A coral disease outbreak highlights vulnerability of remote high-latitude lagoons to global and local stressors

Charlotte E Page; William Leggat; Suhelen Egan; Tracy D Ainsworth

doi:10.1016/j.isci.2023.106205

. 2023 Feb 19;26(3):106205. doi: 10.1016/j.isci.2023.106205

A coral disease outbreak highlights vulnerability of remote high-latitude lagoons to global and local stressors

Charlotte E Page ^1,^3,^∗, William Leggat ², Suhelen Egan ¹, Tracy D Ainsworth ¹

PMCID: PMC10006636 PMID: 36915696

Summary

Outbreaks of coral disease are often associated with global and local stressors like changes in temperature and poor water quality. A severe coral disease outbreak was recorded in the primary reef-building taxa Montipora spp. in a high-latitude lagoon at Norfolk Island following heat stress and pollution events in 2020. Disease signs suggest the occurrence of a Montiporid White Syndrome with four distinct phases and maximum measured tissue loss of 329 mm⁻² day⁻¹. In December 2020 and April 2021, 60% of the Montipora community were impacted and disease severity increased by 54% over this period. Spatial patterns in prevalence indicate the disease is associated with exposure to poor water quality in addition to size class of coral colonies. High prevalence levels make this event comparable to some of the most severe coral disease outbreaks recorded to date demonstrating the vulnerability of this system to combined impacts of warming and pollution.

Subject areas: environmental science, global change, aquatic science, zoology

Graphical abstract

Highlights

•
A coral disease outbreak was recorded at high-latitude reef, Norfolk Island
•
This follows heat stress and pollution events impacting water quality in 2020
•
The disease is found to be impacting 60% of the surveyed community
•
Probability of disease is related to pollution exposure and colony size

Environmental science; Global change; Aquatic science; Zoology

Introduction

Coral diseases have contributed to the rapid decline of tropical reef systems across the Caribbean and Indo-Pacific.¹^,²^,³^,⁴ Severe disease outbreaks have caused mass mortality of affected taxa leading to the local extinction of populations.⁵^,⁶ White syndromes⁷ represent some of the most severe coral diseases reported to date and are described as tissue loss diseases associated with lesions that progress across coral colonies often with variable etiologies (i.e. initial disease-causing agents⁸). Outcomes of white syndromes for coral colonies vary from complete mortality to partial mortality, reductions in fecundity, shifts in coral-associated microbial communities, and reduced resilience to future disturbances.⁹^,¹⁰^,¹¹^,¹²^,¹³ On seemingly healthy coral reefs the baseline prevalence of disease (i.e. the proportion of the community impacted) is considered to be less than 1%,¹⁴ with disease prevalence above 3% considered above normal and over 5% qualifying as a disease outbreak.¹⁴

Over 40 coral diseases have been described as impacting more than 130 coral species globally,¹⁴^,¹⁵^,¹⁶^,¹⁷ including several reports of coral disease at high-latitude coral reef environments.¹⁸^,¹⁹^,²⁰^,²¹ High-latitude coral communities are exposed to sub-optimal often highly fluctuating environments.²² As climate change impacts continue to affect marine systems, several studies have hypothesised that high-latitude reefs could represent transitional environments providing refuge to tropical species.²³^,²⁴^,²⁵ However, corals in these environments face similar anthropogenic threats to their tropical counterparts including climate change impacts on water temperature and local pressures such as water quality contamination.²⁶^,²⁷^,²⁸ Global and local stressors can act both directly and indirectly on coral function and studies have shown cumulative impacts when multiple environmental stressors are present.²⁹^,³⁰^,³¹ Disease outbreaks have increased in frequency over the last 30 years³² where increases in disease baseline levels are often reported following environmental stress events.⁴^,³³^,³⁴^,³⁵ Environmental stressors related to climate change (i.e. anomalous water temperatures) and reduced water quality are the most common disturbance events associated with coral disease.⁴^,¹⁹^,³⁶^,³⁷^,³⁸^,³⁹ These stressors are hypothesized to lower host resilience,¹⁶^,⁴⁰^,⁴¹^,⁴² introduce disease-causing-agents and benefit growth of opportunistic pathogens.⁴³^,⁴⁴ Coral disease has also been associated with winter-conditions preceding thermal stress events.⁴⁵

Notably, the most prevalent coral disease outbreaks recorded to date have been associated with anomalous warming events and water quality issues. These events include outbreaks of Stony Coral Tissue Loss (SCTL) in the Caribbean and Atramentous Necrosis in the Indo-Pacific, both recorded as affecting >70% of the coral community at the most impacted sites.⁴^,³⁵^,³⁹^,⁴⁶ The first reports of these diseases coincide with summer bleaching events and sedimentation related to dredging and run-off.⁴^,⁴⁷^,⁴⁸ Coral diseases can also show predictable patterns with surrounding ecological communities. For example, positive relationships between host abundance and disease prevalence³⁷ have been reported for multiple diseases and can be related to the transmission mode of the disease-causing agent.⁴⁹^,⁵⁰ Coral traits have also been linked to differential disease risk⁵¹ including colony growth form, color morphs, and colony-size.⁵⁰^,⁵²^,⁵³ The role of these factors in driving dynamics during disease outbreaks is currently understudied, in part due to a scarcity of work where disease and colony-level drivers are measured as disease events progress. Understanding drivers of disease can aid in managing and predicting disease risk at reef sites.

In November 2020 a novel tissue loss disease was observed affecting the primary reef-building taxa (Montipora spp.) in the remote high-latitude coastal lagoon at Norfolk Island. This observation followed several environmental stress events, including thermal stress over the 2020 summer period leading to widespread coral bleaching and pollution from a terrestrial source in the following winter period.⁵⁴ Here we provide the first description of the disease and quantify disease prevalence and severity through the Austral summer of 2020–2021. Historic disease prevalence was also assessed through analysis of citizen collected reef images during the period 2015–2020. We further investigate community and colony variables contributing to disease risk. The results of this study establish the local extent and potential drivers of a tissue loss disease within the Norfolk Island lagoonal reef; thereby building an understanding of how global and local stressors can undermine future coral health in high-latitude reef systems.

Results

Environmental conditions

The maximum monthly mean (MMM) temperature for Norfolk Island is 23.5°C. Coral communities were exposed to winter minimum SST between 18 and 19°C in August before temperatures began to increase in September 2020 (Figure 1D). Over the study period (December 2020-April 2021) SSTs were over 24.5°C (MMM +1°C) for 4 days in January and March 2021, accumulating a maximum of 0.84 DHWs on the 3/3/2021 (Figure 1D). DHWs began to decrease 38 days later on 11/4/21 (Figure 1D). Rainfall was associated with flooding and overflow of a plume of sediments, freshwater, and organic nutrients into the lagoonal reef system on 31/7/20, 17/8/20 and 5/11/20 (Figure 1D) where flooding occurs directly into EB. 3-month total rainfall prior to December 2020 surveys was 215 mm, and 258 mm prior to April 2021 surveys.

Study context

(A) Map of Norfolk Island. Point on the globe shows the position of Norfolk in the South Pacific.

(B) Satellite image of the lagoonal reef system on the south side of the Island. The lagoon is split into two bays, Slaughter Bay and Emily Bay. Red dot marks a creek that over-flows into Emily Bay causing terrestrial-pollution events after high rainfall.

(C) Timeline of data collection in this study.

(D) Plot showing sea surface temperature (SST, gray line), degree heating weeks (DHWs, black line), and daily rainfall (blue line) during the monitoring period and in the 11 months prior to the observation of disease signs within the lagoon. Light and dark red hashed lines represent the maximum monthly mean (MMM) and maximum monthly mean +1°C over which temperature stress is expected to accumulate. Light and dark blue hashed lines represent DHWs of 4 (significant coral bleaching expected) and 8 (severe, widespread bleaching and significant mortality) respectively. Arrows point to significant events over reef prior to disease observation. TP stands for time point when ecological monitoring took place.

Disease signs

Signs of disease were observed in all taxa identified as Montipora spp. (hereafter denoted as Montipora). Disease signs manifested similarly in all taxa across multiple growth forms and color morphs (Figures 2A–2D). These included foliose colonies with plating and column structures (Figures 2B–2F), and encrusting colonies growing on the substrate (Figures 2A and 2C), in addition to both brown and purple color morphs (Figure 2A). Disease signs broadly involved irregular shaped acute and subacute tissue loss patches (i.e. lesions). Colonies had a mean number of 3.6 (±0.4) active disease lesions present in December 2020 and 3.1 (±0.3) in April 2021. The distribution of lesions on colonies was focal and multifocal, and the location was either central or peripheral (Figures 2E–2G). Lesions were found on both vertical plating structures in addition to structures with relief that could potentially collect sediment. Disease signs were clustered into four groupings here referred to as (presumed) phases of disease progression⁴⁶:

•
Phase 1 - an initial area of bleached translucent tissue with indistinct edges (Figure 2H);
•
Phase 2 - white skeleton devoid of tissue, indistinct and distinct edges, and undulating margins (Figure 2I);
•
Phase 3 - marked by lack of skeletal structure and a “smooth” white bacterial film covering the lesion with distinct margins and undulating and smooth edges (Figure 2J);
•
Phase 4 - a distinct black sulphurous smelling deposit that accumulates under the white film giving the lesion a gray appearance. Lesions have distinct margins and undulating and smooth edges (Figure 2K).

Disease signs

(A) Purple color morph encrusting colony of *Montipora* spp. Scale bar represents 20 cm.

(B) Brown color morph foliose colony with plates and pillar structures, *Montipora* spp. Scale bar represents 20 cm.

(C) Brown color morph encrusting colony of *Montipora* spp. Scale bar represents 20 cm.

(D) A large brown color morph of *Montipora* spp. showing plating and pillar structures. Scale bar represents 40 cm.

(E) A foliose colony showing multiple irregular shaped tissue loss lesions on plating structures. Scale bar represents 20 cm.

(F) A foliose colony with a single large irregular shaped tissue loss lesion. Scale bar represents 15 cm.

(G) A foliose colony showing multiple tissue loss lesions present centrally and peripherally on plating structures. Scale bar represents 10 cm.

(H–K) The four described phases of lesion progression identified (see results). Scale bar represents 0.5 cm.

(L) Lesion transition dynamics over 7–11 days (based on time of re-survey).

(M) Change in lesion area (mm⁻² day⁻¹) recorded for surveyed lesions that showed a decrease (i.e. colony tissue recovery, n = 4) or an increase in area (i.e. colony tissue loss, n = 14) over the monitoring period.

(N) Change in lesion area (mm⁻² day⁻¹) recorded for surveyed lesions that showed no progression (n = 9), and progression (n = 9) in phase during the monitoring period. Boxplots upper and lower lines correspond to the first and third quartiles, and whiskers represent the minimum and maximum values. Points represent outliers. Asterisks indicate p < 0.01.

(O) Lesion i shows the lesion with the highest measured tissue recovery (see M). Scale bar represents 0.1 cm.

(P) Lesion ii shows the lesion with the highest rates of area increase (see M). Scale bar represents 0.1 cm.

Other disease signs and overgrowth communities were also observed. These included black microalgal overgrowth which gave lesions a speckled appearance (Figure S2); entrapped sediment (Figures S2B–S2D); other algal overgrowths including other microalgae and in some cases macroalgae taxa (e.g. Laurencia, Figure S2H); black and white bands at the lesion margin (Figures S2D and S2G); red coloration of the skeleton (Figure S2C); and the presence of an unknown epifaunal community identified through the presence of fecal matter on or around areas of tissue loss (Figure S2E).

