Coral mortality in a mass bleaching event influenced by proximity to diseased tissue and reef topography

Coral mortality in a mass bleaching event influenced by proximity to diseased tissue and reef topography | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Coral mortality in a mass bleaching event influenced by proximity to diseased tissue and reef topography Camilla L Nivison, Christa R May, Mari Ella Bourbonnais, Shannon Shotz, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9371933/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Coral reefs of the Florida Keys experienced the hottest summer on record in 2023, causing mass bleaching and mortality of scleractinian corals. Sea surface temperatures remained above 31ºC for 41 days, exceeding all prior records for the region. Branching corals fared especially poorly, especially Acropora palmata , which has now been deemed functionally extinct across the entire Florida Reef Tract. High temperatures and prolonged thermal stress were the major causes of mortality. Our study investigates additional stressors contributing to coral mortality during the heatwave. Using benthic imagery, we show that during bleaching, coral tissue death is accelerated by proximity to disease. Using a Cox proportional hazard model, we found that, compared to initially healthy tissue on the same colony, disease lesions and neighboring tissue had a 3.8 times and 1.5 times higher risk of death, respectively. We show that these two stressors, working at different spatial scales, acted synergistically to increase mortality. Furthermore, from our in-situ reef structural measurements, we found that during bleaching, coral survival was greatest along the reef edge. The reef displaces water, resulting in faster local velocity, which we hypothesize reduces the boundary layer at the tissue-water interface and thus simultaneously enhances the removal of cytotoxic metabolic wastes and the opportunity for coral heterotrophic feeding. Our findings reinforce the importance of the interactive effects of disease and reef topography on coral mortality, and suggest that restoration efforts should focus on reef edges where the chance of survival is improved relative to the reef interior. Coral bleaching white pox disease multiple stressors heatwave Florida Reef Tract Acropora palmata Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction In the summer of 2023, the Florida Keys experienced the most extreme marine heatwave on record, for both temperature and duration (NOAA Coral Reef Watch 2019). It caused mass coral bleaching throughout the Florida Reef Tract (FRT) (Neely et al. 2024; Ayad et al. 2025). This heatwave caused the ninth mass bleaching event on the FRT, the first of which occurred in 1987 (Manzello 2015; Manzello et al. 2025). However, 2023 was the most detrimental, exposing corals to up to four times greater prolonged thermal stress than any prior heatwave (Manzello et al. 2025). Bleaching occurs when stressed corals expel their mutualistic endosymbiotic algae, Symbiodiniaceae . While not imminently fatal (Suggett and Smith 2011), bleached corals are deprived of photosynthetically derived nutrition from their Symbiodiniaceae , putting them in severe energy deficit and at risk of death if they are not recolonized. Bleaching can be measured optically, as reflectance in red, green, and blue (RGB) channels shifts in synchrony with symbiont density (Edmunds et al. 2003). While prolonged thermal stress is usually the cause of mortality from bleaching, extreme high temperatures (4-5 ºC above the historical maximum monthly mean) can induce mortality in as little as 4 days (Glynn and D’Croz 1990). If current warming trends continue, the Caribbean will experience an additional temperature increase of 1.5ºC above the baseline by 2100, with progressively more frequent marine heatwaves (Bove et al. 2022) likely to exceed the 31ºC bleaching threshold annually (Manzello 2015). Coupled with hurricanes and disease, these stressors have, and will continue to, decimate the Caribbean coral reefs (Aronson and Precht 2001; Williams and Miller 2012). Coral reefs are regularly exposed to multiple stressors including thermal stress, disease, hurricanes, increased nutrient loads, and poor water quality (e.g. Porter et al. 1999, Hughes et al. 2017). These stressors can have compounding effects: limited metabolic resources due to bleaching (Goreau and Macfarlane 1990; Rädecker et al. 2021) diminishes the coral’s ability to combat other stressors, resulting in reduced survivorship and slower population recovery (Glynn 1996). Hurricanes coupled with disease and reduced herbivory on the FRT have reduced coral cover throughout the 1980’s and 1990’s (Dustan and Halas 1987; Porter and Meier 1992; Ruzicka et al. 2013), flattening the reefs (Alvarez-Filip et al. 2009) and preventing regrowth (Hughes and Tanner 2000; Doropoulos et al. 2017). The simultaneous impacts of thermal and other stressors show synergistic outcomes, whereby bleaching recovery is dampened by the effects of other stressors such as nitrogen loading (Lapointe et al. 2019; Donovan et al. 2020) and sedimentation (Bessell-Browne et al. 2017). Corals activate a uniform response against most major threats, rather than targeted responses to individual stressors (Dixon et al. 2020), which may contribute to the challenges of coping with multiple stressors simultaneously. Disease also shows confounding effects with high temperatures and bleaching: thermal stress reduces disease resistance (Bruno et al. 2007), with no fitness tradeoff between traits (Bruno et al. 2007; Muller et al. 2018). This increase in disease susceptibility could be due to an increase in pathogen growth rates or pathogen load (Haas et al. 2016), or to disrupted coral microbiomes from the increase in temperature (Sparagon et al. 2024). Either mechanism could help explain why disease prevalence is highly correlated with thermal anomalies (Ruiz-Moreno et al. 2012; Randall and van Woesik 2015), and will continue to be an increasing threat as temperatures rise. The combination of disease and temperature has severely impacted Acropora palmata – a once prominent member of the FRT shallow reef community (Ruzicka et al. 2013; Sutherland et al. 2016) – now declared functionally extinct in the region (Manzello et al. 2025). Historically, A. palmata formed large stands on shallow patch reefs and fore-reef slopes, growing quickly, and providing ample reef structure (Gladfelter et al. 1978). With the onslaught of heatwaves, disease, and hurricanes, much of these former iconic stands have been demolished. Williams and Miller (2012) recorded more than 50% of A. palmata colonies were lost between 2004 and 2010, resulting in a major loss of reef topography (Alvarez-Filip et al. 2009). The heatwave in the summer of 2023 exterminated most remaining colonies (Neely et al. 2024; Manzello et al. 2025), though some natural colonies still persist on Elbow Reef in the northern FRT. This oasis of survivors could be due to physical microhabitat features that reduce the severity of bleaching damage such as locally accelerated flow rates, reduced sedimentation and nutrient loading, variations in turbidity, and/or pelagic microbial community composition (Nakamura and Van Woesik 2001; Lenihan et al. 2008; Haas et al. 2016). Unique to A. palmata , white pox disease (WPX) is visually characterized by irregularly shaped white patches as the underlying skeleton becomes visible, while the surrounding tissue appears to be healthy (Patterson et al. 2002). WPX is a bacterial dysbiosis, sometimes caused by Serratia marcescens (Patterson et al. 2002), a human enteric bacterium that could arrive at the reef with sewage runoff (Sutherland et al. 2010). While previously highly lethal, WPX has subsided into being a persistent, but less threatening stressor (Sutherland et al. 2016). There are conflicting data on whether or not high temperatures exacerbate disease outbreaks (Muller and Woesik 2014; Sutherland et al. 2023). At the microbial level, increased temperatures can increase pathogenic microbial activity (Frydenborg et al. 2014; Garren et al. 2016), and may make disease-impacted tissue more susceptible to thermal stress. To our knowledge, no studies have directly quantified how disease and bleaching interact at the tissue level during a heatwave. In our study, we investigated factors affecting the rapid A. palmata bleaching and mortality on reefs across the FRT during the summer heatwave of 2023. At Horseshoe Reef, in the Upper Keys, we investigated the possible interaction between bleaching and WPX, comparing tissue-level mortality rates between initially healthy, diseased, and healthy tissue neighboring disease lesions (hereafter, neighbor) to determine if disease increases the rate of tissue mortality during thermal stress. At the colony level, also at Horseshoe, we characterized how these coral colonies lost their color with increasing short-term thermal stress. At the landscape level, we investigated factors leading to the survival of some A. palmata colonies on the FRT, while most had perished by Fall 2023. We examined whether depth or location on the reef correlated with differential survival. Data from this study will help identify how disease may influence bleaching survival outcomes, and other reef conditions that lead to survival . As A. palmata is an International Union for Conservation of Nature (IUCN)-listed critically endangered species, understanding the underlying drivers of mortality are critical to optimizing intervention strategies for this species. Methods Site Descriptions Horseshoe Reef(25.139736ºN, -80.294314º W) is a shallow patch reef located about 5 miles off the coast of Key Largo. The reef crest, where A. palmata lived, is about 2 m deep, while the adjacent sandy seafloor is 5-6 m deep. Elbow Reef (25.142942ºN, -80.257936ºW), is a spur and groove reef on the outer reef line, approximately two miles farther offshore from Horseshoe. Elbow was the only reef in the FRT with substantial A. palmata survival after 2023. Depths ranged from 3-4 m on the reef crest to 5 m in the sand channels between the reef spurs. Farther south, Sombrero Reef (24.6277289º N, -81.110824º W) and Looe Key Reef (24.5489189º N, -81.4060307º W) are both spur and groove reefs on the outer reef line. Depths at Sombrero range from 3-4 m on the reef crest and 7-8 in the sand channels, with the seafloor slowly dropping deeper to the southeast. Looe has a shallower, patchy inner reef, with spur and grooves at 4-5 m and 8 m depths, respectively, on the ocean-facing (southwest) front ( Fig. 1 ). Image Collection and Analysis Coral imagery of A. palmata was taken on Horseshoe using dually-mounted, downward-facing GoPro Hero 10 cameras. Images were taken either by video (30 frames per second) (July 5-15, 2022) or one-second intervalometer (July 11-25, 2023) of four 25 m 2 plots selected for their high cover of A. palmata (all restored populations) ( Table S1) . Cameras were set to auto exposure in linear mode. A diver swam the cameras back and forth in a lawnmower pattern 1.0 to 1.5 m above the coral, taking approximately 500 overlapping images per plot. Black and white ground control tiles and scale bars were placed on the reef for photogrammetry analysis (Ferrari et al. 2021; Zhong et al. 2024). Individual frames (every 30th frame) were captured from the video transects. We used Agisoft Metashape Professional (Agisoft, 2025) to create mosaic images of each coral plot for each day it was photographed ( Table S1 ). The ground control tiles and scale bars were used to scale the mosaics and their associated digital elevation models. White balance was adjusted in Adobe Photoshop. We used TagLab (Pavoni et al. 2022, 2024) to segment 66 individual coral colonies and their disease lesions (if applicable, July 2022 and July 11-14 2023 only). These colonies were selected because they were well resolved