Journal of Resources and Ecology ›› 2012, Vol. 3 ›› Issue (2): 105-117.DOI: 10.5814/j.issn.1674-764x.2012.02.002

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Probability Models of Fire Risk Based on Forest Fire Indices in Contrasting Climates over China

LI Xiaowei1,2, FU Guobin3, Melanie J. B. ZEPPEL4, YU Xiubo5, ZHAO Gang1,2, Derek EAMUS6, YU Qiang1   

  1. 1 Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
    100101, China;
    2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    3 CSIRO Land and Water, Private Bag 5, Wembley, WA 6913, Australia;
    4 Department of Biological Sciences, Macquarie University, NSW 2109, Australia;
    5 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
    100101, China;
    6 Plant Functional Biology & Climate Change Cluster, School of the Environment, University of Technology, Sydney, NSW 2007, Australia
  • Received:2012-05-03 Revised:2012-05-22 Online:2012-06-30 Published:2012-06-30
  • Supported by:

    this work is supported by the National Basic Research Program, from Ministry of Science and Technology of China (No 2010CB955304).

Abstract: Fire weather indices have been widely applied to predict fire risk in many regions of the world. The objectives of this study were to establish fire risk probability models based on fire indices over different climatic regions in China. We linked the indices adopted in Canadian, US, and Australia with location, time, altitude, vegetation and fire characteristics during 1998-2007 in four regions using semiparametric logistic (SPL) regression models. Different combinations of fire risk indices were selected as explanatory variables for specific regional probability model. SPL regression models of probability of fire ignition and large fire events were established to describe the non-linear relationship between fire risk indices and fire risk probabilities in the four regions. Graphs of observed versus estimated probabilities, fire risk maps, graphs of numbers of large fire events were produced from the probability models to assess the skill of these models. Fire ignition in all regions showed a significant link with altitude and NDVI. Indices of fuel moisture are important factors influencing fire occurrence in northern China. The fuel indices of organic material are significant indicators of fire risk in southern China. Besides the well skill of predicting fire risk, the probability models are a useful method to assess the utility of the fire risk indices in estimating fire events. The analysis presents some of the dynamics of climate-fire interactions and their value for management systems.

Key words: climate, forest fire, meteorological risk, fire risk indices, semi-parametric logistic regression model