The size of lesions initially classified as Phase 2 and Phase 3 (n = 18) were recorded as increasing and decreasing in area (i.e. coral tissue was lost, and gained) over the 9 to 11 days monitoring period in December 2020. Lesions also showed progression between discrete disease phases over this time. At the beginning of the monitoring period, 11 lesions were categorized as Phase 2, and 7 as Phase 3. At the end of the monitoring period, 5 lesions initially categorized as Phase 2 progressed to Phase 3, and 6 lesions did not change phase, remaining at the Phase 2 stage (Figure 2L). Of the monitored lesions initially classified as Phase 3, 3 lesions progressed to Phase 4 and 4 lesions did not change phase, remaining at the Phase 3 stage (Figure 2L). Lesions measured as causing tissue loss, increasing in size over the monitoring period did so at a mean rate of 73 ± 25 mm⁻² day⁻¹ (Figure 2M). Lesions measured as decreasing in size over the monitoring period did so at a mean rate of 22 ± 13 mm⁻² day⁻¹ (Figure 2M). Lesions that decreased in size showed tissue recovery at lesion edges. The maximum recorded increase in lesion area was 329 mm⁻² day⁻¹, representing a 44% increase in lesion size over a period of 9 days (Figures 2M and 2P see point ii). The maximum recorded decrease in lesion area was 60 mm⁻² day⁻¹, representing a 30% reduction in size over a period of 9 days (Figures 3M and 3O see point i). There was no difference in lesion area change between lesions initially categorized as Phase 2 and Phase 3 (H₍₁₎ = 0.1, p = 0.75) (Figure S3), where mean area changes were 65.1 ± 31 mm⁻² day⁻¹ and 32.3 ± 26 mm⁻² day⁻¹ respectively. Lesions that progressed in phase during the monitoring period showed lower changes in lesion size than those that remained in the same phase (H₍₁₎ = 7.25, p < 0.01, see Figure 2N), where mean area changes were 2 ± 9 mm⁻² day⁻¹ for lesions showing progression in phase, and 106 ± 31 mm⁻² day⁻¹ for those showing no progression (Figure 2N).

Disease levels over the Austral summer

Dot plots showing average disease prevalence (A) and severity (B) over time in sites Emily Bay (EB) and Slaughter Bay (SB). Black points and lines represent disease prevalence, whilst gray points and lines represent average total *Montipora* benthic cover. Lines represent SE. Asterisks indicate p < 0.01.

Disease prevalence and severity

In December 2020 130 colonies were surveyed in total for signs of disease over a total space of 240 m⁻² (n = 12 transects, each 20 m⁻² in total area). Following the same monitoring design in April 2021 198 colonies were surveyed. Benthic cover of Montipora varied on transects over a range of 0.1–16.9%. The mean Montipora cover across all time points was 6.1% ± 0.81, and the mean total hard coral cover was 33.3% ± 0.68 (Figure S1). Mean Montipora cover composition across the lagoon in both December 2020 and April 2021 is shown in Figure 3. The mean disease prevalence (proportion of colonies showing active disease signs) across the lagoon was 61.7 ± 5.17% in December 2020 and 60.7 ± 5.03% in April 2021 (Figure 3A). Prevalence varied between SB and EB with time (X₍₁₎ = 6.44, p = 0.01) (Table S2).

A significant interaction between site and time for prevalence across bays was found, where disease prevalence in EB (74.7 ± 3.42%) was 35% higher than in SB (48.8 ± 6.21%) (p = 0.031) (Figure 3A) in December 2020. In April 2021 there was no difference recorded in prevalence between EB (57.8% ± 8.92) and SB (63.7% ± 5.29) (Figure 3A). Disease severity (% of colony impacted by disease) did not vary between EB and SB with time (F₍₁₎ = 21.54, p = 0.2), but did vary significantly over the whole lagoon with time (F₍₁₎ = 171.94, p < 0.1) (Figure 3B). Mean disease severity across the whole lagoon was 10 ± 1% in December 2020 and 15.4 ± 1.6% in April 2021. This represents a 54% increase over the summer period. No relationship between Montipora cover and disease prevalence was evident (X₍₁₎ = 0.28, p = 0.60) (Table S2). Disease severity showed a positive relationship with Montipora cover (F₍₁₎ = 58.68, p = 0.04), where a 1% increase in Montipora cover per transect was associated with a 0.36% increase in disease severity (Figure S3). Model summaries can be found in Table S2.

A total of 228 photographs from 2015 to 2020 were collected from citizens of Norfolk Island who are regular users of the reef. Citizen collected images were assessed for signs of disease impacting lagoonal Montiporids. No photographs were provided for 2016, and limited photographs were available for 2019. Signs of tissue loss in Montipora colonies within EB and SB were observed in the years 2015, 2017, 2018, 2019, and 2020 (Figure S4). In 2017 a single lesion was also observed as showing signs of Phase 4 lesions. Phase 3 lesions were also observed in 2017 and 2020. Disease severity was estimated to be low (<3% on infected colonies) during the period 2015–2020. In 2018 and 2020 extent of tissue loss was variable and estimated to be between 5 and 10% for infected colonies. Figure S4 depicts examples of disease signs identified through time.

Drivers of disease risk

The optimal LASSO penalty parameter that resulted in the most minimized model deviance determined through BIC was 23 (Figure S5). At λ = 23, the penalty reduced 24/28 regression coefficients to zero (Figure 4A, Table S3 for penalized coefficients). The remaining regression coefficients include interactions between coral trait size and time point, size, and site in addition to interactions between community composition variable PC2 and site (Figure 4A). See supplemental information for the description of community composition variables produced by principle-component analysis (PCA) (Figure S1). Specifically, PC2 was primarily loaded by Acropora cover (loading = 0.834) (Figure 4). Colony size had the largest modeled coefficients in the reduced model. Log-Odds ratios maximum coefficients are Site[SB]∗Size[Small] interaction = −1.55, and TP[April]∗Size[Medium] interaction = 0.53) (Figure 4A). The optimal LASSO penalty parameter that resulted in the most minimized model deviance determined through BIC was 45 (Figure S5). At λ = 45, the penalty reduced 26/28 regression coefficients to zero (Figure 4B, Table S3 for penalized coefficients). The remaining regression coefficients include an interaction between the community composition variable PC2 and Site. The coefficient for the interaction between site and PC2 was small (Site[SB]∗PC2 = −0.18) (Figure 4B).

Inspection of interaction plots reveals varying effects of size class dependent on both site and time point (Figures 4C and 4D). The probability of disease occurrence in medium colonies did not vary over time points (0.58 in Dec ’20 and April ’21, Figure 4C). Large colonies were more likely to be diseased in Dec ‘20 (0.88) and April ’21 (0.81) compared to other size classes (Figure 4C). The probability of disease occurrence varies over timepoints for small colonies. Small colonies show a 0.54 probability of disease in Dec ’20 and 0.38 in April ’21 (Figure 4C). The probability of disease occurrence with colony size also varied between sites (Figure 4D). In EB and SB large colonies had the greatest probability of disease occurrence (0.79 and 0.88 respectively, Figure 4D). In EB, medium (0.65) and small (0.56) colonies had greater probability of disease compared to medium (0.51) and small (0.36) colonies in SB (Figure 4D).

Discussion

Anthropogenic global and local stressors which negatively impact the coral holobiont are now widespread over reefs.²⁶^,²⁷^,²⁸ These stressors can lead to coral bleaching and the emergence of diseases, in the most severe cases undermining ecosystem resilience leading to degradation and a reduced ability to support both biological and social systems.¹^,²^,³ In this study we record the extent and potential drivers of a coral disease outbreak that impacted one of the two foundational hard coral taxa at a high-latitude location, Norfolk Island, South Pacific. We find consistently high disease prevalence levels and increasing severity over the Austral summer period. Spatial patterns of disease suggest links with terrestrial pollution events and disease risk among coral colony size classes indicate varying disease impacts within the Montipora community. In characterizing this disease outbreak, we highlight the vulnerability of a high-latitude ecosystem where the future persistence of hard coral taxa and the biodiversity they support is threatened through exposure to climate change and local terrestrial pollution.

Montiporid White Syndrome signs in Norfolk Island lagoon

Description of disease signs and measurement of lesion activity lead to the classification of a novel disease within the Norfolk Island lagoon, here referred to as a tissue loss disease with unknown etiology and thus, a Montiporid white syndrome.⁷ The disease presents with multifocal patterns and discrete patchiness of tissue loss areas across the affected colonies. Here we suggest that the disease first emerges as a bleached patch of tissue with indistinct margins wherein tissue between polyps (the coenosarc) shows reduced endosymbiont densities. Following the initial paling of the tissue, we suggest a further three discrete phases of disease progression occur and have measured transitions between these phases. The final stage of the disease presents as lesions with black disease signs consistent with skeleton colonization and overgrowth.

Bleaching of coral tissues prior to tissue loss is a common feature of many white syndromes and black disease signs have been recorded following tissue loss in other reef locations.⁵⁵^,⁵⁶ For example, in Kenya several coral taxa (including Montiporids) experienced a mass mortality event where tissue loss was followed by the presence of white dust sometimes encapsulated a black layer.⁵⁵ Moreover the four distinct disease phases identified in the present study are similar to those seen in corals affected by Atramentous Necrosis, a disease first described in the Central GBR⁴^,⁴⁶ and subsequently observed in the Indo-Pacific including multiple reef sites in Indonesia.⁵⁷^,⁵⁸ Notably, in this study progression between distinct disease phases was associated with lesions that showed minimal change in area over a period of weeks, suggesting a successional microbial colonization process underlying disease phases. Lesser and colleagues⁵⁹ have hypothesized that macroscopic disease signs may represent secondary overgrowth communities (and successional communities following) that could be taking advantage of a lack of direct competition from coral tissue, and an influx of nutrients associated with tissue decay. We also observed multiple disease signs and organisms in direct association with lesions as they progressed through phases, supporting the ideas of Lesser et al.⁵⁹ and further highlighting the complexities of disease diagnosis based on macroscopic signs alone. Further understanding of the secondary vs primary nature of disease signs and communities is ultimately important for understanding disease impacts on coral health and disease management, both during active disease infection and colony recovery.

Here we recorded a maximum lesion area increase of 329 mm⁻² day⁻¹ implying an acute disease process;⁸ however, we also recorded lesions with active disease signs that decreased in the area during the monitoring period indicating tissue recovery. Lesions that were measured as growing in size over the monitoring period did so at a rate higher than previously observed for white syndromes in the Caribbean (see Bythell et al.⁶⁰ for a review). For example, a rapid tissue loss disease termed white plaque type II in the Caribbean was observed as progressing at a rate of 2 cm a day (Richardson et al., 1998), whereas white plaque type I was observed at progressing mm’s a day.⁶¹ Variable rates of tissue loss within a disease outbreak have been documented elsewhere. Colonies of Acropora impacted by white syndrome on Heron Island, Great Barrier Reef showed tissue loss rates ranging from 0 to 1146 cm⁻² week ⁻¹⁴⁹ and in Hawaii a white syndrome impacting Montipora capitata was classed as chronic or acute based on differential rates of tissue loss.⁶² Both chronic and acute syndromes within a single outbreak event have been linked with different etiologies, suggesting multiple disease-causing agents can be present within a single disease event.⁶³^,⁶⁴^,⁶⁵ These could include infectious and non-infectious disease agents⁵⁵ as a result of primary and secondary infection.³³ Nevertheless, the rates of lesion area change measured here indicate the potential for colony partial mortality that could lead to whole colony mortality in a short period of time (weeks, depending on the size of the colony) if lesion progression is not halted.

A highly prevalent disease outbreak likely associated with exposure to terrestrial pollution

In December 2020 and April 2021, we observed ∼60% of surveyed Montiporid coral colonies with signs of disease, a prevalence in line with the most severe coral disease outbreaks recorded to date worldwide (Table 1). Importantly disease prevalence in the Norfolk lagoonal reef is comparable to recent outbreaks of SCTL on highly impacted reefs of the Caribbean, where up to 70% of the coral community have been recorded as showing signs of disease⁶⁶ (Table 1). Current SCTL rates are much higher than other disease outbreak events on Caribbean reefs over the past 4 decades which have been recorded at < 5%.⁷¹ Analysis of citizen photographs shows that white syndrome signs are present within the lagoon in the years 2015 and 2017 to 2020. These likely represent natural baseline levels of the disease however it is unclear if prevalence levels in November 2020 are higher than historic levels within the lagoon. In this study co-occurrence of multiple environmental stressors in 2020 could have led to the emergence of high disease levels within the population in November 2020 which remained high over the 4-month summer period. Previous outbreaks of tissue loss disease Atramentous Necrosis have been shown to be associated with thermal anomalies and high rainfall,³⁹ and studies have suggested that Montipora taxa may have a higher susceptibility to disease and physiological stress during lower temperatures in winter seasons.⁴^,⁷²^,⁷³ Disease outbreaks have been recorded in some locations as being ephemeral and seasonal but increasingly disease events are recorded as persisting on reefs for long periods of time (months)⁷⁴ often in association with stressors such as poor water quality.