with visible edges across all time points. In TagLab, we generated segmentation masks and calculated 3D surface area for each colony and lesion. Tissue-level survival was tracked in 50 colonies during July 2023. On each colony, 7 cm 2 tissue samples were identified in photographs from one disease lesion, four neighbor regions, and four regions haphazardly selected to be on visually healthy tissue and far from any disease lesion, and visually tracked in Python with Napari (Chiu et al. 2022). For our survival model, tissue samples were noted as surviving until turf algae was visible (in very sharp photos) or that the color had turned from white to off-white/brown during the sampling period, as recolonization by Symbiodinaceae while temperatures were elevated was deemed impossible ( Fig. 2 ). Survival of each tissue type was visualized with a Kaplan-Meier curve in R (ggsurvplot function in the survminer package, Kassambara 2023). A Cox proportional hazard model (Cox 1972) was used to quantify differential survival between diseased, neighbor, and healthy tissue samples (coxme function in the coxme package, Therneau, 2024). This model is ideal for our analysis because it allows for censored data, as colonies were photographed on different days throughout the sampling period. Our base model tested the effect of tissue type (disease, neighbor, healthy) on survival, with colony ID as a random effect. We also tried models including fixed effects of colony size, lesion size, and proportion of the colony with disease, which were each measured using TagLab on the earliest set of photos. While thermal stress was undoubtedly a major cause of mortality, neither temperature nor degree heating weeks (DHW) could be included in the model, because, as all colonies were exposed to the same temperatures, both variables perfectly correlated with time. AIC scores (Akaike 1973) indicated that the base model was the most parsimonious ( Table S2 ). Color image analysis was performed on whole-colony segmentation in Python 3.10.8. Images and colony segmentation masks generated in TagLab were read and processed (imread and connectedComponentsWithStats functions in the OpenCV package, Bradski and Kaehler 2000). To account for any lighting differences, the images were color normalized to the black and white tile by setting the mean of the 5% darkest and lightest pixels as reference values and applying a linear stretch to the mosaic image. Pixel values were extracted for each colony (array operations in the NumPy package, Harris et al. 2020), and median red, green, blue (RGB) and grayscale pixel values were calculated per colony (grayscale derived using the cvtColor function in the Open CV package, Bradski and Kaehler 2000). We analyzed the relationship between median color values and DHW, calculated from NOAA Coral Reef Watch satellite sea surface temperature data for Horseshoe (NOAA Coral Reef Watch 2019). We used linear mixed-effects models with DHW as a fixed effect and colony identity as a random effect, as colonies were measured at multiple, but not all, time points (lmer function in the lme4 package, Bates et al. 2015). Degrees of freedom for fixed effects were estimated using Satterthwaite’s approximation (anova function in the lmerTest package, Kuznetsova et al. 2017). Marginal and conditional R 2 values were calculated for each linear regression (r.squaredGLMM function in the MuMIn package, Bartoń, 2025). Reef Structure Reef structural data were collected only for natural (not out-planted) colonies at Horseshoe, Elbow, Sombrero, and Looe in August of 2025. All colonies were measured at Horseshoe, Sombrero, and Looe. However, at Elbow, because natural colonies were more numerous, colonies were measured in the order found by divers swimming haphazardly across the reef on a 1h 20 minute dive. Coral colony, reef crest or spur, and sand channel depths were taken by dive watch (Garmin Descent G2), and adjusted for tide height to mean lower low water. We measured the distance to the shelf edge in all cardinal directions and the distance to the nearest edge (in any direction) to a maximum distance of 15 m. Spur height was calculated as the difference between the sand channel depth and the spur depth. We tested the difference in coral survival by site using Fisher’s exact test (fisher.test in base R). To determine how each reef structure metric affects the probability of coral survival, we used generalized linear models (GLMs) with a logit link function, to model the binary outcome of survival using the glm function in base R. We did not include reef in these models, as we aimed to determine if, despite reef-level effects, any of these structural metrics influenced survival. We used Kruskal Wallis tests (kruskal.test function in base R) with Dunn’s multiple comparison and Bonferroni adjustment (dunn.Test function in the FSA package, Ogle et al. 2025) to determine how each structural metric differed by reef. Furthermore, we determine how corals were situated relative to reef edges in each cardinal direction. We used the Mann-Whitney U test (wilcox.test in base R) and rank biserial correlation coefficient (wilcox_effsize function in the rstatix package, Kassambara 2023) to determine the difference in distances between living and dead colonies. Results A. Diseased and neighboring tissue dies faster than healthy tissue We found that, compared to initially healthy tissue on the same colony, disease lesions and neighboring tissue had a 3.8 times and 1.5 times higher risk of death, respectively ( Fig. 3 ). The base model with no additional covariates performed best, but all additive models have very similar coefficients. All covariates added to the model had hazard ratio effects of nearly one, thus while many were significant, they did not affect the ecological outcome in any substantial way ( Table S1 ). The data also show that for the healthy coral tissue, the survival probability did not decrease until 12 days after our measurements began, while diseased tissue survival probabilities declined after only four days. B. Bleaching as a color spectrum Increased thermal stress was strongly correlated with increasing color value for all color channels as well as gray ( Fig. 4 ). For the red color channel, for every unit increase in DHW, color increased by 19 units (F 1,142 = 446.7, p < 0.001; R 2 m = 0.64, R 2 c = 0.73). For the green color channel, color increased by 23 units for every unit increase in DHW (F 1,145 = 626.47, p<0.001; R 2 m = 0.74, R 2 c = 0.77). The blue color channel values increased the most with higher thermal stress: for each unit increase in DHW there was an associated 32-unit color value increase (F 1,196 = 575.91, p<0.001). We found no detectable colony-level variation in the blue channel model, thus the marginal and conditional R 2 were equal (R 2 m = R 2 c = 0.75). We saw a similar change in grayscale intensity as we did with the green color channel; gray increased by 22.7 units for each unit increase in DHW (F 1,144 = 703.13, p < 0.001; R 2 m = 0.75, R 2 c = 0.80). C. Reef structure and coral survival Coral survival significantly differed between reefs, (Fisher’s exact test, p <0.001, Fig. 1 ). Of the colonies we surveyed, all A. palmata died at Horseshoe and Looe, while 50% survived at Sombrero and 77% survived at Elbow ( Fig. 1 ). We wanted to determine if any reef structural metrics contributed to the survival patterns we found. However, given these high site-level effects, site masks the potential importance of reef structure on coral survival. Given the unbalanced design, where corals per reef ranged from 2 (Sombrero) to 13 (Elbow), we could not include site as a random effect in our models. When we dropped site from the models, we found proximity to the reef edge was a strong predictor of survival, with each meter farther from the reef edge decreasing survival odds by 42.6% (β = -0.55 ± 0.25 SE, z = -2.21, p = 0.027). While colony depth was also strongly associated with site (χ²(3) = 24.40, p 0.05). Similarly, reef spur height and sand channel depth did not show strong patterns with coral survival (spur height: β = -0.08 ± 0.53 SE, z = -0.14, p >0.05; sand channel depth: β = -0.12 ± 0.38 SE, z = -0.32, p >0.05) ( Fig. 5 ). When investigating if directionality of the reef edge affected survival, we found that surviving corals were significantly closer to the reef edges in both the northern and southern directions (North: W= 38, p= 0.004, r(rb) = 0.530; South: W= 174, p= 0.003, r(rb)= 0.552). Surviving colonies had median distances of 2.94 m and 3.57 m, while those that did not survive were located at median distances of 12.6 m and 14.6 m from the northern and southern edges, respectively. However, proximity to the edge did not differ in the eastern or western directions (East: W= 76, p=0.225, r(rb)= 0.225; West: W= 122, p= 0.456, r(rb)= 0.140; Fig. 6 ). Discussion Coral reefs are complex, yet fragile ecosystems. Across one reef system, multiple stressors such as climate change and disease act in concert, affecting coral survival. The synergistic interactions between these threats is especially important to coral conservation. We studied tissue-level survival of A. palmata colonies and color change with increasing thermal stress at Horseshoe, and how reef structure correlated with survival of natural colonies at four reefs across the FRT. Disease: Disease is an accelerant of mortality due to acute thermal stress. We found both the diseased tissues as well as neighboring tissues had an increased hazard and died sooner than the healthy tissue samples ( Fig. 3 ). This stressor acts on the scale of centimeters, causing some tissue on a given colony to be at higher risk than others. While all colonies at Horseshoe ultimately succumbed to the high thermal stress, we predict that in less extreme thermal events, there would be differential mortality between healthy and diseased colonies, with fewer healthy colonies dying from the heat. Disease lesions were quickly colonized by turf algae, which was visible starting on July 22nd, 2023 at 5 DHW ( Fig. 2, Fig. S1) . Patterson et al. (2002) also found rapid colonization of turf algae after tissue death from WPX. We suspect turf algae became visible four or five days after the coral tissue died, as biomass was measurable with seven days of growth (McClanahan et al. 2007). The edges of the lesions did not remain distinct from the surrounding bleaching tissue, thus we were unable to measure if the lesions grew in size with increased thermal stress. However, by repeatedly monitoring the fate of the surrounding tissue, we discerned the increased hazard to this initially healthy tissue neighboring the WPX lesions. A possible mechanism for this accelerated mortality is that the neighboring tissue is damaged by the disease. Disease causes tissue and surface microbiome changes prior to the onset of visual symptoms (Rosales et al. 2023). Microbiome inoculation increases the metabolic rate of the tissue, with the increased expression for immune, wound healing, and fatty acid metabolism genes (Young et al. 2023). Heat stress also increases metabolism, destabilizes the nitrogen and carbon fluxes between the coral host and its algal symbionts, further reducing carbon availability to the stressed coral (Rädecker et al. 2021). Bleaching from heat stress also leads to release of reactive oxygen species and other cytotoxic wastes, which, if accumulated, further damage the tissue (Lesser 1997). These cellular mechanisms could explain how disease coupled with high heat exposure leads to exacerbated tissue damage and mortality. While many studies have documented the population-level combined effects of thermal and disease stressors on corals (Bruno et al. 2007; Muller et al. 2008, 2018; Muller and Woesik 2014), ours is the first to document how acute heat stress coupled with disease alters tissue-level mortality. Color: Symbiodinaceae levels fluctuate seasonally and