Redirigiendo al acceso original de articulo en 21 segundos...
Inicio  /  Forest Systems  /  Vol: 21 Núm: 1 Par: 0 (2012)  /  Artículo
ARTÍCULO
TITULO

Assessing wildfire occurrence probability in Pinus pinaster Ait. stands in Portugal

S. Marques    
J. Garcia-Gonzalo    
B. Botequim    
A. Ricardo    
J.G. Borges    
M. Tome    
M.M. Oliveira    

Resumen

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.

 Artículos similares

       
 
Laura Lisso, John B. Lindsay and Aaron Berg    
Climate change research identifies risks to agriculture that will impact agricultural land suitability. To mitigate these impacts, agricultural growing regions will need to adapt, diversify, or shift in location. Various machine learning algorithms have ... ver más
Revista: Agronomy

 
Wenfeng Li, Jiao Pan, Wenyi Peng, Yingzhi Li and Chao Li    
Garlic (Allium sativum) is an important economic crop in China. In terms of using remote sensing technology to identify it, there is still room for improvement, and the high-precision classification of garlic has become an important issue. However, to th... ver más
Revista: Agronomy

 
Shuhan Xu, Feng Wang, Yuling Ding, Wenchao Liu, Yiyu Lan, Qingqing Jia, Peng Sun and Zhimin Sha    
Rice?duckweed coculturing as an advanced technique has proven effective for weed control. However, the complex environmental interactions underlying its effectiveness remain unclear. In this study, a controlled pot experiment was conducted to isolate the... ver más
Revista: Agronomy

 
Chunguang Bi, Shuo Zhang, He Chen, Xinhua Bi, Jinjing Liu, Hao Xie, Helong Yu, Shaozhong Song and Lei Shi    
Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classificati... ver más
Revista: Agronomy

 
Seda Sahin and Ayse Torun    
This study was primarily conducted to investigate the potential use of pumpkin seed oil in biodiesel production. Initially, the fatty acid composition of oils extracted from discarded pumpkin seeds was determined. Then, biodiesel produced from discarded ... ver más
Revista: Agriculture