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Continued anthropogenic CO2 emissions are expected to impact tropical coral reefs by further raising sea surface temperatures (SST) and intensifying ocean acidification (OA). Although geoengineering by means of Solar Radiation Management (SRM) may mitigate temperature increases, OA will persist, raising important questions regarding the impact of different stressor combinations. We apply statistical Bioclimatic Envelope Models to project changes in shallow-water tropical coral reef habitat as a single niche (without resolving biodiversity or community composition) under various Representative Concentration Pathway and SRM scenarios, until 2070. We predict substantial reductions in habitat suitability centered on the Indo-Pacific Warm Pool under net anthropogenic radiative forcing of ≥3.0 W/m2. The near-term dominant risk to coral reefs is increasing SSTs; below 3 W/m2 reasonably favorable conditions are maintained, even when achieved by SRM with persisting OA. ‘Optimal’ mitigation occurs at 1.5 W/m2 because tropical SSTs over-cool in a fully-geoengineered (i.e. pre-industrial global mean temperature) world.
Tropical coral reef habitat in a geoengineered, high-
CO2 world
E. Couce, P. J. Irvine, L. J. Gregorie, A. Ridgwell, and E. J. Hendy
Continued anthropogenic CO2 emissions are expected to impact tropical coral
reefs by further raising sea surface temperatures (SST) and intensifying ocean
acidification (OA). Although geoengineering by means of solar radiation
management (SRM) may mitigate temperature increases, OA will persist, raising
important questions regarding the impact of different stressor combinations. We
apply statistical Bioclimatic Envelope Models to project changes in shallow water
tropical coral reef habitat as a single niche (without resolving biodiversity or
community composition) under various representative concentration pathway and
SRM scenarios, until 2070. We predict substantial reductions in habitat suitability
centered on the Indo-Pacific Warm Pool under net anthropogenic radiative forcing
of ! 3.0 W/m2. The near-term dominant risk to coral reefs is increasing SSTs;
below 3 W/m2 reasonably favorable conditions are maintained, even when
achieved by SRM with persisting OA. “Optimal” mitigation occurs at 1.5 W/m2
because tropical SSTs overcool in a fully geoengineered (i.e., preindustrial global
mean temperature) world.
An edited version of this paper was published by AGU. Copyright 2013 American Geophysical
Union. Citation: Couce, E., P. J. Irvine, L. J. Gregorie, A. Ridgwell, and E. J. Hendy (2013), Tropical coral
reef habitat in a geoengineered, high-CO2 world, Geophys. Res. Lett., 40, doi:10.1002/ grl.50340.
1. Introduction
Tropical shallow water coral reefs cover 0.1% of the world’s oceans, yet rank
among the most productive and biodiverse ecosystems. Anthropogenic pressures
have been implicated in significant long-term reef decline as well as abrupt coral
mortality events associated with extreme temperatures and bleaching [Hoegh-
Guldberg et al., 2007]. Solar radiation management (SRM) a form of
geoengineering achieved by adding reflective aerosols to the atmosphere [Crutzen,
2006], increasing cloud albedo [Latham and Smith, 1990], or increasing the albedo
of the Earth’s surface [Irvine et al., 2011], for example has the potential to
mitigate surface warming and hence hypothetically help safeguard shallow water
coral reef habitat. But by only seeking to diminish downward radiation [Angel,
2006], SRM achieves no direct mitigation of atmospheric CO2 and resulting
“ocean acidification”. The latter undermines habitat construction that supports
coral reef ecosystems because higher pCO2 reduces carbonate ion concentration
and associated saturation ("Arag) levels, in turn lowering net carbonate production
by corals and calcareous algae [Kleypas et al., 1999].
Any implementation of SRM geoengineering would therefore produce a complex
pattern of marine environmental changes, overall characterized by relatively low
sea surface temperatures (SST) but with high levels of atmospheric pCO2 and
ocean acidification. This raises important questions about the primary global
environmental threat(s) to tropical coral reefs: whether it is increased SSTs,
reduced "Arag, or that both factors are equally significant. Our motivation in this
paper is hence not to make a case for or against SRM but to explore the spatial and
temporal consequences of different potential global temperature and ocean
acidification futures for shallow water coral reefs. Bioclimatic Envelope Modeling
can be applied to forecast effects of climate change on species’ distribution [e.g.,
Thuiller et al., 2005] and statistically analyze the environmental requirements of
coral reef ecosystems [Couce et al., 2012]. We use this approach to explore how
changing future environmental conditions with and without SRM geoengineering
could affect the potential suitability of global shallow water habitats for coral reef
2. Methods
Bioclimatic Envelope Modeling analyzes the relationship between environmental
factors and the distribution of a species (or an ecosystem), using statistical
correlation to identify acceptable environmental ranges and the relative
significance of the different factors. We used two machine-learning techniques:
maximum entropy (MaxEnt) [Phillips et al., 2006] and boosted regression trees
(BRT) [Friedman, 2001]. The assumption behind MaxEnt is that a
species/ecosystem will occupy all suitable habitat in as random a way as possible;
MaxEnt then identifies which constraints maximize the entropy of the system.
BRT is based on decision trees. A single tree is built by repeatedly finding a
simple rule (whether one of the predictive variables is above or below a specific
threshold) that can split the data into groups providing the best separation of
presence and absence sites. A sequence of trees (typically >1000) is produced,
each grown on reweighted versions of the data, with final predictions obtained
from the weighted average across the tree sequence.