Table 1.

Disease prevalence levels recorded during disease events

Disease	Species	Location	Survey time	Prevalence	Reference
White syndrome	Montipora spp.	Norfolk Island lagoon	Mean prevalence in November 2020 and April 2021	60%
Atrementous Necrosis	Montipora spp.	Central GBR, Magnetic Island	1st October 2003 (spring)	12%	Anthony et al.⁴⁶
Atrementous Necrosis	Montipora spp.	Central GBR, Magnetic Island	27th October 2003 (spring)	52%	Anthony et al.⁴⁶
Atrementous Necrosis	Montipora aequituberculata	Central GBR, Magnetic Island	23rd January 2002	75%	Jones et al.⁴
Stony Coral Tissue Loss	Montastrea cavernosa	Florida Reef Tract	Mean prevalence from May 2014 to December 2017	70%	Muller et al.⁶⁶
	Orbicella faveolata			52%
	Dichocoenia stokesii			58%
Stony Coral Tissue Loss	Pseudodiploria strigosa	Mexican Caribbean	Mean prevalence from 2018 - 2019	42%	Alvarez-Filip et al.⁶⁷
	Meandrina meandrites			40%
	Siderastrea siderea			28%
Skeletal Eroding Band	Pocillopora eydouxi	GBR (18 reefs, spanning 500 km)	Mean prevalence across the summers from 2004 - 2006	8.5%	Page and Willis⁶⁸
	Seriatopora spp.			5.8%
	Stylophora pistillata			4%
Ulcerative White Spot	Staghorn Acropora	Heron Island, Southern GBR	Mean prevalence across November 2007 - August 2009	5.5%	Haapkylä et al.⁶⁹
Ulcerative White Spot	Massive Porites	Heron Island, Southern GBR	Mean prevalence across November 2007 - August 2009	1%	Haapkylä et al.⁶⁹
Black Band	Dipastraea	Red Sea	November and December 2015	6.1%	Hadaidi et al.⁷⁰
	Montipora			3.7%
	Pavona			8.2%

Open in a new tab

Whilst we did not measure a change in disease prevalence over the summer period, we did find significantly higher disease prevalence in Emily Bay than Slaughter Bay in December 2020. This pattern suggests a possible link between disease and exposure of communities to poor water quality during creek overflow events in the preceding Winter period. Exposure is likely higher in Emily Bay due to the proximity to creek outlets although other sources of water quality contamination within the lagoon exist and include ground water intrusion.⁵⁴ Spatial patterns in disease signs are commonly observed along gradients from point sources of pollution,⁴⁴^,⁷⁵ where flow rates and flushing can affect the dilution of water quality contaminants, transporting these contaminants and pathogens to other reef areas⁶⁶^,⁷⁶^,⁷⁷ whilst also impacting the responses of the coral holobiont to these stressors.⁷⁸^,⁷⁹ In addition to direct point-source exposure, the flow conditions present within the lagoon could have further led to higher disease risk in Emily Bay. Measurement of flow conditions within the lagoon suggests high flow conditions and connectivity between the bays with a likely higher retention time in Emily Bay than Slaughter Bay.⁵⁴

Specifically, water quality contaminants of concern for coral health at Norfolk Island include terrestrial sediment released into the lagoon during pollution events. This is supported by observations of sediment either directly on translucent tissue patches, or adjacent to diseased tissue in this study. Sedimentation on coral tissue has been linked to disease through abrasive damage⁸⁰^,⁸¹ that present locations for opportunistic infection.⁶⁸ Tissue loss lesions observed in this study were also found on coral structures that are positioned vertically in the water column (i.e. a foliose column, or vertical plating structure) and therefore are less likely to accumulate sediment than other parts of the coral colony.⁴⁶ However, sedimentation can also impact coral functioning through increasing turbidity which can impact endosymbiont photosynthesis and inhibit heterotrophic feeding.⁸²^,⁸³ Other contaminants present within the creek overflow may also impact coral health, including freshwater, nutrients and pathogens.⁸⁴ Other possible drivers of disease prevalence include bleaching responses in March 2020 and Montipora cover as some diseases show positive relationships with host densities.⁷^,⁴⁹ A lack of spatial patterns in bleaching responses recorded in 2020⁵⁴ suggest that spatial patterns in disease prevalence in the subsequent summer may not be corelated to responses despite Monitporid corals being severely impacted by the 2020 bleaching event.⁵⁴ Additionally, in this study we find no evidence for relationships between disease prevalence and Montipora cover, suggesting other drivers are more likely responsible for disease levels within the community.

In the current study, we found disease severity to be increasing over the summer study period, with disease severity within colonies to be on average to be 10% in early summer and 15% by late summer. Work and Aeby⁸ define disease severity as mild when on average, active disease signs occupy <25% of the impacted coral colony. At Magnetic Island on the Southern GBR, the severity of Atramentous Necrosis signs on Montipora aequituberculata colonies was found to be between 20% of colony (least impacted site) and up to 60% of the colony at the most impacted site in Florence Bay.⁴ Several other studies have also reported within-colony disease spread to be higher during the summer.⁶^,⁸⁵^,⁸⁶ For example, a sub-tropical white syndrome impacting Turbinaria in the Solitary Islands, Australia showed increased rates of tissue loss during summer (26 C).²⁰ It is important to note that in the current study 4-month survey period summer SSTs were not anomalously high (i.e. 4 DHWs⁸⁷). In this study, we also found a positive relationship between disease severity and Montipora cover, although this effect was small (a 1% increase in Montipora cover per transect was associated with a 0.36% increase in disease severity) so does not likely represent a density-related phenomenon.

Disease disproportionately impacted the largest colonies

In this study, we find that the probability of disease occurrence (disease risk) varies between colony size classes where larger colonies were more likely to be diseased than medium and small colonies. We also find that small colonies were more likely to be diseased in December ’20 than April ‘21, and small and medium colonies showed higher disease risk in Emily Bay than Slaughter Bay. Larger colonies have been recorded as being disproportionately affected by the disease in other studies, including white syndrome impacted tabular Acropora on the Southern GBR⁴⁹ and outbreaks of white plaque disease in the Caribbean.¹⁰ Changes in disease dynamics within sites during outbreaks have also been documented for other coral diseases.⁸⁸ If the initiation of the disease observed in this study is associated with sedimentation, higher probability of disease risk in larger colonies could be related to an increased surface area available for sediment accumulation to occur. Colony age has also been related to decreases in microbial diversity and linked functions as a barrier to pathogenic colonization,⁸⁹ while some studies have implicated senescence as a key factor driving differential responses between colony size classes.⁹⁰

Future considerations and limits to recovery

In this study, we record a highly prevalent outbreak of a Montiporid white syndrome within a coastal high-latitude lagoonal reef system. Disease prevalence levels remained high during the 4-month survey period despite low disease severity within the impacted colonies. However, fast rates of lesion progression indicate that there is potential for high colony partial mortality that could lead to whole colony mortality. Therefore colony fate following disease emergence needs to be assessed in future studies. With a disproportionate disease risk for larger colonies found in this study, there is also risk of reduced reproductive capacity and recruitment. Taken alongside marginal environmental conditions at high-latitude reefs which can further limit recovery times after physiological stress events,⁹¹ future assessments of reef benthic structure should assess reproductive impacts of disease events. In conclusion, our results highlight the vulnerability of a high-latitude lagoonal reef system to the combined impacts of global and local stressors. This suggests that sub-tropical reefs face similar threats to coral health as their tropical counterparts, and thus their ability to serve as refuges in the face of future changes in climate requires further evaluation. Continuing to build the understanding of how global and local stressors interact with disease causing-agents, hosts and the environment will ultimately aid in ensuring the persistence of coral reef biodiversity into the future.

Limitations of the study

In this study, we did not capture the full progression of the four described disease phases, overgrowth communities, and fate of impacted colonies limiting conclusions that can be made after disease infection and colony impacts associated with each of the distinct disease signs. Additionally, without repeated surveys of impacted colonies over time the recorded increase in disease severity cannot be attributed to an increase in the size of lesions. In this study, we classified severity as the area of active diseased tissue (lesion phase 1–4) and so does not include previously diseased and overgrown colony area.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Deposited data

GitHub repository with code and data for analysis	GitHub	https://github.com/CharlotteEPage/NFI_Disease_Ecology
Raw data tables	Mendeley	https://data.mendeley.com/datasets/y869bhhmzr/1

Software and algorithms

R version 4.1.1	R Development Core Team⁶⁰	https://posit.co/
ImageJ version 1.52	ImageJ⁵⁷	https://imagej.nih.gov/ij/

Open in a new tab

Resource availability

Lead contact

Further information and requests for resources should be directed to and will be fulfilled by the lead contact, Charlotte Page (charlotte.eve.page@gmail.com).

Materials availability

This study did not generate new unique reagents.

Method details

Study site

Norfolk Island (hereafter NFI) (−29° 01′58.18" S 167° 57′15.81″ E) is an oceanic island situated in the South Pacific approximately 1400 km from the East Coast of Australia (Figure 1A). This study was conducted in the lagoonal reef system on the south-side of the island. Within the lagoon are two bays, Emily Bay (hereafter EB) and Slaughter Bay (hereafter SB) (Figure 1B).

Sea surface temperature (hereafter SST) data and daily rainfall are provided for the period January 2020 to April 2021 (Figure 1C). SST time series and the daily degree heating weeks (DHWs) product were obtained from NOAA Coral Reef Watch (CRW) for Norfolk Island (https://coralreefwatch.noaa.gov/product/vs/gauges/norfolk_island.php).⁹² The DHW product accumulates temperature anomalies exceeding the maximum monthly mean (MMM) SST for the given 5 km grid over a rolling 12-week period.⁸⁷ As terrestrial-pollution has been previously linked to rainfall⁵⁴ daily average rainfall data are obtained from the Bureau of Meteorology are also provided (http://www.bom.gov.au/climate/dwo/IDCJDW2100.latest.shtml).

Disease signs

Following methods by Work and Aeby,⁸ disease signs were categorised through observations of location of lesions on the colony (basal, medial, apical, peripheral, central, colony-wide); lesion edges (distinct, indistinct, annular); the overall shape of lesion edges, called the lesion margin (serrated, undulating, smooth, serpiginous); and the shape of the entire lesion (circular, oblong, pyriform, cruciform, linear, lanceolate, irregular). A disease phase was categorised as a collection of gross disease signs distinct from each other. Other partial mortality was not classed as active disease when there was no uncolonized (i.e. white signs) tissue or skeleton present.

Monitoring of tagged lesions on distinct colonies was conducted to determine phases of lesion progression over a period of 9–11 days in December 2020 (Figure 1C). Lesions were photographed with a calliper placed next to the lesion for scale, and photographs of each lesion were taken from the same viewpoint by using prominent ‘landmarks’ adjacent to lesions to align images. Lesion area was quantified using ImageJ.⁹³ Where edges were unclear, care was taken to only include areas of tissue loss within the lesion polygon. Lesions that were present on complex three-dimensional coral growth forms that can obscure surface area measurements (e.g. foliose pillar structures) were not included. Lesion phase and area was determined at the beginning and end of surveys for all tagged lesions, and activity was calculated as a rate by dividing the change in lesion area by the number of days between repeated observations (mm⁻² day⁻¹).

Disease prevalence and severity

To quantify disease prevalence (i.e. the proportion of community infected) and disease severity (i.e. area of colony infected by disease signs) ecological surveys were conducted at the initial disease observation, December 2020, and at the end of the summer period, April 2021 (Figure 1C) as some studies have reported disease levels increasing after exposure to summer temperatures (e.g. Jones et al.⁴). At each time point, 12-replicate belt-transects were conducted over a 7-day period (TP1: 27/11/20–3/12/20; TP2: 30/03/21–6/03/21). Approximately two belt-transects were completed on each day, where time in water was constrained by tidal heights. 6 belt-transects laid in both EB and SB respectively (Figure 1B). Survey methods involved placing a 10 m transect line along the benthos parallel to the depth contours of the reef structure at approximately 1–2 m depth. All transects were placed at least 10 m apart. Transect sites were semi-fixed (i.e. a permanent reef marker was not used, but the same reef area was re-visited at the repeat time point).

