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Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

机译:用泊松模型对加拿大陆地生态系统的大火频率和燃烧面积建模

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Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.
机译:大型野火是严重干扰加拿大北方生态系统的碳循环和植被动态的主要干扰。尽管最近在科学研究中对大型荒地大火进行了详细审查,但对于研究人员来说,预测大火的频率和燃烧面积仍然是一个挑战。在这里,我们使用Poisson模型使用月度气候和海拔数据来量化大火的发生频率,并使用复合Poisson过程计算燃烧面积超过一定大小的概率。我们发现,泊松模型使用月度气候很好地模拟了火灾季节(5月至8月)期间的大火灾,并且复合泊松模型计算的阈值概率与历史记录非常吻合。在加拿大不同的生态区中,阈值概率存在显着差异,其中“ Boreal Shield”生态区始终显示最高的概率。本研究中描述的火灾预测模型和派生的信息将有助于未来火灾风险的量化,并有助于改善该地区的火灾管理。

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