Introduction

Infectious disease outbreaks are responsible for a substantial loss of living coral cover throughout the world, but especially within the Caribbean region1,2,3,4. Disease outbreaks are also predicted to become more severe as climate change continues to increase global ocean temperatures leading to more virulent pathogens5,6 and more susceptible coral hosts7,8,9. The two largest documented coral disease outbreaks, white band disease and stony coral tissue loss disease (SCTLD), have followed similar trajectories through space and time. White band disease, which caused extensive mortality of the two Caribbean acroporids, reportedly spread over several years from the late 1970s to the early 1980s and reached the entire spatial extent of the Caribbean while reducing the population of Acropora spp. by over 90%2. Similarly, SCTLD began off the coast of Miami, FL, USA in 2014 and has since affected the entirety of Florida’s Coral Reef (FCR) and spread to other regions around the Caribbean3,4,10,11, potentially through ballast water12,13. While white band disease affected only the acroporid species, boulder and brain corals as well as other unique coral species morphologies14 are susceptible to SCTLD. Estimates suggest that SCTLD has reduced living coral cover on affected reefs by up to 62% in areas throughout Florida and the Caribbean15,16,17.

Like most coral diseases, the putative pathogen(s) for SCTLD remains unknown. Studies have indicated that SCTLD lesion progression can be slowed down or halted on some coral species with ointment laced with amoxicillin18,19,20, suggesting that the presumptive pathogen(s) or SCTLD etiology may have a bacterial component. Several SCTLD microbiome studies have determined significant differences in bacterial taxa between diseased and apparently healthy corals21,22,23,24 although it is unknown whether these taxa are primary pathogens or involved in secondary opportunistic infections. Additionally, these microbial taxa can vary across studies, coral species, coral compartments, seawater, and sediment25. A recent microscopy-based study suggested that viruses may be involved in the onset of SCTLD through infection of Symbiodiniaceae26, and the gene expression of corals with SCTLD also supports this concept27.

To date, there are no existing diagnostic tools to positively identify SCTLD, making it difficult to determine if all impacted species are suffering from the same disease. However, SCTLD appears to have a hallmark ecology upon first affecting a reef or region and has been given its own case definition28. Visually, SCTLD appears as acute or subacute tissue loss lesions that spread focally or multifocally throughout the colony, leaving freshly exposed skeleton18,29. The progression of SCTLD lesions within a colony is more rapid compared to other coral diseases4,30. Highly susceptible species (typically first affected during an outbreak and often associated with the Meandrinidae family) demonstrate rapid disease progression, with total mortality ranging from 1 week for smaller colonies to 1–2 months for larger colonies28. Tissue loss appearance in intermediately susceptible species (boulder and brain massive coral species) occurs about 1 month after onset in highly susceptible species, with smaller colonies experiencing mortality over several months, and larger colonies experiencing mortality over several years with the potential of developing new lesions31. Porites spp. appear more resistant to SCTLD and Acropora spp. are not known to be susceptible.

Environmental influence on disease dynamics

Disease dynamics are influenced by a tripartite interaction of the host, pathogenic agent, and the environment. Previous studies showed that corals of Acropora palmata susceptible to thermal bleaching were more susceptible to disease-related mortality compared with those that were more heat tolerant32. Additionally, the direct introduction of novel pathogens to naive hosts within the marine environment, which caused tissue loss lesions on A. palmata, has been associated with human sewage33. However, the environment influences both host immune competence and the virulence of pathogens7, and stressful or suboptimal water quality conditions are often associated with higher prevalence of coral diseases34,35,36. For example, high water temperatures are often correlated with the higher prevalence and/or incidence of several different coral diseases such as black band disease37,38, white pox disease39,40, white syndrome41 and others42. Interestingly, several studies to date have shown the opposite association between water temperature and SCTLD dynamics. A recent SCTLD transmission study 77 found that disease incidence was reduced during exposure to elevated temperature in the species Orbicella faveolata. One study43 showed a negative association between degree heating weeks (a measure of heat stress accumulated within a given region over the period of 12 weeks) and the incidence of SCTLD on reefs in the lower Florida Keys. Similarly, another study44 showed tissue loss rates of SCTLD were negatively correlated with degree heating weeks in St. Thomas, US Virgin Islands. Given that degree heating weeks is often associated with bleached corals, these results suggest the presence or absence of the internal algal symbiont of the coral may play a role in SCTLD dynamics or that prolonged increased temperature, rather than temperature alone, may influence SCTLD dynamics. Furthermore, some studies have demonstrated that stony corals containing algal symbionts in the genus Durusdinium are less susceptible to SCTLD compared to those hosting Breviolum45,46, suggesting a potentially pivotal role that algal symbionts play in SCTLD etiology.