All colonies of Montipora over 10 cm in diameter and within a 1 m belt on either side of the belt-transect were monitored for signs of disease. Following methods used by Page et al.,⁹⁴ for each colony within the belt-transect a photograph was taken of the whole colony in addition to photographs of individual signs of disease or poor health. Disease prevalence was calculated for each belt-transect by dividing the number of Montipora colonies showing signs of disease by the total number of Montipora colonies present within a transect. To determine disease severity at each monitoring time point, the area of diseased tissue and/or tissue loss was estimated for each diseased colony. Disease severity was quantified for each transect by calculating the mean area of infected tissue for all diseased Montipora colonies within the belt-transect. Other variables for further analysis of disease-risk were also collected from colony photographs. These were colony size (small 0.1–0.5 m, medium 0.51–1 m, large >1.01 m), growth form (foliose when plating and column structures are present, encrusting), color morph (purple, brown), colony bleaching status (pale defined as a whole colony response with marked reduction in colony pigmentation, no paling) and percent colony area of other partial mortality (not attributable to active disease).

Benthic community structure was assessed at each replicate belt-transect by placing ten 0.5 m⁻² quadrats and photographed at 1 m intervals along the transect tape. Benthic cover was analyzed from photoquadrats in CoralNet⁹⁵ using a 100-point evenly spaced grid. Abiotic benthos was classified as sediment and other substrate. Biotic benthos was classified as Montipora spp. encrusting, Montipora spp. foliose, Acropora spp., other branching hard corals (Stylophora spp. and Pocillopora spp.), other hard corals, soft corals (including anemones), macroalgae, other calcifiers (e.g. crustose coralline algae), turfs (defined as a mixed algal and microbial assemblage, <3 cm in height), turf-sediment matrix, other benthic invertebrates Diadema spp., zooanthids and sponges) and Microalgae Type I (presumed filamentous cyanobacteria) and other Microalgae Type II (presumed red cyanobacterial biofilm). In situ surveys, variable generation from photographs and quadrat scoring were all undertaken by a single observer to reduce bias (CEP).

To assess historical presence of disease we collated photographs taken by citizens recreationally during 2015–2020 and qualitatively assessed them for active disease signs (Figure 1C). Meta-data retained with each photograph was used to assign date of capture. Disease signs observed were described and when possible, an estimate of disease severity was also made.

Quantification and statistical analysis

All statistical analysis was conducted in R version 4.1.1 (2021-08-10).⁹⁶ Code and data for analysis can be found at https://github.com/CharlotteEPage/NFI_Disease_Ecology.

Disease signs

To test for the effects of initial disease phase (Phase 2 and Phase 3), and phase progression (progression, no progression) on changes in lesion area over the monitoring period we used non-parametric Kruskal-Wallis rank sum tests using the R function kruskal.test because data violated checks for normality and homogeneity of variance.

Disease ecological monitoring

To test whether disease prevalence and severity varied between sites over time and to test for relationships with host abundance, data was modeled as a response of site (EB, SB), time point (December 2020, April 2021) and total Montipora cover per transect (%). We specified an interaction term between site and time point. Prevalence was modeled as a response of covariates using a generalized linear model. We fit the model with the binomial family using glm() from the R package lme4.⁹⁷ Included within the model was an additional offset argument where the total number of coral colonies counted at each transect to generate prevalence values were specified. We examined diagnostic plots using the package DHARMa.⁹⁸ Significance was tested using analysis of deviance – chi-squared test on modeled coefficients. Differences amongst variable levels were further investigated through post hoc testing using a Holm-Bonferroni correction. Mean severity at each transect was normally distributed so was modeled as a response of covariates using a linear model. This model was fit with lmer() from the R package lme4.⁹⁷ Diagnostic plots were examined for outliers, linearity, and normality of residuals. Covariate significance was tested using analysis of variation on modeled coefficients.

Drivers of disease-risk

We used a method of automated variable selection (lambda; a LASSO penalty parameter within the generalised linear mixed effects modeling (glmm) approach to investigate colony and community (benthic cover) variables influencing variation in disease occurrence and severity between time points (December 2020 and April 2021) and sites (EB and SB).⁹⁹^,¹⁰⁰ Lambda was chosen based on best model fit using BIC. Lambda was applied to models of disease occurrence and disease severity using glmmLasso().¹⁰¹

Modeled covariates were colony size (small, medium and large), growth form (encrusting, foliose), color morph (brown, purple), colony bleaching status (pale, no paling) and other partial mortality. We also included community composition variables calculated using Principal Component Analysis (PCA) conducted on benthic cover categories to address collinearity. Principal component scores and factor loadings were calculated using princomp(), and eigenvalues were extracted and visualised using packages Factoextra¹⁰² and PCAtools.¹⁰³ Components that represented >90% of variation in benthic cover (PCs 1–4, representing 90.6% of total variation, see Figure S1; Table S1) were used in models. Transect ID (specific to transects within each time point) was specified as a random effect. Disease occurrence was modeled using a glmm with the binomial family and disease severity was modeled using a linear mixed effects model. Full models included all covariates of interest as fixed effects, and combinations of covariates as interactions between these fixed effects and site and time point. In total 29 regression covariates were modeled as predictors in full models for disease occurrence and severity. Interaction groups include colony trait and condition variables with time point (December 2020 and April 2021), and site (EB and SB); in addition to benthic community components (PC1-4) with site (EB and SB). The effects of benthic community components over time were not assessed because changes in cover of benthic community groups over time were only detected in two groups (microalgae type I and type II), this temporal variation is captured in PC1. Also tested for was an interaction between time point and site. All continuous variables were standardised prior to LASSO. Assumptions of both full (all modeled variables) and reduced models (including only variables with coefficients not reduced to 0 after the LASSO penalty was applied) were assessed through plotting of residuals and diagnostic plots were examined using the package DHARMa.⁹⁸ On assessment of diagnostic plots a log transformation was applied to disease severity.

Acknowledgments

We extend thanks to all of those on Norfolk Island who assisted with this work, including Bette Mathews who provided photographs of the lagoonal reef and Castaways and Christian-Fletcher apartments for being beyond accommodating to the team. We thank Parks Australia for funding, support, and communication throughout the completion of this study. Acknowledgment is also due for several students and academics who kindly assisted with survey work in the field including Dr Alexander Fordyce, Dr Coulson Lantz, and Dr Megan Hugget. We also thank Eve Slavich at StatsCentral, UNSW for help and advice on statistical analysis. This study was partly funded by International Coral Reef Society Graduate Fellowship awarded to CEP and Parks Australia Norfolk Marine Park ecosystem health survey contract awarded to TDA.

Author contributions

Conceptualization CEP, TDA, WL, and SE; methodology CEP, TDA, WL, and SE; investigation and visualization CEP; statistical analysis CEP; writing – original draft, CEP; writing – review & editing CEP, TDA, WL, and SE; funding acquisition TDA, WL, and CEP; supervision TDA, WL, and SE.

Declaration of interests

The authors have no competing interests to declare.

Inclusion and diversity

We support inclusive, diverse, and equitable conduct of research.

Published: February 19, 2023

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2023.106205.

Supplemental information

Document S1. Figures S1–S5 and Tables S1–S3

mmc1.pdf^{(1.3MB, pdf)}

Data and code availability

All data and code for statistical analysis can be found at github repository: https://github.com/CharlotteEPage/NFI_Disease_Ecology. Data has also been archived and can be found at https://data.mendeley.com/datasets/y869bhhmzr/1. Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.

