Digital soil mapping for predicting and managing fire in rangelands

Authors: Levi, Matthew; Bestelmeyer, Brandon

Submitted to: Fire Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/25/2018
Publication Date: 12/27/2018
Citation: Levi, M.R., Bestelmeyer, B.T. 2018. Digital soil mapping for predicting and managing fire in rangelands. Fire Ecology. https://doi.org/10.1186/s42408-018-0018-4.
DOI: https://doi.org/10.1186/s42408-018-0018-4

Interpretive Summary: Effects of fire on soil are well documented, but the influence of soil properties on fire is often overlooked. Fire is tightly linked with vegetation and vegetation is strongly influenced by soil-landscape properties, long-term climate, and short-term weather. Coarse scale soil maps limit our understanding of soil-fire linkages. We estimate 3.7 Mkm2 of rangeland in the continental US and Alaska with an average of 12,462 km2 burned per year and present 1) a conceptual framework of why soil information can be useful for fire models, 2) a comprehensive suite of literature examples that used soil property information in traditional soil survey for predicting wildfire, and 3) specific examples of how more detailed soil information can be applied for pre- and post-fire decisions. Digital soil mapping can improve fire prediction models and inform post-fire management decisions.

Technical Abstract: Effects of fire on soil are well documented, but the influence of soil properties on fire is often overlooked in prediction models. Strong linkages between soil properties, vegetation, and climate extend to fire conditions via influences on fuel condition. Utilizing soil-fire linkages is limited by information in conventional soil maps which establishes a premise for utilizing digital soil mapping (DSM) products (e.g., detailed soil property maps) to facilitate wildfire prediction models and post-fire management decisions. We estimate 3.7 Mkm2 of rangeland in the continental US and Alaska with an average of 12,462 km2 burned per year. To highlight the role of soils in fire ecology, we present 1) a conceptual framework of why soil information can be useful for fire models, 2) a comprehensive suite of literature examples that used soil property information in traditional soil survey for predicting wildfire, and 3) specific examples of how more detailed soil information can be applied for pre- and post-fire decisions. DSM can improve fire prediction models and inform post-fire management decisions.