In addition to elevated water temperatures, rising atmospheric CO2 is causing the ocean to become more acidic. Ocean acidification typically reduces calcium carbonate production within coral reefs around the world48,49; however, net calcification in relation to ocean acidification varies among species50. Since the relationship between ocean acidification and SCTLD dynamics has not been studied to date, we exposed corals to both of these environmental stressors prior to disease exposure to better document the relationship between environmental factors and SCTLD transmission rates.

Genetic variation in disease susceptibility

The host’s immune competence plays an important role in disease dynamics and particularly in susceptibility. Disease is a common component of any ecosystem and as such, there are varying levels of resistance and susceptibility inherent within populations51,52. For example, some genotypes of Acropora cervicornis appear resistant to white band disease in Panama53 and in the Florida Keys32. In regard to SCTLD, laboratory transmission experiments suggest that there are some individuals that never succumb to the disease even when they are kept in direct contact with diseased corals for weeks18,54. Furthermore, survivors are recorded within field studies31,43 again suggesting some corals can withstand and resist the pathogenic agent(s) of SCTLD. However, a study comparing genetic relatedness and SCTLD incidence within field conditions documented no genetic basis for SCTLD resistance or susceptibility55.

Disease susceptibility and coral restoration

With the substantial loss of live coral cover in the wider Caribbean, coral restoration has become an increasingly popular tool to help rejuvenate reef ecosystems. Restoration of acroporid species in this region has been occurring over the last couple decades56 at an ecologically meaningful scale57. The restoration of massive species is a relatively new phenomenon58, but has become increasingly important since the onset of SCTLD. However, outplanted massive coral survival has varied substantially due to several factors, including performance of outplants59, unfavorable water quality conditions at some sites60, and predation61. Despite these challenges, understanding how nursery-reared coral species and genotypes respond to major threats such as SCTLD is imperative for effective ecological restoration in this region. Additionally, understanding how these corals respond to SCTLD under different environmental scenarios will guide thoughtful coral restoration practices, as these threats are likely to increase in persistence and severity. An experiment that was previously published62 exposed different genotypes of Orbicella faveolata and Pseudodiploria clivosa nursery-reared corals to end-of-century ocean warming (OW) and ocean acidification (OA) scenarios for 2 months and detailed the physiological response of the corals to these treatment conditions. Here, we subsequently utilized the same corals to conduct a SCTLD exposure immediately after the 2-month treatment within OW and OA scenarios. The objectives of the present manuscript were to i) identify how previous exposure to OW and OA conditions influenced SCTLD relative risk at the species and genotype level, and ii.) identify potential correlations between algal symbiont composition and SCTLD median relative risk values.

Methods

Ocean warming and acidification exposure

The ocean warming and acidification experiment was detailed in Klepac et al.62. A brief overview of the experimental design is described here. A manipulative aquaria-based experiment was conducted using a fully factorial design to expose experimental corals to OW and OA treatment conditions. This treatment exposure experiment took place from June to August 2018 within Mote Marine Laboratory’s Climate and Acidification Ocean Simulator (CAOS). One mixing tank within the CAOS system contained ambient pCO2 seawater targeting present-day ocean conditions (418.94 ppm pCO2). The other contained elevated pCO2 levels targeting end-of-century IPCC RCP 8.5 projections of 1200 ppm pCO247. Seawater from the mixing tanks flowed into 16 L flow-through aquaria housed within shaded outdoor raceways. The temperature of each raceway was maintained at either ambient temperature (27℃) or elevated temperature (31.5℃, or + 1℃ over the bleaching threshold for the region63).

This exposure consisted of four different treatment scenarios: (1) control (27°C, 500 ppm pCO2), (2) ocean warming (OW: 31.5°C, 500 ppm pCO2), (3) ocean acidification (OA: 27°C, 1100 ppm pCO2) and 4) ocean acidification with warming (OAOW: 31.5°C, 1100 ppm pCO2). This design allowed us to quantify changes in coral health related to individual stressors and stressors in concert. Six replicates of thirteen genotypes (10 O. faveolata and 3 P. clivosa) collected from Mote Marine Laboratory’s ex-situ coral nursery were exposed to each treatment scenario for a 2-month period. For the elevated temperature treatments, this equated to 10.34 Degree Heating Weeks64. Corals were genotyped via 2bRAD65 to confirm genotype differences.