References

1.Aronson R.B., Precht W.F. The Ecology and Etiology of Newly Emerging Marine Diseases. Springer; 2001. White-band disease and the changing face of Caribbean coral reefs; pp. 25–38. [Google Scholar]
2.Estrada-Saldívar N., Quiroga-García B.A., Pérez-Cervantes E., Rivera-Garibay O.O., Alvarez-Filip L. Effects of the stony coral tissue loss disease outbreak on coral communities and the benthic composition of Cozumel reefs. Front. Mar. Sci. 2021;8:306. [Google Scholar]
3.Heres M.M., Farmer B.H., Elmer F., Hertler H. Ecological consequences of Stony coral tissue loss disease in the Turks and Caicos Islands. Coral Reefs. 2021;40:609–624. [Google Scholar]
4.Jones R.J., Bowyer J., Hoegh-Guldberg O., Blackall L.L. Dynamics of a temperature-related coral disease outbreak. Mar. Ecol. Prog. Ser. 2004;281:63–77. [Google Scholar]
5.Lessios H.A., Cubit J.D., Robertson D.R., Shulman M.J., Parker M.R., Garrity S.D., Levings S.C. Mass mortality of Diadema antillarum on the Caribbean coast of Panama. Coral Reefs. 1984;3:173–182. [Google Scholar]
6.Patterson K.L., Porter J.W., Ritchie K.B., Polson S.W., Mueller E., Peters E.C., Santavy D.L., Smith G.W. The etiology of white pox, a lethal disease of the Caribbean elkhorn coral, Acropora palmata. Proc. Natl. Acad. Sci. USA. 2002;99:8725–8730. doi: 10.1073/pnas.092260099. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Bourne D.G., Ainsworth T.D., Pollock F.J., Willis B.L. Towards a better understanding of white syndromes and their causes on Indo-Pacific coral reefs. Coral Reefs. 2015;34:233–242. [Google Scholar]
8.Work T.M., Aeby G.S. Systematically describing gross lesions in corals. Dis. Aquat. Organ. 2006;70:155–160. doi: 10.3354/dao070155. [DOI] [PubMed] [Google Scholar]
9.Rippe J.P., Kriefall N.G., Davies S.W., Castillo K.D. Differential disease incidence and mortality of inner and outer reef corals of the upper Florida Keys in association with a white syndrome outbreak. Bull. Mar. Sci. 2019;95:305–316. [Google Scholar]
10.Nugues M.M. Impact of a coral disease outbreak on coral communities in St. Lucia: what and how much has been lost? Mar. Ecol. Prog. Ser. 2002;229:61–71. [Google Scholar]
11.Borger J.L., Colley S. The effects of a coral disease on the reproductive output of Montastraea faveolata (Scleractinia: Faviidae) Rev. Biol. Trop. 2010;58:99–110. [PubMed] [Google Scholar]
12.Lirman D. Fragmentation in the branching coral Acropora palmata (Lamarck): growth, survivorship, and reproduction of colonies and fragments. J. Exp. Mar. Biol. Ecol. 2000;251:41–57. doi: 10.1016/s0022-0981(00)00205-7. [DOI] [PubMed] [Google Scholar]
13.Pollock F.J., Wada N., Torda G., Willis B.L., Bourne D.G. White syndrome-affected corals have a distinct microbiome at disease lesion fronts. Appl. Environ. Microbiol. 2017;83:e02799-16. doi: 10.1128/AEM.02799-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Willis B.L., Page C.A., Dinsdale E.A. Coral Health and Disease. Springer; 2004. Coral disease on the great barrier reef; pp. 69–104. [Google Scholar]
15.Sutherland K.P., Porter J.W., Torres C. Disease and immunity in Caribbean and Indo-Pacific zooxanthellate corals. Mar. Ecol. Prog. Ser. 2004;266:273–302. [Google Scholar]
16.Harvell D., Jordán-Dahlgren E., Merkel S., Rosenberg E., Raymundo L., Smith G., Weil E., Willis B. Coral disease, environmental drivers, and the balance between coral and microbial associates. Oceanography. 2007;20:172–195. [Google Scholar]
17.Moriarty T., Leggat W., Huggett M.J., Ainsworth T.D. Coral disease causes, consequences, and risk within coral restoration. Trends Microbiol. 2020;28:793–807. doi: 10.1016/j.tim.2020.06.002. [DOI] [PubMed] [Google Scholar]
18.Williams G.J., Aeby G.S., Davy S.K. Coral disease at Palmyra Atoll, a remote reef system in the central Pacific. Coral Reefs. 2008;27:207. [Google Scholar]
19.Miller J., Muller E., Rogers C., Waara R., Atkinson A., Whelan K.R.T., Patterson M., Witcher B. Coral disease following massive bleaching in 2005 causes 60% decline in coral cover on reefs in the US Virgin Islands. Coral Reefs. 2009;28:925–937. [Google Scholar]
20.Dalton S.J., Godwin S., Smith S.D.A., Pereg L. Australian subtropical white syndrome: a transmissible, temperature-dependent coral disease. Mar. Freshw. Res. 2010;61:342–350. [Google Scholar]
21.Dalton S.J., Smith S.D.A. Coral disease dynamics at a subtropical location, Solitary Islands Marine Park, eastern Australia. Coral Reefs. 2006;25:37–45. [Google Scholar]
22.Guinotte J.M., Buddemeier R.W., Kleypas J.A. Future coral reef habitat marginality: temporal and spatial effects of climate change in the Pacific basin. Coral Reefs. 2003;22:551–558. [Google Scholar]
23.Riegl B. Climate change and coral reefs: different effects in two high-latitude areas (Arabian Gulf, South Africa) Coral Reefs. 2003;22:433–446. [Google Scholar]
24.Beger M., Sommer B., Harrison P.L., Smith S.D., Pandolfi J.M. Conserving potential coral reef refuges at high latitudes. Divers. Distrib. 2014;20:245–257. [Google Scholar]
25.Riegl B., Piller W.E. Possible refugia for reefs in times of environmental stress. Int. J. Earth Sci. 2003;92:520–531. [Google Scholar]
26.Jones N.P., Figueiredo J., Gilliam D.S. Thermal stress-related spatiotemporal variations in high-latitude coral reef benthic communities. Coral Reefs. 2020;39:1661–1673. [Google Scholar]
27.Hoegh-Guldberg O., Poloczanska E.S. The effect of climate change across ocean regions. Front. Mar. Sci. 2017;4:361. [Google Scholar]
28.Wear S.L., Thurber R.V. Sewage pollution: mitigation is key for coral reef stewardship. Ann. N. Y. Acad. Sci. 2015;1355:15–30. doi: 10.1111/nyas.12785. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Harborne A.R., Rogers A., Bozec Y.-M., Mumby P.J. Multiple stressors and the functioning of coral reefs. Ann. Rev. Mar. Sci. 2017;9:445–468. doi: 10.1146/annurev-marine-010816-060551. [DOI] [PubMed] [Google Scholar]
30.Darling E.S., McClanahan T.R., Côté I.M. Combined effects of two stressors on Kenyan coral reefs are additive or antagonistic, not synergistic. Conserv. Lett. 2010;3:122–130. [Google Scholar]
31.Bessell-Browne P., Negri A.P., Fisher R., Clode P.L., Jones R. Cumulative impacts: thermally bleached corals have reduced capacity to clear deposited sediment. Sci. Rep. 2017;7:2716. doi: 10.1038/s41598-017-02810-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Ward J.R., Lafferty K.D., Crowder L. The elusive baseline of marine disease: are diseases in ocean ecosystems increasing? PLoS Biol. 2004;2 doi: 10.1371/journal.pbio.0020120. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Aeby G.S., Callahan S., Cox E.F., Runyon C., Smith A., Stanton F.G., Ushijima B., Work T.M. Emerging coral diseases in Kāne ‘ohe Bay, O ‘ahu, Hawai ‘i (USA): two major disease outbreaks of acute Montipora white syndrome. Dis. Aquat. Organ. 2016;119:189–198. doi: 10.3354/dao02996. [DOI] [PubMed] [Google Scholar]
34.Hobbs J.-P.A., Frisch A.J., Newman S.J., Wakefield C.B. Selective impact of disease on coral communities: outbreak of white syndrome causes significant total mortality of Acropora plate corals. PLoS One. 2015;10 doi: 10.1371/journal.pone.0132528. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Precht W.F., Gintert B.E., Robbart M.L., Fura R., Van Woesik R. Unprecedented disease-related coral mortality in Southeastern Florida. Sci. Rep. 2016;6:31374. doi: 10.1038/srep31374. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Bruno J.F., Petes L.E., Drew Harvell C., Hettinger A. Nutrient enrichment can increase the severity of coral diseases. Ecol. Lett. 2003;6:1056–1061. [Google Scholar]
37.Bruno J.F., Selig E.R., Casey K.S., Page C.A., Willis B.L., Harvell C.D., Sweatman H., Melendy A.M. Thermal stress and coral cover as drivers of coral disease outbreaks. PLoS Biol. 2007;5:e124. doi: 10.1371/journal.pbio.0050124. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Brandt M.E., McManus J.W. Disease incidence is related to bleaching extent in reef-building corals. Ecology. 2009;90:2859–2867. doi: 10.1890/08-0445.1. [DOI] [PubMed] [Google Scholar]
39.Haapkylä J., Unsworth R.K.F., Flavell M., Bourne D.G., Schaffelke B., Willis B.L. Seasonal rainfall and runoff promote coral disease on an inshore reef. PLoS One. 2011;6 doi: 10.1371/journal.pone.0016893. [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Vega Thurber R.L., Burkepile D.E., Fuchs C., Shantz A.A., McMinds R., Zaneveld J.R. Chronic nutrient enrichment increases prevalence and severity of coral disease and bleaching. Glob. Chang. Biol. 2014;20:544–554. doi: 10.1111/gcb.12450. [DOI] [PubMed] [Google Scholar]
41.Wang L., Shantz A.A., Payet J.P., Sharpton T.J., Foster A., Burkepile D.E., Vega Thurber R. Corals and their microbiomes are differentially affected by exposure to elevated nutrients and a natural thermal anomaly. Front. Mar. Sci. 2018;5:101. [Google Scholar]
42.Vega Thurber R., Mydlarz L.D., Brandt M., Harvell D., Weil E., Raymundo L., Willis B.L., Langevin S., Tracy A.M., Littman R., et al. Deciphering coral disease dynamics: integrating host, microbiome, and the changing environment. Front. Ecol. Evol. 2020;8:402. [Google Scholar]
43.Sutherland K.P., Shaban S., Joyner J.L., Porter J.W., Lipp E.K. Human pathogen shown to cause disease in the threatened eklhorn coral Acropora palmata. PLoS One. 2011;6 doi: 10.1371/journal.pone.0023468. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Kaczmarsky L.T., Draud M., Williams E.H. Is there a relationship between proximity to sewage effluent and the prevalence of coral disease. Caribb. J. Sci. 2005;41:124–137. [Google Scholar]
45.Heron S.F., Willis B.L., Skirving W.J., Eakin C.M., Page C.A., Miller I.R. Summer hot snaps and winter conditions: modelling white syndrome outbreaks on Great Barrier Reef corals. PLoS One. 2010;5 doi: 10.1371/journal.pone.0012210. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Anthony S.L., Page C.A., Bourne D.G., Willis B.L. Newly characterized distinct phases of the coral disease ‘atramentous necrosis’ on the Great Barrier Reef. Dis. Aquat. Organ. 2008;81:255–259. doi: 10.3354/dao01962. [DOI] [PubMed] [Google Scholar]
47.Miller M.W., Karazsia J., Groves C.E., Griffin S., Moore T., Wilber P., Gregg K. Detecting sedimentation impacts to coral reefs resulting from dredging the Port of Miami, Florida USA. PeerJ. 2016;4 doi: 10.7717/peerj.2711. [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Manzello D.P. Rapid recent warming of coral reefs in the Florida Keys. Sci. Rep. 2015;5:16762. doi: 10.1038/srep16762. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Roff G., Kvennefors E.C.E., Fine M., Ortiz J., Davy J.E., Hoegh-Guldberg O. The ecology of ‘Acroporid white syndrome’, a coral disease from the southern Great Barrier Reef. PLoS One. 2011;6 doi: 10.1371/journal.pone.0026829. [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Caldwell J.M., Donahue M.J., Harvell C.D. Host size and proximity to diseased neighbours drive the spread of a coral disease outbreak in Hawai ‘i. Proc. Biol. Sci. 2018;285 doi: 10.1098/rspb.2017.2265. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Díaz M., Madin J. Macroecological relationships between coral species’ traits and disease potential. Coral Reefs. 2011;30:73–84. [Google Scholar]
52.Shore-Maggio A., Callahan S.M., Aeby G.S. Trade-offs in disease and bleaching susceptibility among two color morphs of the Hawaiian reef coral, Montipora capitata. Coral Reefs. 2018;37:507–517. [Google Scholar]
53.Greene A., Donahue M.J., Caldwell J.M., Heron S.F., Geiger E., Raymundo L.J. Coral disease time series highlight size-dependent risk and other drivers of white syndrome in a multi-species model. Front. Mar. Sci. 2020;7:1022. [Google Scholar]
54.Ainsworth T.D., Heron S.F., Lantz C.A., Leggat W., Fordyce A.J., Page C.E., Gardner S.G., Caldwell J., Moriarty T. Norfolk Island Lagoonal Reef Ecosystem Health Assessment 2020-2021. Parks Australia; 2021. [Google Scholar]
55.McClanahan T.R., McLaughlin S.M., Davy J.E., Wilson W.H., Peters E.C., Price K.L., Maina J. Observations of a new source of coral mortality along the Kenyan coast. Hydrobiologia. 2004;530–531:469–479. [Google Scholar]
56.Thinesh T., Diraviya Raj K., Mathews G., Patterson Edward J.K. Coral diseases are major contributors to coral mortality in Shingle Island, Gulf of Mannar, southeastern India. Dis. Aquat. Organ. 2013;106:69–77. doi: 10.3354/dao02634. [DOI] [PubMed] [Google Scholar]
57.Subhan B., Arafat D., Rahmawati F., Dasmasela Y., Royhan Q., Madduppa H., Santoso P., Prabowo B. Coral Disease at Mansuar Island, Raja Ampat, Indonesia. IOP Publishing; 2020. [Google Scholar]
58.Haapkylä J., Seymour A., Trebilco J., Smith D. Coral disease prevalence and coral health in the Wakatobi Marine Park, south-east Sulawesi, Indonesia. J. Mar. Biol. Assoc. U. K. 2007;87:403–414. [Google Scholar]
59.Lesser M.P., Bythell J.C., Gates R.D., Johnstone R.W., Hoegh-Guldberg O. Are infectious diseases really killing corals? Alternative interpretations of the experimental and ecological data. J. Exp. Mar. Biol. Ecol. 2007;346:36–44. [Google Scholar]
60.Bythell J., Pantos O., Richardson L. Coral Health and Disease. Springer; 2004. White plague, white band, and other “white” diseases; pp. 351–365. [Google Scholar]
61.Dustan P. Vitality of reef coral populations off Key Largo, Florida: recruitment and mortality. Environ. Geol. 1977;2:51–58. [Google Scholar]
62.Aeby G.S., Williams G.J., Franklin E.C., Kenyon J., Cox E.F., Coles S., Work T.M. Patterns of coral disease across the Hawaiian archipelago: relating disease to environment. PLoS One. 2011;6 doi: 10.1371/journal.pone.0020370. [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Brown T., Sonett D., Zaneveld J.R., Padilla-Gamiño J.L. Characterization of the microbiome and immune response in corals with chronic Montipora white syndrome. Mol. Ecol. 2021;30:2591–2606. doi: 10.1111/mec.15899. [DOI] [PubMed] [Google Scholar]
64.Work T.M., Russell R., Aeby G.S. Tissue loss (white syndrome) in the coral Montipora capitata is a dynamic disease with multiple host responses and potential causes. Proc. Biol. Sci. 2012;279:4334–4341. doi: 10.1098/rspb.2012.1827. [DOI] [PMC free article] [PubMed] [Google Scholar]
65.Ushijima B., Videau P., Burger A.H., Shore-Maggio A., Runyon C.M., Sudek M., Aeby G.S., Callahan S.M. Vibrio coralliilyticus strain OCN008 is an etiological agent of acute Montipora white syndrome. Appl. Environ. Microbiol. 2014;80:2102–2109. doi: 10.1128/AEM.03463-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Muller E.M., Sartor C., Alcaraz N.I., van Woesik R. Spatial epidemiology of the stony-coral-tissue-loss disease in Florida. Front. Mar. Sci. 2020;7:163. [Google Scholar]
67.Alvarez-Filip L., Estrada-Saldívar N., Pérez-Cervantes E., Molina-Hernández A., González-Barrios F.J. A rapid spread of the stony coral tissue loss disease outbreak in the Mexican Caribbean. PeerJ. 2019;7 doi: 10.7717/peerj.8069. [DOI] [PMC free article] [PubMed] [Google Scholar]
68.Page C.A., Willis B.L. Epidemiology of skeletal eroding band on the Great Barrier Reef and the role of injury in the initiation of this widespread coral disease. Coral Reefs. 2008;27:257–272. [Google Scholar]
69.Haapkylä J., Melbourne-Thomas J., Flavell M., Willis B.L. Spatiotemporal patterns of coral disease prevalence on Heron island, great barrier reef, Australia. Coral Reefs. 2010;29:1035–1045. [Google Scholar]
70.Hadaidi G., Ziegler M., Shore-Maggio A., Jensen T., Aeby G., Voolstra C.R. Ecological and molecular characterization of a coral black band disease outbreak in the Red Sea during a bleaching event. PeerJ. 2018;6:e5169. doi: 10.7717/peerj.5169. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Cróquer A., Weil E. Spatial variability in distribution and prevalence of Caribbean scleractinian coral and octocoral diseases. II. Genera-level analysis. Dis. Aquat. Organ. 2009;83:209–222. doi: 10.3354/dao02012. [DOI] [PubMed] [Google Scholar]
72.Yamashiro H., Mikame Y., Suzuki H. Localized outbreak of attached diatoms on the coral Montipora due to low-temperature stress. Sci. Rep. 2012;2:552–554. doi: 10.1038/srep00552. [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Saxby T., Dennison W.C., Hoegh-Guldberg O. Photosynthetic responses of the coral Montipora digitata to cold temperature stress. Mar. Ecol. Prog. Ser. 2003;248:85–97. [Google Scholar]
74.Walton C.J., Hayes N.K., Gilliam D.S. Impacts of a regional, multi-year, multi-species coral disease outbreak in Southeast Florida. Front. Mar. Sci. 2018;5:323. [Google Scholar]
75.Kaczmarsky L., Richardson L.L. Do elevated nutrients and organic carbon on Philippine reefs increase the prevalence of coral disease? Coral Reefs. 2011;30:253–257. [Google Scholar]
76.Abaya L.M., Wiegner T.N., Beets J.P., Colbert S.L., Carlson K.M., Kramer K.L. Spatial distribution of sewage pollution on a Hawaiian coral reef. Mar. Pollut. Bull. 2018;130:335–347. doi: 10.1016/j.marpolbul.2018.03.028. [DOI] [PubMed] [Google Scholar]
77.Dobbelaere T., Muller E.M., Gramer L.J., Holstein D.M., Hanert E. Coupled epidemio-hydrodynamic modeling to understand the spread of a deadly coral disease in Florida. Front. Mar. Sci. 2020;7:1016. [Google Scholar]
78.Page C.E., Leggat W., Heron S.F., Fordyce A.J., Ainsworth T.D. High flow conditions can mediate the damaging impacts of thermal stress on the endosymbiosis in Acropora aspera. Conserv. Physiol. 2021;9:coab046. doi: 10.1093/conphys/coab046. [DOI] [PMC free article] [PubMed] [Google Scholar]
79.Page C.E., Leggat W., Heron S.F., Choukroun S.M., Lloyd J., Ainsworth T.D. Seeking resistance in coral reef ecosystems: the interplay of biophysical factors and bleaching resistance under a changing climate. Bioessays. 2019;41 doi: 10.1002/bies.201800226. [DOI] [PubMed] [Google Scholar]
80.Hodgson G. Tetracycline reduces sedimentation damage to corals. Mar. Biol. 1990;104:493–496. [Google Scholar]
81.Aeby G.S., Santavy D.L. Factors affecting susceptibility of the coral Montastraea faveolata to black-band disease. Mar. Ecol. Prog. Ser. 2006;318:103–110. [Google Scholar]
82.Richmond R.H. Coral reefs: present problems and future concerns resulting from anthropogenic disturbance. Am. Zool. 1993;33:524–536. [Google Scholar]
83.Falkowski P.G., Jokiel P.L., Kinzie R.A. Irradiance and corals. Ecosyst. World. 1990;25:89–107. [Google Scholar]
84.Pastorok R.A., Bilyard G.R. Effects of sewage pollution on coral-reef communities. Mar. Ecol. Prog. Ser. 1985;21:175–189. [Google Scholar]
85.Edmunds P.J. Extent and effect of black band disease on a Caribbean reef. Coral Reefs. 1991;10:161–165. [Google Scholar]
86.Kuta K., Richardson L. Ecological aspects of black band disease of corals: relationships between disease incidence and environmental factors. Coral Reefs. 2002;21:393–398. [Google Scholar]
87.Liu G., Heron S., Eakin C., Muller-Karger F., Vega-Rodriguez M., Guild L., De La Cour J., Geiger E., Skirving W., Burgess T., et al. Reef-scale thermal stress monitoring of coral ecosystems: new 5-km global products from NOAA Coral Reef Watch. Rem. Sens. 2014;6:11579–11606. [Google Scholar]
88.Aeby G., Ushijima B., Bartels E., Walter C., Kuehl J., Jones S., Paul V.J. Changing stony coral tissue loss disease dynamics through time in Montastraea cavernosa. Front. Mar. Sci. 2021;8 [Google Scholar]
89.Pollock F.J., Lamb J.B., van de Water J.A., Smith H.A., Schaffelke B., Willis B.L., Bourne D.G. Reduced diversity and stability of coral-associated bacterial communities and suppressed immune function precedes disease onset in corals. R. Soc. Open Sci. 2019;6 doi: 10.1098/rsos.190355. [DOI] [PMC free article] [PubMed] [Google Scholar]
90.Meesters E.H., Bak R. Age-related deterioration of a physiological function in the branching coral Acropora palmata. Mar. Ecol. Prog. Ser. 1995;121:203–209. [Google Scholar]
91.Moriarty, T., Leggat, W., Heron, S.F., Steinberg, R. and Ainsworth, T.D. (in review). Bleaching, mortality and lengthy recovery on the coral reefs of Lord Howe Island. The 2019 marine heatwave suggests an uncertain future for high-latitude ecosystems. PLOS Climate
92.Skirving W., Marsh B., De La Cour J., Liu G., Harris A., Maturi E., Geiger E., Eakin C.M. CoralTemp and the coral reef watch coral bleaching heat stress product suite version 3.1. Rem. Sens. 2020;12:3856. [Google Scholar]
93.Schneider C.A., Rasband W.S., Eliceiri K.W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods. 2012;9:671–675. doi: 10.1038/nmeth.2089. [DOI] [PMC free article] [PubMed] [Google Scholar]
94.Page C.A., Field S.N., Pollock F.J., Lamb J.B., Shedrawi G., Wilson S.K. Assessing coral health and disease from digital photographs and in situ surveys. Environ. Monit. Assess. 2017;189:1–12. doi: 10.1007/s10661-016-5743-z. [DOI] [PubMed] [Google Scholar]
95.Chen Q., Beijbom O., Chan S., Bouwmeester J., Kriegman D. 2021. A New Deep Learning Engine for CoralNet; pp. 3693–3702. [Google Scholar]
96.R Development Core Team . R Foundation for Statistical Computing; 2010. R: A Language and Environment for Statistical Computing. [Google Scholar]
97.Bates D., Maechler M., Bolker B., Walker S., Christensen R.H.B., Singmann H., Dai B., Scheipl F., Grothendieck G. 2011. Package ‘lme4’. Linear Mixed-Effects Models Using S4 Classes. R package version 1. [Google Scholar]
98.Hartig F., Hartig M.F. 2017. Package ‘DHARMa’. [Google Scholar]
99.Bates D., Maechler M., Bolker B., Walker S. Ftting linear mixed-effects models using lme4. J. Stat. Softw. 2015;67:1–48. [Google Scholar]
100.Douma J.C., Weedon J.T. Analysing continuous proportions in ecology and evolution: a practical introduction to beta and Dirichlet regression. Methods Ecol. Evol. 2019;10:1412–1430. [Google Scholar]
101.Groll A., Groll M.A. 2017. Package ‘glmmLasso’. [Google Scholar]
102.Kassambara A., Mundt F. 2017. Factoextra: Extract and Visualize the Results of Multivariate Data Analyses; pp. 337–354. R package version 1. [Google Scholar]
103.Blighe K., Lewis M., Lun A., Blighe M.K. 2019. Package ‘PCAtools’. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S5 and Tables S1–S3

