Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PloS one 2021-11, Vol.16 (11), p.e0254723
Hauptverfasser: Park, Isaac W, Mann, Michael L, Flint, Lorraine E, Flint, Alan L, Moritz, Max
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 11
container_start_page e0254723
container_title PloS one
container_volume 16
creator Park, Isaac W
Mann, Michael L
Flint, Lorraine E
Flint, Alan L
Moritz, Max
description In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.
doi_str_mv 10.1371/journal.pone.0254723
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2593006118</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A681151537</galeid><doaj_id>oai_doaj_org_article_8a6a3455c82042fea21bc84dc6b3cd4d</doaj_id><sourcerecordid>A681151537</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-6c55ee3b4a6fa24b3aa725552fb225218ce2f4cf383a060b698cef07db61301e3</originalsourceid><addsrcrecordid>eNqNk11r2zAUhs3YWLtu_2BsgsFg0GT6sGTnZlDCPgKFQvdxK45lKVZxLE-Sw3K9Pz4lcUsMGwxdSBw97yvxck6WvSR4TlhB3t-5wXfQznvX6TmmPC8oe5SdkwWjM0Exe3xyPsuehXCHMWelEE-zM5YXjJACn2e_b3UL0bouNLYPyBmkWruBqC9RM2ygQ6Ci3dq4u0TQ1chYr1FjQ3R-h6JDod-Lo970zkOLtuDtwQ3ZpOy6IdUOkt67CirbJqPk6F0IaAmtNc53Fp5nTwy0Qb8Y94vs-6eP35ZfZtc3n1fLq-uZEgsaZ0JxrjWrchAGaF4xgIJyzqmpKOWUlEpTkyvDSgZY4EosUsXgoq4EYZhodpG9Pvr2rQtyzC9IyhcMY0FImYjVkagd3MnepyT8Tjqw8lBwfi3BR6taLUsQwHLOVUlxTo0GSipV5rUSFVN1XievD-NrQ7XRtdJdTBFNTKc3nW3k2m1lyQUvRJEM3owG3v0cdIj_-PJIrSH9ynbGJTO1sUHJK1ESwglne6_5X6i0ar2xKnWQsak-EbybCBIT9a-4hiEEufp6-__szY8p-_aEbTS0sQmuHQ4tOAXzI3joFq_NQ3IEy_0A3Kch9wMgxwFIslenqT-I7jue_QHK8QNp</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2593006118</pqid></control><display><type>article</type><title>Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Park, Isaac W ; Mann, Michael L ; Flint, Lorraine E ; Flint, Alan L ; Moritz, Max</creator><contributor>Pickell, Paul</contributor><creatorcontrib>Park, Isaac W ; Mann, Michael L ; Flint, Lorraine E ; Flint, Alan L ; Moritz, Max ; Pickell, Paul</creatorcontrib><description>In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0254723</identifier><identifier>PMID: 34731170</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Agriculture ; Analysis ; Building codes ; California ; Carbon footprint ; Causes of ; Climate ; Climate and human activity ; Climate and land use ; Climate and vegetation ; Climate Change ; Climate effects ; Climate models ; Climate variations ; Climatic changes ; Climatic extremes ; Ecology and Environmental Sciences ; Ecosystem ; Ecosystems ; Emissions ; Engineering and Technology ; Environmental accounting ; Environmental aspects ; Fire resistance ; Geospatial data ; Housing ; Human Activities ; Humans ; Influence ; Land use ; Local climates ; Mapping ; Modelling ; People and places ; Physical Sciences ; Population density ; Probability ; Regions ; Residential density ; Scale models ; Spatial distribution ; Sustainability reporting ; Variation ; Vegetation ; Wildfires</subject><ispartof>PloS one, 2021-11, Vol.16 (11), p.e0254723</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-6c55ee3b4a6fa24b3aa725552fb225218ce2f4cf383a060b698cef07db61301e3</citedby><cites>FETCH-LOGICAL-c692t-6c55ee3b4a6fa24b3aa725552fb225218ce2f4cf383a060b698cef07db61301e3</cites><orcidid>0000-0001-5539-1641</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565767/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565767/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34731170$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Pickell, Paul</contributor><creatorcontrib>Park, Isaac W</creatorcontrib><creatorcontrib>Mann, Michael L</creatorcontrib><creatorcontrib>Flint, Lorraine E</creatorcontrib><creatorcontrib>Flint, Alan L</creatorcontrib><creatorcontrib>Moritz, Max</creatorcontrib><title>Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.