Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions
Coral disease outbreaks have increased in frequency and extent worldwide since the 1970s, coinciding with the rapid increase in ocean warming. Summer and winter temperature-based metrics have proven effective in predicting coral disease outbreaks in seasonal coral reef regions. However, their utilit...
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MDPI AG
2025-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/2/262 |
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| author | Momoe Yoshida Scott F. Heron |
| author_facet | Momoe Yoshida Scott F. Heron |
| author_sort | Momoe Yoshida |
| collection | DOAJ |
| description | Coral disease outbreaks have increased in frequency and extent worldwide since the 1970s, coinciding with the rapid increase in ocean warming. Summer and winter temperature-based metrics have proven effective in predicting coral disease outbreaks in seasonal coral reef regions. However, their utility is unknown in non-seasonal coral reef areas. Here, a new methodology, independent of seasonal patterns, is developed for application in both seasonal and non-seasonal coral reef regions. Percentile-based metric thresholds were defined from seasonal equivalents in the Great Barrier Reef (GBR) and tested in seasonal and non-seasonal coral reef regions of the tropical Pacific Ocean. Between new and existing methodologies, median differences of 0.00 °C (thresholds) and 0.00 °C-weeks (metrics) for Hot Snap and Cold Snap; and 0.01 °C (threshold) and −0.17 °C-weeks (metric) for Winter Condition were observed among reef pixels of the GBR. The new methodology shows strong consistency with the existing tools used for seasonal regions (e.g., R<sup>2</sup> = 0.811–0.903; GBR case studies). Comparisons of the new metrics with disease observations were constrained by the limited availability of disease data; however, the comparisons undertaken suggest predictive capability in non-seasonal regions. To establish robust correlations, further direct comparisons of the new metrics with disease data across various non-seasonal regions and timeframes are essential. With ocean warming projected to persist in the coming decades, improving the predictive tools used to assess ecological impacts is necessary to support effective coral reef management. |
| format | Article |
| id | doaj-art-6286a029987e48f28620ca0b39e05d96 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-6286a029987e48f28620ca0b39e05d962025-01-24T13:47:55ZengMDPI AGRemote Sensing2072-42922025-01-0117226210.3390/rs17020262Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef RegionsMomoe Yoshida0Scott F. Heron1Physical Sciences, College of Science and Engineering, James Cook University, Townsville, QLD 4811, AustraliaPhysical Sciences, College of Science and Engineering, James Cook University, Townsville, QLD 4811, AustraliaCoral disease outbreaks have increased in frequency and extent worldwide since the 1970s, coinciding with the rapid increase in ocean warming. Summer and winter temperature-based metrics have proven effective in predicting coral disease outbreaks in seasonal coral reef regions. However, their utility is unknown in non-seasonal coral reef areas. Here, a new methodology, independent of seasonal patterns, is developed for application in both seasonal and non-seasonal coral reef regions. Percentile-based metric thresholds were defined from seasonal equivalents in the Great Barrier Reef (GBR) and tested in seasonal and non-seasonal coral reef regions of the tropical Pacific Ocean. Between new and existing methodologies, median differences of 0.00 °C (thresholds) and 0.00 °C-weeks (metrics) for Hot Snap and Cold Snap; and 0.01 °C (threshold) and −0.17 °C-weeks (metric) for Winter Condition were observed among reef pixels of the GBR. The new methodology shows strong consistency with the existing tools used for seasonal regions (e.g., R<sup>2</sup> = 0.811–0.903; GBR case studies). Comparisons of the new metrics with disease observations were constrained by the limited availability of disease data; however, the comparisons undertaken suggest predictive capability in non-seasonal regions. To establish robust correlations, further direct comparisons of the new metrics with disease data across various non-seasonal regions and timeframes are essential. With ocean warming projected to persist in the coming decades, improving the predictive tools used to assess ecological impacts is necessary to support effective coral reef management.https://www.mdpi.com/2072-4292/17/2/262coral reefssea surface temperaturesatellite SSTHot SnapCold SnapWinter Condition |
| spellingShingle | Momoe Yoshida Scott F. Heron Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions Remote Sensing coral reefs sea surface temperature satellite SST Hot Snap Cold Snap Winter Condition |
| title | Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions |
| title_full | Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions |
| title_fullStr | Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions |
| title_full_unstemmed | Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions |
| title_short | Extending Satellite Predictions of Coral Disease Outbreak Risk to Non-Seasonal Coral Reef Regions |
| title_sort | extending satellite predictions of coral disease outbreak risk to non seasonal coral reef regions |
| topic | coral reefs sea surface temperature satellite SST Hot Snap Cold Snap Winter Condition |
| url | https://www.mdpi.com/2072-4292/17/2/262 |
| work_keys_str_mv | AT momoeyoshida extendingsatellitepredictionsofcoraldiseaseoutbreakrisktononseasonalcoralreefregions AT scottfheron extendingsatellitepredictionsofcoraldiseaseoutbreakrisktononseasonalcoralreefregions |