Couce et al. [2012] provides a detailed analysis and background to BRT and
MaxEnt in relation to establishing environmental controls on tropical coral reef
biogeography. In the current study 12 environmental fields were considered
including SST, "Arag, salinity, nutrients, and light availability. We chose "Arag
over pH because coral calcification is directly linked to saturation state, although
under rapid fossil fuel CO2 release changes in both variables will be closely
correlated [Hönisch et al., 2012]. In total, 27 predictive variables were used,
including mean annual and extreme monthly values for most fields in addition to
weekly extremes and standard deviation of SST (for complete list and relative
contribution to predictions see Appendix S1). Model training data sets were
generally observation-based except "Arag and SST, which were obtained from
1990 projections of the University of Victoria (UVic) Earth System Climate
Model [Weaver et al., 2001; Turley et al., 2010] of open ocean water in proximity
to reefs. All fields were mapped onto a 1°x1° global grid between 60°S and 60°N;
for cells outside the open-ocean mask, environmental data were extrapolated up to
1° by linear average of neighboring cells. The models were trained on a “shallow
water mask” defined by bathymetry within the euphotic zone and the area covered
by UVic projections (Figure S1.1). Locations of shallow water reef and coral
communities were provided by ReefBase (version 2000;
[Vergara et al., 2000]) and projected on the 1°x1° grid as binary presence/absence
data. See Appendix S1 and Couce et al. [2012] for further details on model
development and variables.
Figure 1. Simulated spatial anomalies, year 2070 minus preindustrial (P-I), of (top, a and b) sea
surface temperature (SST) and (bottom, c and d) aragonite saturation state ("Arag) under RCP 8.5
(a and c) and with SRM geoengineering returning total anthropogenic radiative forcing to P-I
values in the “RCP 8.5 & GEO 8.5” scenario (b and d). Change in shallow water tropical coral
90°E 180° 90°W
a) RCP 8.5
ï ï ï 0 1 2 3
SST anomaly (°C)
90°E 180° 90°W
b) RCP 8.5 & GEO 8.5
90°E 180° 90°W
c) RCP 8.5
ï ï ï ï ï 0.0
1Arag anomaly
90°E 180° 90°W
d) RCP 8.5 & GEO 8.5
90°E 180° 90°W
e) RCP 8.5
ï ï ï 0.00 0.25 0.50 
Average change in suitability
90°E 180° 90°W
reef habitat suitability between 2070 and P-I, averaged from BRT and MaxEnt model outputs for
RCP 8.5 (e) and “RCP 8.5 & GEO 7,” with SRM geoengineering to reduce anthropogenic
radiative forcing to 1.5 W/m2 above P-I by 2100 (f). Green dotted line corresponds to 0 change;
black hatched pattern overlays area where projections move beyond training range with
significant influence on predictions. For other scenarios, see Appendix S2.
Future and preindustrial (P-I) projections of mean annual SST and "Arag were
determined using the UVic model [Weaver et al., 2001] version 2.9, which
comprises an atmosphere Energy Moisture Balance Model coupled to a 3D ocean
general circulation model, both at a spatial resolution of 1.8°x3.6°. Ocean
chemistry was calculated by the biogeochemical and carbon cycle model of
Schmittner et al. [2008]. The UVic model was forced with concentrations of CO2
and other greenhouse gases from the representative concentration pathways
(RCPs) [Moss et al., 2010] developed for the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change corresponding to a total
anthropogenic radiative forcing of 3, 4.5, 6, and 8.5 W/m2 above P-I at 2100,
respectively (labeled “RCP 3” to “RCP 8.5”). The extent of SRM geoengineering
considered for each RCP scenario either brought radiative forcing back to P-I
levels or to a particular forcing above P-I (the geoengineering forcing is labeled
“GEO” followed by the amount reduced; e.g., “GEO 1.5” refers to an equivalent
SRM geoengineering to bring anthropogenic forcing down by 1.5 W/m2 by 2100).
The SRM forcing was applied from 2020 with an e-folding time of 5 years and
following the equivalent RCP scenario when available (i.e., “RCP 6 & GEO 1.5”
will have the same total forcing as “RCP 4.5”). As for model training, the
maximum and minimum monthly and weekly SST values were computed by
adding observed present-day anomalies to UVic projected annual mean SST data
(i.e., assuming variability remains unchanged). Future irradiance levels under
SRM geoengineering were calculated by applying a -1% to -3% reduction to
present observed values depending on emission scenario and desired total level of
forcing. Additional variations in cloudiness patterns were not considered. All other
environmental fields were kept at present values. Predictions were generated at 10-
year intervals from 2010 to 2070 and for 1850 to establish the P-I baseline (for P-I
projection map, see Figure S1.4, Appendix S1). The 2070 cutoff for future
projections was chosen because 14% of coral reef cells are out of training range by
this date under RCP 8.5. Bioclimatic Envelope Models become less reliable for
forecasts that involve extrapolation to novel conditions because statistical
relationships observed in training may no longer hold.
