Ocean acidification affects coral growth by reducing skeletal density
- aMassachusetts Institute of Technology–Woods Hole Oceanographic Institution Joint Program in Oceanography, Woods Hole, MA 02543;
- bDepartment of Geology and Geophysics, Woods Hole Oceanographic Institution, Woods Hole, MA 02543;
- cInstitute of Earth Sciences, Academia Sinica, Nangang, Taipei 11529, Taiwan;
- dOcean and Earth Science, University of Southampton, SO14 3ZH Southampton, United Kingdom;
- eMarine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, MA 02543
See allHide authors and affiliations
Edited by Nancy Knowlton, Smithsonian Institution, Washington, DC, and approved December 11, 2017 (received for review July 18, 2017)

Significance
Ocean acidification (OA) threatens coral reef futures by reducing the concentration of carbonate ions that corals need to construct their skeletons. However, quantitative predictions of reef futures under OA are confounded by mixed responses of corals to OA in experiments and field observations. We modeled the skeletal growth of a dominant reef-building coral, Porites, as a function of seawater chemistry and validated the model against observational data. We show that OA directly and negatively affects one component of the two-step growth process (density) but not the other (linear extension). Combining our growth model with Global Climate Model output, we show that skeletal density of Porites corals could decline by up to 20.3% over the 21st century solely due to OA.
Abstract
Ocean acidification (OA) is considered an important threat to coral reef ecosystems, because it reduces the availability of carbonate ions that reef-building corals need to produce their skeletons. However, while theory predicts that coral calcification rates decline as carbonate ion concentrations decrease, this prediction is not consistently borne out in laboratory manipulation experiments or in studies of corals inhabiting naturally low-pH reefs today. The skeletal growth of corals consists of two distinct processes: extension (upward growth) and densification (lateral thickening). Here, we show that skeletal density is directly sensitive to changes in seawater carbonate ion concentration and thus, to OA, whereas extension is not. We present a numerical model of Porites skeletal growth that links skeletal density with the external seawater environment via its influence on the chemistry of coral calcifying fluid. We validate the model using existing coral skeletal datasets from six Porites species collected across five reef sites and use this framework to project the impact of 21st century OA on Porites skeletal density across the global tropics. Our model predicts that OA alone will drive up to 20.3 ± 5.4% decline in the skeletal density of reef-building Porites corals.
Coral reefs are among the most diverse ecosystems on Earth, with enormous cultural, ecological, and economic value. The calcium carbonate (aragonite) skeletons of stony corals are the main building blocks of the reef structure and provide food, shelter, and substrate for a myriad of other organisms. However, corals are vulnerable to environmental changes, including ocean acidification, which reduces the concentration of carbonate ions ([CO32−]) that corals need to build their skeletons (1, 2). Under the “business as usual” emissions scenario, seawater [CO32−] is projected to decline across the global tropics by ∼100 µmol/kg by 2100 (1, 3, 4), almost halving preindustrial concentration. Predictions based on abiogenic precipitation experiments imply an associated decrease in the precipitation rate of aragonite of ∼48% (5). Such predictions raise concerns that many coral reefs will shift from a state of net carbonate accretion to net dissolution (3). Nevertheless, both laboratory manipulation experiments rearing corals under high pCO2 conditions and field studies of naturally low-pH reefs that are designed to explore the impact of ocean acidification on coral calcification, have yielded inconsistent results (e.g., refs. 6⇓⇓⇓⇓⇓⇓–13). Field-based measurements of calcification rates of corals inhabiting naturally low pH reefs today vary widely from sharp decreases in calcification rate with decreasing pH to no significant response. For example, a nonlinear response of Porites astreoides to declines in seawater aragonite saturation state (Ωsw) was observed in the Yucatan Ojos, with no change in calcification rate at Ωsw > 1 and a sharp decline in calcification when conditions become undersaturated (9). At CO2 vent sites on the volcanic island Maug (northern Mariana Islands), a significant decline in Porites calcification rate was observed between ambient and mid Ωsw conditions (3.9 and 3.6, respectively), yet no change between the mid and low (Ωsw = 3.4) conditions (14). On other reefs, calcification rates are constant across the Ωsw range. For example, Porites calcification at Milne Bay (Papua New Guinea) CO2 vents showed no significant change between Ωsw of 3.5 and 2.9 (10), and on Palau, no change in calcification rate of two massive genera of coral (Porites and Favia) was observed across an Ωsw gradient of 3.7–2.4 (11).