with bleaching (Fitt et al. 2000), which can be visually monitored through color analysis (Edmunds et al. 2003; Winters et al. 2009). Bleaching is usually a gradual process, thus fine-scale spectral color analyses create a continuous and reproducible numeric metric of bleaching severity. This method is a major improvement over categorical metrics, which are less informative because they are subjective and the category designations are somewhat arbitrary. We applied this concept at the colony level, showing the loss of coral symbiont optical signals throughout the heatwave. Our results indicate that across all color channels and grayscale, bleaching can reliably be measured as a linear change in color as temperature stress accumulates ( Fig. 4) . We can assume full summer-level symbiont density was present at 0 DHWs, which we measured on July 5-8, 2022 ( Fig. S1 ) with baseline (healthy) RGB levels of 137, 90, and 0 respectively ( Fig. 4 ). Because symbiont density changes linearly with color (Winters et al. 2009) , we interpret our RGB color values to indicate that about 30% of symbiont density waslost by July 11th 2023, where the accumulated thermal stress was 2 DHW ( Fig. S1) and the acute thermal anomaly was 2.4ºC (NOAA Coral Reef Watch 2019). The highest benthic temperature recorded during our study period was 33.3ºC, 2.8ºC above the bleaching threshold, recorded on July 12-13, 2023 (Williams and Miller 2015). While this was below the 4ºC predicted by Glynn and D’Croz (1990) to be acutely lethal, the temperatures remained elevated by around 2ºC for much of July ( Fig. S1, Fig. S2 ), which proved deadly for A. palmata . By July 24th, at 5.6 DHW ( Fig. S1 ), RGB values were 244, 221, 150 ( Fig. 4 ), indicating a nearly complete loss of chlorophyll from the tissues. Turf algal overgrowth on dead coral skeletons became detectable through our color analysis at 5.94 DHW on July 25th ( Fig. S1 ), when color values exhibited a slight decrease ( Fig. 4 ). This color level shift occurred only three days after we first observed turf in some colony photos, indicating the utility and precision of this macroscopic optical method. We found the strongest effect of DHW on color for the blue channel, while studies on other species have found other colors to show the strongest effect. Winters et al. (2009) found the red color channel to correlate most strongly with chlorophyll concentration in Stylophora pistillata , whereas Davies et al. (2018) found the summation of all three color channels to correlate most strongly with fluorescence in Siderastrea siderea . Both of these studies were conducted in highly controlled environments, using a light-occluding cone and flash (Winters et al. 2009) or indoors with artificial lights (Davies et al. 2018), which may affect how RGB color reads. Alternatively, there may be species-specific signatures of color loss that affect the color channels differently, as each coral has a different healthy hue. Gray-scale analyses help eliminate this discrepancy, and in our study produced a similar change to the green channel. Chow et al. (2016) also used greyscale, and found strong correlation with bleaching in Goniopora lobata , even in highly turbid water, indicating that color-normalization with in situ color cards may not be necessary for useful monitoring data. Differences in RGB regressions might be due to algal pigmentation or differential wavelength absorption, though the latter does not seem to affect grayscale metrics (Chow et al. 2016). Future studies should refine in situ methods with variable lighting and turbidity across all color channels using multiple coral species to strengthen this technique for monitoring during bleaching and coral restoration. Reef Structure: All A. palmata colonies that survived the heatwave lived within four meters of a reef edge, and most were within one meter of the edge ( Fig. 5 ). While our data reveal a strong correlation between survival and colony position, it is difficult to extrapolate these findings to the entire FRT due to the small number of surviving A. palmata colonies in the region. The benefit to edge location is likely from locally increased water velocity – as water flows onto the reef, its path is constricted as it must go up and over or around the reef spur, increasing in velocity. Lenihan et al. (2008) found this effect on 3 m coral bommies, where the current was 3.3 times faster than on the adjacent seafloor. The corals elevated on bommies experienced reduced bleaching relative to those in the slower moving water (Lenihan et al. 2008). Further, we observed morphological differences that also indicate differential flow rates. The rosettes of reef interior colonies often had thin blade-shaped branches in all cardinal directions, whereas the branches of those on reef edges were often narrower, thicker blades, extending in the plane of the flow, which would help reduce breakage in higher flow regimes (Graus et al. 1977). Reef edge colonies often had more upright branching, which would cause water stagnation in low-flow regimes (Chamberlain and Graus 1975), but would optimize heterotrophy in faster currents. Neither the height of the reef spur itself nor the depth of the sand channel was implicated in coral survival ( Fig. 5 ), indicating that this hypothesized increased current velocity at the edge occurred sufficiently to affect survival regardless of specific reef dimensions. Moreover, we found that surviving colonies were closer to the edge in the North and South directions, but not the East and West ( Fig. 6 ). The differences we observed can be explained by the East-northeast to West-northwest orientation of the reef spurs, whereby the edges are always closer in the north-to-south dimension. Increased water flow could improve coral survival in multiple ways during heat stress. Higher flow rates would deliver more zooplankton to supplement the coral’s carbon resources during thermal stress (Rädecker et al. 2021). Faster currents reduce the boundary layer around the corals, increasing the rate of diffusion (Nakamura and Van Woesik 2001), and removing cytotoxic wastes such as reactive oxygen species (Lesser 1997). Fifer et al. (2021) found Acropora cf. pulchra was able to preventatively upregulate heat-stress-related genes and those related to heterotrophy when in high flow environments, but not in low-flow regimes. These three mechanisms may all contribute to increased survival and recovery from bleaching for corals on reef edges. Faster flow regimes improve A. palmata growth and calcification rates (Gladfelter et al. 1978), suggesting shallow, low-flow backreefs are a suboptimal environment even under non-bleaching conditions. Deeper depth did not appear protective of A. palmata during the 2023 heatwave. A. palmata has a narrow depth distribution of 1-5 m (Lighty et al. 1982), so it does not live at depths where boulder and brain corals survived on the same reefs (Neely et al. 2024). In our study, all surviving colonies were found in 1.6-3.2 m of water, with both deeper and shallower colonies succumbing to the thermal stress ( Fig. 5 ). This finding is likely an artifact of Elbow as the site with most survivors, rather than a protective effect of intermediate depths, as depth was highly associated with reef site ( Fig. S3 ). Other studies have found depth to be protective (Smith et al. 2014; Muir et al. 2017), with as little as an additional two meters of water preventing bleaching (Chung et al. 2024). However, the heatwave in 2023 on the FRT was more severe than that studied by Chung et al. (2024), which could explain why we did not find depth to be protective. Nearly all of the surviving colonies surveyed were located at one reef (Elbow) ( Fig. 1 ), so we cannot account for site-level effects in this study. All the spur and groove reefs (Elbow, Sombrero, and Looe) would have had similar local current features, but the higher temperatures experienced at the Lower Keys reefs likely were too extreme for currents to buffer ( Fig. S1) . Horseshoe also experienced a benthic temperature spike to 33.3ºC on July 12-13, 2023, not recorded by satellite or at the other reefs ( Fig. S2 ), which could be due to stagnation at the patch reef in low wind conditions (Thompson et al. 2025), despite wind velocity being generally consistent across the region (Chapron et al. 2023). The extreme temperature at Horseshoe may have kick-started the acute mortality we observed. Sites may also differ in water quality. Horseshoe likely has higher nitrogen loads than areas farther offshore (Weber et al. 2020), and historically, Looe has suffered from nitrogen loading from the Everglades and Florida Bay (Lapointe et al. 2019). Excess nitrogen causes phosphorus starvation and increases bleaching susceptibility (Wiedenmann et al. 2013). Nutrient loading also increases microbialization, where opportunistic microbial activity can flourish (Haas et al. 2016). Elbow also had the most genetic diversity of the northern FRT, however, genotypes at Horseshoe were also considered resilient (Williams et al. 2024), but they did not persist through the heatwave. With its northern position on the outer reef line, Elbow may be in a prime location to receive eddies spiraling off the already closer-to-shore Florida Current (Smith and Pitts 2002), and thus may intermittently have the best water quality, zooplankton availability, and lowest temperatures of all four reefs we surveyed. Future studies should measure flow rates and water quality parameters at each reef to help determine the causes of increased survival at Elbow, and to assess whether Sombrero, where A. palmata also survived the heatwave, would be an additional promising candidate for successful A. palmata restoration. We advise that restoration efforts outplant to reef edges, and to focus on Elbow and Sombrero, where survivors were found. Based on our findings, Horseshoe and Looe, while common dive tour destinations, should not be the recipient of A. palmata restoration work. However, outplanting on the seaward side of Looe, on reef finger edges, would be interesting to determine if proximity to the reef edge alone is sufficiently protective at a site that otherwise evidenced complete mortality. Horseshoe, on the other hand, is not on the outer reef line, and does not have spur and groove topography with distinct drop-offs to accelerate local current velocity. Despite its status as an Iconic Reef (https://missioniconicreefs.org/), our study suggests that Horseshoe is not a strong candidate for outplant success of A. palmata . Implications: Our data from the 2023 extreme marine heat wave demonstrate that disease accelerates coral tissue death during a bleaching event. The presence of disease increased the risk of death of disease lesions and neighboring tissue by 3.8 times and 1.5 times, respectively, as compared to the risk of death of initially healthy tissue. Our data also show that diseased tissue died at least four days before healthy tissue during this heat stress. We demonstrate that bleaching can be reliably measured as a linear change in color across all color channels and grayscale as temperature stress accumulates. Finally, a coral’s chance for survival is strongly correlated with its proximity to the edge of a reef, with each meter farther from the edge decreasing survival chances by over 42%. We speculate that this higher survival rate on reef margins, relative to reef interiors, is due to faster water flow. These findings are actionable. While individuals and seaside communities have limited ability to reduce global greenhouse gas emissions, we do have the power to reduce water pollution on a local scale. Everything from sewage (Kaczmarsky et al. 2005; Sutherland et al. 2010) and nutrients (Wiedenmann et al. 2013), to plastic pollution (Lamb et al. 2018) have direct links to coral disease and can be mitigated by local coastal zone protection (Kruczynski and McManus 2002). Without