Resilience of Coral-Associated Bacterial Communities Exposed to Fish Farm Effluent

10.1371/journal.pone.0007319PLoS ONE410

Coral disease time series highlight size-dependent risk and other drivers of white syndrome in a multi-species model

Coral diseases contribute to the decline of reef communities, but factors that lead to disease are difficult to detect. In the present study, we develop a multi-species model of colony-scale risk for the class of coral diseases referred to as White Syndromes, investigating the role of current or past conditions, including both environmental stressors and biological drivers at the colony and community scales. Investigating 7 years of coral survey data at five sites in Guam we identify multiple environmental and ecological associations with White Syndrome, including a negative relationship between short-term heat stress and White Syndrome occurrence, and strong evidence of increasing size-dependent White Syndrome risk across coral species. Our findings result in a generalized model used to predict colony-scale White Syndrome risk for multiple species, highlighting the value of long-term monitoring efforts to detect drivers of coral disease

Local-scale projections of coral reef futures and implications of the Paris Agreement

International audienceIncreasingly frequent severe coral bleaching is among the greatest threats to coral reefs posed by climate change. Global climate models (GCMs) project great spatial variation in the timing of annual severe bleaching (ASB) conditions; a point at which reefs are certain to change and recovery will be limited. However, previous model-resolution projections (~1 × 1°) are too coarse to inform conservation planning. To meet the need for higher-resolution projections, we generated statistically downscaled projections (4-km resolution) for all coral reefs; these projections reveal high local-scale variation in ASB. Timing of ASB varies >10 years in 71 of the 87 countries and territories with >500 km 2 of reef area. Emissions scenario RCP4.5 represents lower emissions mid-century than will eventuate if pledges made following the 2015 Paris Climate Change Conference (COP21) become reality. These pledges do little to provide reefs with more time to adapt and acclimate prior to severe bleaching conditions occurring annually. RCP4.5 adds 11 years to the global average ASB timing when compared to RCP8.5; however, >75% of reefs still experience ASB before 2070 under RCP4.5. Coral reef futures clearly vary greatly among and within countries, indicating the projections warrant consideration in most reef areas during conservation and management planning

Assessing relative resilience potential of coral reefs to inform management

International audienceEcological resilience assessments are an important part of resilience-based management (RBM) and can help prioritize and target management actions. Use of such assessments has been limited due to a lack of clear guidance on the assessment process. This study builds on the latest scientific advances in RBM to provide that guidance from a resilience assessment undertaken in the Commonwealth of the Northern Mariana Islands (CNMI). We assessed spatial variation in ecological resilience potential at 78 forereef sites near the populated islands of the CNMI: Saipan, Tinian/Aguijan, and Rota. The assessments are based on measuring indicators of resilience processes and are combined with information on anthropogenic stress and larval connectivity. We find great spatial variation in relative resilience potential with many high resilience sites near Saipan (5 of 7) and low resilience sites near Rota (7 of 9). Criteria were developed to identify priority sites for six types of management actions (e.g., conservation, land-based sources of pollution reduction, and fishery management and enforcement) and 51 of the 78 sites met at least one of the sets of criteria. The connectivity simulations developed indicate that Tinian and Aguijan are each roughly 10 × the larvae source that Rota is and twice as frequent a destination. These results may explain the lower relative resilience potential of Rota reefs and indicates that actions in Saipan and Tinian/Aguijan will be important to maintaining supply of larvae. The process we describe for undertaking resilience assessments can be tailored for use in coral reef areas globally and applied to other ecosystems

Growth anomalies on the coral genera Acropora and Porites are strongly associated with host density and human population size across the Indo-Pacific