Carbonate water chemistry parameters (dissolved inorganic carbon, total alkalinity) were collected once per week on randomly selected treatment tanks and the mixing tanks. Seawater samples were collected in 125 mL amber bottles, stored in the dark at 4°C and analyzed following methods from Dickson et al.66. For dissolved inorganic carbon (DIC), water samples were filtered to 0.2 μM prior to analysis. Total alkalinity (TA) was measured using a Metrohm 905 Titrator with an 800 Dosino and dissolved inorganic carbon was measured using an Apollo SciTech AS-C3 and then corrected with certified reference materials (CRMs 170,174,175, and 176) provided by A.G. Dickson (Scripps Institution of Oceanography, Oceanic Carbon Dioxide Quality Control, La Jolla, CA). CO2SYS was used to calculate the partial pressure of carbon dioxide (pCO2), pH total (pHT), and saturated aragonite (Ωar); the metrics used to monitor carbonate chemistry in the experimental tanks. Throughout the experiment, there was minimal fluctuation in carbonate chemistry parameters (see Supplemental Figure 1).

Fig. 1
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Experimental tank setup of the SCTLD exposure.

Water quality (temperature, salinity, pHNBS, dissolved oxygen) within aquaria was monitored daily with handheld water quality meters (YSI Multimeter Professional Series, Yellow Springs, OH; Mettler Toledo Seven2GO pH meter, Columbus, OH). Light levels within the aquarium tanks were measured twice per week at 2 pm with a Li-Cor Light Sensor Logger (Li500, Lincoln, NE). Light levels in the aquaria averaged 385 ± 29.5 μmol photons m−2 s−1 for the duration of the experiment. Supplemental Table 1 outlines the mean (± SE) water quality parameters from the experimental tanks for each treatment (n = 6 experimental tanks per treatment). There was one powerhead (songlong SL-381 submersible pump) in each tank to maintain circulation. Flow to the aquarium tanks via manifolds and black tubing was set to a rate of 300 ml/min per tank. The coral substrates, tanks, racks, and powerheads were cleaned once per week for nuisance algae removal. Corals were not fed during the experiment but received nearshore water that was only processed through a sand filter and likely contained food sources for heterotrophic feeding.

After the ocean warming and acidification exposure ended, half of the corals from each treatment were utilized for the SCTLD exposure (present study), and half were utilized for the destructive physiological trait measurements detailed in Klepac et al.62. For Symbiodiniaceae identification, samples were collected from three separate ex-situ nursery replicates of each genotype used in the study. DNA was extracted using a DNeasy PowerSoil Kit (QIAGEN, Germantown, MD) with modifications to the manufacturer’s protocol22. The forward and reverse ITS2 regions were sequenced at MR DNA laboratory (www.mrdnalab.com, Shallowater, TX, USA) and results were submitted to SymPortal67. Supplemental Figures 2 and 3 display the proportion of Symbiodiniaceae ITS2 type profiles for each genotype of O. faveolata and P. clivosa.

Fig. 2
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Disease susceptibility (percent of fragments to get diseased) for (a) Orbicella faveolata and (b) Pseudodiploria clivosa in the different environmental treatments. Letters denote statistically significant differences between the treatments. Bayesian relative risk analysis for (c) Orbicella faveolata and (d) Pseudodiploria clivosa. Horizontal lines indicate the 95% credible interval of the Bayesian risk analysis. Black dots indicate the median relative risk value. The vertical line is a risk value of 1, which indicates that there is no risk of disease after exposure. Credible intervals residing completely above one indicate significant risk after exposure to the diseased colony.

Fig. 3
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Bayesian relative risk analysis of Orbicella faveolata genotypes in the (a) control, (b) OA, (c) OW, and (d) OAOW conditions. Horizontal lines indicate the 95% credible interval of the Bayesian risk analysis. Black dots indicate the median relative risk value. The vertical line is a risk value of 1, which indicates that there is no risk of disease after exposure. Credible intervals residing completely above one indicate significant risk after exposure to the diseased colony.