mmc1.pdf^{(1.3MB, pdf)}

Data Availability Statement

[bib1] 1.Aronson R.B., Precht W.F. The Ecology and Etiology of Newly Emerging Marine Diseases. Springer; 2001. White-band disease and the changing face of Caribbean coral reefs; pp. 25–38. [Google Scholar]

[bib2] 2.Estrada-Saldívar N., Quiroga-García B.A., Pérez-Cervantes E., Rivera-Garibay O.O., Alvarez-Filip L. Effects of the stony coral tissue loss disease outbreak on coral communities and the benthic composition of Cozumel reefs. Front. Mar. Sci. 2021;8:306. [Google Scholar]

[bib3] 3.Heres M.M., Farmer B.H., Elmer F., Hertler H. Ecological consequences of Stony coral tissue loss disease in the Turks and Caicos Islands. Coral Reefs. 2021;40:609–624. [Google Scholar]

[bib4] 4.Jones R.J., Bowyer J., Hoegh-Guldberg O., Blackall L.L. Dynamics of a temperature-related coral disease outbreak. Mar. Ecol. Prog. Ser. 2004;281:63–77. [Google Scholar]

[bib5] 5.Lessios H.A., Cubit J.D., Robertson D.R., Shulman M.J., Parker M.R., Garrity S.D., Levings S.C. Mass mortality of Diadema antillarum on the Caribbean coast of Panama. Coral Reefs. 1984;3:173–182. [Google Scholar]

[bib6] 6.Patterson K.L., Porter J.W., Ritchie K.B., Polson S.W., Mueller E., Peters E.C., Santavy D.L., Smith G.W. The etiology of white pox, a lethal disease of the Caribbean elkhorn coral, Acropora palmata. Proc. Natl. Acad. Sci. USA. 2002;99:8725–8730. doi: 10.1073/pnas.092260099. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib7] 7.Bourne D.G., Ainsworth T.D., Pollock F.J., Willis B.L. Towards a better understanding of white syndromes and their causes on Indo-Pacific coral reefs. Coral Reefs. 2015;34:233–242. [Google Scholar]

[bib8] 8.Work T.M., Aeby G.S. Systematically describing gross lesions in corals. Dis. Aquat. Organ. 2006;70:155–160. doi: 10.3354/dao070155. [DOI] [PubMed] [Google Scholar]

[bib9] 9.Rippe J.P., Kriefall N.G., Davies S.W., Castillo K.D. Differential disease incidence and mortality of inner and outer reef corals of the upper Florida Keys in association with a white syndrome outbreak. Bull. Mar. Sci. 2019;95:305–316. [Google Scholar]

[bib10] 10.Nugues M.M. Impact of a coral disease outbreak on coral communities in St. Lucia: what and how much has been lost? Mar. Ecol. Prog. Ser. 2002;229:61–71. [Google Scholar]

[bib11] 11.Borger J.L., Colley S. The effects of a coral disease on the reproductive output of Montastraea faveolata (Scleractinia: Faviidae) Rev. Biol. Trop. 2010;58:99–110. [PubMed] [Google Scholar]

[bib12] 12.Lirman D. Fragmentation in the branching coral Acropora palmata (Lamarck): growth, survivorship, and reproduction of colonies and fragments. J. Exp. Mar. Biol. Ecol. 2000;251:41–57. doi: 10.1016/s0022-0981(00)00205-7. [DOI] [PubMed] [Google Scholar]

