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Predicting coral bleaching in response to environmental stressors using 8 years of global-scale data

Environmental Monitoring and Assessment volume 161, pages 423–438 (2010)Cite this article

Abstract

Coral reefs have experienced extensive mortality over the past few decades as a result of temperature-induced mass bleaching events. There is an increasing realization that other environmental factors, including water mixing, solar radiation, water depth, and water clarity, interact with temperature to either exacerbate bleaching or protect coral from mass bleaching. The relative contribution of these factors to variability in mass bleaching at a global scale has not been quantified, but can provide insights when making large-scale predictions of mass bleaching events. Using data from 708 bleaching surveys across the globe, a framework was developed to predict the probability of moderate or severe bleaching as a function of key environmental variables derived from global-scale remote-sensing data. The ability of models to explain spatial and temporal variability in mass bleaching events was quantified. Results indicated approximately 20% improved accuracy of predictions of bleaching when solar radiation and water mixing, in addition to elevated temperature, were incorporated into models, but predictive accuracy was variable among regions. Results provide insights into the effects of environmental parameters on bleaching at a global scale.

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  1. United States Environmental Protection Agency, Gulf Ecology Division, National Health and Environmental Effects Research Laboratory, 1 Sabine Island Drive, Gulf Breeze, FL, 32561, USA

    Susan Harrell Yee & Mace G. Barron

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  1. Susan Harrell Yee
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  2. Mace G. Barron
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Correspondence to Susan Harrell Yee.

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Yee, S.H., Barron, M.G. Predicting coral bleaching in response to environmental stressors using 8 years of global-scale data. Environ Monit Assess 161, 423–438 (2010). https://doi.org/10.1007/s10661-009-0758-3

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  • DOI: https://doi.org/10.1007/s10661-009-0758-3

Keywords

  • Coral bleaching
  • Sea surface temperature
  • Solar radiation
  • Logistic regression
  • Model selection
  • Remote sensing