disease, the A. palmata on Horseshoe are unlikely to have survived the 2023 heatwave because the temperatures exceeded thermal tolerances for all acroporids (Williams et al. 2017). Unfortunately, there will be many more heatwaves of varying severity in the future (Manzello 2015; Bove et al. 2022; Reimer et al. 2024; Eakin et al. 2026), and mitigating coastal pollution would reduce this co-hazard. Furthermore, our finding that A. palmata survived best near reef edges suggests that outplanting efforts with nursery-grown corals should target reef edges where A. palmata is most likely to survive into the future. Declarations Author Contributions CLN, EKL, and JWP conceived the study. CLN, MEB, and JWP conducted the fieldwork, and CLN, CRM, MEB and SS processed the photographs. CLN performed all analyses and wrote the manuscript, with feedback from AGG, ELK and JWP. All authors read and approved the manuscript as part of the CoralReef3D working group. Acknowledgements The authors would like to thank Steve Campbell and the team at Quiescence Diving Services, Key Largo, FL, for their invaluable local expertise, and safe transit to the reefs in the Upper Keys, and to Captain Hook’s Dive Shop for boat service to Sombrero and Looe Key Reefs. The authors would like to thank Alyssa Quan, Clarissa Hane, Jake McGrew, Kelsey Vaughn, and Nicole Pontzer for their assistance in the field, and Dr. William Fitt for providing fieldwork accommodations. Funding This research was funded by National Science Foundation Grant DBI 2316801 to JWP and National Science Foundation Grant DBI 2316800 to RQ and AGG; the University of Georgia Presidential Fellowship to CLN; the Georgia Museum of Natural History Laerm Award to CLN; and the American Museum of Natural History Lerner-Grey Award in Marine Zoology to CLN. Data Availability All datasets and R and Python scripts for analysis are available at the following URL: https://github.com/cln98332/Coral-mortality-in-a-mass-bleaching-event. Conflict of Interest The authors declare no conflict of interests. References Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov B.N., Csáki F. (eds) 2nd international symposium on information theory. Akadémia Kiadó, Budapest, Hungary, pp 267–281 Alvarez-Filip L, Dulvy NK, Gill JA, Côté IM, Watkinson AR (2009) Flattening of Caribbean coral reefs: region-wide declines in architectural complexity. 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Coral Reefs 31:369–382. https://doi.org/10.1007/s00338-011-0847-y Williams DE, Miller MW (2015) Water temperature data from reef sites off the upper Florida Keys from 2003-09-18 to 2024-12-31 (NCEI Accession 0126994). https://www.ncei.noaa.gov/archive/accession/0126994 Williams DE, Miller MW, Bright AJ, Pausch RE, Valdivia A (2017) Thermal stress exposure, bleaching response, and mortality in the threatened coral Acropora palmata. Mar Pollut Bull 124:189–197. https://doi.org/10.1016/j.marpolbul.2017.07.001 Winters G, Holzman R, Blekhman A, Beer S, Loya Y (2009) Photographic assessment of coral chlorophyll contents: Implications for ecophysiological studies and coral monitoring. J Exp Mar Biol Ecol 380:25–35. https://doi.org/10.1016/j.jembe.2009.09.004 Young BD, Rosales SM, Enochs IC, Kolodziej G, Formel N, Moura A, D’Alonso GL, Traylor-Knowles N (2023) Different disease inoculations cause common responses of the host immune system and prokaryotic component of the microbiome in Acropora palmata. PLOS ONE 18:e0286293. https://doi.org/10.1371/journal.pone.0286293 Zhong J, Li M, Gruen A, Gong J, Li D, Li M, Qin J (2024) Application of Photogrammetric Computer Vision and Deep Learning in High-Resolution Underwater Mapping: A Case Study of Shallow-Water Coral Reefs. ISPRS Ann Photogramm Remote Sens Spat Inf Sci X-2–2024:247–254. https://doi.org/10.5194/isprs-annals-X-2-2024-247-2024 Additional Declarations No competing interests reported. Supplementary Files SupplementalInformationNivisonetal.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers agreed at journal 15 May, 2026 Reviewers agreed at journal 14 May, 2026 Reviewers agreed at journal 13 May, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Submission checks completed at journal 11 Apr, 2026 First submitted to journal 09 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9371933","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":634992860,"identity":"61b62a14-a398-4d9b-ad05-db20d62f5d43","order_by":0,"name":"Camilla L Nivison","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYJCCAw8KgCQzkAGk5CBibAS0JBggtBgTpYUBrAUKEhsIaeFvP50ItMWOwZydx/Dgj4o76RvOL37A8KHsME4tEmdyNwC1JDNYNvMYHOY58yx3w41nBowzzuHWYsAA1sLMYHCYLeEwY9thoJYDBsy8bXi08L8FaakHazn4s+1wusGN4x+Y/+LTIgG25TBQC/OBA0DDEwzO9xgwM+LRInEDbMtxHpAWoF8OG868wVNwsOdcOk4t/P25mz98qKiWMzh/sPnjj4rD8nznj2988KPMGqcWGOBBsjgBHKekAH5SNYyCUTAKRsFwBwBFJGB3RAk5lAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Georgia","correspondingAuthor":true,"prefix":"","firstName":"Camilla","middleName":"L","lastName":"Nivison","suffix":""},{"id":634992861,"identity":"923732d2-3dc1-4b60-b24c-cc3f6855b2f2","order_by":1,"name":"Christa R May","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Christa","middleName":"R","lastName":"May","suffix":""},{"id":634992862,"identity":"eb02567f-135c-4d89-9023-04f91237633b","order_by":2,"name":"Mari Ella Bourbonnais","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Mari","middleName":"Ella","lastName":"Bourbonnais","suffix":""},{"id":634992863,"identity":"52148bb7-c0fb-4228-9a09-5c405447d93b","order_by":3,"name":"Shannon Shotz","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Shannon","middleName":"","lastName":"Shotz","suffix":""},{"id":634992864,"identity":"da5722bf-9a0f-482f-ad47-0b88258b0116","order_by":4,"name":"Isabelle Basden","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Isabelle","middleName":"","lastName":"Basden","suffix":""},{"id":634992865,"identity":"370d2350-aa65-4dd7-8618-0776debe1053","order_by":5,"name":"Deyan Deng","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Deyan","middleName":"","lastName":"Deng","suffix":""},{"id":634992866,"identity":"373a63f0-d0c1-4b2a-95af-4f5d7d25c79d","order_by":6,"name":"Shannon Dixon","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Shannon","middleName":"","lastName":"Dixon","suffix":""},{"id":634992867,"identity":"1afc2220-8496-49e4-a602-0686c8751077","order_by":7,"name":"Debao Huang","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Debao","middleName":"","lastName":"Huang","suffix":""},{"id":634992868,"identity":"fa86e886-277a-4694-a3ff-b46d64df8149","order_by":8,"name":"Ann Marie Hulver","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Ann","middleName":"Marie","lastName":"Hulver","suffix":""},{"id":634992869,"identity":"ca02f071-af94-4e8d-9e95-1403bfc47fee","order_by":9,"name":"Mariam Ayad","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Mariam","middleName":"","lastName":"Ayad","suffix":""},{"id":634992870,"identity":"5d77474d-55b2-4847-8ce3-53b80c026fb1","order_by":10,"name":"Erin K Lipp","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Erin","middleName":"K","lastName":"Lipp","suffix":""},{"id":634992871,"identity":"c9ef9ac6-d2de-43c9-bf3f-50201640b971","order_by":11,"name":"Rongjun Qin","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Rongjun","middleName":"","lastName":"Qin","suffix":""},{"id":634992872,"identity":"ce8ef9c9-bc47-4c70-bfe3-d3036250db24","order_by":12,"name":"Andréa G Grottoli","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Andréa","middleName":"G","lastName":"Grottoli","suffix":""},{"id":634992873,"identity":"92b5e908-7413-44ba-b534-8fa200736a65","order_by":13,"name":"James W Porter","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"W","lastName":"Porter","suffix":""}],"badges":[],"createdAt":"2026-04-09 19:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9371933/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9371933/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108593872,"identity":"2e386883-3d4a-44c0-9d5f-fc2dc9d371b8","added_by":"auto","created_at":"2026-05-06 10:11:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121110,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the Florida Reef Tract, including sampled reefs. Pie charts show the proportion of living (gold) and dead (crimson) \u003cem\u003eAcropora palmata\u003c/em\u003e colonies as of August 12th, 2025 (Elbow, n = 13; Horseshoe, n = 8; Sombrero, n = 2; Looe, n = 7).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/cb221b3a648e2730f86a1cae.png"},{"id":108593945,"identity":"97340df1-46d5-40ad-b080-627f6ac95174","added_by":"auto","created_at":"2026-05-06 10:11:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3982078,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAcropora palmata\u003c/em\u003e colony at Horseshoe Reef, Florida, during the 2023 marine heatwave. Most of the colony is healthy (circle 1, blue) with the disease lesion (circle 2, crimson) visible on July 13, 2023 (A). The colony became paler on July 14, 2023 (B). The diseased area and surrounding tissue are covered by turf algae (circle 3, purple) by July 22, 2023 (C), which continued to grow on July 25, 2023 (D), while more distant tissue is bleached with polyps still intact (circle 4, orange).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/271f5da3e1757b1c177b8d18.png"},{"id":108593871,"identity":"6babab28-f119-4ddd-8d58-e0eb2492e485","added_by":"auto","created_at":"2026-05-06 10:11:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25815,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curve for \u003cem\u003eAcropora palmata\u003c/em\u003etissue samples from disease lesions (1), neighboring (4), and visually healthy (4) tissue samples per colony (n=50). Shading shows 95% confidence intervals. The color band at the bottom shows degree heating weeks.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/3e14cf743ca753457d305abd.png"},{"id":108593854,"identity":"f4f892f2-06ca-4e83-9bfb-2ec786a48360","added_by":"auto","created_at":"2026-05-06 10:11:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55193,"visible":true,"origin":"","legend":"\u003cp\u003eColor channel intensity as a function of degree heating weeks across surveyed dates in July 2022 and 2023. Points show individual colony medians (n=66 colonies), which were measured at multiple but not all time points. Regression lines show the predicted fixed-effects relationships from linear mixed-effects models (median color intensity ~ DHW + (1|colony)) with 95% confidence intervals for (A) red (F\u003csub\u003e1,142\u003c/sub\u003e = 446.7, p \u0026lt; 0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.64, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.73 ), (B) green (F\u003csub\u003e1,145\u003c/sub\u003e = 626.47, p\u0026lt;0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.74, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.77), (C) blue (F\u003csub\u003e1,196\u003c/sub\u003e = 575.91, p\u0026lt;0.001, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.75) color saturations, and (D) grayscale (F\u003csub\u003e1,144\u003c/sub\u003e = 703.13, p \u0026lt; 0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.75, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.80) saturation.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/75105491bf0986af59d5ea71.png"},{"id":108593870,"identity":"93f2041b-299e-4e0a-a279-80df0ee91292","added_by":"auto","created_at":"2026-05-06 10:11:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":161831,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival probability as a function of distance to nearest reef edge (A), reef spur height (B), coral depth (C), and sand channel depth (D) of each colony (n=30) across four reefs (Elbow, Horseshoe, Sombrero, and Looe). Lines show logistic regression with 95% confidence intervals. Distance to reef edge (A) was a strong predictor of coral survival (β = -0.55 ± 0.25 SE, z = -2.21, p = 0.027), while all others were not significant (coral depth: β = -0.02 ± 0.38 SE, z = 0.04, p \u0026gt;0.05; spur height: β = -0.08 ± 0.53 SE, z = -0.14, p \u0026gt;0.05; sand channel depth: β = -0.12 ± 0.38 SE, z = -0.32, p \u0026gt;0.05).