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Ocean warming is increasing the incidence, scale, and severity of global-scale coral bleaching and mortality, culminating in the third global coral bleaching event that occurred during record marine heatwaves of 2014-2017. While local effects of these events have been widely reported, the global implications remain unknown. Analysis of 15,066 reef surveys during 2014-2017 revealed that 80% of surveyed reefs experienced significant coral bleaching and 35% experienced significant coral mortality. The global extent of significant coral bleaching and mortality was assessed by extrapolating results from reef surveys using comprehensive remote-sensing data of regional heat stress. This model predicted that 51% of the world’s coral reefs suffered significant bleaching and 15% significant mortality, surpassing damage from any prior global bleaching event. These observations demonstrate that global warming’s widespread damage to coral reefs is accelerating and underscores the threat anthropogenic climate change poses for the irreversible transformation of these essential ecosystems.

Rising sea temperatures cause mass coral bleaching and threaten reefs worldwide. We show how maps of variations in thermal stress can be used to help manage reefs for climate change. We map proxies of chronic and acute thermal stress and develop evidence-based hypotheses for the future response of corals to each stress regime. We then incorporate spatially realistic predictions of larval connectivity among reefs of the Bahamas and apply novel reserve design algorithms to create reserve networks for a changing climate. We show that scales of larval dispersal are large enough to connect reefs from desirable thermal stress regimes into a reserve network. Critically, we find that reserve designs differ according to the anticipated scope for phenotypic and genetic adaptation in corals, which remains uncertain. Attempts to provide a complete reserve design that hedged against different evolutionary outcomes achieved limited success, which emphasises the importance of considering the scope for adaptation explicitly. Nonetheless, 15% of reserve locations were selected under all evolutionary scenarios, making them a high priority for early designation. Our approach allows new insights into coral holobiont adaptation to be integrated directly into an adaptive approach to management.

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An examination of IKONOS satellite imagery of the Keppel Islands (Great Barrier Reef) acquired before and during a coral bleaching event indicates that severe bleaching of reefs can be detected as an increase in brightness in the band 1 (blue) and band 2 (green) IKONOS spectral bands (4-m resolution). The bleaching was not detected in band 3 (red), band 4 (near-infrared), or in the 1-m panchromatic band data. A total of 0.74 km2 of bleached coral was identified, with detection occurring in waters as deep as 15 m. The procedure requires that one of the scenes be radiometrically normalized to match the reference scene prior to image differencing. A relative radiometric normalization was used in this case because variable cloud cover present in the image acquired during the bleaching event prevented reliable modeling of atmospheric effects. The success at coral bleaching detection at Keppel Islands represents both a “best-case” and a “cloud-challenged” scenario. It was a best-case scenario in that coral cover was extensive (70–90% live coral cover, mostly acroporids) and the bleaching level was extreme (92–95% of coral cover white bleached). It was a cloud-challenged scenario in terms of having extensive and highly variable cloud cover present in the image acquired during the bleaching event. Color difference images reveal extensive areas of bleached coral at sites away from our study area, indicating that this platform and methodology may be a valuable tool for mapping high coral cover areas during bleaching events. Additional studies and technique refinements would be required to test the detection limits of bleaching with IKONOS imagery or to develop a spectrally based bleaching detection index.