Development of customized fire behavior fuel models for boreal forests of northeastern China.
Identifieur interne : 002F30 ( Main/Exploration ); précédent : 002F29; suivant : 002F31Development of customized fire behavior fuel models for boreal forests of northeastern China.
Auteurs : Zhi Wei Wu [République populaire de Chine] ; Hong Shi He ; Yu Chang ; Zhi Hua Liu ; Hong Wei ChenSource :
- Environmental management [ 1432-1009 ] ; 2011.
Descripteurs français
- KwdFr :
- MESH :
- méthodes : Science forêt.
- prévention et contrôle : Catastrophes, Incendies.
- Arbres, Chine, Conservation des ressources naturelles, Modèles théoriques, Temps (météorologie).
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic : China.
- methods : Forestry.
- prevention & control : Disasters, Fires.
- Conservation of Natural Resources, Models, Theoretical, Trees, Weather.
Abstract
Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.
DOI: 10.1007/s00267-011-9707-3
PubMed: 21691875
Affiliations:
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Hua" last="Liu">Zhi Hua Liu</name></author><author><name sortKey="Chen, Hong Wei" sort="Chen, Hong Wei" uniqKey="Chen H" first="Hong Wei" last="Chen">Hong Wei Chen</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2011">2011</date><idno type="RBID">pubmed:21691875</idno><idno type="pmid">21691875</idno><idno type="doi">10.1007/s00267-011-9707-3</idno><idno type="wicri:Area/Main/Corpus">002D67</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">002D67</idno><idno type="wicri:Area/Main/Curation">002D67</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">002D67</idno><idno type="wicri:Area/Main/Exploration">002D67</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Development of customized fire behavior fuel models for boreal forests of northeastern China.</title><author><name sortKey="Wu, Zhi Wei" sort="Wu, Zhi Wei" uniqKey="Wu Z" first="Zhi Wei" last="Wu">Zhi Wei Wu</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016</wicri:regionArea><wicri:noRegion>Shenyang 110016</wicri:noRegion></affiliation></author><author><name sortKey="He, Hong Shi" sort="He, Hong Shi" uniqKey="He H" first="Hong Shi" last="He">Hong Shi He</name></author><author><name sortKey="Chang, Yu" sort="Chang, Yu" uniqKey="Chang Y" first="Yu" last="Chang">Yu Chang</name></author><author><name sortKey="Liu, Zhi Hua" sort="Liu, Zhi Hua" uniqKey="Liu Z" first="Zhi Hua" last="Liu">Zhi Hua Liu</name></author><author><name sortKey="Chen, Hong Wei" sort="Chen, Hong Wei" uniqKey="Chen H" first="Hong Wei" last="Chen">Hong Wei Chen</name></author></analytic><series><title level="j">Environmental management</title><idno 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xml:lang="en"><term>Forestry</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Science forêt</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Disasters</term><term>Fires</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Catastrophes</term><term>Incendies</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Conservation of Natural Resources</term><term>Models, Theoretical</term><term>Trees</term><term>Weather</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Arbres</term><term>Chine</term><term>Conservation des ressources naturelles</term><term>Modèles théoriques</term><term>Temps (météorologie)</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">21691875</PMID><DateCompleted><Year>2012</Year><Month>03</Month><Day>26</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1432-1009</ISSN><JournalIssue CitedMedium="Internet"><Volume>48</Volume><Issue>6</Issue><PubDate><Year>2011</Year><Month>Dec</Month></PubDate></JournalIssue><Title>Environmental management</Title><ISOAbbreviation>Environ Manage</ISOAbbreviation></Journal><ArticleTitle>Development of customized fire behavior fuel models for boreal forests of northeastern China.</ArticleTitle><Pagination><MedlinePgn>1148-57</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s00267-011-9707-3</ELocationID><Abstract><AbstractText>Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wu</LastName><ForeName>Zhi Wei</ForeName><Initials>ZW</Initials><AffiliationInfo><Affiliation>Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>He</LastName><ForeName>Hong Shi</ForeName><Initials>HS</Initials></Author><Author ValidYN="Y"><LastName>Chang</LastName><ForeName>Yu</ForeName><Initials>Y</Initials></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Zhi Hua</ForeName><Initials>ZH</Initials></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Hong Wei</ForeName><Initials>HW</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2011</Year><Month>06</Month><Day>21</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Environ Manage</MedlineTA><NlmUniqueID>7703893</NlmUniqueID><ISSNLinking>0364-152X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003247" MajorTopicYN="N">Conservation of Natural Resources</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004190" MajorTopicYN="N">Disasters</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005390" MajorTopicYN="N">Fires</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016468" MajorTopicYN="N">Forestry</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014197" MajorTopicYN="Y">Trees</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014887" MajorTopicYN="N">Weather</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2010</Year><Month>12</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2011</Year><Month>06</Month><Day>01</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2011</Year><Month>6</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2011</Year><Month>6</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2012</Year><Month>3</Month><Day>27</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">21691875</ArticleId><ArticleId IdType="doi">10.1007/s00267-011-9707-3</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>J Environ Manage. 2003 Jul;68(3):239-52</Citation><ArticleIdList><ArticleId IdType="pubmed">12837253</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><noCountry><name sortKey="Chang, Yu" sort="Chang, Yu" uniqKey="Chang Y" first="Yu" last="Chang">Yu Chang</name><name sortKey="Chen, Hong Wei" sort="Chen, Hong Wei" uniqKey="Chen H" first="Hong Wei" last="Chen">Hong Wei Chen</name><name sortKey="He, Hong Shi" sort="He, Hong Shi" uniqKey="He H" first="Hong Shi" last="He">Hong Shi He</name><name sortKey="Liu, Zhi Hua" sort="Liu, Zhi Hua" uniqKey="Liu Z" first="Zhi Hua" last="Liu">Zhi Hua Liu</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Wu, Zhi Wei" sort="Wu, Zhi Wei" uniqKey="Wu Z" first="Zhi Wei" last="Wu">Zhi Wei Wu</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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