0 1
0 1
0 1
0 1 0 1
0 1
0 1 0 1 0 1
0 1
0 1 0 1 0 1
0 1
0 1 0 1 0 1 0 1
sllec fo rebmuN
Modelled reef probability
Level of geoengineering (W/m
Emission scenario (W/m2)
3.0 4.5 6.0 8.5
0 0.4 0.8 1
0 50 150 250
RCP 4.5
RCP 8.5
x0.62 x 0.56 x 0.52
0 250
x0.58 x 0.56
0 250
2010 2020 2030 2040 2050 2060 2070
0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00
a) RCP 8.5 (BRT)
2010 2020 2030 2040 2050 2060 2070
GEO 8.5
GEO 5.5
GEO 2.5
c) Reef cells only, 2070 (BRT)
Figure 2. Habitat Suitability Index (defined as the average suitability for coral reefs within the
shallow water mask between 60°S and 60°N) for (a) BRT and (b) MaxEnt. Values are normalized
to preindustrial (P-I) predictions and show the evolution at 10-year intervals until 2070 under the
unmitigated RCP 8.5 scenario (black) and various level of SRM (lighter colors show
progressively higher degrees of SRM intervention). For all other scenarios, see Appendix S2 and
Figures S2.8 and S2.9. (c) Histograms showing the proportion of reef cells within binned BRT
modeled suitability values. The bottom left histogram is for P-I conditions; all remaining
histograms are for 2070 conditions and reflect potential changes in suitability under the four
unmitigated RCPs (bottom row, along x axis) and various levels of SRM geoengineering (y axis).
Reef cells are cells where reefs or non-reef coral communities are presently found (ReefBase
v2000). Novel environmental conditions, compared to the 1990 values used for model training,
are simulated by UVic Earth System Climate Model for SST and "Arag on some reef cells. The
solid colored histogram bars contain all cells either with environmental conditions within the
bioclimatic envelope used to train the models or where out-of-range variables do not significantly
affect predictions. The average suitability value (x
!) of reef cells for each scenario is calculated
from this sample set. Cells where predictions are less reliable (i.e., SST and/or "Arag values out of
training range and MaxEnt clamping value > 0.1; see Appendix S3) are indicated by hatched
pattern and have been excluded from the calculated average.
3. Results
Under the highest CO2 scenario considered (RCP 8.5), year 2070 tropical SSTs are
generally ~2°C–3°C higher than preindustrial (P-I), with the strongest warming
occurring in the western Pacific (Figure 1a). Associated with rising atmospheric
pCO2 and invasion of fossil fuel CO2 into the ocean, "Arag falls by 1.52 units,
with least change in upwelling areas (Figure 1c). Under these conditions, we
forecast a marked decline in environmental suitability for shallow coral reef
habitats across the central Indo-Pacific (Figure 1e; see also Appendix S2).
Elsewhere, conditions generally became less favorable, except for higher latitudes
and upwelling regions. Values of a Habitat Suitability Index (defined as the mean
probability of a coral reef being present within the shallow water mask,
normalized as a percentage relative to P-I) fell from 93%97% in 2010 to 65%
70% by 2070 (Figures 2a and 2b). As an alternative way to measure impact on
existing reefs, we also compared changes in suitability values across all 1° grid
cells with present-day coral communities and reefs (i.e., with entries from the
ReefBase v2000 database). These values declined substantially under all
unmitigated RCP scenarios and by 2070 had reached average values as low as 0.49
(RCP 8.5) compared to the P-I average of 0.62 for the BRT model output (Figure
2c, bottom row; MaxEnt values given in Figure S2.7). The pattern of impact does
not scale simply with increasing radiative forcing; instead an impact threshold is
apparent at ~3W/m2. When levels of anthropogenic forcing were below 3 W/m2,
the probabilities on cells currently associated with reefs remained high (Figures 2c
and S2.7), and the area of significantly reduced suitability was confined to within
the central Indo-Pacific Warm Pool (IPWP; Figure S2.1).
In the UVic simulations, application of SRM geoengineering sufficient to return
the average global temperature to P-I levels leaves the tropics on average ~1°C
cooler (Figure 1b), similar to previous findings using fully coupled GCM models
[e.g., Lunt et al., 2008; Irvine et al., 2010]. Because cooling increases CO2
solubility, a subsidiary consequence of this SRM-driven overcooling is that "Arag
is lower than under the unmitigated scenarios (Figure 1d). The net result of cooler
temperatures and further enhanced ocean acidification is that suitabilities for coral
reefs (averaged across cells associated with modern reef sites) are lower under a
geoengineering scenario of radiative forcing returned to 0 W/m2 compared to P-I
(i.e., 1:1 line in Figure 2c for BRT results). In fact, suitabilities for a fully
geoengineering climate are similar to those obtained for unmitigated RCP 4.5 and
RCP 3 scenarios, although this reduction was less significant for MaxEnt (Figure
S2.7). In contrast, application of SRM geoengineering equivalent to reducing the
forcing to 1.5 W/m2 above P-I not only forestalls the projected decline in shallow
water reef habitat suitability across the central Indo-Pacific but also leads to
improved conditions in the central Pacific due to the residual warming there
(Figure 1f; Appendix S2). The probability histograms calculated for currently
designated reef cells (Figure 2c) show that all SRM geoengineering scenarios
where forcing is reduced to 3 or 1.5 W/m2 maintained reasonably favorable
conditions and averages were preserved (0.560.62) near the P-I value (0.62).
4. Discussion and Conclusions
In our statistical models, unmitigated climate change leads to an SST-driven
collapse in environmental suitability for shallow water coral reefs, spreading from
the center of the IPWP and across the central Indo-Pacific as radiative forcing
increases beyond 3 W/m2. For a radiative forcing of > 4.5 W/m2, the affected area
encompasses the “Coral Triangle”, the richest region of biodiversity for corals and
reef-associated fauna [e.g., Tittensor et al., 2010]. In contrast, declines in shallow
water habitat suitable for coral reefs are averted in relatively aggressive SRM
geoengineering scenarios in which net radiative forcing is restricted to 3 W/m2
despite the existence of high pCO2. Due to residual warming, forecast
environmental conditions even improved slightly across the central Pacific, a
region sparsely populated in terms of shallow coral reefs, but critical in terms of
connectivity of reef-dependent species across the Pacific basin [e.g., Lessios and
Robertson, 2006; Mora et al., 2012]. Similarly, upwelling regions were generally
less impacted as a consequence of upwelled waters, previously isolated from the
atmosphere, providing some buffering against acidification (Figure 1c).
