Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/4669 |
Resumo: | Maritime pine (Pinus pinaster Ait.) is an important conifer from the western Mediterranean Basin extending over 22% of the forest area in Portugal. In the last three decades nearly 4% of Maritime pine area has been burned by wildfires. Yet no wildfire occurrence probability models are available and forest and fire management planning activities are thus carried out mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a model to assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developing a model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data from the last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004 and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFL Biometric data included indicators that might be changed by operations prescribed in forest planning. Results showed that the probability of wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreases with precipitation and with stand basal area. These results are instrumental for assessing the impact of forest management options on wildfire probability thus helping forest managers to reduce the risk of wildfires |
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Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in PortugalEvaluacion de la probabilidad de ocurrencia de fuegos en rodales de Pinus pinaster Ait en Portugalforest managementriskfire occurrence modelPinus pinasterMaritime pine (Pinus pinaster Ait.) is an important conifer from the western Mediterranean Basin extending over 22% of the forest area in Portugal. In the last three decades nearly 4% of Maritime pine area has been burned by wildfires. Yet no wildfire occurrence probability models are available and forest and fire management planning activities are thus carried out mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a model to assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developing a model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data from the last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004 and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFL Biometric data included indicators that might be changed by operations prescribed in forest planning. Results showed that the probability of wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreases with precipitation and with stand basal area. These results are instrumental for assessing the impact of forest management options on wildfire probability thus helping forest managers to reduce the risk of wildfiresINIARepositório da Universidade de LisboaMarques, S.Garcia-Gonzalo, J.Botequim, B.Ricardo, A.Borges, J.G.Tomé, MargaridaOliveira, M.M.2012-09-14T13:35:39Z20122012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/4669eng"Forest Systems". ISSN 2171-9845. 21(1) (2012) 111-1202171-9845info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:35:38Zoai:www.repository.utl.pt:10400.5/4669Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:52:17.029070Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal Evaluacion de la probabilidad de ocurrencia de fuegos en rodales de Pinus pinaster Ait en Portugal |
title |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
spellingShingle |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal Marques, S. forest management risk fire occurrence model Pinus pinaster |
title_short |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
title_full |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
title_fullStr |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
title_full_unstemmed |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
title_sort |
Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
author |
Marques, S. |
author_facet |
Marques, S. Garcia-Gonzalo, J. Botequim, B. Ricardo, A. Borges, J.G. Tomé, Margarida Oliveira, M.M. |
author_role |
author |
author2 |
Garcia-Gonzalo, J. Botequim, B. Ricardo, A. Borges, J.G. Tomé, Margarida Oliveira, M.M. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Marques, S. Garcia-Gonzalo, J. Botequim, B. Ricardo, A. Borges, J.G. Tomé, Margarida Oliveira, M.M. |
dc.subject.por.fl_str_mv |
forest management risk fire occurrence model Pinus pinaster |
topic |
forest management risk fire occurrence model Pinus pinaster |
description |
Maritime pine (Pinus pinaster Ait.) is an important conifer from the western Mediterranean Basin extending over 22% of the forest area in Portugal. In the last three decades nearly 4% of Maritime pine area has been burned by wildfires. Yet no wildfire occurrence probability models are available and forest and fire management planning activities are thus carried out mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a model to assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developing a model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data from the last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004 and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFL Biometric data included indicators that might be changed by operations prescribed in forest planning. Results showed that the probability of wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreases with precipitation and with stand basal area. These results are instrumental for assessing the impact of forest management options on wildfire probability thus helping forest managers to reduce the risk of wildfires |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-09-14T13:35:39Z 2012 2012-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/4669 |
url |
http://hdl.handle.net/10400.5/4669 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
"Forest Systems". ISSN 2171-9845. 21(1) (2012) 111-120 2171-9845 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
INIA |
publisher.none.fl_str_mv |
INIA |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799130998972088320 |