</description><subject>Agriculture</subject><subject>Analysis</subject><subject>Building codes</subject><subject>California</subject><subject>Carbon footprint</subject><subject>Causes of</subject><subject>Climate</subject><subject>Climate and human activity</subject><subject>Climate and land use</subject><subject>Climate and vegetation</subject><subject>Climate Change</subject><subject>Climate effects</subject><subject>Climate models</subject><subject>Climate variations</subject><subject>Climatic changes</subject><subject>Climatic extremes</subject><subject>Ecology and Environmental Sciences</subject><subject>Ecosystem</subject><subject>Ecosystems</subject><subject>Emissions</subject><subject>Engineering and Technology</subject><subject>Environmental accounting</subject><subject>Environmental aspects</subject><subject>Fire resistance</subject><subject>Geospatial data</subject><subject>Housing</subject><subject>Human Activities</subject><subject>Humans</subject><subject>Influence</subject><subject>Land use</subject><subject>Local climates</subject><subject>Mapping</subject><subject>Modelling</subject><subject>People and places</subject><subject>Physical Sciences</subject><subject>Population density</subject><subject>Probability</subject><subject>Regions</subject><subject>Residential density</subject><subject>Scale models</subject><subject>Spatial distribution</subject><subject>Sustainability reporting</subject><subject>Variation</subject><subject>Vegetation</subject><subject>Wildfires</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11r2zAUhs3YWLtu_2BsgsFg0GT6sGTnZlDCPgKFQvdxK45lKVZxLE-Sw3K9Pz4lcUsMGwxdSBw97yvxck6WvSR4TlhB3t-5wXfQznvX6TmmPC8oe5SdkwWjM0Exe3xyPsuehXCHMWelEE-zM5YXjJACn2e_b3UL0bouNLYPyBmkWruBqC9RM2ygQ6Ci3dq4u0TQ1chYr1FjQ3R-h6JDod-Lo970zkOLtuDtwQ3ZpOy6IdUOkt67CirbJqPk6F0IaAmtNc53Fp5nTwy0Qb8Y94vs-6eP35ZfZtc3n1fLq-uZEgsaZ0JxrjWrchAGaF4xgIJyzqmpKOWUlEpTkyvDSgZY4EosUsXgoq4EYZhodpG9Pvr2rQtyzC9IyhcMY0FImYjVkagd3MnepyT8Tjqw8lBwfi3BR6taLUsQwHLOVUlxTo0GSipV5rUSFVN1XievD-NrQ7XRtdJdTBFNTKc3nW3k2m1lyQUvRJEM3owG3v0cdIj_-PJIrSH9ynbGJTO1sUHJK1ESwglne6_5X6i0ar2xKnWQsak-EbybCBIT9a-4hiEEufp6-__szY8p-_aEbTS0sQmuHQ4tOAXzI3joFq_NQ3IEy_0A3Kch9wMgxwFIslenqT-I7jue_QHK8QNp</recordid><startdate>20211103</startdate><enddate>20211103</enddate><creator>Park, Isaac W</creator><creator>Mann, Michael L</creator><creator>Flint, Lorraine E</creator><creator>Flint, Alan L</creator><creator>Moritz, Max</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-5539-1641</orcidid></search><sort><creationdate>20211103</creationdate><title>Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California</title><author>Park, Isaac W ; Mann, Michael L ; Flint, Lorraine E ; Flint, Alan L ; Moritz, Max</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-6c55ee3b4a6fa24b3aa725552fb225218ce2f4cf383a060b698cef07db61301e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agriculture</topic><topic>Analysis</topic><topic>Building codes</topic><topic>California</topic><topic>Carbon footprint</topic><topic>Causes of</topic><topic>Climate</topic><topic>Climate and human activity</topic><topic>Climate and land use</topic><topic>Climate