Fine-Tuning Heat Stress Algorithms to Optimise Global Predictions of Mass Coral Bleaching

Lachs, Liam, Bythell, John C., East, Holly K., Edwards, Alasdair J., Mumby, Peter J., Skirving, William J., Spady, Blake L. and Guest, James R. (2021) Fine-Tuning Heat Stress Algorithms to Optimise Global Predictions of Mass Coral Bleaching. Remote Sensing, 13 (14). p. 2677. ISSN 2072-4292

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Official URL: https://doi.org/10.3390/rs13142677

Abstract

Increasingly intense marine heatwaves threaten the persistence of many marine ecosystems. Heat stress-mediated episodes of mass coral bleaching have led to catastrophic coral mortality globally. Remotely monitoring and forecasting such biotic responses to heat stress is key for effective marine ecosystem management. The Degree Heating Week (DHW) metric, designed to monitor coral bleaching risk, reflects the duration and intensity of heat stress events and is computed by accumulating SST anomalies (HotSpot) relative to a stress threshold over a 12-week moving window. Despite significant improvements in the underlying SST datasets, corresponding revisions of the HotSpot threshold and accumulation window are still lacking. Here, we fine-tune the operational DHW algorithm to optimise coral bleaching predictions using the 5 km satellite-based SSTs (CoralTemp v3.1) and a global coral bleaching dataset (37,871 observations, National Oceanic and Atmospheric Administration). After developing 234 test DHW algorithms with different combinations of the HotSpot threshold and accumulation window, we compared their bleaching prediction ability using spatiotemporal Bayesian hierarchical models and sensitivity–specificity analyses. Peak DHW performance was reached using HotSpot thresholds less than or equal to the maximum of monthly means SST climatology (MMM) and accumulation windows of 4–8 weeks. This new configuration correctly predicted up to an additional 310 bleaching observations globally compared to the operational DHW algorithm, an improved hit rate of 7.9%. Given the detrimental impacts of marine heatwaves across ecosystems, heat stress algorithms could also be fine-tuned for other biological systems, improving scientific accuracy, and enabling ecosystem governance.

Item Type: Article
Uncontrolled Keywords: marine heatwaves, sea surface temperature, mass coral bleaching, algorithm optimisation, spatiotemporal Bayesian modelling, R-INLA
Subjects: F700 Ocean Sciences
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Geography and Environmental Sciences
Depositing User: John Coen
Date Deposited: 09 Jul 2021 13:29
Last Modified: 09 Jul 2021 13:30
URI: http://nrl.northumbria.ac.uk/id/eprint/46644

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