globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2625
论文题名:
Projections of climate conditions that increase coral disease susceptibility and pathogen abundance and virulence
作者: Jeffrey Maynard
刊名: Nature Climate Change
ISSN: 1758-923X
EISSN: 1758-7043
出版年: 2015-05-04
卷: Volume:5, 页码:Pages:688;694 (2015)
语种: 英语
英文关键词: Conservation biology ; Tropical ecology
英文摘要:

Rising sea temperatures are likely to increase the frequency of disease outbreaks affecting reef-building corals through impacts on coral hosts and pathogens. We present and compare climate model projections of temperature conditions that will increase coral susceptibility to disease, pathogen abundance and pathogen virulence. Both moderate (RCP 4.5) and fossil fuel aggressive (RCP 8.5) emissions scenarios are examined. We also compare projections for the onset of disease-conducive conditions and severe annual coral bleaching, and produce a disease risk summary that combines climate stress with stress caused by local human activities. There is great spatial variation in the projections, both among and within the major ocean basins, in conditions favouring disease development. Our results indicate that disease is as likely to cause coral mortality as bleaching in the coming decades. These projections identify priority locations to reduce stress caused by local human activities and test management interventions to reduce disease impacts.

The 2014 boreal summer was the warmest on record1, breaking air temperature records in hundreds of cities and causing unprecedented highs in sea surface temperatures in the North Pacific2. Concurrently, a catastrophic outbreak of starfish wasting disease decimated US West Coast populations of ~20 starfish species3 and outbreaks of eelgrass wasting disease resulted in declines in habitat area as high as 90% in parts of California and Washington (Wyllie-Echeverria, personal observation). Pathogens causing these wasting disease outbreaks have been in the environment for at least decades4, although the causative virus for sea-star wasting is newly described3. These recent examples serve as reminders that disease outbreaks can rapidly and extensively devastate populations of keystone species and key habitat builders. Both events also caught the scientific and management communities by surprise, underscoring the importance of developing forecasts and long-term projections of conditions that increase outbreak likelihood.

Forecasts of conditions conducive to disease onset have been most extensively developed for the agricultural crop sector5, 6 because of the economic value of optimizing the timing of pesticide application. Studies presenting longer-term, climate-model-based projections of conditions that promote disease onset for other plants and animals are far more rare. So far, climate models driven by Intergovernmental Panel on Climate Change (IPCC) emissions scenarios have been used only to develop projections of conditions related to the causative agents and vectors of human diseases7, such as malaria8, 9, 10 and Chikungunya virus11. Overall, the science of developing forecasts and projections for wildlife diseases is in its infancy and warrants much greater research focus7, especially in the marine environment, where disease outbreaks have been increasing in frequency and severity over recent decades12.

Climate-related diseases have already severely impacted the primary framework builders of coral reef habitats12, 13, 14, 15. Of the range of bacterial, fungal and protozoan diseases known to affect stony corals16, many have explicit links to temperature, including black band disease17, yellow band disease18, 19 and white syndromes13, 20, 21. Here, we apply the climate models used in the IPCC 5th Assessment Report (see Supplementary Table 1 for list) to project three temperature conditions that increase the susceptibility of coral hosts to disease or increase pathogen abundance or virulence.

We posit that temperature conditions that increase host susceptibility, pathogen abundance and pathogen virulence will substantially increase the likelihood of disease outbreaks once the set threshold frequencies and stress levels are surpassed. The output from the climate model ensemble for each of these three conditions is a projected year by which the target frequency or stress level is reached. All projections are presented for RCP 8.5, the emissions scenario that best characterizes current conditions and emission trends, and for RCP 4.5, which represents a pathway to stabilization at 4.5 W m−2 (~650 ppm CO2 equivalent) after 2100 (ref. 22). Along with the individual projections, we present maps of the earliest and latest projected year one of these three conditions favourable to disease development is projected to occur. We also present: comparisons between the projected timing of these conditions and annual severe coral bleaching, a map of a composite metric of stress caused by local human activities that can also increase host susceptibility, and a map of disease risk under RCP 8.5 that combines global climate and local anthropogenic stress.

