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A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon

The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased hous...

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Autores principales: Schmidt, Andres, Leavell, Daniel, Punches, John, Rocha Ibarra, Marco A., Kagan, James S., Creutzburg, Megan, McCune, Myrica, Salwasser, Janine, Walter, Cara, Berger, Carrie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903305/
https://www.ncbi.nlm.nih.gov/pubmed/35259177
http://dx.doi.org/10.1371/journal.pone.0264826
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author Schmidt, Andres
Leavell, Daniel
Punches, John
Rocha Ibarra, Marco A.
Kagan, James S.
Creutzburg, Megan
McCune, Myrica
Salwasser, Janine
Walter, Cara
Berger, Carrie
author_facet Schmidt, Andres
Leavell, Daniel
Punches, John
Rocha Ibarra, Marco A.
Kagan, James S.
Creutzburg, Megan
McCune, Myrica
Salwasser, Janine
Walter, Cara
Berger, Carrie
author_sort Schmidt, Andres
collection PubMed
description The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased housing density. Furthermore, the associated stress of prolonged droughts and change in land cover/land use puts more population at risk. We present results of a multi-phase Extension Fire Program Initiative combining fire model results based on worst-case meteorological conditions recorded at 50 weather stations across Oregon with spatially distinct valuations of resources and assets based on regional ecological and socio-economic conditions. Our study focuses on six different Fire Service Areas covering the state of Oregon. We used a geostatistical approach to find weather stations that provide worst-case meteorological input data on record for representative sub-domains. The results provide regionally distinct assessments of potential value loss by wildfire and show that, depending on the region, 12% to 52% of the highest relative risk areas are on private land. This underscores the need to unite strategies and efforts on the landscape scale by including different landowners, managers, and stakeholders of public land and private land efficiently address wildfire damage protection and mitigation. Our risk assessments closely agreed with risks identified during landscape-scale ground projects.
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spelling pubmed-89033052022-03-09 A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon Schmidt, Andres Leavell, Daniel Punches, John Rocha Ibarra, Marco A. Kagan, James S. Creutzburg, Megan McCune, Myrica Salwasser, Janine Walter, Cara Berger, Carrie PLoS One Research Article The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased housing density. Furthermore, the associated stress of prolonged droughts and change in land cover/land use puts more population at risk. We present results of a multi-phase Extension Fire Program Initiative combining fire model results based on worst-case meteorological conditions recorded at 50 weather stations across Oregon with spatially distinct valuations of resources and assets based on regional ecological and socio-economic conditions. Our study focuses on six different Fire Service Areas covering the state of Oregon. We used a geostatistical approach to find weather stations that provide worst-case meteorological input data on record for representative sub-domains. The results provide regionally distinct assessments of potential value loss by wildfire and show that, depending on the region, 12% to 52% of the highest relative risk areas are on private land. This underscores the need to unite strategies and efforts on the landscape scale by including different landowners, managers, and stakeholders of public land and private land efficiently address wildfire damage protection and mitigation. Our risk assessments closely agreed with risks identified during landscape-scale ground projects. Public Library of Science 2022-03-08 /pmc/articles/PMC8903305/ /pubmed/35259177 http://dx.doi.org/10.1371/journal.pone.0264826 Text en © 2022 Schmidt et al 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Schmidt, Andres
Leavell, Daniel
Punches, John
Rocha Ibarra, Marco A.
Kagan, James S.
Creutzburg, Megan
McCune, Myrica
Salwasser, Janine
Walter, Cara
Berger, Carrie
A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title_full A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title_fullStr A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title_full_unstemmed A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title_short A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
title_sort quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—a case study in oregon
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903305/
https://www.ncbi.nlm.nih.gov/pubmed/35259177
http://dx.doi.org/10.1371/journal.pone.0264826
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