[bib13] 13.Pollock F.J., Wada N., Torda G., Willis B.L., Bourne D.G. White syndrome-affected corals have a distinct microbiome at disease lesion fronts. Appl. Environ. Microbiol. 2017;83:e02799-16. doi: 10.1128/AEM.02799-16. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib14] 14.Willis B.L., Page C.A., Dinsdale E.A. Coral Health and Disease. Springer; 2004. Coral disease on the great barrier reef; pp. 69–104. [Google Scholar]

[bib15] 15.Sutherland K.P., Porter J.W., Torres C. Disease and immunity in Caribbean and Indo-Pacific zooxanthellate corals. Mar. Ecol. Prog. Ser. 2004;266:273–302. [Google Scholar]

[bib16] 16.Harvell D., Jordán-Dahlgren E., Merkel S., Rosenberg E., Raymundo L., Smith G., Weil E., Willis B. Coral disease, environmental drivers, and the balance between coral and microbial associates. Oceanography. 2007;20:172–195. [Google Scholar]

[bib17] 17.Moriarty T., Leggat W., Huggett M.J., Ainsworth T.D. Coral disease causes, consequences, and risk within coral restoration. Trends Microbiol. 2020;28:793–807. doi: 10.1016/j.tim.2020.06.002. [DOI] [PubMed] [Google Scholar]

[bib18] 18.Williams G.J., Aeby G.S., Davy S.K. Coral disease at Palmyra Atoll, a remote reef system in the central Pacific. Coral Reefs. 2008;27:207. [Google Scholar]

[bib19] 19.Miller J., Muller E., Rogers C., Waara R., Atkinson A., Whelan K.R.T., Patterson M., Witcher B. Coral disease following massive bleaching in 2005 causes 60% decline in coral cover on reefs in the US Virgin Islands. Coral Reefs. 2009;28:925–937. [Google Scholar]

[bib20] 20.Dalton S.J., Godwin S., Smith S.D.A., Pereg L. Australian subtropical white syndrome: a transmissible, temperature-dependent coral disease. Mar. Freshw. Res. 2010;61:342–350. [Google Scholar]

[bib21] 21.Dalton S.J., Smith S.D.A. Coral disease dynamics at a subtropical location, Solitary Islands Marine Park, eastern Australia. Coral Reefs. 2006;25:37–45. [Google Scholar]

[bib22] 22.Guinotte J.M., Buddemeier R.W., Kleypas J.A. Future coral reef habitat marginality: temporal and spatial effects of climate change in the Pacific basin. Coral Reefs. 2003;22:551–558. [Google Scholar]

[bib23] 23.Riegl B. Climate change and coral reefs: different effects in two high-latitude areas (Arabian Gulf, South Africa) Coral Reefs. 2003;22:433–446. [Google Scholar]

[bib24] 24.Beger M., Sommer B., Harrison P.L., Smith S.D., Pandolfi J.M. Conserving potential coral reef refuges at high latitudes. Divers. Distrib. 2014;20:245–257. [Google Scholar]

[bib25] 25.Riegl B., Piller W.E. Possible refugia for reefs in times of environmental stress. Int. J. Earth Sci. 2003;92:520–531. [Google Scholar]

[bib26] 26.Jones N.P., Figueiredo J., Gilliam D.S. Thermal stress-related spatiotemporal variations in high-latitude coral reef benthic communities. Coral Reefs. 2020;39:1661–1673. [Google Scholar]

[bib27] 27.Hoegh-Guldberg O., Poloczanska E.S. The effect of climate change across ocean regions. Front. Mar. Sci. 2017;4:361. [Google Scholar]

[bib28] 28.Wear S.L., Thurber R.V. Sewage pollution: mitigation is key for coral reef stewardship. Ann. N. Y. Acad. Sci. 2015;1355:15–30. doi: 10.1111/nyas.12785. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib29] 29.Harborne A.R., Rogers A., Bozec Y.-M., Mumby P.J. Multiple stressors and the functioning of coral reefs. Ann. Rev. Mar. Sci. 2017;9:445–468. doi: 10.1146/annurev-marine-010816-060551. [DOI] [PubMed] [Google Scholar]

[bib30] 30.Darling E.S., McClanahan T.R., Côté I.M. Combined effects of two stressors on Kenyan coral reefs are additive or antagonistic, not synergistic. Conserv. Lett. 2010;3:122–130. [Google Scholar]

[bib31] 31.Bessell-Browne P., Negri A.P., Fisher R., Clode P.L., Jones R. Cumulative impacts: thermally bleached corals have reduced capacity to clear deposited sediment. Sci. Rep. 2017;7:2716. doi: 10.1038/s41598-017-02810-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib32] 32.Ward J.R., Lafferty K.D., Crowder L. The elusive baseline of marine disease: are diseases in ocean ecosystems increasing? PLoS Biol. 2004;2 doi: 10.1371/journal.pbio.0020120. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib33] 33.Aeby G.S., Callahan S., Cox E.F., Runyon C., Smith A., Stanton F.G., Ushijima B., Work T.M. Emerging coral diseases in Kāne ‘ohe Bay, O ‘ahu, Hawai ‘i (USA): two major disease outbreaks of acute Montipora white syndrome. Dis. Aquat. Organ. 2016;119:189–198. doi: 10.3354/dao02996. [DOI] [PubMed] [Google Scholar]

[bib34] 34.Hobbs J.-P.A., Frisch A.J., Newman S.J., Wakefield C.B. Selective impact of disease on coral communities: outbreak of white syndrome causes significant total mortality of Acropora plate corals. PLoS One. 2015;10 doi: 10.1371/journal.pone.0132528. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib35] 35.Precht W.F., Gintert B.E., Robbart M.L., Fura R., Van Woesik R. Unprecedented disease-related coral mortality in Southeastern Florida. Sci. Rep. 2016;6:31374. doi: 10.1038/srep31374. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib36] 36.Bruno J.F., Petes L.E., Drew Harvell C., Hettinger A. Nutrient enrichment can increase the severity of coral diseases. Ecol. Lett. 2003;6:1056–1061. [Google Scholar]

[bib37] 37.Bruno J.F., Selig E.R., Casey K.S., Page C.A., Willis B.L., Harvell C.D., Sweatman H., Melendy A.M. Thermal stress and coral cover as drivers of coral disease outbreaks. PLoS Biol. 2007;5:e124. doi: 10.1371/journal.pbio.0050124. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib38] 38.Brandt M.E., McManus J.W. Disease incidence is related to bleaching extent in reef-building corals. Ecology. 2009;90:2859–2867. doi: 10.1890/08-0445.1. [DOI] [PubMed] [Google Scholar]

[bib39] 39.Haapkylä J., Unsworth R.K.F., Flavell M., Bourne D.G., Schaffelke B., Willis B.L. Seasonal rainfall and runoff promote coral disease on an inshore reef. PLoS One. 2011;6 doi: 10.1371/journal.pone.0016893. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib40] 40.Vega Thurber R.L., Burkepile D.E., Fuchs C., Shantz A.A., McMinds R., Zaneveld J.R. Chronic nutrient enrichment increases prevalence and severity of coral disease and bleaching. Glob. Chang. Biol. 2014;20:544–554. doi: 10.1111/gcb.12450. [DOI] [PubMed] [Google Scholar]

[bib41] 41.Wang L., Shantz A.A., Payet J.P., Sharpton T.J., Foster A., Burkepile D.E., Vega Thurber R. Corals and their microbiomes are differentially affected by exposure to elevated nutrients and a natural thermal anomaly. Front. Mar. Sci. 2018;5:101. [Google Scholar]

[bib42] 42.Vega Thurber R., Mydlarz L.D., Brandt M., Harvell D., Weil E., Raymundo L., Willis B.L., Langevin S., Tracy A.M., Littman R., et al. Deciphering coral disease dynamics: integrating host, microbiome, and the changing environment. Front. Ecol. Evol. 2020;8:402. [Google Scholar]

[bib43] 43.Sutherland K.P., Shaban S., Joyner J.L., Porter J.W., Lipp E.K. Human pathogen shown to cause disease in the threatened eklhorn coral Acropora palmata. PLoS One. 2011;6 doi: 10.1371/journal.pone.0023468. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib44] 44.Kaczmarsky L.T., Draud M., Williams E.H. Is there a relationship between proximity to sewage effluent and the prevalence of coral disease. Caribb. J. Sci. 2005;41:124–137. [Google Scholar]

[bib45] 45.Heron S.F., Willis B.L., Skirving W.J., Eakin C.M., Page C.A., Miller I.R. Summer hot snaps and winter conditions: modelling white syndrome outbreaks on Great Barrier Reef corals. PLoS One. 2010;5 doi: 10.1371/journal.pone.0012210. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib46] 46.Anthony S.L., Page C.A., Bourne D.G., Willis B.L. Newly characterized distinct phases of the coral disease ‘atramentous necrosis’ on the Great Barrier Reef. Dis. Aquat. Organ. 2008;81:255–259. doi: 10.3354/dao01962. [DOI] [PubMed] [Google Scholar]

[bib47] 47.Miller M.W., Karazsia J., Groves C.E., Griffin S., Moore T., Wilber P., Gregg K. Detecting sedimentation impacts to coral reefs resulting from dredging the Port of Miami, Florida USA. PeerJ. 2016;4 doi: 10.7717/peerj.2711. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib48] 48.Manzello D.P. Rapid recent warming of coral reefs in the Florida Keys. Sci. Rep. 2015;5:16762. doi: 10.1038/srep16762. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib49] 49.Roff G., Kvennefors E.C.E., Fine M., Ortiz J., Davy J.E., Hoegh-Guldberg O. The ecology of ‘Acroporid white syndrome’, a coral disease from the southern Great Barrier Reef. PLoS One. 2011;6 doi: 10.1371/journal.pone.0026829. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib50] 50.Caldwell J.M., Donahue M.J., Harvell C.D. Host size and proximity to diseased neighbours drive the spread of a coral disease outbreak in Hawai ‘i. Proc. Biol. Sci. 2018;285 doi: 10.1098/rspb.2017.2265. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib51] 51.Díaz M., Madin J. Macroecological relationships between coral species’ traits and disease potential. Coral Reefs. 2011;30:73–84. [Google Scholar]

[bib52] 52.Shore-Maggio A., Callahan S.M., Aeby G.S. Trade-offs in disease and bleaching susceptibility among two color morphs of the Hawaiian reef coral, Montipora capitata. Coral Reefs. 2018;37:507–517. [Google Scholar]

[bib53] 53.Greene A., Donahue M.J., Caldwell J.M., Heron S.F., Geiger E., Raymundo L.J. Coral disease time series highlight size-dependent risk and other drivers of white syndrome in a multi-species model. Front. Mar. Sci. 2020;7:1022. [Google Scholar]

[bib54] 54.Ainsworth T.D., Heron S.F., Lantz C.A., Leggat W., Fordyce A.J., Page C.E., Gardner S.G., Caldwell J., Moriarty T. Norfolk Island Lagoonal Reef Ecosystem Health Assessment 2020-2021. Parks Australia; 2021. [Google Scholar]

[bib55] 55.McClanahan T.R., McLaughlin S.M., Davy J.E., Wilson W.H., Peters E.C., Price K.L., Maina J. Observations of a new source of coral mortality along the Kenyan coast. Hydrobiologia. 2004;530–531:469–479. [Google Scholar]

[bib56] 56.Thinesh T., Diraviya Raj K., Mathews G., Patterson Edward J.K. Coral diseases are major contributors to coral mortality in Shingle Island, Gulf of Mannar, southeastern India. Dis. Aquat. Organ. 2013;106:69–77. doi: 10.3354/dao02634. [DOI] [PubMed] [Google Scholar]

[bib57] 57.Subhan B., Arafat D., Rahmawati F., Dasmasela Y., Royhan Q., Madduppa H., Santoso P., Prabowo B. Coral Disease at Mansuar Island, Raja Ampat, Indonesia. IOP Publishing; 2020. [Google Scholar]

[bib58] 58.Haapkylä J., Seymour A., Trebilco J., Smith D. Coral disease prevalence and coral health in the Wakatobi Marine Park, south-east Sulawesi, Indonesia. J. Mar. Biol. Assoc. U. K. 2007;87:403–414. [Google Scholar]

