Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal
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. Yetno wildfire occurrence probability models are available and fo...
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Veröffentlicht in: | Forest systems 2012-04, Vol.21 (1), p.111-120 |
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creator | Marques, S. Garcia-Gonzalo, J. Botequim, B. Ricardo, A. Borges, J.G. Tome, M. Oliveira, M.M. |
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. Yetno wildfire occurrence probability models are available and forest and fire management planning activities are thus carriedout mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a modelto assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developinga model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data fromthe last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFI. Biometricdata included indicators that might be changed by operations prescribed in forest planning. Results showed that the probabilityof wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreaseswith precipitation and with stand basal area. These results are instrumental for assessing the impact of forestmanagement options on wildfire probability thus helping forest managers to reduce the risk of wildfires. |
doi_str_mv | 10.5424/fs/2112211-11374 |
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In the last three decades nearly 4% of Maritime pine area has been burned by wildfires. Yetno wildfire occurrence probability models are available and forest and fire management planning activities are thus carriedout mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a modelto assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developinga model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data fromthe last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFI. Biometricdata included indicators that might be changed by operations prescribed in forest planning. Results showed that the probabilityof wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreaseswith precipitation and with stand basal area. These results are instrumental for assessing the impact of forestmanagement options on wildfire probability thus helping forest managers to reduce the risk of wildfires.</description><identifier>ISSN: 2171-5068</identifier><identifier>EISSN: 2171-9845</identifier><identifier>DOI: 10.5424/fs/2112211-11374</identifier><language>eng</language><publisher>Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)</publisher><ispartof>Forest systems, 2012-04, Vol.21 (1), p.111-120</ispartof><rights>LICENCIA DE USO: Los documentos a texto completo incluidos en Dialnet son de acceso libre y propiedad de sus autores y/o editores. 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Any link to this document should be made using its official URL in Dialnet. More info: https://dialnet.unirioja.es/info/derechosOAI</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c268t-f806fa9a91a534ba10a337caf255a6bd43d757dfc10e2dffc38715c2cec4262b3</citedby><cites>FETCH-LOGICAL-c268t-f806fa9a91a534ba10a337caf255a6bd43d757dfc10e2dffc38715c2cec4262b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,874,27924,27925</link.rule.ids></links><search><creatorcontrib>Marques, S.</creatorcontrib><creatorcontrib>Garcia-Gonzalo, J.</creatorcontrib><creatorcontrib>Botequim, B.</creatorcontrib><creatorcontrib>Ricardo, A.</creatorcontrib><creatorcontrib>Borges, J.G.</creatorcontrib><creatorcontrib>Tome, M.</creatorcontrib><creatorcontrib>Oliveira, M.M.</creatorcontrib><title>Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal</title><title>Forest systems</title><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. Yetno wildfire occurrence probability models are available and forest and fire management planning activities are thus carriedout mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a modelto assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developinga model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data fromthe last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFI. Biometricdata included indicators that might be changed by operations prescribed in forest planning. Results showed that the probabilityof wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreaseswith precipitation and with stand basal area. 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In the last three decades nearly 4% of Maritime pine area has been burned by wildfires. Yetno wildfire occurrence probability models are available and forest and fire management planning activities are thus carriedout mostly independently of each other. This paper presents research to address this gap. Specifically, it presents a modelto assess wildfire occurrence probability in regular and pure Maritime pine stands in Portugal. Emphasis was in developinga model based on easily available inventory data so that it might be useful to forest managers. For that purpose, data fromthe last two Portuguese National Forest Inventories (NFI) and data from wildfire perimeters in the years from 1998 to 2004and from 2006 to 2007 were used. A binary logistic regression model was build using biometric data from the NFI. Biometricdata included indicators that might be changed by operations prescribed in forest planning. Results showed that the probabilityof wildfire occurrence in a stand increases in stand located at steeper slopes and with high shrubs load while it decreaseswith precipitation and with stand basal area. These results are instrumental for assessing the impact of forestmanagement options on wildfire probability thus helping forest managers to reduce the risk of wildfires.</abstract><pub>Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)</pub><doi>10.5424/fs/2112211-11374</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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title | Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal |
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