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/7180a5f65dd48f9c7c90d984.png"},{"id":108593873,"identity":"9050e196-deb0-4483-b39f-0447364a991a","added_by":"auto","created_at":"2026-05-06 10:11:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":63762,"visible":true,"origin":"","legend":"\u003cp\u003eMean distance to reef edge in each cardinal direction for every colony (n=30) across three reefs (Elbow, Horseshoe, and Looe). Error bars show 95% confidence intervals. Distances were significantly different between living and dead corals in the North and South directions (North: W= 38, p= 0.004, r(rb) = 0.530; South: W= 174, p= 0.003, r(rb)= 0.552), but not in the East and West (East: W= 76, p=0.225, r(rb)= 0.225; West: W= 122, p= 0.456, r(rb)= 0.140).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/fa65989142d2e84f2921020c.png"},{"id":108805630,"identity":"b11da890-5b61-400a-b4ed-7052af8023fd","added_by":"auto","created_at":"2026-05-08 15:26:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4328633,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/15b4cfed-bf0a-45a9-bef1-b42857bedc98.pdf"},{"id":108593869,"identity":"3d95061a-6d60-4bfc-b3ef-bb41b72a4c7a","added_by":"auto","created_at":"2026-05-06 10:11:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":631045,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalInformationNivisonetal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9371933/v1/8851a0a8bfe2d860ca067244.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Coral mortality in a mass bleaching event influenced by proximity to diseased tissue and reef topography","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the summer of 2023, the Florida Keys experienced the most extreme marine heatwave on record, for both temperature and duration (NOAA Coral Reef Watch 2019). It caused mass coral bleaching throughout the Florida Reef Tract (FRT) (Neely et al. 2024; Ayad et al. 2025). This heatwave caused the ninth mass bleaching event on the FRT, the first of which occurred in 1987 (Manzello 2015; Manzello et al. 2025). However, 2023 was the most detrimental, exposing corals to up to four times greater prolonged thermal stress than any prior heatwave (Manzello et al. 2025).\u003c/p\u003e\n\u003cp\u003eBleaching occurs when stressed corals expel their mutualistic endosymbiotic algae, \u003cem\u003eSymbiodiniaceae\u003c/em\u003e. While not imminently fatal (Suggett and Smith 2011), bleached corals are deprived of photosynthetically derived nutrition from their \u003cem\u003eSymbiodiniaceae\u003c/em\u003e, putting them in severe energy deficit and at risk of death if they are not recolonized. Bleaching can be measured optically, as reflectance in red, green, and blue (RGB) channels shifts in synchrony with symbiont density (Edmunds et al. 2003). While prolonged thermal stress is usually the cause of mortality from bleaching, extreme high temperatures (4-5 ºC above the historical maximum monthly mean) can induce mortality in as little as 4 days (Glynn and D’Croz 1990). If current warming trends continue, the Caribbean will experience an additional temperature increase of 1.5ºC above the baseline by 2100, with progressively more frequent marine heatwaves (Bove et al. 2022) likely to exceed the 31ºC bleaching threshold annually (Manzello 2015). Coupled with hurricanes and disease, these stressors have, and will continue to, decimate the Caribbean coral reefs (Aronson and Precht 2001; Williams and Miller 2012).\u003c/p\u003e\n\u003cp\u003eCoral reefs are regularly exposed to multiple stressors including thermal stress, disease, hurricanes, increased nutrient loads, and poor water quality (e.g. Porter et al. 1999, Hughes et al. 2017). These stressors can have compounding effects: limited metabolic resources due to bleaching (Goreau and Macfarlane 1990; Rädecker et al. 2021) diminishes the coral’s ability to combat other stressors, resulting in reduced survivorship and slower population recovery (Glynn 1996). Hurricanes coupled with disease and reduced herbivory on the FRT have reduced coral cover throughout the 1980’s and 1990’s (Dustan and Halas 1987; Porter and Meier 1992; Ruzicka et al. 2013), flattening the reefs (Alvarez-Filip et al. 2009) and preventing regrowth (Hughes and Tanner 2000; Doropoulos et al. 2017). The simultaneous impacts of thermal and other stressors show synergistic outcomes, whereby bleaching recovery is dampened by the effects of other stressors such as nitrogen loading (Lapointe et al. 2019; Donovan et al. 2020) and sedimentation (Bessell-Browne et al. 2017). Corals activate a uniform response against most major threats, rather than targeted responses to individual stressors (Dixon et al. 2020), which may contribute to the challenges of coping with multiple stressors simultaneously. Disease also shows confounding effects with high temperatures and bleaching: thermal stress reduces disease resistance (Bruno et al. 2007), with no fitness tradeoff between traits \u0026nbsp;(Bruno et al. 2007; Muller et al. 2018). This increase in disease susceptibility could be due to an increase in pathogen growth rates or pathogen load (Haas et al. 2016), or to disrupted coral microbiomes from the increase in temperature (Sparagon et al. 2024). Either mechanism could help explain why disease prevalence is highly correlated with thermal anomalies (Ruiz-Moreno et al. 2012; Randall and van Woesik 2015), and will continue to be an increasing threat as temperatures rise.\u003c/p\u003e\n\u003cp\u003eThe combination of disease and temperature has severely impacted \u003cem\u003eAcropora palmata –\u0026nbsp;\u003c/em\u003ea \u0026nbsp;once prominent member of the FRT shallow reef community (Ruzicka et al. 2013; Sutherland et al. 2016) – now declared functionally extinct in the region (Manzello et al. 2025). Historically, \u003cem\u003eA. palmata\u003c/em\u003e formed large stands on shallow patch reefs and fore-reef slopes, growing quickly, and providing ample reef structure (Gladfelter et al. 1978). With the onslaught of heatwaves, disease, and hurricanes, much of these former iconic stands have been demolished. Williams and Miller (2012) recorded more than 50% of \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003ecolonies were lost between 2004 and 2010, resulting in a major loss of reef topography (Alvarez-Filip et al. 2009). The heatwave in the summer of 2023 exterminated most remaining colonies (Neely et al. 2024; Manzello et al. 2025), though some natural colonies still persist on Elbow Reef in the northern FRT. This oasis of survivors could be due to physical microhabitat features that reduce the severity of bleaching damage such as locally accelerated flow rates, reduced sedimentation and nutrient loading, variations in turbidity, and/or pelagic microbial community composition (Nakamura and Van Woesik 2001; Lenihan et al. 2008; Haas et al. 2016).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnique to \u003cem\u003eA. palmata\u003c/em\u003e, white pox disease (WPX) is visually characterized by irregularly shaped white patches as the underlying skeleton becomes visible, while the surrounding tissue appears to be healthy (Patterson et al. 2002). WPX is a bacterial dysbiosis, sometimes caused by \u003cem\u003eSerratia marcescens\u0026nbsp;\u003c/em\u003e(Patterson et al. 2002), a human enteric bacterium that could arrive at the reef with sewage runoff (Sutherland et al. 2010). While previously highly lethal, WPX has subsided into being a persistent, but less threatening stressor (Sutherland et al. 2016). There are conflicting data on whether or not high temperatures exacerbate disease outbreaks (Muller and Woesik 2014; Sutherland et al. 2023). At the microbial level, increased temperatures can increase pathogenic microbial activity (Frydenborg et al. 2014; Garren et al. 2016), and may make disease-impacted tissue more susceptible to thermal stress. To our knowledge, no studies have directly quantified how disease and bleaching interact at the tissue level during a heatwave.\u003c/p\u003e\n\u003cp\u003eIn our study, we investigated factors affecting the rapid \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003ebleaching and mortality on reefs across the FRT during the summer heatwave of 2023. At Horseshoe Reef, in the Upper Keys, we investigated the possible interaction between bleaching and WPX, comparing tissue-level mortality rates between initially healthy, diseased, and healthy tissue neighboring disease lesions (hereafter, neighbor) to determine if disease increases the rate of tissue mortality during thermal stress. At the colony level, also at Horseshoe, we characterized how these coral colonies lost their color with increasing short-term thermal stress. At the landscape level, we investigated factors leading to the survival of some \u003cem\u003eA. palmata\u003c/em\u003e colonies on the FRT, while most had perished by Fall 2023. We examined whether depth or location on the reef correlated with differential survival. Data from this study will help identify how disease may influence bleaching survival outcomes, and other reef conditions that lead to survival\u003cem\u003e.\u003c/em\u003e As \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003eis an International Union for Conservation of Nature (IUCN)-listed critically endangered species, understanding the underlying drivers of mortality are critical to optimizing intervention strategies for this species.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eSite Descriptions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHorseshoe Reef(25.139736\u0026ordm;N, -80.294314\u0026ordm; W) is a shallow patch reef located about 5 miles off the coast of Key Largo. The reef crest, where \u003cem\u003eA. palmata\u003c/em\u003e lived, is about 2 m deep, while the adjacent sandy seafloor is 5-6 m deep. Elbow Reef (25.142942\u0026ordm;N, -80.257936\u0026ordm;W), is a spur and groove reef on the outer reef line, approximately two miles farther offshore from Horseshoe. Elbow was the only reef in the FRT with substantial \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003esurvival after 2023. Depths ranged from 3-4 m on the reef crest to 5 m in the sand channels between the reef spurs. Farther south, Sombrero Reef (24.6277289\u0026ordm; N, -81.110824\u0026ordm; W) and Looe Key Reef (24.5489189\u0026ordm; N, -81.4060307\u0026ordm; W) are both spur and groove reefs on the outer reef line. Depths at Sombrero range from 3-4 m on the reef crest and 7-8 in the sand channels, with the seafloor slowly dropping deeper to the southeast. Looe has a shallower, patchy inner reef, with spur and grooves at 4-5 m and 8 m depths, respectively, on the ocean-facing (southwest) front (\u003cstrong\u003eFig. 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImage Collection and Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCoral imagery of \u003cem\u003eA. palmata\u003c/em\u003e was taken on Horseshoe using dually-mounted, downward-facing GoPro Hero 10 cameras. Images were taken either by video (30 frames per second) (July 5-15, 2022) or one-second intervalometer (July 11-25, 2023) of four 25 m\u003csup\u003e2\u003c/sup\u003e plots selected for their high cover of \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003e(all restored populations) (\u003cstrong\u003eTable S1)\u003c/strong\u003e. Cameras were set to auto exposure in linear mode. A diver swam the cameras back and forth in a lawnmower pattern 1.0 to 1.5 m above the coral, taking approximately 500 overlapping images per plot. Black and white ground control tiles and scale bars were\u0026nbsp;placed on the reef for photogrammetry analysis (Ferrari et al. 2021; Zhong et al. 2024).