Growth anomalies (GAs) are common, tumor-like diseases that can cause significant morbidity and decreased fecundity in the major Indo-Pacific reef-building coral genera, Acropora and Porites. GAs are unusually tractable for testing hypotheses about drivers of coral disease because of their pan-Pacific distributions, relatively high occurrence, and unambiguous ease of identification. We modeled multiple disease-environment associations that may underlie the prevalence of Acropora growth anomalies (AGA) (n = 304 surveys) and Porites growth anomalies (PGA) (n = 602 surveys) from across the Indo-Pacific. Nine predictor variables were modeled, including coral host abundance, human population size, and sea surface temperature and ultra-violet radiation anomalies. Prevalence of both AGAs and PGAs were strongly host density-dependent. PGAs additionally showed strong positive associations with human population size. Although this association has been widely posited, this is one of the first broad-scale studies unambiguously linking a coral disease with human population size. These results emphasize that individual coral diseases can show relatively distinct patterns of association with environmental predictors, even in similar diseases (growth anomalies) found on different host genera (Acropora vs. Porites). As human densities and environmental degradation increase globally, the prevalence of coral diseases like PGAs could increase accordingly, halted only perhaps by declines in host density below thresholds required for disease establishment

Deciphering coral disease dynamics: integrating host, microbiome, and the changing environment

Diseases of tropical reef organisms is an intensive area of study, but despite significant advances in methodology and the global knowledge base, identifying the proximate causes of disease outbreaks remains difficult. The dynamics of infectious wildlife diseases are known to be influenced by shifting interactions among the host, pathogen, and other members of the microbiome, and a collective body of work clearly demonstrates that this is also the case for the main foundation species on reefs, corals. Yet, among wildlife, outbreaks of coral diseases stand out as being driven largely by a changing environment. These outbreaks contributed not only to significant losses of coral species but also to whole ecosystem regime shifts. Here we suggest that to better decipher the disease dynamics of corals, we must integrate more holistic and modern paradigms that consider multiple and variable interactions among the three major players in epizootics: the host, its associated microbiome, and the environment. In this perspective, we discuss how expanding the pathogen component of the classic host-pathogen-environment disease triad to incorporate shifts in the microbiome leading to dysbiosis provides a better model for understanding coral disease dynamics. We outline and discuss issues arising when evaluating each component of this trio and make suggestions for bridging gaps between them. We further suggest that to best tackle these challenges, researchers must adjust standard paradigms, like the classic one pathogen-one disease model, that, to date, have been ineffectual at uncovering many of the emergent properties of coral reef disease dynamics. Lastly, we make recommendations for ways forward in the fields of marine disease ecology and the future of coral reef conservation and restoration given these observations

Water temperature recorded at the Luminao reef flat, Guam, in 2014-2015

This dataset provides water temperature measurements at the Luminao reef flat, Guam, in 2014 to 2015. They were conducted by the Raymundo Lab (University of Guam, Marine Laboratory), using an in situ mounted temperature logger that logged with an hourly resolution. They provide background temperature conditions at the native reef site of the Pocillopora acuta mother colonies' thermal acclimation study. Diurnal temperature characteristics are provided as daily minimum, maximum, and mean temperature values including the standard deviation around mean temperature

Underwater fluorescence on nearshore reefs in Guam during 2014 (Reef Resilience in Guam project)

Dataset: PAM fluorescenceMaximum excitation pressure of Symbiodinium assemblages was assessed as an indicator for holobiont photosynthetic performance of Pocillopora damicornis in shallow (1-2m), back reef and P. eydouxi in deeper fore reef (>3m). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/639986NSF Division of Ocean Sciences (NSF OCE) OCE-141867

Temperature and light intensity at 7 locations from the nearshore reefs in Guam during 2014 (Reef Resilience in Guam project)

Dataset: Temperature and LightTemperature and light intensity data from seven locations from the nearshore reefs in Guam, January to August 2014. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/640026NSF Division of Ocean Sciences (NSF OCE) OCE-141867

Coral health survey from the nearshore reefs in Guam during 2014 (Reef Resilience in Guam project)

Dataset: Coral health surveyCoral health survey from the nearshore reefs in Guam during 2014. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/639879NSF Division of Ocean Sciences (NSF OCE) OCE-141867