Disease exposure experiment set up

Corals were exposed to SCTLD under the same treatment conditions as the 2-month OW and OA exposure. The disease exposure studies took place within Mote’s Coral Health and Disease and Ocean Acidification wetlabs in Sarasota, FL to avoid potential introduction of SCTLD into Mote’s ex-situ nursery. Due to space limitations in these labs, the corals within the four different treatment scenarios were transported to Sarasota and exposed at varying times from September to November 2018 (see Supplemental Table 2). Wild coral colonies displaying signs consistent with SCTLD were collected opportunistically for the exposures from Looe Key buoy #4 (24.54642 x − 81.40297) and buoy #7 (24.54609, − 81.40397). These colonies were approximately 30 cm in diameter with ~ 30% disease progression. Disease species consisted of Diploria labyrinthiformis, Montastraea cavernosa, Pseudodiploria strigosa, Pseudodiploria clivosa, and Stephanocoenia intersepta. Diseased ‘donor’ colonies were transported to the Coral Health and Disease wetlab on the day of collection and held overnight prior to manipulation.

One 3 m × 1.2 m fiberglass raceway holding twenty 9.5 L aquaria was used for each exposure. The diseased donor colonies were fragmented into ~ 6 cm wide strips using a Dewalt DWE402 angle grinder and diamond blade band saw (C-40 Band Saw, Gryphon) and placed randomly throughout 2.5-gallon tanks. O. faveolata and P. clivosa replicates were randomly dispersed and placed in direct contact with the diseased lesion on the fragment (Fig. 1). The temperature of the raceway was maintained using a heat exchanger set to the appropriate treatment condition. OA conditions were maintained using venturi pumps and solenoids to inject pure CO2 into a mixing tank that was used for the aquaria. Corals were held under a 10-h light: 14-h dark photoperiod using Radion XR30W Pro aquaria lights (EcoTech Marine, Allentown, PA, United States). Each disease exposure experiment ran for approximately 3 weeks.

Disease exposure experimental monitoring and maintenance

Fifty percent water changes were completed daily on all aquarium tanks, and a recirculating water pump (songlong SL-381) was used to maintain water motion within each aquarium. All contaminated seawater along with any exposed equipment was bleached and UV sterilized using a 1:9 bleach-to-water ratio. Observations and photographs were recorded daily to monitor tissue loss appearance and mortality rates.

Statistical analysis

All statistical analyses were performed in R 4.4.068. Figures were made using the ggplot2 package69 or Prism software (version 8.0.0 for Windows, GraphPad Software, San Diego, CA, United States). At the species level, chi-squared tests were used to test for differences in disease susceptibility under the different environmental scenarios for O. faveolata, and Fisher’s Exact tests70 were used for P. clivosa. A Bayesian relative risk analysis was also performed for each treatment within each coral species. The risk analysis was also used to quantify SCTLD susceptibility among genotypes. The risk analyses were conducted in OpenBUGS, a Bayesian inference Gibbs Sampling (BUGS) software package71. Spearman’s correlation was used to assess the association between the algal symbiont composition and the median SCTLD relative risk values within treatment conditions and among all treatments combined. To assess symbiont composition of the separate ex-situ nursery replicates, we calculated the ratio of Durusdinium counts to Breviolum counts (higher ratio indicates increased amounts of Breviolum). All analyses were conducted for each species separately.

Results

High temperature and ocean acidification treatments maintained or reduced SCTLD susceptibility

The chi-square test showed the control O. faveolata treatment corals had significantly higher disease susceptibility compared to the OW (Fig. 2a, p < 0.001) and OA (Fig. 2a, p = 0.001) treated corals. Additionally, the OAOW treated corals had significantly higher disease susceptibility compared to the OW (Fig. 2a, p = 0.003) and OA (Fig. 2a, p = 0.004) treated corals. Similarly, the Bayesian relative risk analysis showed a significantly higher risk of disease occurring in the control and OAOW conditions (Fig. 2c) compared with the OA and OW treatments. There were varying levels of risk at the genotype level, with 9 out of 10 genets in the control treatment showing an increased risk of disease after exposure (Fig. 3a). Under the OA treatment, only three genotypes showed an increased risk (Fig. 3b) and under the OW conditions there were only two genotypes that showed an increased risk (Fig. 3c). Under the OAOW treatment scenario, there were two genotypes (OF126 and OF8) that had significantly higher risk of SCTLD (Fig. 3d). Additionally, there were four other genotypes in this treatment that had an increased risk of SCTLD, which were not significant.

