Cargando…
Treating coral bleaching as weather: a framework to validate and optimize prediction skill
Few coral reefs remain unscathed by mass bleaching over the past several decades, and much of the coral reef science conducted today relates in some way to the causes, consequences, or recovery pathways of bleaching events. Most studies portray a simple cause and effect relationship between anomalou...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337031/ https://www.ncbi.nlm.nih.gov/pubmed/32685288 http://dx.doi.org/10.7717/peerj.9449 |
_version_ | 1783554437085659136 |
---|---|
author | DeCarlo, Thomas M. |
author_facet | DeCarlo, Thomas M. |
author_sort | DeCarlo, Thomas M. |
collection | PubMed |
description | Few coral reefs remain unscathed by mass bleaching over the past several decades, and much of the coral reef science conducted today relates in some way to the causes, consequences, or recovery pathways of bleaching events. Most studies portray a simple cause and effect relationship between anomalously high summer temperatures and bleaching, which is understandable given that bleaching rarely occurs outside these unusually warm times. However, the statistical skill with which temperature captures bleaching is hampered by many “false alarms”, times when temperatures reached nominal bleaching levels, but bleaching did not occur. While these false alarms are often not included in global bleaching assessments, they offer valuable opportunities to improve predictive skill, and therefore understanding, of coral bleaching events. Here, I show how a statistical framework adopted from weather forecasting can optimize bleaching predictions and validate which environmental factors play a role in bleaching susceptibility. Removing the 1 °C above the maximum monthly mean cutoff in the typical degree heating weeks (DHW) definition, adjusting the DHW window from 12 to 9 weeks, using regional-specific DHW thresholds, and including an El Niño threshold already improves the model skill by 45%. Most importantly, this framework enables hypothesis testing of other factors or metrics that may improve our ability to forecast coral bleaching events. |
format | Online Article Text |
id | pubmed-7337031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73370312020-07-17 Treating coral bleaching as weather: a framework to validate and optimize prediction skill DeCarlo, Thomas M. PeerJ Conservation Biology Few coral reefs remain unscathed by mass bleaching over the past several decades, and much of the coral reef science conducted today relates in some way to the causes, consequences, or recovery pathways of bleaching events. Most studies portray a simple cause and effect relationship between anomalously high summer temperatures and bleaching, which is understandable given that bleaching rarely occurs outside these unusually warm times. However, the statistical skill with which temperature captures bleaching is hampered by many “false alarms”, times when temperatures reached nominal bleaching levels, but bleaching did not occur. While these false alarms are often not included in global bleaching assessments, they offer valuable opportunities to improve predictive skill, and therefore understanding, of coral bleaching events. Here, I show how a statistical framework adopted from weather forecasting can optimize bleaching predictions and validate which environmental factors play a role in bleaching susceptibility. Removing the 1 °C above the maximum monthly mean cutoff in the typical degree heating weeks (DHW) definition, adjusting the DHW window from 12 to 9 weeks, using regional-specific DHW thresholds, and including an El Niño threshold already improves the model skill by 45%. Most importantly, this framework enables hypothesis testing of other factors or metrics that may improve our ability to forecast coral bleaching events. PeerJ Inc. 2020-07-03 /pmc/articles/PMC7337031/ /pubmed/32685288 http://dx.doi.org/10.7717/peerj.9449 Text en ©2020 DeCarlo https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Conservation Biology DeCarlo, Thomas M. Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title | Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title_full | Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title_fullStr | Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title_full_unstemmed | Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title_short | Treating coral bleaching as weather: a framework to validate and optimize prediction skill |
title_sort | treating coral bleaching as weather: a framework to validate and optimize prediction skill |
topic | Conservation Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337031/ https://www.ncbi.nlm.nih.gov/pubmed/32685288 http://dx.doi.org/10.7717/peerj.9449 |
work_keys_str_mv | AT decarlothomasm treatingcoralbleachingasweatheraframeworktovalidateandoptimizepredictionskill |