These results have raised questions about the potential for adaptation, acclimation, and/or the role of non-pH factors in modulating the influence of ocean acidification in natural systems, confounding efforts to predict reef calcification responses to 21st century ocean acidification (13). The reefs in the studies discussed above are very different both compositionally and environmentally, and in each case, the low Ωsw is a result of different factors (e.g., CO2 vents vs. freshwater seeps). However, one commonality among these studies is that calcification rates are reported for massive species by measuring linear extension and skeletal density in cores extracted from living colonies. The product of annual linear extension and mean skeletal density is used to estimate the annual calcification rate (15). While this measure provides an accurate estimate of the annual amount of CaCO3 produced by the coral, it does not account for the possibility that density and extension could be influenced by different factors (e.g., seawater chemistry, light exposure, nutrient level). Here, we combine measurements of seawater saturation state, skeletal growth of Porites, and constraints on the coral’s calcifying fluid composition to examine the impact of ocean acidification on each skeletal growth parameter separately.
Results and Discussion
Porites Skeletal Density but Not Extension Is Sensitive to Ocean Acidification.
Extension, density, and calcification rates were quantified in nine Porites skeletal cores from four Pacific reefs (Palau, Donghsa Atoll, Green Island, and Saboga) representing average Ωsw ranging from ∼2.4 to ∼3.9 (Fig. 1). We observed no correlation between annual calcification rates and Ωsw either within or between reef sites. However, coral calcification does not take place directly from ambient seawater but within an extracellular calcifying fluid or medium (ECM) that is located between the coral skeleton and its calicoblastic cell membrane (16⇓–18). The carbonate chemistry of the ECM is strongly regulated by corals and can differ significantly from ambient seawater (19, 20). Most notably, pH of the ECM is elevated above ambient seawater by up to 1 unit (21⇓⇓⇓–25). Geochemical proxy data suggest that dissolved inorganic carbon (DIC) concentrations in Porites ECM are also elevated relative to seawater (e.g., by a factor of ∼1.4 or ∼2.6) (26, 27), although in vivo microelectrode measurements of other coral species imply a DIC concentration in the ECM similar to seawater (28). A combination of elevated pH and DIC leads to higher aragonite saturation state in the ECM (ΩECM), which exerts direct control on the rate of aragonite precipitation by the coral.
Coral skeletal parameters measured in representative Porites cores from four reefs across the Pacific. Coral calcification rates do not correlate with either Ωsw or ΩECM (A and B). Instead, skeletal density exhibits a significant positive correlation with both Ωsw and ΩECM (C and D), but extension does not (E and F; P = 0.14 and P = 0.09, respectively). Individual points represent annual averages of skeletal growth. Error bars denote 1 SD of Ω propagated from seasonal variability in seawater physicochemical parameters (for Ωsw and ΩECM) and in boron isotope compositions of coral skeletons (for ΩECM).
To estimate ΩECM of our coral cores, we first reconstructed the pH of coral ECM based on their boron isotope compositions and then combined these pH estimates with in situ measurements of seawater temperature, salinity, and DIC concentration. An elevation factor (α) of 2 is adopted to account for the elevation of DIC concentration within the ECM relative to seawater values (SI Text). Our estimated ΩECM for these cores varies from 11.6 ± 0.9 to 17.8 ± 2.0, ∼3.5–4.6 times higher than the Ωsw in which the corals grew. Nevertheless, we observe no correlation between coral calcification rates and ΩECM (Fig. 1B). Instead, when we deconvolve calcification into skeletal extension and skeletal density, a significant correlation is observed between coral skeletal density and ΩECM and also, skeletal density and Ωsw (Fig. 1 C and D). Skeletal extension, however, does not show a statistically significant correlation with ΩECM or Ωsw (Fig. 1 E and F). Correlations between skeletal density and Ωsw, similar to that observed in our data, have also been reported in other field studies (9⇓–11, 29), including at some of the key ocean acidification study sites (e.g., CO2 vents in Italy, Papua New Guinea, and the Caribbean Ojos) (9, 10, 29), but not all (14, 30) (Fig. S1).
