold by ;1.0–1.58C (Fig. 3f ). A complementary investigation suggests these figures could be as
much as 2.0–2.58C in the most DIN-enriched locations
(Wooldridge 2009b). These findings are consistent
observations that global reef locations that exhibit
naturally high (.338C) upper thermal bleaching thresholds generally have extremely low summer nutrient
regimes (e.g., Red Sea; Genin et al. 1995). More
importantly, the findings confirm that coral reef
management interventions that seek to cause nutrients
to become limiting to proliferation of benthic algae on
reefs also have a strong rational basis as a bleaching
prevention strategy.
Terrestrial runoff is not the only source of DIN that
impacts upon the GBR, with periodic upwelling of deep
(nutrient-rich) oceanic water often a dominating feature
on the outer-shelf reefs (Andrews and Gentien 1982).
Field observations from elsewhere around the world
suggest that reefs which are exposed to nutrient
upwelling also have enhanced thermal bleaching impacts
(D’Croz et al. 2001). Clearly, the influence of oceanic
(upwelled) DIN on bleaching sensitivity remains outside
the realm of management, so coral reef management
interventions will be most effective on the inner-shelf
reefs of the GBR where terrestrial nutrients sources are
most often the dominating influence (Wooldridge et al.
2006). However, a better understanding of the spatio-
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FIG. 4. Schematic representation of trends in sea temperatures (solid line) and ‘‘resistance’’ to coral bleaching (dotted lines).
Anthropogenic pressures tend to reduce resistance through time (falling dotted line). Prospective mechanisms that could increase
resistance (rising dotted line) include (1) endsoymbiont reshuffling (Berkelmans and van Oppen 2006), (2) community composition
shifts toward corals that can counter the bleaching response via access to stored tissue reserves (Loya et al. 2001) or heterotrophic
energy sources (Borell and Bischof 2008), and (3) region-scale amelioration of poor water quality (this study).
temporal dynamics of DIN loading across the entire
GBR is necessary for identifying those areas most
vulnerable to heat stress. Within the GBR, DIN loading
is typically highest at coastal locations that are exposed
to terrestrial runoff, lowest at mid-shelf locations, and
moderate at offshore (upwelling) locations (see, e.g.,
Sammarco et al. 1999). All things being equal, it is
therefore predicted that the mid-shelf reefs of the GBR
should display the highest resistance to heat stress.
However, all things are not equal, and we note in
particular the existence of different zooxanthellae strains
(clades) with different kinetic growth dynamics (Fitt
1985, Kinzie et al. 2001). The Wooldridge (2009a) model
predicts that for maximum heat resistance it would be
advantageous for the symbiosis to be dominated by
zooxanthellae with a slow growth dynamic, such as
clade D (M. J. H. van Oppen, unpublished data). The
superior heat tolerance of corals that harbor clade D
zooxanthellae (see, e.g., Berkelmans and van Oppen
2006) is therefore consistent with MI being an important
consideration in defining upper thermal bleaching
thresholds. It follows that areas exposed to high summer
nutrient loads and heat stress should differentially favor
the presence of clade D symbionts. Indeed, following the
2002 GBR bleaching event, the occurrence of clade D
symbionts was highest on inshore reef sites that
experience high nutrient loads, and extremely rare on
the mid-shelf reefs (van Oppen et al. 2005). A similar
spatial pattern has been noted in Panama (Caribbean
Sea), where clade D symbionts dominate the coastal and
deep offshore (potential upwelling) locations (Toller et
al. 2001).
All is not equal also in relation to the specific risk of
exposure to terrestrial runoff. In the present study, the
calculation of this exposure risk was based on a
quantitative expectation that flood plumes reach and
deliver new nutrients to a reef (Devlin et al. 2003). This
approach provides a useful indicator for the long-runaveraged summer condition, but the potential exists for
this exposure risk to dynamically vary in response to
flood-plume specific differences in the extent of crossshelf dispersion. Furthermore, on the GBR the initial
enriching impact of a flood plume is experienced as a
short-term (days to weeks) pulse of high DIN water
(Devlin and Brodie 2005). This flux of inorganic
nutrients is subsequently recycled through pelagic food
webs (e.g., via nitrification), which maintains a longerterm (weeks to months) persistence of the initial
enriching impact, all be it at progressively lower levels
of DIN availability (Alongi and McKinnon 2005). In
this way, a coral’s bleaching resistance to heat stress may
also display subtle temporal dynamics based on the
specific timing of a flood in relation to a heat wave. The
intensity of summer upwelling events on the GBR will
vary on an annual basis. Clearly, the predictive capacity
of the present BBN model for offshore sites could be
improved by the development of a water quality index
that captures the dominant GBR upwelling zones.
The thermal history of a site is often considered to be
a fundamental determinant of a coral’s bleaching
resistance to heat stress, with cooler-water acclimated
corals often being more sensitive than warm-water
acclimated corals (see, e.g., Coles and Brown 2003).
For the present study, we observed the opposing
outcome, with (1) the most bleaching-resistant corals
being those that were acclimatized to cool, low-nutrient
(oceanic) conditions and (2) the least bleaching-resistant
corals being those that were acclimatized to warm, highnutrient (coastal) conditions. Cooler conditions lead to
lower zooxanthellae turnover and MI, which according
to Wooldridge (2009a) better facilitates the accumulation of tissue stores that can be drawn upon to provide
sustained offset to the autotrophic disruption that
underpins the warm-water bleaching response (see Fig.
2). This is consistent with the higher bleaching resistance
of corals that maintain thick tissue reserves (Loya et al.
2001). For reef sites that have upwelling as the dominant
physical feature responsible for their cool summer
thermal regime, we suggest that our generalized resistance response may be limiting.
The new conceptual picture that emerges from this
paper is of the fundamental importance of nutrient
loading, in particular DIN, in defining the bleaching
resistance of corals to heat stress (Fig. 4). A federally
funded program to reduce ambient DIN loads to reef
waters is being implemented with a view to lessening the
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SCOTT A. WOOLDRIDGE AND TERENCE J. DONE
fertilization of benthic algae and their propensity to
overwhelm coral reefs (Anonymous 2007). With this
analysis, we have shown that these actions also represent
a rational strategy for ameliorating climate change
effects on coral reefs, raising the temperature thresholds
that cause corals to bleach, and reducing bleaching
probability across the whole range of temperatures
predicted for the inshore GBR by 2100.
ACKNOWLEDGMENTS
We thank Ray Berklemans (AIMS) for making available the
GBR aerial bleaching survey data. This work was supported by
the Australian Government’s Marine and Tropical Science
Facility (MTSRF).
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APPENDIX A
Schematic overview of the active ‘‘CO2-concentrating mechanisms’’ of the coral host (Ecological Archives A019-060-A1).
APPENDIX B
Development and justification of the proxy indicators used to describe Great Barrier Reef system dynamics (Ecological Archives
A019-060-A2).