Probability models of forest fire risk based on ecology factors in different vegetation regions over China
- Publication Type:
- Journal Article
- Citation:
- Shengtai Xuebao/ Acta Ecologica Sinica, 2013, 33 (4), pp. 1219 - 1229
- Issue Date:
- 2013-03-18
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Forest fires are considered an important disturbance factor for forest ecosystems. Forest fires are influenced by ecological factors. There are different relationships between diverse ecological factors and forest fires in disparate vegetation regions in China. The objectives of this study were two-fold: i) to assess relationships between ecological factors (NDVI and weather elements) and probability of occurrence of fires (i. e. fire risk), and, ii) to establish fire probability models in four contrasting vegetation regions across China. This study covers the monsoonal region where plenty of rainfall is received but significant seasonal variation within dry and wet seasons are characterised by air mass transitions between inland air and oceanic air. The study area was divided into four sub-regions according to their distinct biomes: i) north China plain with a dominant vegetation of deciduous broad- leaved trees; ii) north-east of China dominated by cool temperate coniferous forest; iii) southeast of China dominated by mixed evergreen broadleaf and deciduous broad-leaved forest, and iv) southwest of China dominated by tropical rain forest. Fire data were extracted from the Along Track Scanning Radiometer of the European Space Agency. Daily values of weather elements from 245 stations covering majority of the four climatic regions above were obtained from China Meteorological Administration. Normalized Difference Vegetation Index (NDVI) was applied as a measure of vegetation status. We linked vegetation with location, time, altitude, weather elements, and fire characteristics during 1998-2007 in the four regions above using semi-parametric logistic (SPL) regression models. Non-linear relationships between different ecological factors and fire risk (i. e. probability of fire ignition and occurrence of large fire events) were assessed by semi-parametric logistic regression models. We analyzed characteristics of forest fire activity in the four contrasting vegetation regions across China. NDVI was found to be a significant indicator of probability of fire ignition in all the four forest regions except tropical rain forest. On the other hand, NDVI had a significant effect on probability of occurrence of large fire events in all the three forest regions except for evergreen broadleaf region. There was a significant correlation between probability of fire ignition and altitude. Location was found to have a highly significant effect on fire risk in all the four regions, except for the cool temperate coniferous forest. Mean monthly values of ecological factors had more effect on probability of fire ignition than monthly maximum values of those ecological factors. On the contrary, maximum monthly values of ecological factors had more effect on probability of large fire events than mean monthly values of the ecological factors. For each of the four regions of China, a different model of probability of fire ignition and occurrence of large fire events was established. Graphs of observed versus estimated probabilities of large fire events and fire danger maps were produced from the probability models to assess robustness of these models. The results of these final models with selected ecological factors as explanatory variables seem reasonable. The analysis presents some of the dynamics of ecosystem-fire interactions and their value for management systems.
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