These observations, although counterintuitive, are consistent with the two-step model of coral calcification, in which coral skeleton is accreted in two distinct phases (31): vertical upward growth (i.e., extension) creating new skeletal elements and lateral thickening of existing elements in contact with living tissue. These two components of coral growth are fundamentally different processes. Skeletal extension is driven by the accretion of successive, elongated early mineralization zones (EMZs; also referred to as centers of calcification and the immediately associated fibers) in a continuous or semicontinuous column parallel to the upward growth axis of the skeleton (17, 32, 33). Conversely, skeletal thickening occurs via growth of bundles of mature, c axis-aligned aragonite fibers at an angle that is perpendicular or semiperpendicular to the EMZ and upward growth axis of the coral. This thickening affects the bulk density of the skeleton, because the more the fiber bundles thicken or lengthen, the lower the skeletal porosity (Fig. S2) (17, 33, 34). Our data reveal the strong sensitivity of skeletal density to ECM carbonate chemistry and ocean acidification (Fig. 1). Conversely, skeletal extension seems less sensitive or insensitive to ECM carbonate chemistry. One explanation for this finding is that the EMZs, which contain a relatively high concentration of organic material (34⇓–36), are under stronger biological control (37⇓–39) and are thus shielded from changes in calcifying fluid pH and external seawater pH. Conversely, weaker biological control of fiber bundle growth would render skeletal density more exposed to physicochemical influences and thus, more sensitive to changes in both calcifying fluid pH and ocean acidification.
Results of experimental studies support this hypothesis. Laboratory experiments showed no decline in the extension rate of Stylophora pistillata over a year of growth in low-Ωsw seawater (1.1–3.2) (7). Similarly, most field studies, except one (14), have found no significant effect of ocean acidification on coral skeletal extension over pH ranges expected in the 21st century (9⇓–11, 29). Instead, the extension is believed to be controlled by other environmental factors, such as irradiance, temperature, and nutrient environment (40). For example, studies show that coral extension rates decline exponentially with water depth over a range of ∼40 m after light attenuation (41⇓–43) but increase with mean annual sea surface temperature (SST) until an optimum thermal threshold (44, 45). In addition, sediment influx and nutrient loading have also been suggested to influence extension rates in a nonlinear fashion, with minor increases in nutrient availability promoting growth and more severe nutrient loading leading to abrupt declines (46). We, however, observe none of these correlations in our coral cores, presumably due to the small depth and temperature ranges that they cover (i.e., 1–6 m and 26.4 °C to 30.3 °C) (Table S1).
Our observation that skeletal density but not extension is affected by seawater chemistry may explain the large variability in the response of coral calcification to ocean acidification, as calcification is calculated as the product of linear extension and mean skeletal density. Our findings are consistent with previous suggestions that the accretion of EMZ during coral calcification is under stronger biological control (17, 34⇓–36), presumably through the organic matrix (47⇓⇓–49), and also with previous reports of the sensitivity of skeletal porosity to ocean acidification (7, 29). Furthermore, because density is a critical component of the coral growth process, our results support laboratory and field-based studies that report negative impacts of ocean acidification on coral calcification and consequently, the health of coral reef ecosystems (12).
A Numerical Model of Porites Skeletal Growth.
Within the two-step model of coral calcification, coral skeletal density is strongly controlled by the rate of skeletal thickening, which is expected to vary as a function of ΩECM:
Correlation between coral skeletal density and expected aragonite precipitation rate in the coral ECM (RECM) on both the annual (A) and seasonal (B and C) scales. Data in A represent the same cores as in Fig. 1. Error bars (A) and shaded areas (B and C) denote 1 SD in RECM as propagated from uncertainties in seawater parameters and in boron isotope measurements. Seasonal density profiles were retrieved parallel to the sampling track for boron isotope measurements.
