Abstract

Coral reefs are one of the world’s most threatened ecosystems, with global and local stressors contributing to their decline. Excessive sea-surface temperatures (SSTs) can cause coral bleaching, resulting in coral death and decreases in coral cover. A SST threshold of 1 °C over the climatological maximum is widely used to predict coral bleaching. In this study, we refined thermal indices predicting coral bleaching at high-spatial resolution (1 km) by statistically optimizing thermal thresholds, as well as considering other environmental influences on bleaching such as ultraviolet (UV) radiation, water turbidity, and cooling effects. We used a coral bleaching dataset derived from the web-based monitoring system Sango Map Project, at scales appropriate for the local and regional conservation of Japanese coral reefs. We recorded coral bleaching events in the years 2004–2016 in Japan. We revealed the influence of multiple factors on the ability to predict coral bleaching, including selection of thermal indices, statistical optimization of thermal thresholds, quantification of multiple environmental influences, and use of multiple modeling methods (generalized linear models and random forests). After optimization, differences in predictive ability among thermal indices were negligible. Thermal index, UV radiation, water turbidity, and cooling effects were important predictors of the occurrence of coral bleaching. Predictions based on the best model revealed that coral reefs in Japan have experienced recent and widespread bleaching. A practical method to reduce bleaching frequency by screening UV radiation was also demonstrated in this paper.

Highlights

  • Biological communities can shift toward alternative stable states in response to changing climate (Parmesan & Yohe, 2003)

  • Effects of environmental variables Predicted probability of bleaching increased with increasing values of thermal indices, including sea-surface temperatures (SSTs), degree heating month (DHM), degree heating week (DHW), and UV-B (Fig. 2)

  • Predictive performance of coral bleaching models can be improved by the use of optimized thresholds, multiple environmental influences, and multiple modeling methods

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Summary

Introduction

Biological communities can shift toward alternative stable states in response to changing climate (Parmesan & Yohe, 2003). Coral reefs are one of the most susceptible ecosystems to global warming and local environmental stressors (Hoegh-Guldberg, 1999; West & Salm, 2003). Rising sea-surface temperatures (SST) can cause bleaching in reef-building corals, especially during summer (Hoegh-Guldberg, 1999; Brown et al, 2002; West & Salm, 2003). Reef management relies on global measures to reduce climate warming and local measures to control environmental influences on coral resilience (West & Salm, 2003). Spatial and temporal predictions of coral bleaching under varying environmental conditions could provide valuable information to support local management of coral reefs

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