In P. clivosa, the OA-treated corals were the least susceptible to SCTLD (Fig. 2b). Although the Fisher’s Exact test did not detect any statistically significant differences, likely due to low sample size, the Bayesian relative risk analysis showed a significant risk of disease occurring in the control and OW conditions (Fig. 2d). At the genotype level, only one genotype had significant risk of disease, PC12 in the OW treatment (Fig. 4c). Additionally, the relative risk values for this genotype were higher in the control and OA treatments compared to the other two genotypes, but this result was not significant (Fig. 4a–b). The remaining two genotypes (PC17 and PC3) had comparable risk values for the control, OW, and OA treatments, with slightly lower risk values in the OA treatment (Fig. 4b). All three genotypes had similar risk values in the OAOW treatment (Fig. 4d).

Fig. 4
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Bayesian relative risk analysis of Pseudodiploria clivosa genotypes in the (a) control, (b) OA, (c) OW, and d.) OAOW conditions. Horizontal lines indicate the 95% credible interval of the Bayesian risk analysis. Black dots indicate the median relative risk value. The vertical line is a risk value of 1, which indicates that there is no risk of disease after exposure. Credible intervals residing completely above one indicate significant risk after exposure to the diseased colony.

Algal symbiont composition, in part, influenced the relative risk to SCTLD

In O. faveolata, there were no significant correlations between SCTLD susceptibility and symbiont composition for the treatments combined or within individual treatments. However, at the genotype level, the two genotypes (OF8 and OF126) that had significantly higher risk of SCTLD in the OAOW treatment (Fig. 3d) had higher ratios compared to the rest of the genotypes (Fig. 5).

Fig. 5
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Scatterplot comparing the median relative risk values and ratio of  Durusdinium counts to Breviolum counts for O. faveolata genotypes in the different treatments. Higher ‘ratio’ values indicate higher relative abundance of Breviolum.

In P. clivosa, there was a significant correlation between SCTLD susceptibility and symbiont composition with the treatments combined (p = 0.038, r = 0.603), with a positive association between relative risk and higher ratios. There were no significant correlations within individual treatments. At the genotype level, the genotype (PC12) that had increased relative risk values in the control and OW treatments had the highest ratio compared to the other genotypes (Fig. 6).

Fig. 6
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Scatterplot comparing the median relative risk values and ratio of Durusdinium counts to Breviolum counts for P.clivosa genotypes in the different treatments. Higher ‘ratio’ values indicate higher relative abundance of Breviolum.

Discussion

Although many previously studied coral diseases are often more virulent with increasing water temperatures, the present study showed the opposite trend. In fact, O. faveolata corals had significantly lower SCTLD susceptibility in the OW and OA treatments alone compared to the control and combined (OAOW) treatments. Additionally, O. faveolata was equally as susceptible to SCTLD in the control and combined treatment conditions, suggesting that exposure to high temperatures and ocean acidification for 2 months prior and during SCTLD exposure did not increase susceptibility. When comparing these results to the physiological responses measured by Klepac et al.62 there was little correspondence. After the 2-month long exposure, Klepac et al. reported little physiological change associated with O. faveolata under the OW and the OAOW treatments as compared with controls. The present study observed a reduced SCTLD risk under OW and OA treatment conditions, suggesting that the response observed may be driven by environmental conditions during exposure to SCTLD rather than the physiological condition of the corals. Further studies should aim to create more distinct physiological change within the corals to better assess the potential links between host condition and susceptibility to SCTLD.

For P. clivosa, there were similar relative risk values for the control and OW treatments, and these values trended higher compared to the other two treatments. In the present study, the OW-treated corals were exposed to 10.34 Degree Heating Weeks and had either lower or similar disease susceptibility compared to the controls. This result is comparable to that of Williams et al.43, where there was reduced disease progression and incidence rates after 2–3 Degree Heating Weeks. Additionally, the results of the present study are comparable to Meiling et al.44, where there was a slowing or cessation of disease progression when the corals were exposed to a maximum of 9.13 Degree Heating Weeks. Here we showed reduced SCTLD transmission and a higher or similar level of resistance for P. clivosa exposed to prolonged high temperatures prior to and during disease exposure.