To quantitatively evaluate the sensitivity of skeletal density to ocean acidification, we construct a numerical model of Porites skeletal growth that builds on previous modeling studies (e.g., ref. 50) (Fig. 3A and SI Text). In this model, the coral calyx is approximated as a ring in which coral growth proceeds in two consecutive steps: vertical construction of new skeletal framework representing daily extension of EMZs (E) followed by lateral aragonite precipitation around the interior of the ring representing thickening. Thickening of the skeletal elements, which we prescribe an initial ring wall thickness of wo, occurs throughout the tissue layer—most prominently at the polyp surface and diminishing with depth (31, 51):
Schematic representation of our Porites skeletal growth model (A) and comparison between model-predicted skeletal density and measured density (B). Also shown in A are a cross-section view of our model polyp geometry and a representative SEM image of a Porites calyx (orange dashed line). Porites cores in B were collected from reefs in the Pacific, Atlantic, and Indian Oceans reported in previous studies (9, 30, 54⇓⇓–57). Data points from this study, the Caribbean, and the Andaman Sea represent densities of individual cores; data points from the Galapagos, the Great Barrier Reef, and the Andaman Sea represent site average densities for which error bars denote 2σ uncertainties. Vertical error bars represent uncertainties in model prediction propagated from uncertainties in model parameters α, λ, and wo as well as measurements of in situ seawater conditions where available. Where seawater conditions were not reported, outputs from the CESM-BGC historical run were adopted.
Within this model framework, five key factors control the density of coral skeleton: initial calyx size (ro), thickness of the new skeletal framework (wo), aragonite precipitation rate in the ECM (RECM), decline of thickening rate from the surface to the depth of the tissue layer (λ), and the time that a skeletal element spends within the tissue layer (t = Td/E). RECM is calculated based on seawater physicochemical parameters, pH of the ECM, and the DIC elevation factor (i.e., α) in the ECM and assumes that the sensitivity of coral aragonite formation to the ECM carbonate chemistry is the same as that determined in abiotic precipitation experiments (Methods and Eq. 1) (6, 32, 37). Most of these model parameters (e.g., ro, Td, E) can be accurately determined via computed tomography (CT) imaging and inspection of each coral core. However, there are limited experimental constraints on the other parameters, including wo, λ, and α. We assume that these three parameters are the same for all Porites corals and optimize their values to reproduce the measured skeletal density of our cores via a Bayesian statistical method (SI Text). Our estimated α value (
To evaluate the performance of our model, we use it to predict the skeletal densities of Porites corals at five tropical reefs and compare our model-predicted densities with the experimentally measured densities reported in previous studies (Fig. 3B and Fig. S6) (9, 30, 54⇓⇓–57). These studies were selected, because they report not only coral skeletal density but also, extension and at least one of the following factors needed for our model prediction: ro, Td, or in situ seawater carbonate chemistry. This minimizes the uncertainty in our model prediction propagated from estimations of unmeasured parameters (Methods). Corals in these studies consist of six different Porites species and represent a wide range of reef environments across the Atlantic, Pacific, and Indian Ocean basins (21.7° S to 22.6° N), with large variations in annual SST (22.3 °C to 29.5 °C), pH (7.20–8.24), DIC (1,780–3,170 μmol kg−1), and coral skeletal density (0.9–1.6 g cm−3).
Our model predictions quantitatively reproduce the experimentally measured coral densities and explain a large amount of the variance in the measured densities (Fig. 3B) [root-mean-square error (RMSE) = 0.15, r2 = 0.494, P < 0.0001]. The exact agreements between modeled and measured densities vary between studies and are related to the uncertainties in the unmeasured parameters in each study. Among these parameters, ro has the strongest effect on the model-predicted density, producing about −1% change in density for every 1% change in ro. The model is less sensitive to RECM and Td, yielding about 0.54 and 0.28% changes in density for every 1% change in each parameter, respectively (Fig. S5). Three parameters, wo, λ, and α, were held constant in the model simulations for all studies. However, only two of the six species examined in these studies (i.e., Porites lobata, Porites lutea) were included in our estimation of these three parameters, which could introduce additional uncertainties in our model predictions. Accordingly, we observe better agreements between model-predicted density and measured density for studies in which skeletal and physiochemical parameters are well-constrained and that are dominated by the same species as this study (e.g., the Arabian Gulf and Great Barrier Reef studies) (Fig. S6). In contrast, locations with poor constraints on ro, Td, and RECM (e.g., the Andaman Sea and the Caribbean region) yield less satisfactory agreements.
Other than the parameters discussed above, the rate of skeletal extension that was measured in all of these studies also affects coral skeletal density, as it influences the amount of time that each skeletal element spends inside the coral tissue layer subject to thickening (t = Td/E). Although we do not observe significant correlations between skeletal density and extension rate in our Porites cores on either annual or seasonal scales, as were observed in some previous studies (55, 57), two of the six studies included in our model–data comparison show apparent correlations between annual density and extension (Fig. S7). When examined as a whole, skeletal data from most of these studies also show an apparent correlation between these two parameters across the large range of extension (∼0.2–2.3 cm y−1) (Fig. S7), yielding a sensitivity of −0.20% change in density for every 1% change in extension. This observed correlation is consistent with our model-predicted sensitivity of skeletal density to extension [i.e., −0.30% change in density for 1% change in extension (Fig. S5)] and contributes to the agreement between our model-predicted density and experimentally measured density.
