High frequency temperature variability reduces the risk of coral bleaching
Safaie, Aryan, Silbiger, Nyssa J., McClanahan, Timothy R., Pawlak, Geno, Barshis, Daniel J., Hench, James L., Rogers, Justin S., Williams, Gareth J., and Davis, Kristen A. (2018) High frequency temperature variability reduces the risk of coral bleaching. Nature Communications, 9. 1671.
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Abstract
Coral bleaching is the detrimental expulsion of algal symbionts from their cnidarian hosts, and predominantly occurs when corals are exposed to thermal stress. The incidence and severity of bleaching is often spatially heterogeneous within reef-scales (<1 km), and is therefore not predictable using conventional remote sensing products. Here, we systematically assess the relationship between in situ measurements of 20 environmental variables, along with seven remotely sensed SST thermal stress metrics, and 81 observed bleaching events at coral reef locations spanning five major reef regions globally. We find that high-frequency temperature variability (i.e., daily temperature range) was the most influential factor in predicting bleaching prevalence and had a mitigating effect, such that a 1 °C increase in daily temperature range would reduce the odds of more severe bleaching by a factor of 33. Our findings suggest that reefs with greater high-frequency temperature variability may represent particularly important opportunities to conserve coral ecosystems against the major threat posed by warming ocean temperatures.
| Item ID: | 59407 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2041-1723 |
| Copyright Information: | © 2018 The Author(s). Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article's Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly fromthe copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
| Funders: | UC Irvine Data Science Initiative, UCI OCEANS Initiative, National Science Foundation (NSF) |
| Projects and Grants: | NSF Award No. 1436254, NSF Award No. 1436522 |
| Date Deposited: | 05 Aug 2020 01:45 |
| FoR Codes: | 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410402 Environmental assessment and monitoring @ 100% |
| SEO Codes: | 96 ENVIRONMENT > 9603 Climate and Climate Change > 960305 Ecosystem Adaptation to Climate Change @ 100% |
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