Interestingly, both O. faveolata and P. clivosa corals appeared less susceptible to SCTLD in the OA treatment. Klepac et al.62 found that OA was potentially beneficial for O. faveolata health metrics (chlorophyll a content, symbiont density, and host protein concentration), and the P. clivosa physiological responses under OA were comparable to control conditions. These results suggest the corals were not showing apparent signs of stress after 2 months of elevated pCO2 conditions. Indeed, the treatment conditions could be positively influencing the host immunity, promoting the ability of the host to respond to pathogenic infections72. Other marine diseases appear less virulent under ocean acidification conditions—for example, a fungal disease of crustose coralline algae has slower lesion expansion rates when under ocean acidification conditions73. Additionally, black band disease progresses more slowly under elevated pCO2 conditions, perhaps because OA disrupts the composition of the bacterial consortium responsible for this disease74. In both of these examples, however, the fungal CCA disease and black band disease show more virulence under ocean warming conditions. Here, we demonstrate that OA may reduce SCTLD transmission rates, but there is no evidence that increasing water temperatures increase the virulence of SCTLD. Although studies suggest that some coral species are more susceptible to infectious disease outbreaks after stressful events such as bleaching9,75, this may not be the case for SCTLD. To date, evidence suggests that SCTLD is a novel pathogen introduced into the marine environment and that the dynamics of this disease etiology is largely not influenced by environmental conditions. However, we suggest further evidence is needed to definitively determine the relationship between ocean acidification, ocean warming, and SCTLD dynamics.

At the genotype level, there were varying levels of disease susceptibility in both species, and most genotypes within both species also showed varying levels of susceptibility depending on the treatment conditions. However, one O. faveolata genotype, OF3, showed complete resistance, suggesting that 10% of the population tested may have inherent resistance to SCTLD. This level of population resistance is comparable to other levels of resistance to known coral diseases such as white band disease on Acropora cervicornis53 and Vibrio bacterial infection in Montastraea cavernosa76. Evidence to date, however, suggests that there is no association between genetic markers or genetic lineages and SCTLD susceptibility55 so further understanding of the mechanism underpinning SCTLD resistance is paramount.

While the role of the symbiont in SCTLD dynamics is still poorly understood, two studies have suggested that stony corals containing algal symbionts in the genus Durusdinium are less susceptible to SCTLD compared to those hosting Breviolum45,46, but see Klein et al.55. All the stony coral species that have been classified as “highly susceptible” to SCTLD typically only host Breviolum. In the present study, one P. clivosa genotype (PC12) and two O. faveolata genotypes (OF8 and OF126) contained higher amounts of Breviolum compared to the other genotypes within each species. Interestingly, these genotypes had a significantly higher risk for SCTLD transmission, but only under OW or OAOW conditions. Nonetheless, this further supports that corals hosting mostly Breviolum are possibly more susceptible to SCTLD. Additionally, just because a coral hosted Durusdinium did not mean the coral was resistant to SCTLD, it was simply less susceptible with some replicates showing no disease signs after exposure and some succumbing to the disease. Future studies with higher replication are needed to better understand the role of the symbiont in SCTLD dynamics. Also, we recognize that the symbiont communities could have shifted after exposure to OW and OA conditions, and not sampling corals before exposure to SCTLD is a limitation of our study. We suggest that future studies examine the symbiont community of corals after exposure to climate change scenarios and before exposure to SCTLD, as the present study explored the symbiont community of separate ex-situ nursery replicates of each coral genotype.

Conclusions

While coral restoration practitioners have, in part, already established successful outplant and monitoring methods at an ecologically meaningful scale, there is still the challenge of ensuring long-term survival of coral outplants under future climate change scenarios. Understanding how corals respond to environmental threats is critical for the long-term survival of coral outplants. This information is particularly important for coral species and genotypes already undergoing captive rearing and restoration. In the present study, different genotypes of the corals Orbicella faveolata and Pseudodiploria clivosa were exposed to OW, OA, and SCTLD; three major threats that these corals face within FCR and the wider Caribbean. We found that for both species, pre-exposure to OW and/or OA did not make corals more susceptible to SCTLD. In fact, corals exposed to OA conditions showed reduced risk to SCTLD. Additionally, coral genotypes hosting higher levels of the algal symbiont Breviolum had a higher risk of getting SCTLD under climate change scenarios, suggesting that the symbiont may influence SCTLD dynamics. Only one genotype (10% of the tested broodstock) of O. faveolata was consistently resistant to SCTLD under the end-of-century climate scenarios, indicating that natural levels of resistance exist and may increase in prevalence over time. Understanding why this genet can withstand exposure without showing tissue loss may be critical for upscaling corals that are disease resistant as SCTLD is now endemic throughout Florida and much of the Caribbean.