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Revision as of 20:14, 22 August 2024 by Sky (talk | contribs) (Created page with "{ "USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Fire and tree death: Understanding and improving modeling of fire-induced tree mortality", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70216309", "url": "https://pubs.usgs.gov/publication/70216309" }, {...")
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   "name": "Fire and tree death: Understanding and improving modeling of fire-induced tree mortality",
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   "abstract": "Each year wildland fires kill and injure trees on millions of forested hectares globally, affecting plant and animal biodiversity, carbon storage, hydrologic processes, and ecosystem services. The underlying mechanisms of fire-caused tree mortality remain poorly understood, however, limiting the ability to accurately predict mortality and develop robust modeling applications, especially under novel future climates. Virtually all post-fire tree mortality prediction systems are based on the same underlying empirical model described in Ryan and Reinhardt (1988\u00a0Can. J. For. Res.\u00a018\u00a01291\u20137), which was developed from a limited number of species, stretching model assumptions beyond intended limits. We review the current understanding of the mechanisms of fire-induced tree mortality, provide recommended standardized terminology, describe model applications and limitations, and conclude with key knowledge gaps and future directions for research. We suggest a two-pronged approach to future research: (1) continued improvements and evaluations of empirical models to quantify uncertainty and incorporate new regions and species and (2) acceleration of basic, physiological research on the proximate and ultimate causes of fire-induced tree mortality to incorporate processes of tree death into models. Advances in both empirical and process fire-induced tree modeling will allow creation of hybrid models that could advance understanding of how fire injures and kills trees, while improving prediction accuracy of fire-driven feedbacks on ecosystems and landscapes, particularly under novel future conditions.",
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}

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