Projecting the Impact of Ocean Acidification on Porites Skeletal Density.
Our model takes into account the different factors that can influence Porites coral skeletal growth (e.g., seawater conditions, extension, polyp geometry) and enables us to isolate and evaluate the influence of each factor. Here, we use it to evaluate the response of Porites coral skeletal density to ocean acidification by forcing our model with outputs from the Community Earth System Model Biogeochemical (CESM-BGC) run in the RCP 8.5 projection (i.e., the business as usual emission scenario). Among global reef sites, the CESM-BGC run predicts a 0.25 to 0.35 units decrease in seawater pH, a −50 to 250 µmol/kg change in DIC, and a 1.7 °C to 3 °C increase in SSTs by the end of the 21st century. These translate to a 0.85–1.95 decrease in seawater aragonite saturation states. There remain large uncertainties in how rising SSTs will affect coral calcification via its effects on zooxanthellae photosynthesis and coral bleaching (58⇓–60). Thus, we focus solely on the impact of ocean acidification on coral skeletal density and do not include the effects of temperature on the reaction kinetics of aragonite precipitation in the following model simulations (SI Text). For the similar reasons, all model parameters (i.e., ro, Td, E, λ, wo, and α) were held constant in these simulations.
Our simulations predict an average 12.4 ± 5.8% (2σ) decline in Porites skeletal density across global reef sites by the end of the 21st century due to ocean acidification alone (Fig. 4). This decline results from the interplay between changes in seawater pH and DIC, with decreases in pH leading to an average decline in density of 16.8 ± 4.7% mitigated by increasing DIC, which drives a 6.4 ± 3.7% increase in density. Our model predicted that density declines vary among different reefs, with equatorial reefs generally more impacted than higher-latitude reefs. For example, our model predicts the largest decreases in skeletal density (11.4–20.3%) in the coral triangle region driven by the largest pH decreases projected for this region (up to 0.35 units). In contrast, reefs in the Caribbean and the Arabian Gulf are predicted to experience no significant decline in coral skeletal density. In these regions, the effect of relatively small projected pH decrease (∼0.29 units on average) is balanced by the largest increases in DIC (∼175 µmol/kg on average). The model-predicted density changes also vary across reef systems. For example, up to 13% density decline is predicted in the northern Great Barrier Reef, while no significant change is predicted in the southern edges.
Model-predicted decline in Porites skeletal density over the 21st century due to ocean acidification. Our model predicts an average 12.4 ± 5.8% (2σ) decline in density across global reef sites, with the largest decline in the western tropical Pacific coral triangle region (an average of ∼14% and a maximum of 20.3%) and the least in the Caribbean (∼6%). Simulations were conducted based on outputs from the CESM-BGC RCP 8.5 run for the years 2006–2015 and 2090–2099 (Methods). Skeletal extension, initial radius, and tissue thickness were held constant in these simulations. Error represents only that propagated from estimation of model parameters.
Our results suggest that ocean acidification alone would lead to declines in Porites coral skeletal density over the 21st century. Such declines in skeletal density could increase the susceptibility of coral reef ecosystems to bioerosion, dissolution, and storm damage (61⇓–63). It is important to note that, in addition to ocean acidification, coral reefs today face many other environmental stressors, including changes in temperature, nutrient concentration, and sea level (40). Our model enables us to isolate the impact of ocean acidification on coral skeletal growth. With accurate incorporation of the impacts of these other stressors, future models of this kind will be able to quantitatively project the fate of reef ecosystems under 21st century climate change.
Methods
Coral Samples and Reef Sites.
