Predicting fire frequency with chemistry and climate.

摘要

A predictive equation for estimating fire frequency was developed from theories and data in physical chemistry, ecosystem ecology, and climatology. We refer to this equation as the Physical Chemistry Fire Frequency Model (PC2FM). The equation was calibrated and validated with North American fire data (170 sites) prior to widespread industrial influences (before ~1850 CE) related to land use, fire suppression, and recent climate change to minimize non-climatic effects. We derived and validated the empirically based PC2FM for the purpose of estimating mean fire intervals (MFIs) from proxies of mean maximum temperature, precipitation, their interaction, and estimated reactant concentrations. Parameterization of the model uses reaction rate equations based on the concentration and physical chemistry of fuels and climate. The model was then calibrated and validated using centuries of empirical fire history data. An application of the PC2FM regression equation is presented and used to estimate historic MFIas controlled by climate. We discuss the effects of temperature, precipitation, and their interactions on fire frequency using the PC2FM concept and results. The exclusion of topographic, vegetation, and ignition variables from the PC2FM increased error at fine spatial scales, but allowed for the prediction of complex climate effects at broader temporal and spatial scales. The PC2FM equation is used to map coarse-scale historic fire frequency and assess climate impacts on landscape-scale fire regimes.