Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/9781

Title: Assessing wildfire risk probability in Pinus pinaster Ait. stands in Portugal.
Authors: Marques, Susete
Botequim, Brigite
Garcia-Gonzalo, Jordi
Borges, José Guilherme
Tomé, Margarida
Oliveira, Manuela
Keywords: forest management
risk
fire occurrence model
Pinus pinaster Ait.
Issue Date: 1-Jan-2012
Publisher: Forest Systems.
Citation: Assessing wildfire risk probability in Pinus pinaster Ait. stands in Portugal. Forest Systems 21: 111-120. Issue: 2012
Abstract: 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 NFI. 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.
URI: http://hdl.handle.net/10174/9781
ISBN: ISSN: 2171-5068. eISSN: 2171-9845.
Type: article
Appears in Collections:CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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