The difference in modeled response between unmitigated and geoengineered
scenarios reflects the importance placed on SST variables; both MaxEnt and BRT
use a combination of SST variables to explain 50%60% of the variation in
models trained on present-day global shallow water coral reef distribution [Couce
et al., 2012]. As a result, simulated future SST changes dominate predictions.
Other environmental fields, in particular "Arag, light availability, and nutrients, are
used to reinforce the SST-derived pattern and to model coral reef presence at
regional scales where the correlation with temperature breaks down [Couce et al.,
2012]. Consequently, when global temperatures are controlled by SRM, the
strongest negative responses map onto regions identified as sensitive during model
development to reduced "Arag and light availability: the Coral Triangle, southwest
Pacific, and South China Sea [Couce et al., 2012]. This spatial impact pattern was
also observed in an empirically supported modeling study on the response of
global shallow water coral reefs to future "Arag reductions [Silverman et al., 2009].
The strongest decline in habitat suitability for shallow water coral reefs
corresponds to areas where maximum weekly SST increases above a threshold of
31.9°C and is centered on the IPWP. Shallow water coral reef ecosystems as a
whole are very sensitive to elevated SSTs as evident from the recent observations
of mass bleaching, mortality events, and subsequent reef deterioration associated
with SST anomalies [Hoegh-Guldberg et al., 2007]. However, the model focus on
the IPWP as a thermally sensitive region is supported by observations and
empirical studies of physiological tolerances to thermal stress in reef-forming
species of coral and coralline algae. Reduced thermal tolerance has been linked to
both low SST variability environments [e.g., Ateweberhan and McClanahan,
2010; Teneva et al., 2012] and synergistic stress from reduced "Arag [e.g., Anthony
et al., 2008]. The relative sensitivity of this region is further evident in recent
observations of declining coral cover [Bruno and Selig, 2007] and exceptionally
high susceptibility to mass bleaching events [Donner et al., 2005; Teneva et al.,
2012]. The amelioration of future SST warming is therefore of primary importance
for minimizing impacts in this key region.
The relative dominance of SST in our statistical models helps explain why, in
contrast to Silverman et al. [2009], our projections do not forecast a global
collapse of coral reefs by ca. 560ppm atmospheric CO2. Instead, the potential
presence of coral cover at high pCO2 values (up to 677ppm, by 2070 under RCP
8.5) is consistent with Fabricius et al. [2011], who observed massive Porites
colonies growing within this range of geochemical conditions with no significant
impact on calcification rates. Tropical coral reef ecosystems are treated as a single
entity in our models, so our results should be considered a simplified first order
approximation and cannot be directly compared to the substantial changes in coral
community composition and diversity versus environmental gradient observations
also reported by Fabricius et al. [2011]. The future loss of biodiversity is likely to
be significant under high pCO2, but the models cannot separate potentially
significant shifts in the distributions of individual reef-forming species and so the
modeled habitat suitability response is likely muted. Future use of correlative
models created at the species (of functional type) level may provide a means to
start addressing this question.
To what degree can the statistical model projections be treated as robust in the face
of potential future changes in both variable correlation and spatial patterns? Under
SRM scenarios, the first-order inverse correlation that exists between SST
variables and "Arag in the modern surface ocean no longer holds. As a result, the
two Bioclimatic Envelope Model class types used in our study might have yielded
divergent projections because of their different internal use of correlated variables
[Couce et al., 2012] (Appendix S1). Instead, the strong agreement between the
MaxEnt and BRT predictions (Appendix S2) suggests the models are not over-
relying on present-day correlations between variables, thus increasing confidence
in the projections. There is also an implicit decoupling between specific local
and/or hourly conditions occurring at a reef site and the relatively large spatial
(1°x1° scale) and weekly-to-annual average data employed in our models.
However, as long as local reef environments change in tandem with large-scale
“open ocean” changes, our results should not be substantially biased.
It is important to note that it becomes necessary to extrapolate when variables
exceed the range of present-day environmental values used for model calibration
(e.g., when mean annual SST increases over 31.4°C). Both BRT and MaxEnt
techniques deal with such situations by setting the response outside of training
range at the level set for the nearest most extreme within-training value. A detailed
discussion of the effect of the chosen extrapolation method on the results is given
in Appendix S3. The net result is a constant positive response in the case of
increasing "Arag (e.g., experienced under P-I conditions) and a conservative
assessment of the negative impacts of warming by setting a constant negative
response in the case of higher SSTs. Grid cells with novel conditions for which the
extrapolation method strongly impacts predictions are explicitly shown in the
results (hatched areas in Figures 1e and 1f and in the histograms in Figures 2c and
S2.7). By 2070, these areas of problematic extrapolation affect a minority of cells
where shallow water coral communities and reefs are currently found (014%; on
average 2.5%), and conclusions remain unaltered by excluding these areas (e.g.,
the general reduction in shallow reef habitat suitability under all unmitigated RCP
scenarios in Figures 2c and S2.7 is a robust finding). In fact, the extrapolation of a
negative response onto extreme SSTs imposed by both models would be a logical
decision from empirically driven evidence (e.g., thermal damage limits of coral
reviewed in Brown and Cossins [2011]). Significantly, this response implies that
the data set used to calibrate our statistical models contains sites where present-
day shallow water coral reef distribution is already limited by thermal thresholds.