\u003c/p\u003e\n\u003cp\u003eIndividual frames (every 30th frame) were captured from the video transects. We used Agisoft Metashape Professional (Agisoft, 2025) to create mosaic images of each coral plot for each day it was photographed (\u003cstrong\u003eTable S1\u003c/strong\u003e). The ground control tiles and scale bars were used to scale the mosaics and their associated digital elevation models. White balance was adjusted in Adobe Photoshop. We used TagLab (Pavoni et al. 2022, 2024) to segment 66 individual coral colonies and their disease lesions (if applicable, July 2022 and July 11-14 2023 only). These colonies were selected because they were well resolved with visible edges across all time points. In TagLab, we generated segmentation masks and calculated 3D surface area for each colony and lesion.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTissue-level survival was tracked in 50 colonies during July 2023. On each colony, 7 cm\u003csup\u003e2\u003c/sup\u003e tissue samples were identified in photographs from one disease lesion, four neighbor regions, and four regions haphazardly selected to be on visually healthy tissue and far from any disease lesion, and visually tracked in Python with Napari (Chiu et al. 2022). For our survival model, tissue samples were noted as surviving until turf algae was visible (in very sharp photos) or that the color had turned from white to off-white/brown during the sampling period, as recolonization by \u003cem\u003eSymbiodinaceae\u0026nbsp;\u003c/em\u003ewhile temperatures were elevated was deemed impossible (\u003cstrong\u003eFig. 2\u003c/strong\u003e). Survival of each tissue type was visualized with a Kaplan-Meier curve in R (ggsurvplot function in the survminer package, Kassambara 2023). A Cox proportional hazard model (Cox 1972) was used to quantify differential survival between diseased, neighbor, and healthy tissue samples (coxme function in the coxme package, Therneau, 2024). This model is ideal for our analysis because it allows for censored data, as colonies were photographed on different days throughout the sampling period. Our base model tested the effect of tissue type (disease, neighbor, healthy) on survival, with colony ID as a random effect. We also tried models including fixed effects of colony size, lesion size, and proportion of the colony with disease, which were each measured using TagLab on the earliest set of photos. While thermal stress was undoubtedly a major cause of mortality, neither temperature nor degree heating weeks (DHW) could be included in the model, because, as all colonies were exposed to the same temperatures, both variables perfectly correlated with time. AIC scores (Akaike 1973) indicated that the base model was the most parsimonious (\u003cstrong\u003eTable S2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eColor image analysis was performed on whole-colony segmentation in Python 3.10.8. Images and colony segmentation masks generated in TagLab were read and processed (imread and connectedComponentsWithStats functions in the OpenCV package, Bradski and Kaehler 2000). To account for any lighting differences, the images were color normalized to the black and white tile by setting the mean of the 5% darkest and lightest pixels as reference values and applying a linear stretch to the mosaic image. Pixel values were extracted for each colony (array operations in the NumPy package, Harris et al. 2020), and median red, green, blue (RGB) and grayscale pixel values were calculated per colony (grayscale derived using the cvtColor function in the Open CV package, Bradski and Kaehler 2000). We analyzed the relationship between median color values and DHW, calculated from NOAA Coral Reef Watch satellite sea surface temperature data for Horseshoe (NOAA Coral Reef Watch 2019). We used linear mixed-effects models with DHW as a fixed effect and colony identity as a random effect, as colonies were measured at multiple, but not all, time points (lmer function in the lme4 package, Bates et al. 2015). Degrees of freedom for fixed effects were estimated using Satterthwaite\u0026rsquo;s approximation (anova function in the lmerTest package, Kuznetsova et al. 2017). Marginal and conditional R\u003csup\u003e2\u003c/sup\u003e values were calculated for each linear regression (r.squaredGLMM function in the MuMIn package, Bartoń, 2025).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eReef Structure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eReef structural data were collected only for natural (not out-planted) colonies at Horseshoe, Elbow, Sombrero, and Looe in August of 2025. All colonies were measured at Horseshoe, Sombrero, and Looe. However, at Elbow, because natural colonies were more numerous, colonies were measured in the order found by divers swimming haphazardly across the reef on a 1h 20 minute dive. Coral colony, reef crest or spur, and sand channel depths were taken by dive watch (Garmin Descent G2), and adjusted for tide height to mean lower low water. We measured the distance to the shelf edge in all cardinal directions and the distance to the nearest edge (in any direction) to a maximum distance of 15 m. Spur height was calculated as the difference between the sand channel depth and the spur depth.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe tested the difference in coral survival by site using Fisher\u0026rsquo;s exact test (fisher.test in base R). To determine how each reef structure metric affects the probability of coral survival, we used generalized linear models (GLMs) with a logit link function, to model the binary outcome of survival using the glm function in base R. We did not include reef in these models, as we aimed to determine if, despite reef-level effects, any of these structural metrics influenced survival. We used Kruskal Wallis tests (kruskal.test function in base R) with Dunn\u0026rsquo;s multiple comparison and Bonferroni adjustment (dunn.Test function in the FSA package, Ogle et al. 2025) to determine how each structural metric differed by reef. Furthermore, we determine how corals were situated relative to reef edges in each cardinal direction. We used the Mann-Whitney U test (wilcox.test in base R) and rank biserial correlation coefficient (wilcox_effsize function in the rstatix package, Kassambara 2023) to determine the difference in distances between living and dead colonies. \u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA. \u003cu\u003eDiseased and neighboring tissue dies faster than healthy tissue\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe found that, compared to initially healthy tissue on the same colony, disease lesions and neighboring tissue had a 3.8 times and 1.5 times higher risk of death, respectively (\u003cstrong\u003eFig. 3\u003c/strong\u003e). The base model with no additional covariates performed best, but all additive models have very similar coefficients. All covariates added to the model had hazard ratio effects of nearly one, thus while many were significant, they did not affect the ecological outcome in any substantial way (\u003cstrong\u003eTable S1\u003c/strong\u003e). \u0026nbsp;The data also show that for the healthy coral tissue, the survival probability did not decrease until 12 days after our measurements began, while diseased tissue survival probabilities declined after only four days.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eB. \u003cu\u003eBleaching as a color spectrum\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIncreased thermal stress was strongly correlated with increasing color value for all color channels as well as gray (\u003cstrong\u003eFig. 4\u003c/strong\u003e). For the red color channel, for every unit increase in DHW, color increased by 19 units (F\u003csub\u003e1,142\u003c/sub\u003e = 446.7, p \u0026lt; 0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.64, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.73). For the green color channel, color increased by 23 units for every unit increase in DHW (F\u003csub\u003e1,145\u003c/sub\u003e = 626.47, p\u0026lt;0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.74, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.77). The blue color channel values increased the most with higher thermal stress: for each unit increase in DHW there was an associated 32-unit color value increase (F\u003csub\u003e1,196\u003c/sub\u003e = 575.91, p\u0026lt;0.001). We found no detectable colony-level variation in the blue channel model, thus the marginal and conditional R\u003csup\u003e2\u003c/sup\u003e were equal (R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.75). We saw a similar change in grayscale intensity as we did with the green color channel; gray increased by 22.7 units for each unit increase in DHW (F\u003csub\u003e1,144\u003c/sub\u003e = 703.13, p \u0026lt; 0.001; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e = 0.75, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ec\u003c/sub\u003e = 0.80).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eC. \u003cu\u003eReef structure and coral survival\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCoral survival significantly differed between reefs, (Fisher\u0026rsquo;s exact test, p \u0026lt;0.001, \u003cstrong\u003eFig. 1\u003c/strong\u003e). Of the colonies we surveyed, all \u003cem\u003eA. palmata\u003c/em\u003e died at Horseshoe and Looe, while 50% survived at Sombrero and 77% survived at Elbow (\u003cstrong\u003eFig. 1\u003c/strong\u003e). We wanted to determine if any reef structural metrics contributed to the survival patterns we found. However, given these high site-level effects, site masks the potential importance of reef structure on coral survival. Given the unbalanced design, where corals per reef ranged from 2 (Sombrero) to 13 (Elbow), we could not include site as a random effect in our models. When we dropped site from the models, we found proximity to the reef edge was a strong predictor of survival, with each meter farther from the reef edge decreasing survival odds by 42.6% (\u0026beta; = -0.55 \u0026plusmn; 0.25 SE, z = -2.21, p = 0.027). While colony depth was also strongly associated with site (\u0026chi;\u0026sup2;(3) = 24.40, p \u0026lt; 0.001, \u003cstrong\u003eFig. S3\u003c/strong\u003e), all surviving corals were at an intermediate depth of 1.6-3.2 m, and this metric was not a significant predictor of survival (\u0026beta; = -0.02 \u0026plusmn; 0.38 SE, z = 0.04, p \u0026gt;0.05). Similarly, reef spur height and sand channel depth did not show strong patterns with coral survival (spur height: \u0026beta; = -0.08 \u0026plusmn; 0.53 SE, z = -0.14, p \u0026gt;0.05; sand channel depth: \u0026beta; = -0.12 \u0026plusmn; 0.38 SE, z = -0.32, p \u0026gt;0.05) (\u003cstrong\u003eFig. 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eWhen investigating if directionality of the reef edge affected survival, we found that surviving corals were significantly closer to the reef edges in both the northern and southern directions (North: W= 38, p= 0.004, r(rb) = 0.530; South: W= 174, p= 0.003, r(rb)= 0.552). Surviving colonies had median distances of 2.94 m and 3.57 m, while those that did not survive were located at median distances of 12.6 m and 14.6 m from the northern and southern edges, respectively. However, proximity to the edge did not differ in the eastern or western directions (East: W= 76, p=0.225, r(rb)= 0.225; West: W= 122, p= 0.456, r(rb)= 0.140; \u003cstrong\u003eFig. 6\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCoral reefs are complex, yet fragile ecosystems. Across one reef system, multiple stressors such as climate change and disease act in concert, affecting coral survival. The synergistic interactions between these threats is especially important to coral conservation. We studied tissue-level survival of \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003ecolonies and color change with increasing thermal stress at Horseshoe, and how reef structure correlated with survival of natural colonies at four reefs across the FRT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eDisease:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eDisease is an accelerant of mortality due to acute thermal stress. We found both the diseased tissues as well as neighboring tissues had an increased hazard and died sooner than the healthy tissue samples (\u003cstrong\u003eFig.