The year in which host susceptibility is projected to exceed the set threshold (that is, sublethal bleaching stress three times per decade) varied spatially throughout all reef regions, but with a clear latitudinal trend. Reef locations in the tropics (<23° latitude) suffered thermal stress conducive to disease before subtropical reefs (23°–32.5° latitude), a pattern that was similar under both RCPs (Figs 1a and 2a). There was little variation (<5 years) in the projected timing of this condition among locations in the tropics (Fig. 1a). In contrast, some northern hemisphere subtropical reefs, such as in the Red Sea and Persian Gulf, were projected to experience these conditions ~20 years later than subtropical reefs in the south of Australia and Madagascar. Overall, under both RCP 8.5 and RCP 4.5, the median year this threshold will be surpassed was 2011; most (~76% as of 2014) of the world’s reefs are already experiencing thermal stress potentially conducive to disease outbreaks. Under both RCP 8.5 and RCP 4.5, the metric for increased host susceptibility will be reached at >90% of reef locations by 2020 (Fig. 2a).

Figure 1: Projections of temperature conditions that increase host susceptibility, pathogen abundance and pathogen virulence under RCPs 8.5 and 4.5.
Projections of temperature conditions that increase host susceptibility, pathogen abundance and pathogen virulence under RCPs 8.5 and 4.5.

a, Host susceptibility with the threshold being the first year in which thermal stress first exceeds four DHWs three times per decade. b, Pathogen abundance with the threshold being the first year in which the three cool season months exceed 0.5 °C above the minimum monthly mean (1982–2008). c, Pathogen virulence with the threshold being the first year in which the number of months of temperatures greater than or equal to the maximum monthly mean (1982–2008) is twice that observed on average from 2006 to 2011. See Supplementary Table 1 for a list of climate models.

The same model ensemble for RCP 8.5 was used to project the onset of annual severe bleaching conditions, defined as the year in which eight degree heating weeks (DHWs) is exceeded annually during the warm season23. At present, most corals will bleach once eight DHWs is reached (Fig. 3), and coral diversity and cover are likely to decline drastically when temperature stress of this severity begins to recur with insufficient time for recovery23. We sought to determine whether temperature conditions that favour disease development are projected to occur earlier or later than annual severe coral bleaching. To make this comparison, we calculated the difference in the number of years between the projected timing of any two of the three temperature conditions set here for coral disease and the onset of annual severe bleaching conditions (Fig. 3d). Under RCP 8.5, at least two of the three disease-favouring temperature conditions occurred at 96% of reef locations (Fig. 3d) before the onset of annual severe bleaching (98% under RCP 4.5, Supplementary Fig. 1d). All three conditions occur before the onset of annual severe bleaching at 40% of locations. The comparisons of projected timing of disease versus bleaching conditions offered here suggest disease outbreaks will be at least as great a driver of future coral reef condition and community composition as bleaching.

Anthropogenic stress refers here to local human activities rather than the anthropogenic component of global climate change. Anthropogenic stress is likely to be as important a driver of coral disease dynamics over the coming decades as the temperature conditions presented here24, 25, 26, 27. The integrated local threat (ILT) index28 combines four threats that increase disease susceptibility: increased sedimentation and nutrients associated with coastal development27, 29, 30; watershed-based pollution26, 29, 30, 31, 32; marine-based pollution and damage25, 33, 34; and injuries associated with fishing activities, particularly destructive fishing12. The ILT index (500-m resolution) results are resampled here to match the climate model grid used for the temperature projections and the highest threat level within each model pixel is shown (Fig. 4a). This ensures the global patterns can be seen at the resolution at which the figure is printed within the article.

Figure 4: Anthropogenic stress patterns and disease risk based on exposure to anthropogenic and climate stress.
Anthropogenic stress patterns and disease risk based on exposure to anthropogenic and climate stress.

a, Anthropogenic stress is a resampling of the Reefs at Risk Revisited28 ILT index to the climate model grid used in Figs 1 and 3; the highest value for stress within each model pixel is retained so that approximate global patterns can be interpreted at this resolution. b, Disease risk, in relative terms, relates to whether two or three of the temperature conditions (from Fig. 1) occur before annual severe bleaching (ASB; see Fig. 3c), and anthropogenic stress is high or very high. Reef location (model cell) counts and percentages are as follows and are from the 500-m resolution data, which are presented in Supplementary Fig. 2: Criterion 1 (353,485, 78%), Criterion 2 (35,975, 8%), Criterion 3 (23,378, 5%), Criterion 4 (25,184, 6%), Criterion 5 (13,375, 3%).