The data set does not, however, include coral reefs from the Red Sea and Arabian
Gulf, which tolerate similar extreme maximum SSTs but are potentially
conditioned by very high SST variability [Ateweberhan and McClanahan, 2010],
because it was not possible to simulate conditions using the UVic model in these
enclosed seas. While assessment of habitat beyond 2070 and under CO2
concentrations higher than the maximum we consider here (677 ppm at year 2070
under RCP 8.5) may be desirable for a fuller and longer-term picture, the utility of
the Bioclimatic Envelope Modeling approach becomes increasing limited as more
of the ocean exceeds training limits.
Overall, our work highlights the complex patterns of global change induced by
even simple (and spatially uniform) geoengineering scenarios, with consequences
that can be non-obvious. Specifically, we find that tropical overcooling by full
geoengineering, together with a relatively low comparative sensitivity to "Arag in
our models, creates an apparent “optimum” for shallow coral reef habitat (this is
particularly evident in the BRT model output; Figures 2a, 2c, and S2.8). This
optimum occurs under environmental conditions corresponding to a partially, but
not fully, mitigated high CO2 climate (i.e., SRM geoengineering of radiative
forcing to 1.5 W/m2 above P-I). A high degree of geoengineering with a global net
residual warming acts to even out surface meridional temperature gradients while
preventing tropical overcooling to the net advantage of tropical corals. This
outcome is possibly exaggerated because terrestrial carbon storage feedback
cannot be explicitly accounted for under the fixed atmospheric CO2 concentrations
of the RCP-based approach. For example, Matthews et al. [2009] found that SRM
could slightly mitigate ocean acidification, although "Arag would still decrease,
due to a simulated increase in terrestrial CO2 uptake and hence atmospheric pCO2
In conclusion, while SRM geoengineering fails to tackle the causes or
consequences of ocean acidification, the detrimental effect of higher SSTs appears
to strongly outweigh the impacts of reduced "Arag for tropical shallow water coral
reefs when treated as a single entity. Further studies are needed to resolve potential
changes in coral reef community composition and biodiversity; however, severe
reductions in the area of suitable shallow water coral reef habitat might be averted
if anthropogenic forcing is limited # 3 W/m2 or returned below this level via SRM.
Overall, our work highlights the need for a multistressor and spatially explicit
framework in assessing ecological implications of future global change, whether
mitigated or not, so that the complex patterns of induced change and the nonlinear
combinations of environmental pressures can be adequately evaluated.
Acknowledgments. This work was supported by a U. Bristol postgraduate scholarship to E.C., a
UK NERC postgraduate studentship to P.J.I., a Royal Society Advanced Fellowship to A.R., and
an RCUK Academic Fellowship to E.J.H. L.J.G. was funded by the UK Ocean Acidification
Research Program (NE/H017453/1) and EPSRC grant EP/I014721/1. We thank H. Russell and A.
Wilmot-Sitwell for additional funding to support E.C.
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... 24,111,112)]; none have assessed the benefits and risks of SAI to higher trophic levels, which are expected to decline under anthropogenic climate change (14). Furthermore, the relative impacts of OA, changes in storm intensity, and extreme temperatures need to be better understood, especially for coral communities that are expected to be particularly vulnerable to these climate changes (107,(113)(114)(115). Coral reefs are marine biodiversity hotspots and supply ecosystem services estimated to be worth US$36 billion per year globally (116). ...
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Making informed future decisions about solar radiation modification (SRM; also known as solar geoengineering)—approaches such as stratospheric aerosol injection (SAI) that would cool the climate by reflecting sunlight—requires projections of the climate response and associated human and ecosystem impacts. These projections, in turn, will rely on simulations with global climate models. As with climate-change projections, these simulations need to adequately span a range of possible futures, describing different choices, such as start date and temperature target, as well as risks, such as termination or interruptions. SRM modeling simulations to date typically consider only a single scenario, often with some unrealistic or arbitrarily chosen elements (such as starting deployment in 2020), and have often been chosen based on scientific rather than policy-relevant considerations (e.g., choosing quite substantial cooling specifically to achieve a bigger response). This limits the ability to compare risks both between SRM and non-SRM scenarios and between different SRM scenarios. To address this gap, we begin by outlining some general considerations on scenario design for SRM. We then describe a specific set of scenarios to capture a range of possible policy choices and uncertainties and present corresponding SAI simulations intended for broad community use.
... 24,111,112)]; none have assessed the benefits and risks of SAI to higher trophic levels, which are expected to decline under anthropogenic climate change (14). Furthermore, the relative impacts of OA, changes in storm intensity, and extreme temperatures need to be better understood, especially for coral communities that are expected to be particularly vulnerable to these climate changes (107,(113)(114)(115). Coral reefs are marine biodiversity hotspots and supply ecosystem services estimated to be worth US$36 billion per year globally (116). ...
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As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.
... A huge canvas of more aggressive management interventions have been proposed for coral reefs (Anthony et al., 2017;National Academies of Sciences, Engineering, & Medicine, 2019;van Oppen et al., 2017; and references therein)-approaches range from mitigation of incident environmental stressors (e.g., reef cooling or shading, Couce, Irvine, Gregorie, Ridgwell, & Hendy, 2013;Kwaitkowski et al., 2015) to enhancing stress resistance (e.g., Chakravarti et al., 2017;Chan, Peplow, Menéndez, Hoffmann, & Oppen, 2018) However, success of these various efforts-and hence accurate evaluation of feasibility-again rests on resolving what environmental factors have contributed to the fitness of corals being used to rebuild reefs: are the survivors more stress tolerant or simply "lucky" via refugia? (e.g., . ...