Nine 3-cm-diameter Porites cores were collected from reefs in Palau (six cores from four different sites), Donghsa Atoll (one core), Green Island (one core), and Isla Saboga (one core). For Palau sites, seawater salinity and carbonate chemistry parameters were acquired from 4 y of discrete sampling at each site (11), and seawater temperatures were derived from the National Oceanic and Atmospheric Administration Optimum Interpolation Sea Surface Temperature (oiSST) dataset after correcting for any mean and variance bias during overlapping periods of in situ logger temperatures (64). At other reef sites, seawater salinity and carbonate chemistry parameters were either determined based on discrete samples of seawater collected during coring and on subsequent visits to the respective reefs or compiled from reported values in the literature (Table S1). Seawater temperatures for these sites were derived from the oiSST dataset and were assumed to be representative of in situ reef conditions, since no temperature loggers were deployed and satellite SST agreed reasonably with literature values. Total alkalinity and DIC of all seawater samples were measured on a Versatile Instrument for Determination of Total inorganic Carbon at Woods Hole Oceanographic Institution with the open cell potentiometric and coulometric titration method. Seawater pH and aragonite saturation states were then calculated using the CO2SYS program (65).
Determination of Coral Skeletal Growth Parameters.
Coral cores were imaged with a Siemens Volume Zoom Spiral Computerized Tomography scanner to determine skeletal density and to identify annual density bands. Annual extension rates, skeletal density, and calcification rates were then determined based on these CT images along polyp growth axes (66) (Table S1). Specifically, annual extension rate (
Boron Isotope Measurements.
Each core was sampled at ∼1-mm intervals for boron isotope measurements over at least one annual density band couplet, resulting in 6–10 measurements in each annual band (Table S1). The isotope measurements were conducted at the Thermo Scientific Neptune multicollector ICP-MS either at Academia Sinica (Taiwan) or at National Oceanography Centre Southampton (67). The pH of the ECM was then estimated based on the measured δ11B values:
where pK*B is the equilibrium constant for the dissociation reaction of boric acid to borate estimated at respective seawater temperature and salinity (68), and the δ11B of seawater was taken to be 39.61‰ (69). The boron isotope fractionation factor, αB, is assumed to be 1.0272 (70).
Estimation of Aragonite Precipitation Rate in ECM.
Aragonite precipitation rate in the ECM (
Aragonite saturation state in the ECM was estimated as
where
Estimation of Model Parameters with Bayesian Methods.
Three parameters in our coral skeletal growth model were estimated with a Bayesian inference method (SI Text). These are the thickness of each new skeletal framework (wo), the decline of thickening rate with depth within the tissue layer (λ), and the DIC elevation factor in the ECM (α). Prior distributions for each parameter were constructed based on constraints from existing studies and were combined to form a joint prior distribution. The likelihood of each combination of parameters was then evaluated by comparing measured densities in our cores with the associated model predictions. The prior distribution was updated using the likelihood function via Bayes’ Theorem to form a posterior distribution, from which the most likely values for each parameter were acquired.
Comparison of Model Prediction with Existing Studies.
Porites corals from five reefs reported in six previous studies were used to evaluate the accuracy of our skeletal growth model in predicting coral skeletal density. These corals were collected from reefs in the Galapagos, the Andaman Sea, the Great Barrier Reef, the Caribbean, and the Arabian Gulf (9, 30, 54⇓–56, 74). Other than the three parameters estimated above with Bayesian methods, other parameters required for our model prediction include E, ro, Td, seawater temperature, salinity, and carbonate chemistry (from which
Projection of Future Skeletal Density Changes for Global Reefs.
Changes in skeletal density on different reefs over the 21st century were predicted based on output from the CESM-BGC RCP 8.5 run. Monthly projections of DIC, pH, T, and S from the first 10 y (2006–2015) and the last 10 y (2090–2099) of the run were extracted from the 1° × 1° model and averaged to represent the current and end of century seawater conditions at different reef sites around the globe. Reef site locations are provided by the ReefBase database of reef sites (75). Skeletal growth parameters, E (annual extension rate), Td (tissue thickness), and ro (polyp radii), were prescribed at 1.0 cm y−1, 0.56 cm, and 0.063 cm, respectively, (the average values observed in our cores) and were held constant for predictions over the 21st century. The effect of temperature on the kinetics of aragonite precipitation was not considered in the model simulation. A detailed analysis of the effects of the projected 21st century warming on model predictions is presented in SI Text.