[bib59] 59.Lesser M.P., Bythell J.C., Gates R.D., Johnstone R.W., Hoegh-Guldberg O. Are infectious diseases really killing corals? Alternative interpretations of the experimental and ecological data. J. Exp. Mar. Biol. Ecol. 2007;346:36–44. [Google Scholar]

[bib60] 60.Bythell J., Pantos O., Richardson L. Coral Health and Disease. Springer; 2004. White plague, white band, and other “white” diseases; pp. 351–365. [Google Scholar]

[bib61] 61.Dustan P. Vitality of reef coral populations off Key Largo, Florida: recruitment and mortality. Environ. Geol. 1977;2:51–58. [Google Scholar]

[bib62] 62.Aeby G.S., Williams G.J., Franklin E.C., Kenyon J., Cox E.F., Coles S., Work T.M. Patterns of coral disease across the Hawaiian archipelago: relating disease to environment. PLoS One. 2011;6 doi: 10.1371/journal.pone.0020370. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib63] 63.Brown T., Sonett D., Zaneveld J.R., Padilla-Gamiño J.L. Characterization of the microbiome and immune response in corals with chronic Montipora white syndrome. Mol. Ecol. 2021;30:2591–2606. doi: 10.1111/mec.15899. [DOI] [PubMed] [Google Scholar]

[bib64] 64.Work T.M., Russell R., Aeby G.S. Tissue loss (white syndrome) in the coral Montipora capitata is a dynamic disease with multiple host responses and potential causes. Proc. Biol. Sci. 2012;279:4334–4341. doi: 10.1098/rspb.2012.1827. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib65] 65.Ushijima B., Videau P., Burger A.H., Shore-Maggio A., Runyon C.M., Sudek M., Aeby G.S., Callahan S.M. Vibrio coralliilyticus strain OCN008 is an etiological agent of acute Montipora white syndrome. Appl. Environ. Microbiol. 2014;80:2102–2109. doi: 10.1128/AEM.03463-13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib66] 66.Muller E.M., Sartor C., Alcaraz N.I., van Woesik R. Spatial epidemiology of the stony-coral-tissue-loss disease in Florida. Front. Mar. Sci. 2020;7:163. [Google Scholar]

[bib67] 67.Alvarez-Filip L., Estrada-Saldívar N., Pérez-Cervantes E., Molina-Hernández A., González-Barrios F.J. A rapid spread of the stony coral tissue loss disease outbreak in the Mexican Caribbean. PeerJ. 2019;7 doi: 10.7717/peerj.8069. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib68] 68.Page C.A., Willis B.L. Epidemiology of skeletal eroding band on the Great Barrier Reef and the role of injury in the initiation of this widespread coral disease. Coral Reefs. 2008;27:257–272. [Google Scholar]

[bib69] 69.Haapkylä J., Melbourne-Thomas J., Flavell M., Willis B.L. Spatiotemporal patterns of coral disease prevalence on Heron island, great barrier reef, Australia. Coral Reefs. 2010;29:1035–1045. [Google Scholar]

[bib70] 70.Hadaidi G., Ziegler M., Shore-Maggio A., Jensen T., Aeby G., Voolstra C.R. Ecological and molecular characterization of a coral black band disease outbreak in the Red Sea during a bleaching event. PeerJ. 2018;6:e5169. doi: 10.7717/peerj.5169. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib71] 71.Cróquer A., Weil E. Spatial variability in distribution and prevalence of Caribbean scleractinian coral and octocoral diseases. II. Genera-level analysis. Dis. Aquat. Organ. 2009;83:209–222. doi: 10.3354/dao02012. [DOI] [PubMed] [Google Scholar]

[bib72] 72.Yamashiro H., Mikame Y., Suzuki H. Localized outbreak of attached diatoms on the coral Montipora due to low-temperature stress. Sci. Rep. 2012;2:552–554. doi: 10.1038/srep00552. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib73] 73.Saxby T., Dennison W.C., Hoegh-Guldberg O. Photosynthetic responses of the coral Montipora digitata to cold temperature stress. Mar. Ecol. Prog. Ser. 2003;248:85–97. [Google Scholar]

[bib74] 74.Walton C.J., Hayes N.K., Gilliam D.S. Impacts of a regional, multi-year, multi-species coral disease outbreak in Southeast Florida. Front. Mar. Sci. 2018;5:323. [Google Scholar]

[bib75] 75.Kaczmarsky L., Richardson L.L. Do elevated nutrients and organic carbon on Philippine reefs increase the prevalence of coral disease? Coral Reefs. 2011;30:253–257. [Google Scholar]

[bib76] 76.Abaya L.M., Wiegner T.N., Beets J.P., Colbert S.L., Carlson K.M., Kramer K.L. Spatial distribution of sewage pollution on a Hawaiian coral reef. Mar. Pollut. Bull. 2018;130:335–347. doi: 10.1016/j.marpolbul.2018.03.028. [DOI] [PubMed] [Google Scholar]

[bib77] 77.Dobbelaere T., Muller E.M., Gramer L.J., Holstein D.M., Hanert E. Coupled epidemio-hydrodynamic modeling to understand the spread of a deadly coral disease in Florida. Front. Mar. Sci. 2020;7:1016. [Google Scholar]

[bib78] 78.Page C.E., Leggat W., Heron S.F., Fordyce A.J., Ainsworth T.D. High flow conditions can mediate the damaging impacts of thermal stress on the endosymbiosis in Acropora aspera. Conserv. Physiol. 2021;9:coab046. doi: 10.1093/conphys/coab046. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib79] 79.Page C.E., Leggat W., Heron S.F., Choukroun S.M., Lloyd J., Ainsworth T.D. Seeking resistance in coral reef ecosystems: the interplay of biophysical factors and bleaching resistance under a changing climate. Bioessays. 2019;41 doi: 10.1002/bies.201800226. [DOI] [PubMed] [Google Scholar]

[bib80] 80.Hodgson G. Tetracycline reduces sedimentation damage to corals. Mar. Biol. 1990;104:493–496. [Google Scholar]

[bib81] 81.Aeby G.S., Santavy D.L. Factors affecting susceptibility of the coral Montastraea faveolata to black-band disease. Mar. Ecol. Prog. Ser. 2006;318:103–110. [Google Scholar]

[bib82] 82.Richmond R.H. Coral reefs: present problems and future concerns resulting from anthropogenic disturbance. Am. Zool. 1993;33:524–536. [Google Scholar]

[bib83] 83.Falkowski P.G., Jokiel P.L., Kinzie R.A. Irradiance and corals. Ecosyst. World. 1990;25:89–107. [Google Scholar]

[bib84] 84.Pastorok R.A., Bilyard G.R. Effects of sewage pollution on coral-reef communities. Mar. Ecol. Prog. Ser. 1985;21:175–189. [Google Scholar]

[bib85] 85.Edmunds P.J. Extent and effect of black band disease on a Caribbean reef. Coral Reefs. 1991;10:161–165. [Google Scholar]

[bib86] 86.Kuta K., Richardson L. Ecological aspects of black band disease of corals: relationships between disease incidence and environmental factors. Coral Reefs. 2002;21:393–398. [Google Scholar]

[bib87] 87.Liu G., Heron S., Eakin C., Muller-Karger F., Vega-Rodriguez M., Guild L., De La Cour J., Geiger E., Skirving W., Burgess T., et al. Reef-scale thermal stress monitoring of coral ecosystems: new 5-km global products from NOAA Coral Reef Watch. Rem. Sens. 2014;6:11579–11606. [Google Scholar]

[bib88] 88.Aeby G., Ushijima B., Bartels E., Walter C., Kuehl J., Jones S., Paul V.J. Changing stony coral tissue loss disease dynamics through time in Montastraea cavernosa. Front. Mar. Sci. 2021;8 [Google Scholar]

[bib89] 89.Pollock F.J., Lamb J.B., van de Water J.A., Smith H.A., Schaffelke B., Willis B.L., Bourne D.G. Reduced diversity and stability of coral-associated bacterial communities and suppressed immune function precedes disease onset in corals. R. Soc. Open Sci. 2019;6 doi: 10.1098/rsos.190355. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib90] 90.Meesters E.H., Bak R. Age-related deterioration of a physiological function in the branching coral Acropora palmata. Mar. Ecol. Prog. Ser. 1995;121:203–209. [Google Scholar]

[bib91] 91.Moriarty, T., Leggat, W., Heron, S.F., Steinberg, R. and Ainsworth, T.D. (in review). Bleaching, mortality and lengthy recovery on the coral reefs of Lord Howe Island. The 2019 marine heatwave suggests an uncertain future for high-latitude ecosystems. PLOS Climate

[bib92] 92.Skirving W., Marsh B., De La Cour J., Liu G., Harris A., Maturi E., Geiger E., Eakin C.M. CoralTemp and the coral reef watch coral bleaching heat stress product suite version 3.1. Rem. Sens. 2020;12:3856. [Google Scholar]

[bib93] 93.Schneider C.A., Rasband W.S., Eliceiri K.W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods. 2012;9:671–675. doi: 10.1038/nmeth.2089. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib94] 94.Page C.A., Field S.N., Pollock F.J., Lamb J.B., Shedrawi G., Wilson S.K. Assessing coral health and disease from digital photographs and in situ surveys. Environ. Monit. Assess. 2017;189:1–12. doi: 10.1007/s10661-016-5743-z. [DOI] [PubMed] [Google Scholar]

[bib95] 95.Chen Q., Beijbom O., Chan S., Bouwmeester J., Kriegman D. 2021. A New Deep Learning Engine for CoralNet; pp. 3693–3702. [Google Scholar]

[bib96] 96.R Development Core Team . R Foundation for Statistical Computing; 2010. R: A Language and Environment for Statistical Computing. [Google Scholar]

[bib97] 97.Bates D., Maechler M., Bolker B., Walker S., Christensen R.H.B., Singmann H., Dai B., Scheipl F., Grothendieck G. 2011. Package ‘lme4’. Linear Mixed-Effects Models Using S4 Classes. R package version 1. [Google Scholar]

[bib98] 98.Hartig F., Hartig M.F. 2017. Package ‘DHARMa’. [Google Scholar]

[bib99] 99.Bates D., Maechler M., Bolker B., Walker S. Ftting linear mixed-effects models using lme4. J. Stat. Softw. 2015;67:1–48. [Google Scholar]

[bib100] 100.Douma J.C., Weedon J.T. Analysing continuous proportions in ecology and evolution: a practical introduction to beta and Dirichlet regression. Methods Ecol. Evol. 2019;10:1412–1430. [Google Scholar]

[bib101] 101.Groll A., Groll M.A. 2017. Package ‘glmmLasso’. [Google Scholar]

[bib102] 102.Kassambara A., Mundt F. 2017. Factoextra: Extract and Visualize the Results of Multivariate Data Analyses; pp. 337–354. R package version 1. [Google Scholar]

[bib103] 103.Blighe K., Lewis M., Lun A., Blighe M.K. 2019. Package ‘PCAtools’. [Google Scholar]

PERMALINK

A coral disease outbreak highlights vulnerability of remote high-latitude lagoons to global and local stressors

Charlotte E Page

William Leggat

Suhelen Egan

Tracy D Ainsworth

Summary

Graphical abstract

Highlights

Introduction

Results

Environmental conditions

Figure 1.

Disease signs

Figure 2.

Figure 3.

Disease prevalence and severity

Drivers of disease risk

Figure 4.

Discussion

Montiporid White Syndrome signs in Norfolk Island lagoon

A highly prevalent disease outbreak likely associated with exposure to terrestrial pollution

Table 1.

Disease disproportionately impacted the largest colonies

Future considerations and limits to recovery

Limitations of the study

STAR★Methods

Key resources table

Resource availability

Lead contact

Materials availability

Method details

Study site

Disease signs

Disease prevalence and severity

Quantification and statistical analysis

Disease signs

Disease ecological monitoring

Drivers of disease-risk

Acknowledgments

Author contributions

Declaration of interests

Inclusion and diversity

Footnotes

Supplemental information

Data and code availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases