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William J. Skirving

Researcher at National Oceanic and Atmospheric Administration

Publications -  78
Citations -  9323

William J. Skirving is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Coral bleaching & Coral reef. The author has an hindex of 35, co-authored 73 publications receiving 7413 citations. Previous affiliations of William J. Skirving include James Cook University & Australian Institute of Marine Science.

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Global warming and recurrent mass bleaching of corals

TL;DR: The distinctive geographic footprints of recurrent bleaching on the Great Barrier Reef in 1998, 2002 and 2016 were determined by the spatial pattern of sea temperatures in each year, suggesting that local protection of reefs affords little or no resistance to extreme heat.
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Global warming transforms coral reef assemblages

TL;DR: This study bridges the gap between the theory and practice of assessing the risk of ecosystem collapse, under the emerging framework for the International Union for Conservation of Nature (IUCN) Red List of Ecosystems, by rigorously defining both the initial and collapsed states, identifying the major driver of change, and establishing quantitative collapse thresholds.
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Caribbean corals in crisis: record thermal stress, bleaching, and mortality in 2005.

C. Mark Eakin, +70 more
- 15 Nov 2010 - 
TL;DR: Comparison of satellite data against field surveys demonstrated a significant predictive relationship between accumulated heat stress (measured using NOAA Coral Reef Watch's Degree Heating Weeks) and bleaching intensity.
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Global assessment of coral bleaching and required rates of adaptation under climate change

TL;DR: This article conducted a comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low and high-climate sensitivity GCM.
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A comparison of the 1998 and 2002 coral bleaching events on the Great Barrier Reef: spatial correlation, patterns, and predictions

TL;DR: In this article, the authors examined a wide range of satellite-derived SST variables to determine which one best correlated with the observed bleaching patterns, and found that the maximum SST occurring over any 3-day period (max3d) during the bleaching season predicted bleaching better than anomaly-based variables and that short averaging periods (3-6 days) predicted the presence/absence of bleaching with an accuracy of 732%