期刊
NATURAL HAZARDS
卷 84, 期 3, 页码 2049-2070出版社
SPRINGER
DOI: 10.1007/s11069-016-2533-4
关键词
Trends; Wildfire; GLM; GWR; Human driving factors; Occurrence
资金
- Spanish Ministry of Education FPU grant [13/06618]
Fire regimes are strongly dependent on human activities. Understanding the relative influence of human factors on wildfire is an important ongoing task especially in human-dominated landscapes such as the Mediterranean, where anthropogenic ignitions greatly surpass natural ignitions and human activities are modifying historical fire regimes. Most human drivers of wildfires have a temporal dimension, far beyond the appearance of change, and it is for this reason that we require an historical/temporal analytical perspective coupled to the spatial dimension. In this paper, we investigate and analyze spatial-temporal changes in the contribution of major human factors influencing forest fire occurrence, using Spanish historical statistical fire data from 1988 to 2012. We hypothesize that the influence of socioeconomic drivers on wildfires has changed over this period. Our method is based on fitting yearly explanatory regression models-testing several scenarios of wildfire data aggregation-using logit and Poisson generalized linear models to determine the significance thresholds of the covariates. We then conduct a trend analysis using the Mann-Kendall test to calculate and analyze possible trends in the explanatory power of human driving factors of wildfires. Finally, Geographically Weighted Regression Models are explored to examine potential spatial-temporal patterns. Our results suggest that some of the explanatory factors of logistic models do vary over time and that new explanatory factors might be considered (such as arson-related variables or climate factors), since some of the traditional ones seem to be losing significance in the presence-absence models, opposite to fire frequency models. In particular, the wildland-agricultural interface and wildland-urban interface appear to be losing explanatory power regarding ignition probability, and protected areas are becoming less significant in fire frequency models. GWR models revealed that this temporal behavior is not stationary neither over space nor time.
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