Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds
Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, l...
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ftpubmed:oai:pubmedcentral.nih.gov:7062726 2023-05-15T17:32:53+02:00 Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds Hall, Jazlynn Muscarella, Robert Quebbeman, Andrew Arellano, Gabriel Thompson, Jill Zimmerman, Jess K. Uriarte, María 2020-03-09 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062726/ http://www.ncbi.nlm.nih.gov/pubmed/32152355 https://doi.org/10.1038/s41598-020-61164-2 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062726/ http://www.ncbi.nlm.nih.gov/pubmed/32152355 http://dx.doi.org/10.1038/s41598-020-61164-2 © The Author(s) 2020 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 party material in this article are included in the article’s Creative Commons license, unless indicated 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 statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. CC-BY Article Text 2020 ftpubmed https://doi.org/10.1038/s41598-020-61164-2 2020-03-22T01:30:59Z Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems. Text North Atlantic PubMed Central (PMC) Scientific Reports 10 1 |
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Article Hall, Jazlynn Muscarella, Robert Quebbeman, Andrew Arellano, Gabriel Thompson, Jill Zimmerman, Jess K. Uriarte, María Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
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Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems. |
format |
Text |
author |
Hall, Jazlynn Muscarella, Robert Quebbeman, Andrew Arellano, Gabriel Thompson, Jill Zimmerman, Jess K. Uriarte, María |
author_facet |
Hall, Jazlynn Muscarella, Robert Quebbeman, Andrew Arellano, Gabriel Thompson, Jill Zimmerman, Jess K. Uriarte, María |
author_sort |
Hall, Jazlynn |
title |
Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
title_short |
Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
title_full |
Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
title_fullStr |
Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
title_full_unstemmed |
Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds |
title_sort |
hurricane-induced rainfall is a stronger predictor of tropical forest damage in puerto rico than maximum wind speeds |
publisher |
Nature Publishing Group UK |
publishDate |
2020 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062726/ http://www.ncbi.nlm.nih.gov/pubmed/32152355 https://doi.org/10.1038/s41598-020-61164-2 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062726/ http://www.ncbi.nlm.nih.gov/pubmed/32152355 http://dx.doi.org/10.1038/s41598-020-61164-2 |
op_rights |
© The Author(s) 2020 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 party material in this article are included in the article’s Creative Commons license, unless indicated 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 statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
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CC-BY |
op_doi |
https://doi.org/10.1038/s41598-020-61164-2 |
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Scientific Reports |
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10 |
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