Continued declines in coral reef health over the past three decades have been punctuated by severe mass coral bleaching-induced mortality events that have grown in intensity and frequency under climate change. Intensive global research efforts have therefore persistently focused on bleaching phenomena to understand where corals bleach, when and why-resulting in a large-yet still somewhat patchy-knowledge base. Particularly catastrophic bleaching-induced coral mortality events in the past 5 years have catalyzed calls for a more diverse set of reef management tools, extending far beyond climate mitigation and reef protection, to also include more aggressive interventions. However, the effectiveness of these various tools now rests on rapidly assimilating our knowledge base of coral bleaching into more integrated frameworks. Here, we consider how the past three decades of intensive coral bleaching research has established the basis for complex biological and environmental networks, which together regulate outcomes of bleaching severity. We discuss how we now have enough scaffold for conceptual biological and environmental frameworks underpinning bleaching susceptibility, but that new tools are urgently required to translate this to an operational system informing-and testing-bleaching outcomes. Specifically, adopting network models that can fully describe and predict metabolic functioning of coral holobionts, and how this functioning is regulated by complex doses and interactions among environmental factors. Identifying knowledge gaps limiting operation of such models is the logical step to immediately guide and prioritize future experiments and observations. We are at a time-critical point where we can implement new capacity to resolve how coral bleaching patterns emerge from complex biological-environmental networks, and so more effectively inform rapidly evolving ecological management and social adaptation frameworks aimed at securing the future of coral reefs.
... In such cases, presence-only models like Maxent have been shown to be more robust and consistent (Elith et al. 2006, Reiss et al. 2011, Yesson et al. 2012) because they utilize pseudo-absence (background) data rather than true absence data and have consistently outperformed other presence-only techniques (Elith et al. 2006, Elith & Leathwick 2009, Tittensor et al. 2009, Tong et al. 2013. Maxent assigns non-negative probability values to each background pixel of the study area such that their total sums to 1. Furthermore, presence-only modeling results have produced results consistent with traditional presence/absence methods in shallow corals (Bridge et al. 2012, Couce et al. 2013) and deep-water corals (Davies & Guinotte 2011, Howell et al. 2011, Tracey et al. 2011, Yesson et al. 2012, Rengstorf et al. 2013, Taylor et al. 2013. ...
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The mesophotic coral ecosystem (MCE) of the eastern Gulf of Mexico hosts diverse invertebrate and fish fauna across an array of hard-ground features. However, the extent of the potential MCE habitat in the region is poorly constrained. Maximum entropy modeling was used to predict the spatial extent of mesophotic azooxanthellate octocorals and antipatharians within the mesophotic area located between Mississippi (Pinnacle Trend Area) and the mid-continental shelf and upper slope of Florida, eastern Gulf of Mexico. Habitat prediction models were generated using geo-referenced, coral-presence records obtained by classifying photographic samples with co-located geophysical data, oceanographic variables, and atmospheric variables. Resulting models were used to predict the extent of suitable habitat in the study area. An independent set of presence records was used to test the model performance. Results (general and by taxon) predict that suitable areas for MCE exceed 400 km2 and occur along carbonate mounds and paleo-shoreline ridges (hard substrata and high surface rugosity). Reduced amounts of fine sediments, surrounding waters rich in chromophoric dissolved organic matter (CDOM), and downwelling currents also increased predicted suitability. The model significantly exceeded random performance and predicted that surface rugosity and CDOM are the most important variables contributing to coral habitat. Areas of hard substrate within the study area that were not identified as coral habitat by the model suggest that mesophotic sea fans and sea whips apparently depend as much on the chemical and physical conditions (e.g. currents that transport oxygen and food) as on hard substrata for settlement.
... Limits to physiological adjustments are affected by hypoxia, food availability, and stress (P€ ortner et al., 2014). Ocean acidification is also a limiting factor on the ability of organisms to adapt to warming water temperatures (P€ ortner et al., 2014) and in particular, it is expected to limit poleward range expansion of corals (Couce, Irvine, Gregoire, Ridgwell, & Hendy, 2013;Wong et al., 2014;Yara et al., 2012). Limits to the extent that organisms can adapt to ocean acidification also exist but to date remain largely unexplored (P€ ortner et al., 2014). ...
The world's oceans are highly impacted by climate change and other human pressures, with significant implications for marine ecosystems and the livelihoods that they support. Adaptation for both natural and human systems is increasingly important as a coping strategy due to the rate and scale of ongoing and potential future change. Here, we conduct a review of literature concerning specific case studies of adaptation in marine systems, and discuss associated characteristics and influencing factors, including drivers, strategy, timeline, costs, and limitations. We found ample evidence in the literature that shows that marine species are adapting to climate change through shifting distributions and timing of biological events, while evidence for adaptation through evolutionary processes is limited. For human systems, existing studies focus on frameworks and principles of adaptation planning, but examples of implemented adaptation actions and evaluation of outcomes are scarce. These findings highlight potentially useful strategies given specific social-ecological contexts, as well as key barriers and specific information gaps requiring further research and actions. This article is protected by copyright. All rights reserved.
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Ocean and cryosphere changes already impact Low-Lying Islands and Coasts (LLIC), including Small Island Developing States, with cascading and compounding risks. Disproportionately higher risks are expected in the course of the 21st century. Reinforcing the findings of the IPCC Special Report on Global Warming of 1.5°C, vulnerable human communities, especially those in coral reef environments and polar regions, may exceed adaptation limits well before the end of this century and even in a low greenhouse gas emission pathway (high confidence1). Depending on the effectiveness of 21st century mitigation and adaptation pathways under all emission scenarios, most of the low-lying regions around the world may face adaptation limits beyond 2100, due to the long-term commitment of sea level rise (medium confidence).