\u003c/strong\u003e \u003cstrong\u003e3\u003c/strong\u003e). This stressor acts on the scale of centimeters, causing some tissue on a given colony to be at higher risk than others. While all colonies at Horseshoe ultimately succumbed to the high thermal stress, we predict that in less extreme thermal events, there would be differential mortality between healthy and diseased colonies, with fewer healthy colonies dying from the heat. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDisease lesions were quickly colonized by turf algae, which was visible starting on July 22nd, 2023 at 5 DHW (\u003cstrong\u003eFig. 2, Fig. S1)\u003c/strong\u003e. Patterson et al. (2002) also found rapid colonization of turf algae after tissue death from WPX. We suspect turf algae became visible four or five days after the coral tissue died, as biomass was measurable with\u0026nbsp;seven days of growth (McClanahan et al. 2007). The edges of the lesions did not remain distinct from the surrounding bleaching tissue, thus we were unable to measure if the lesions grew in size with increased thermal stress. However, by repeatedly monitoring the fate of the surrounding tissue, we discerned the increased hazard to this initially healthy tissue neighboring the WPX lesions. A possible mechanism for this accelerated mortality is that the neighboring tissue is damaged by the disease. Disease causes tissue and surface microbiome changes prior to the onset of visual symptoms (Rosales et al. 2023). Microbiome inoculation increases the metabolic rate of the tissue, with the increased expression for immune, wound healing, and fatty acid metabolism genes (Young et al. 2023). Heat stress also increases metabolism, destabilizes the nitrogen and carbon fluxes between the coral host and its algal symbionts, further reducing carbon availability to the stressed coral (R\u0026auml;decker et al. 2021). Bleaching from heat stress also leads to release of reactive oxygen species and other cytotoxic wastes, which, if accumulated, further damage the tissue (Lesser 1997). These cellular mechanisms could explain how disease coupled with high heat exposure leads to exacerbated tissue damage and mortality. While many studies have documented the population-level combined effects of thermal and disease stressors on corals (Bruno et al. 2007; Muller et al. 2008, 2018; Muller and Woesik 2014), ours is the first to document how acute heat stress coupled with disease alters tissue-level mortality.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eColor:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSymbiodinaceae\u0026nbsp;\u003c/em\u003elevels fluctuate seasonally and with bleaching (Fitt et al. 2000), which can be visually monitored through color analysis (Edmunds et al. 2003; Winters et al. 2009). Bleaching is usually a gradual process, thus fine-scale spectral color analyses create a continuous and reproducible numeric metric of bleaching severity. This method is a major improvement over categorical metrics, which are less informative because they are subjective and the category designations are somewhat arbitrary. We applied this concept at the colony level, showing the loss of coral symbiont optical signals throughout the heatwave. Our results indicate that across all color channels and grayscale, bleaching can reliably be measured as a linear change in color as temperature stress accumulates (\u003cstrong\u003eFig. 4)\u003c/strong\u003e. We can assume full summer-level symbiont density was present at 0 DHWs, which we measured on July 5-8, 2022 (\u003cstrong\u003eFig. S1\u003c/strong\u003e) with baseline (healthy) RGB levels of 137, 90, and 0 respectively (\u003cstrong\u003eFig. 4\u003c/strong\u003e). Because symbiont density changes linearly with color (Winters et al. 2009)\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003ewe interpret our RGB color values to indicate that about 30% of symbiont density waslost by July 11th 2023, where the accumulated thermal stress was 2 DHW (\u003cstrong\u003eFig. S1)\u003c/strong\u003e and the acute thermal anomaly was 2.4\u0026ordm;C (NOAA Coral Reef Watch 2019). The highest benthic temperature recorded during our study period was 33.3\u0026ordm;C, 2.8\u0026ordm;C above the bleaching threshold, recorded on July 12-13, 2023 (Williams and Miller 2015). While this was below the 4\u0026ordm;C predicted by Glynn and D\u0026rsquo;Croz (1990) to be acutely lethal, the temperatures remained elevated by around 2\u0026ordm;C for much of July (\u003cstrong\u003eFig. S1, Fig. S2\u003c/strong\u003e), which proved deadly for \u003cem\u003eA. palmata\u003c/em\u003e. By July 24th, at 5.6 DHW (\u003cstrong\u003eFig. S1\u003c/strong\u003e), RGB values were 244, 221, 150 (\u003cstrong\u003eFig. 4\u003c/strong\u003e), indicating a nearly complete loss of chlorophyll from the tissues. Turf algal overgrowth on dead coral skeletons became detectable through our color analysis at 5.94 DHW on July 25th (\u003cstrong\u003eFig. S1\u003c/strong\u003e), when color values exhibited a slight decrease (\u003cstrong\u003eFig. 4\u003c/strong\u003e). This color level shift occurred only three days after we first observed turf in some colony photos, indicating the utility and precision of this macroscopic optical method.\u003c/p\u003e\n\u003cp\u003eWe found the strongest effect of DHW on color for the blue channel, while studies on other species have found other colors to show the strongest effect. Winters et al. (2009) found the red color channel to correlate most strongly with chlorophyll concentration in \u003cem\u003eStylophora pistillata\u003c/em\u003e, whereas Davies et al. (2018) found the summation of all three color channels to correlate most strongly with fluorescence in \u003cem\u003eSiderastrea siderea\u003c/em\u003e. Both of these studies were conducted in highly controlled environments, using a light-occluding cone and flash (Winters et al. 2009) or indoors with artificial lights (Davies et al. 2018), which may affect how RGB color reads. Alternatively, there may be species-specific signatures of color loss that affect the color channels differently, as each coral has a different healthy hue. Gray-scale analyses help eliminate this discrepancy, and in our study produced a similar change to the green channel. Chow et al. (2016) also used greyscale, and found strong correlation with bleaching in \u003cem\u003eGoniopora lobata\u003c/em\u003e, even in highly turbid water, indicating that color-normalization with\u003cem\u003e\u0026nbsp;in situ\u003c/em\u003e color cards may not be necessary for useful monitoring data. Differences in RGB regressions might be due to algal pigmentation or differential wavelength absorption, though the latter does not seem to affect grayscale metrics (Chow et al. 2016). Future studies should refine \u003cem\u003ein situ\u003c/em\u003e methods with variable lighting and turbidity across all color channels using multiple coral species to strengthen this technique for monitoring during bleaching and coral restoration.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eReef Structure:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll \u003cem\u003eA. palmata\u003c/em\u003e colonies that survived the heatwave lived within four meters of a reef edge, and most were within one meter of the edge (\u003cstrong\u003eFig. 5\u003c/strong\u003e). While our data reveal a strong correlation between survival and colony position, it is difficult to extrapolate these findings to the entire FRT due to the small number of surviving \u003cem\u003eA. palmata\u003c/em\u003e colonies in the region.\u0026nbsp;The benefit to edge location is likely from locally increased water velocity \u0026ndash; as water flows onto the reef, its path is constricted as it must go up and over or around the reef spur, increasing in velocity. Lenihan et al. (2008) found this effect on 3 m coral bommies, where the current was 3.3 times faster than on the adjacent seafloor. The corals elevated on bommies experienced reduced bleaching relative to those in the slower moving water (Lenihan et al. 2008). Further, we observed morphological differences that also indicate differential flow rates. The rosettes of reef interior colonies often had thin blade-shaped branches in all cardinal directions, whereas the branches of those on reef edges were often narrower, thicker blades, extending in the plane of the flow, which would help reduce breakage in higher flow regimes (Graus et al. 1977). Reef edge colonies often had more upright branching, which would cause water stagnation in low-flow regimes (Chamberlain and Graus 1975), but would optimize heterotrophy in faster currents. Neither the height of the reef spur itself nor the depth of the sand channel was implicated in coral survival (\u003cstrong\u003eFig. 5\u003c/strong\u003e), indicating that this hypothesized increased current velocity at the edge occurred sufficiently to affect survival regardless of specific reef dimensions. Moreover, we found that surviving colonies were closer to the edge in the North and South directions, but not the East and West (\u003cstrong\u003eFig. 6\u003c/strong\u003e). The differences we observed can be explained by the East-northeast to West-northwest orientation of the reef spurs, whereby the edges are always closer in the north-to-south dimension.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIncreased water flow could improve coral survival in multiple ways during heat stress. Higher flow rates would deliver more zooplankton to supplement the coral\u0026rsquo;s carbon resources during thermal stress (R\u0026auml;decker et al. 2021). Faster currents reduce the boundary layer around the corals, increasing the rate of diffusion (Nakamura and Van Woesik 2001), and removing cytotoxic wastes such as reactive oxygen species (Lesser 1997). Fifer et al. (2021) found \u003cem\u003eAcropora cf. pulchra\u003c/em\u003e was able to\u0026nbsp;preventatively upregulate heat-stress-related genes and those related to heterotrophy when in high flow environments, but not in low-flow regimes. These three mechanisms may all contribute to increased survival and recovery from bleaching for corals on reef edges. Faster flow regimes improve \u003cem\u003eA. palmata\u003c/em\u003e growth and calcification rates (Gladfelter et al. 1978), suggesting shallow, low-flow backreefs are a suboptimal environment even under non-bleaching conditions.\u003c/p\u003e\n\u003cp\u003eDeeper depth did not appear protective of \u003cem\u003eA. palmata\u0026nbsp;\u003c/em\u003eduring the 2023 heatwave. \u003cem\u003eA. palmata\u003c/em\u003e has a narrow depth distribution of 1-5 m (Lighty et al. 1982), so it does not live at depths where boulder and brain corals survived on the same reefs (Neely et al. 2024). In our study, all surviving colonies were found in 1.6-3.2 m of water, with both deeper and shallower colonies succumbing to the thermal stress (\u003cstrong\u003eFig. 5\u003c/strong\u003e). This finding is likely an artifact of Elbow as the site with most survivors, rather than a protective effect of intermediate depths, as depth was highly associated with reef site (\u003cstrong\u003eFig. S3\u003c/strong\u003e). Other studies have found depth to be protective (Smith et al. 2014; Muir et al. 2017), with as little as an additional two meters of water preventing bleaching (Chung et al. 2024). However, the heatwave in 2023 on the FRT was more severe than that studied by Chung et al. (2024), which could explain why we did not find depth to be protective.