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Predicting Fire Frequency with Chemistry and Climate

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Abstract

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 MFI as 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.

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Acknowledgments

Development of the PC2FM was supported by the Joint Fire Science Program (Project 06-3-1-16), the National Park Service and Great Plains Cooperative Ecosystem Studies Unit (CESU), and the US Forest Service Northern Research Station. We thank the many authors who have made their work available through publications and the International Multiproxy Paleofire Database (see Supplementary Data 2) as well as the comments provided by reviewers.

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Authors and Affiliations

  1. School of Natural Resources, University of Missouri, Missouri Tree Ring Laboratory, 203 ABNR Building, Columbia, Missouri, 65211, USA

    Richard P. Guyette, Michael C. Stambaugh & Rose-Marie Muzika

  2. Northern Research Station, U.S. Forest Service, Columbia, Missouri, 65211, USA

    Daniel C. Dey

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  1. Richard P. Guyette
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  2. Michael C. Stambaugh
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  3. Daniel C. Dey
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  4. Rose-Marie Muzika
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Correspondence to Richard P. Guyette.

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Author Contributions

RP conceived study, site selection and collection, performed research, chemistry and process model design and analysis, wrote paper; MS contributed to study design, data collection and analysis, mapping, and editing; DD performed research, data collection, wrote paper; RM contributed to data collection, editing, and paper writing.

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Guyette, R.P., Stambaugh, M.C., Dey, D.C. et al. Predicting Fire Frequency with Chemistry and Climate. Ecosystems 15, 322–335 (2012). https://doi.org/10.1007/s10021-011-9512-0

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