and vegetation</topic><topic>Climate Change</topic><topic>Climate effects</topic><topic>Climate models</topic><topic>Climate variations</topic><topic>Climatic changes</topic><topic>Climatic extremes</topic><topic>Ecology and Environmental Sciences</topic><topic>Ecosystem</topic><topic>Ecosystems</topic><topic>Emissions</topic><topic>Engineering and Technology</topic><topic>Environmental accounting</topic><topic>Environmental aspects</topic><topic>Fire resistance</topic><topic>Geospatial data</topic><topic>Housing</topic><topic>Human Activities</topic><topic>Humans</topic><topic>Influence</topic><topic>Land use</topic><topic>Local climates</topic><topic>Mapping</topic><topic>Modelling</topic><topic>People and places</topic><topic>Physical Sciences</topic><topic>Population density</topic><topic>Probability</topic><topic>Regions</topic><topic>Residential density</topic><topic>Scale models</topic><topic>Spatial distribution</topic><topic>Sustainability reporting</topic><topic>Variation</topic><topic>Vegetation</topic><topic>Wildfires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Park, Isaac W</creatorcontrib><creatorcontrib>Mann, Michael L</creatorcontrib><creatorcontrib>Flint, Lorraine E</creatorcontrib><creatorcontrib>Flint, Alan L</creatorcontrib><creatorcontrib>Moritz, Max</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Park, Isaac W</au><au>Mann, Michael L</au><au>Flint, Lorraine E</au><au>Flint, Alan L</au><au>Moritz, Max</au><au>Pickell, Paul</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-11-03</date><risdate>2021</risdate><volume>16</volume><issue>11</issue><spage>e0254723</spage><pages>e0254723-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34731170</pmid><doi>10.1371/journal.pone.0254723</doi><tpages>e0254723</tpages><orcidid>https://orcid.org/0000-0001-5539-1641</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-6203
ispartof PloS one, 2021-11, Vol.16 (11), p.e0254723
issn 1932-6203
1932-6203
language eng
recordid cdi_plos_journals_2593006118
source MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry
subjects Agriculture
Analysis
Building codes
California
Carbon footprint
Causes of
Climate
Climate and human activity
Climate and land use
Climate and vegetation
Climate Change
Climate effects
Climate models
Climate variations
Climatic changes
Climatic extremes
Ecology and Environmental Sciences
Ecosystem
Ecosystems
Emissions
Engineering and Technology
Environmental accounting
Environmental aspects
Fire resistance
Geospatial data
Housing
Human Activities
Humans
Influence
Land use
Local climates
Mapping
Modelling
People and places
Physical Sciences
Population density
Probability
Regions
Residential density
Scale models
Spatial distribution
Sustainability reporting
Variation
Vegetation
Wildfires
title Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T12%3A49%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Relationships%20of%20climate,%20human%20activity,%20and%20fire%20history%20to%20spatiotemporal%20variation%20in%20annual%20fire%20probability%20across%20California&rft.jtitle=PloS%20one&rft.au=Park,%20Isaac%20W&rft.date=2021-11-03&rft.volume=16&rft.issue=11&rft.spage=e0254723&rft.pages=e0254723-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0254723&rft_dat=%3Cgale_plos_%3EA681151537%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2593006118&rft_id=info:pmid/34731170&rft_galeid=A681151537&rft_doaj_id=oai_doaj_org_article_8a6a3455c82042fea21bc84dc6b3cd4d&rfr_iscdi=true