Acknowledgments
We thank Pat Lohmann and Kathryn Pietro (Woods Hole Oceanographic Institution), Jay Andrew (Palau International Coral Reef Center), and Edgardo Ochoa (Smithsonian Tropical Research Institute) for assistance with coral core collection. This research was supported by US National Science Foundation Award OCE-1220529, the Robertson Foundation, Woods Hole Oceanographic Institution through the Ocean Life Institute, Investment in Science Fund and Early Career Award, Taiwan MOST Grant 104-2628-M-001-007-MY3, and the Leverhulme Trust in UK.
Footnotes
- ↵1To whom correspondence may be addressed. Email: nmollica{at}whoi.edu or wfguo{at}whoi.edu.
Author contributions: N.R.M., W.G., and A.L.C. designed research; N.R.M., W.G., A.L.C., K.-F.H., G.L.F., H.K.D., and A.R.S. performed research; A.L.C., K.-F.H., and G.L.F. contributed new reagents/analytical tools; N.R.M. and W.G. analyzed data; and N.R.M., W.G., and A.L.C. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1712806115/-/DCSupplemental.
Published under the PNAS license.
References
- ↵
- ↵
- Kleypas J
- ↵
- Hoegh-Guldberg O, et al.
- ↵
- Meissner KJ,
- Lippmann T,
- Sen Gupta A
- ↵
- Burton EA,
- Walter LM
- ↵
- Comeau S,
- Edmunds PJ,
- Spindel NB,
- Carpenter RC
- ↵
- ↵
- ↵
- Crook ED,
- Cohen AL,
- Rebolledo-Vieyra M,
- Hernandez L,
- Paytan A
- ↵
- ↵
- Barkley HC, et al.
- ↵
- Chan NCS,
- Connolly SR
- ↵
- Pandolfi JM,
- Connolly SR,
- Marshall DJ,
- Cohen AL
- ↵
- Enochs IC, et al.
- ↵
- Lough JM
- ↵
- Allemand D,
- Tambutté É,
- Zoccola D,
- Tambutté S
- ↵
- Cohen AL,
- McConnaughey TA
- ↵
- Constantz BR
- ↵
- ↵
- ↵
- ↵
- McCulloch M,
- Falter J,
- Trotter J,
- Montagna P
- ↵
- Trotter J, et al.
- ↵
- ↵
- ↵
- ↵
- Mcculloch MT,
- Olivo JPD,
- Falter J,
- Holcomb M,
- Trotter JA
- ↵
- ↵
- Fantazzini P, et al.
- ↵
- ↵
- ↵
- Wells JW
- ↵
- ↵
- Stolarski J
- ↵
- ↵
- ↵
- ↵
- ↵
- van de Locht R, et al.
- ↵
- Lough JM,
- Cooper TF
- ↵
- ↵
- ↵
- Al-Rousan S
- ↵
- Cantin NE,
- Cohen AL,
- Karnauskas KB,
- Tarrant AM,
- McCorkle DC
- ↵
- Cooper TF,
- De’ath G,
- Fabricius KE,
- Lough JM
- ↵
- ↵
- Euw SVon, et al.
- ↵
- Allemand D,
- TambuttE E,
- Girard JP,
- Jaubert J
- ↵
- ↵
- Taylor RB,
- Barnes DJ,
- Lough JM
- ↵
- Gagan MK,
- Dunbar GB,
- Suzuki A
- ↵
- Sorauf J
- ↵
- ↵
- Tanzil JTI, et al.
- ↵
- ↵
- Poulsen A,
- Burns K,
- Lough J,
- Brinkman D,
- Delean S
- ↵
- Decarlo TM,
- Cohen AL
- ↵
- ↵
- ↵
- Van Hooidonk R, et al.
- ↵
- Sammarco P,
- Risk M
- ↵
- van Woesik R,
- van Woesik K,
- van Woesik L,
- van Woesik S
- ↵
- ↵
- ↵
- Pierrot D,
- Lewis E,
- Wallace DWR
- ↵
- Decarlo TM
- ↵
- Foster GL,
- Rae J,
- Elliot T
- ↵
- ↵
- Foster GL,
- Pogge Von Strandmann PAE,
- Rae JWB
- ↵
- Klochko K,
- Kaufman AJ,
- Yao W,
- Byrne RH,
- Tossell JA
- ↵
- ↵
- Krumgalz BS
- ↵
- ↵
- ↵
- McManus JM,
- Ablan MC
Citation Manager Formats
Article Classifications
- Physical Sciences
- Environmental Sciences
- Biological Sciences
- Ecology


