These are the first climate-model-based projections of conditions that influence the likelihood of marine disease outbreaks. Some important complexities are necessarily excluded here so that global-scale conservative projections could be produced. The four main examples are: variation among and within coral communities and species in host susceptibility due to variation in genetics related to immunity, the expression of immunity genes, and exposure to environmental disturbances and anthropogenic stress; the potential for coral evolution of resistance, which will be highly variable among and even potentially variable within species; the relationships between temperature conditions and the virulence of other pathogens that cause diseases in stony corals, which are not as well known or understood as Vibrio coralliilyticus and white syndromes; and extreme stochastic events such as extreme climatic events or the evolution of new ‘super’ pathogens, which could invalidate some of the presented conclusions. Other possible conditions that can increase disease susceptibility and pathogen abundance and virulence that are not included here are: sediment runoff and lowered salinity following monsoonal rain events, and coral injuries from cyclones35, 36 or predation by coral-feeding gastropods37, crown-of-thorns starfish38 and reef fish39, 40. Future scenarios that include ocean acidification projections would also be valuable for understanding conditions that increase coral disease susceptibility and pathogen virulence. Members of the research community can use the data presented here to refine or produce higher-resolution projections for areas for which spatially explicit data on some or all of the information described above becomes available.

The standard caveats and assumptions related to the use of climate models also apply41, 42, and two are especially pertinent. First, model resolution is coarse and a 1° × 1° cell can contain many individual coral reefs, a fact related to the computational-intensiveness of climate modelling and to modelling uncertainties (see below). Although spatial variation within single model cells is not resolved here, there is considerable variation within reef regions in the projected timing of all three temperature conditions for disease and in anthropogenic stress. Therefore, even at this resolution, the results can be used to target applied research and management actions. Second, all climate models have uncertainties and vary greatly in their capacity to project trends in key drivers of climate in the tropics, such as the El Niño Southern Oscillation and its global teleconnections. We include the standard deviation around the ensemble average (the ‘model spread’) for each temperature condition (Fig. 2d–i). The spread in the model results is small (standard deviation of 2–6.5 years), which increases confidence in the major conclusions presented based on the ensemble results and supports use of the ensemble rather than one or more of the individual models. A review of the robustness and uncertainties in the new CMIP5 climate model projections (used here) suggests that climate models are improving, representing more climate processes in greater detail, and that the ‘uncertainties should not stop decisions being made’41. For this study, the relevant decisions involve the targeting of actions to reduce anthropogenic stress and trials of the efficacy of interventions that reduce disease impacts and support recovery.

At present, the role of disease as a significant driver of future reef community composition is under-appreciated, especially in the Indo-Pacific, and needs to be given greater consideration for at least two reasons. First, disease has a tendency to result in greater coral mortality than bleaching14, 43, 44. Second, given the strong links between anthropogenic stress and disease susceptibility24, 26, 29, 30, management actions that reduce anthropogenic stress are probably more likely to reduce the prevalence and severity of coral diseases than reduce the impacts of thermal bleaching. Immediate actions to reduce anthropogenic stress are needed at locations with high or very high anthropogenic stress (Fig. 4a), and are especially urgent at locations also predicted to experience all three temperature conditions set here in the coming two decades (Fig. 4b). These sets of conditions apply to ~20% of the reef locations (Fig. 4b, categories 4 and 5). These locations are priority targets for proactive conservation efforts to reduce anthropogenic stress, such as managing watersheds and coastal development, reducing destructive fishing, and addressing other extractive practices. Furthermore, there is a need for collaborative efforts between researchers and managers to both better understand disease outbreaks and test reactive management interventions that reduce disease transmission rates. Examples include quarantining or culling infected corals, which could be followed by actions that mitigate impacts and support recovery such as managing human activities through temporary closures or other use restrictions. Many of these actions (reviewed in refs 45, 46) are at present experimental and feasible only at small local scales. Trials of the efficacy of these actions can lead to broader implementation in the coming decades.

There is also a need for researchers and managers to ex

URL: http://www.nature.com/nclimate/journal/v5/n7/full/nclimate2625.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/4751
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Jeffrey Maynard. Projections of climate conditions that increase coral disease susceptibility and pathogen abundance and virulence[J]. Nature Climate Change,2015-05-04,Volume:5:Pages:688;694 (2015).
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