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNearly all of the surviving colonies surveyed were located at one reef (Elbow) (\u003cstrong\u003eFig. 1\u003c/strong\u003e), so we cannot account for site-level effects in this study. All the spur and groove reefs (Elbow, Sombrero, and Looe) would have had similar local current features, but the higher temperatures experienced at the Lower Keys reefs likely were too extreme for currents to buffer (\u003cstrong\u003eFig. S1)\u003c/strong\u003e. Horseshoe also experienced a benthic temperature spike to 33.3\u0026ordm;C on July 12-13, 2023, not recorded by satellite or at the other reefs (\u003cstrong\u003eFig. S2\u003c/strong\u003e), which could be due to stagnation at the patch reef in low wind conditions (Thompson et al. 2025), despite wind velocity being generally consistent across the region (Chapron et al. 2023). The extreme temperature at Horseshoe may have kick-started the acute mortality we observed. Sites may also differ in water quality. Horseshoe likely has higher nitrogen loads than areas farther offshore (Weber et al. 2020), and historically, Looe has suffered from nitrogen loading from the Everglades and Florida Bay (Lapointe et al. 2019). Excess nitrogen causes phosphorus starvation and increases bleaching susceptibility (Wiedenmann et al. 2013). Nutrient loading also increases microbialization, where opportunistic microbial activity can flourish (Haas et al. 2016). Elbow also had the most genetic diversity of the northern FRT, however, genotypes at Horseshoe were also considered resilient (Williams et al. 2024), but they did not persist through the heatwave. With its northern position on the outer reef line, Elbow may be in a prime location to receive eddies spiraling off the already closer-to-shore Florida Current (Smith and Pitts 2002), and thus may intermittently have the best water quality, zooplankton availability, and lowest temperatures of all four reefs we surveyed.\u003c/p\u003e\n\u003cp\u003eFuture studies should measure flow rates and water quality parameters at each reef to help determine the causes of increased survival at Elbow, and to assess whether Sombrero, where \u003cem\u003eA. palmata\u003c/em\u003e also survived the heatwave, would be an additional promising candidate for successful \u003cem\u003eA. palmata\u003c/em\u003e restoration. We advise that restoration efforts outplant to reef edges, and to focus on Elbow and Sombrero, where survivors were found. Based on our findings, Horseshoe and Looe, while common dive tour destinations, should not be the recipient of \u003cem\u003eA. palmata\u003c/em\u003e restoration work. However, outplanting on the seaward side of Looe, on reef finger edges, would be interesting to determine if proximity to the reef edge alone is sufficiently protective at a site that otherwise evidenced complete mortality. Horseshoe, on the other hand, is not on the outer reef line, and does not have spur and groove topography with distinct drop-offs to accelerate local current velocity. Despite its status as an Iconic Reef (https://missioniconicreefs.org/), our study suggests that Horseshoe is not a strong candidate for outplant success of \u003cem\u003eA. palmata\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eImplications:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eOur data from the 2023 extreme marine heat wave demonstrate that disease accelerates coral tissue death during a bleaching event. The presence of disease increased the risk of death of disease lesions and neighboring tissue by 3.8 times and 1.5 times, respectively, as compared to the risk of death of initially healthy tissue. Our data also show that diseased tissue died at least four days before healthy tissue during this heat stress. We demonstrate that bleaching can be reliably measured as a linear change in color across all color channels and grayscale as temperature stress accumulates. Finally, a coral\u0026rsquo;s chance for survival is strongly correlated with its proximity to the edge of a reef, with each meter farther from the edge decreasing survival chances by over 42%. We speculate that this higher survival rate on reef margins, relative to reef interiors, is due to faster water flow.\u003c/p\u003e\n\u003cp\u003eThese findings are actionable. While individuals and seaside communities have limited ability to reduce global greenhouse gas emissions, we do have the power to reduce water pollution on a local scale. Everything from sewage (Kaczmarsky et al. 2005; Sutherland et al. 2010) and nutrients (Wiedenmann et al. 2013), to plastic pollution (Lamb et al. 2018) have direct links to coral disease and can be mitigated by local coastal zone protection (Kruczynski and McManus 2002). Without disease, the \u003cem\u003eA. palmata\u003c/em\u003e on Horseshoe are unlikely to have survived the 2023 heatwave because the temperatures exceeded thermal tolerances for all acroporids (Williams et al. 2017). Unfortunately, there will be many more heatwaves of varying severity in the future (Manzello 2015; Bove et al. 2022; Reimer et al. 2024; Eakin et al. 2026), and mitigating coastal pollution would reduce this co-hazard. Furthermore, our finding that \u003cem\u003eA. palmata\u003c/em\u003e survived best near reef edges suggests that outplanting efforts with nursery-grown corals should target reef edges where\u0026nbsp;\u003cem\u003eA. palmata\u003c/em\u003e is most likely to survive into the future.\u003cbr clear=\"all\"\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCLN, EKL, and JWP conceived the study. CLN, MEB, and JWP conducted the fieldwork, and CLN, CRM, MEB and SS processed the photographs. CLN performed all analyses and wrote the manuscript, with feedback from AGG, ELK and JWP. All authors read and approved the manuscript as part of the CoralReef3D working group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Steve Campbell and the team at Quiescence Diving Services, Key Largo, FL, for their invaluable local expertise, and safe transit to the reefs in the Upper Keys, and to Captain Hook\u0026rsquo;s Dive Shop for boat service to Sombrero and Looe Key Reefs. The authors would like to thank Alyssa Quan, Clarissa Hane, Jake McGrew, Kelsey Vaughn, and Nicole Pontzer for their assistance in the field, and Dr. William Fitt for providing fieldwork accommodations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by National Science Foundation Grant DBI 2316801 to JWP and National Science Foundation Grant DBI 2316800 to RQ and AGG; the University of Georgia Presidential Fellowship to CLN; the Georgia Museum of Natural History Laerm Award to CLN; and the American Museum of Natural History Lerner-Grey Award in Marine Zoology to CLN.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll datasets and R and Python scripts for analysis are available at the following URL: https://github.com/cln98332/Coral-mortality-in-a-mass-bleaching-event.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkaike H (1973) Information theory and an extension of the maximum likelihood principle. 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ISPRS Ann Photogramm Remote Sens Spat Inf Sci X-2\u0026ndash;2024:247\u0026ndash;254. https://doi.org/10.5194/isprs-annals-X-2-2024-247-2024\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"coral-reefs","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"core","sideBox":"Learn more about [Coral Reefs](http://link.springer.com/journal/338)","snPcode":"338","submissionUrl":"https://submission.nature.com/new-submission/338/3","title":"Coral Reefs","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Coral bleaching, white pox disease, multiple stressors, heatwave, Florida Reef Tract, Acropora palmata","lastPublishedDoi":"10.21203/rs.3.rs-9371933/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9371933/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoral reefs of the Florida Keys experienced the hottest summer on record in 2023, causing mass bleaching and mortality of scleractinian corals. Sea surface temperatures remained above 31\u0026ordm;C for 41 days, exceeding all prior records for the region. Branching corals fared especially poorly, especially \u003cem\u003eAcropora palmata\u003c/em\u003e, which has now been deemed functionally extinct across the entire Florida Reef Tract. High temperatures and prolonged thermal stress were the major causes of mortality. Our study investigates additional stressors contributing to coral mortality during the heatwave. Using benthic imagery, we show that during bleaching, coral tissue death is accelerated by proximity to disease. Using a Cox proportional hazard model, we found that, compared to initially healthy tissue on the same colony, disease lesions and neighboring tissue had a 3.8 times and 1.5 times higher risk of death, respectively. We show that these two stressors, working at different spatial scales, acted synergistically to increase mortality. Furthermore, from our \u003cem\u003ein-situ\u003c/em\u003e reef structural measurements, we found that during bleaching, coral survival was greatest along the reef edge. The reef displaces water, resulting in faster local velocity, which we hypothesize reduces the boundary layer at the tissue-water interface and thus simultaneously enhances the removal of cytotoxic metabolic wastes and the opportunity for coral heterotrophic feeding. Our findings reinforce the importance of the interactive effects of disease and reef topography on coral mortality, and suggest that restoration efforts should focus on reef edges where the chance of survival is improved relative to the reef interior.\u003c/p\u003e","manuscriptTitle":"Coral mortality in a mass bleaching event influenced by proximity to diseased tissue and reef topography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 10:10:42","doi":"10.21203/rs.3.rs-9371933/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"298802155655842137159615341442704885444","date":"2026-05-18T17:49:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109959304688707537626322251697280429719","date":"2026-05-15T14:03:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132793970950993912059850720613990517411","date":"2026-05-14T23:46:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183771248086060336404114214237071361288","date":"2026-05-13T22:47:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T07:21:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-14T22:48:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-11T12:28:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Coral Reefs","date":"2026-04-09T18:58:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"coral-reefs","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"core","sideBox":"Learn more about [Coral Reefs](http://link.springer.com/journal/338)","snPcode":"338","submissionUrl":"https://submission.nature.com/new-submission/338/3","title":"Coral Reefs","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2a7d9f0f-ac65-4af4-abfc-7b0c3d505552","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"298802155655842137159615341442704885444","date":"2026-05-18T17:49:53+00:00","index":30,"fulltext":""},{"type":"reviewerAgreed","content":"109959304688707537626322251697280429719","date":"2026-05-15T14:03:50+00:00","index":29,"fulltext":""},{"type":"reviewerAgreed","content":"132793970950993912059850720613990517411","date":"2026-05-14T23:46:08+00:00","index":27,"fulltext":""},{"type":"reviewerAgreed","content":"183771248086060336404114214237071361288","date":"2026-05-13T22:47:16+00:00","index":26,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T10:10:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 10:10:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9371933","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9371933","identity":"rs-9371933","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}