Climate engineering with stratospheric sulfate aerosol injections (SSAI) has the potential to reduce risks of injustice related to anthropogenic emissions of greenhouse gases. Relying on evidence from modeling studies, this paper makes the case that SSAI could have the potential to reduce many of the key physical risks of climate change identified by the Intergovernmental Panel on Climate Change. Such risks carry potential injustice because they are often imposed on low-emitters who do not benefit from climate change. Because SSAI has the potential to reduce those risks, it thereby has the potential to reduce the injustice associated with anthropogenic emissions. While acknowledging important caveats, including uncertainty in modeling studies and the potential for SSAI to carry its own risks of injustice, the paper argues that there is a strong case for continued research into SSAI, especially if attention is paid to how it might be used to reduce emissions-driven injustice.
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Geoengineering could remake environments and societies, and early governance can help to steer the development of technologies towards sustainable outcomes. In the absence of observational data, geoengineering research and discussions are increasingly informed by scenarios, which provide heuristic tools for ‘envisioning’ potential futures. Although designed for specific research goals, scenarios can have broader implications by influencing expectations about the societal role that emerging geoengineering technologies can play. Yet the design of geoengineering scenarios has gone largely unscrutinized. This study is a meta-analysis in which we evaluate geoengineering scenarios from the literature to identify emerging expectations and assess these in the context of sustainability science. We find that geoengineering scenarios can be classified into three types based on purpose and use: for scientific knowledge-building; as ‘structured conversation’ starters; or as exploratory research tools. The first category dominates the literature; these scenarios stem from physical science disciplines where scientific tradition dictates simplification and standardization, both of which may provide misleading images of the future and therefore hinder robust decision-making. In contrast, scenarios used as exploratory tools depict not one single image of why and how geoengineering might evolve, but many. Analysis of these exploratory scenarios reveal expectations that a geoengineered future may hinge on at least four key elements—the potential for a universal geoengineering agreement, public perceptions of geoengineering, technical controllability, and the severity of climate impacts. These elements were not studied in the scientific knowledge-building scenarios, suggesting the need for an additional category of scenarios. Aligning with concepts of sustainability science, new geoengineering scenario exercises would merge participatory practices of exploratory scenarios with deterministic practices of technical scientific scenarios.
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Various surface albedo modification geoengineering schemes such as those involving desert, urban, or agricultural areas have been proposed as potential strategies for helping counteract the warming caused by greenhouse gas emissions. However, such schemes tend to be inherently limited in their potential and would create a much more heterogeneous radiative forcing than propositions for space-based "reflectors" and enhanced stratospheric aerosol concentrations. Here we present results of a series of atmosphere-ocean general circulation model (GCM) simulations to compare three surface albedo geoengineering proposals: urban, cropland, and desert albedo enhancement. We find that the cooling effect of surface albedo modification is strongly seasonal and mostly confined to the areas of application. For urban and cropland geoengineering, the global effects are minor but, because of being colocated with areas of human activity, they may provide some regional benefits. Global desert geoengineering, which is associated with significant global-scale changes in circulation and the hydrological cycle, causes a smaller reduction in global precipitation per degree of cooling than sunshade geoengineering, 1.1% K-1 and 2.0% K-1 respectively, but a far greater reduction in the precipitation over land, 3.9% K-1 compared with 1.0% K-1. Desert geoengineering also causes large regional-scale changes in precipitation with a large reduction in the intensity of the Indian and African monsoons in particular. None of the schemes studied reverse the climate changes associated with a doubling of CO2, with desert geoengineering profoundly altering the climate and with urban and cropland geoengineering providing only some regional amelioration at most.
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Aim Elucidating the environmental limits of coral reefs is central to projecting future impacts of climate change on these ecosystems and their global distribution. Recent developments in species distribution modelling (SDM) and the availability of comprehensive global environmental datasets have provided an opportunity to reassess the environmental factors that control the distribution of coral reefs at the global scale as well as to compare the performance of different SDM techniques. Location Shallow waters world-wide. Methods The SDM methods used were maximum entropy (Maxent) and two presence/absence methods: classification and regression trees (CART) and boosted regression trees (BRT). The predictive variables considered included sea surface temperature (SST), salinity, aragonite saturation state (ΩArag), nutrients, irradiance, water transparency, dust, current speed and intensity of cyclone activity. For many variables both mean and SD were considered, and at weekly, monthly and annually averaged time-scales. All were transformed to a global 1° × 1° grid to generate coral reef probability maps for comparison with known locations. Model performance was compared in terms of receiver operating characteristic (ROC) curves and area under the curve (AUC) scores. Potential geographical bias was explored via misclassification maps of false positive and negative errors on test data. Results Boosted regression trees consistently outperformed other methods, although Maxent also performed acceptably. The dominant environmental predictors were the temperature variables (annual mean SST, and monthly and weekly minimum SST), followed by, and with their relative importance differing between regions, nutrients, light availability and ΩArag. No systematic bias in SDM performance was found between major coral provinces, but false negatives were more likely for cells containing ‘marginal’ non-reef-forming coral communities, e.g. Bermuda. Main conclusions Agreement between BRT and Maxent models gives predictive confidence for exploring the environmental limits of coral reef ecosystems at a spatial scale relevant to global climate models (c. 1° × 1°). Although SST-related variables dominate the coral reef distribution models, contributions from nutrients, ΩArag and light availability were critical in developing models of reef presence in regions such as the Bahamas, South Pacific and Coral Triangle. The steep response in SST-driven probabilities at low temperatures indicates that latitudinal expansion of coral reef habitat is very sensitive to global warming.
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A coral reef represents the net accumulation of CaCO3 produced by corals and other calcifying organisms. If calcification declines, then reef-building capacity also declines. Coral reef calcification depends on the saturation state of the carbonate mineral aragonite of surface waters. By the middle of next century, increased CO2 concentration will decrease aragonite saturation state in the tropics by 30%, and biogenic aragonite precipitation by 14–30%. Coral reefs are particularly threatened, since reef-building organisms secrete metastable forms of CaCO3, but the biogeochemical consequences on other calcifying marine ecosystems may be equally severe.
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Experiments have shown that ocean acidification due to rising atmospheric carbon dioxide concentrations has deleterious effects on the performance of many marine organisms. However, few empirical or modelling studies have addressed the long-term consequences of ocean acidification for marine ecosystems. Here we show that as pH declines from 8.1 to 7.8 (the change expected if atmospheric carbon dioxide concentrations increase from 390 to 750ppm, consistent with some scenarios for the end of this century) some organisms benefit, but many more lose out. We investigated coral reefs, seagrasses and sediments that are acclimatized to low pH at three cool and shallow volcanic carbon dioxide seeps in Papua New Guinea. At reduced pH, we observed reductions in coral diversity, recruitment and abundances of structurally complex framework builders, and shifts in competitive interactions between taxa. However, coral cover remained constant between pH 8.1 and ~7.8, because massive Porites corals established dominance over structural corals, despite low rates of calcification. Reef development ceased below pH 7.7. Our empirical data from this unique field setting confirm model predictions that ocean acidification, together with temperature stress, will probably lead to severely reduced diversity, structural complexity and resilience of Indo-Pacific coral reefs within this century.
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1] Climate engineering has been proposed as a possible response to anthropogenic climate change. While climate engineering may be able to stabilize temperatures, it is generally assumed that this will not prevent continued ocean acidification. However, due to the strong coupling between climate and the carbon cycle, climate engineering could indirectly affect ocean chemistry. We used a global Earth-system model to investigate how climate engineering may affect surface ocean pH and the degree of aragonite saturation. Climate engineering could significantly re-distribute carbon emissions among atmosphere, land and ocean reservoirs. This could slow pH decreases somewhat relative to the non-engineered case, but would not affect the level of aragonite saturation due to opposing responses of pH and aragonite saturation to temperature change. However, these effects are dependent on enhanced carbon accumulation in the land biosphere; without this, climate engineering has little effect on pH, and leads to accelerated declines in aragonite saturation.
Function estimation/approximation is viewed from the perspective of numerical optimization iti function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest-descent minimization. A general gradient descent "boosting" paradigm is developed for additive expansions based on any fitting criterion. Specific algorithms are presented for least-squares, least absolute deviation, and Huber-M loss functions for regression, and multiclass logistic likelihood for classification. Special enhancements are derived for the particular case where the individual additive components are regression trees, and tools for interpreting such "TreeBoost" models are presented. Gradient boosting of regression trees produces competitives highly robust, interpretable procedures for both regression and classification, especially appropriate for mining less than clean data. Connections between this approach and the boosting methods of Freund and Shapire and Friedman, Hastie and Tibshirani are discussed.
[1] Sunshade geoengineering - the installation of reflective mirrors between the Earth and the Sun to reduce incoming solar radiation, has been proposed as a mitigative measure to counteract anthropogenic global warming. Although the popular conception is that geoengineering can re-establish a ‘natural’ pre-industrial climate, such a scheme would itself inevitably lead to climate change, due to the different temporal and spatial forcing of increased CO2 compared to reduced solar radiation. We investigate the magnitude and nature of this climate change for the first time within a fully coupled General Circulation Model. We find significant cooling of the tropics, warming of high latitudes and related sea ice reduction, a reduction in intensity of the hydrological cycle, reduced ENSO variability, and an increase in Atlantic overturning. However, the changes are small relative to those associated with an unmitigated rise in CO2 emissions. Other problems such as ocean acidification remain unsolved by sunshade geoengineering.
The hypothesis that pelagic larval duration (PLD) influences range size in marine species with a benthic adult stage and a pelagic larval period is intuitively attractive; yet, studies conducted to date have failed to support it. A possibility for the lack of a relationship between PLD and range size may stem from the failure of past studies to account for the effect of species evolutionary ages, which may add to the dispersal capabilities of species. However, if dispersal over ecological (i.e. PLD) and across evolutionary (i.e. species evolutionary age) time scales continues to show no effect on range size then an outstanding question is why? Here we collected data on PLD, evolutionary ages and range sizes of seven tropical fish families (five families were reef-associated and two have dwell demersal habitats) to explore the independent and interactive effects of PLD and evolutionary age on range size. Separate analyses on each family showed that even after controlling for evolutionary age, PLD has an insignificant or a very small effect on range size. To shed light on why dispersal has such a limited effect on range size, we developed a global ocean circulation model to quantify the connectivity among tropical reefs relative to the potential dispersal conferred by PLD. We found that although there are several areas of great isolation in the tropical oceans, most reef habitats are within the reach of most species given their PLDs. These results suggest that the lack of habitat isolation can potentially render the constraining effect of dispersal on range size insignificant and explain why dispersal does not relate to range size in reef fishes.