Sponsor
Research conducted by Scheller and Kretchun funded by USDA Forest Service Pacific Southwest Research Station, RJVA 17-JV-11272138-007 and 17-JV-11272138-069, respectively. Contributions from U.S. Geological Survey (USGS) authors were supported by the National Biologic Carbon Sequestration Assessment Program under the USGS Land Resources Mission Area. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Josep Serra-Diaz and Brandon Collins provided valuable comments on earlier versions of this manuscript. Jonathan Long and Patricia Manley provided support and guidance throughout the Lake Tahoe West project.
Published In
Ecological Modelling
Document Type
Article
Publication Date
6-2019
Subjects
Forest management -- Environmental aspects, Forests and forestry
Abstract
Fire regimes are now recognized as the product of social processes whereby fire on any landscape is the product of human-generated drivers: climate change, historical patterns of vegetation manipulation, invasive species, active fire suppression, ongoing fuel management efforts, prescribed burning, and accidental ignitions. We developed a new fire model (Social-Climate Related Pyrogenic Processes and their Landscape Effects: SCRPPLE) that emphasizes the social dimensions of fire and enables simulation of fuel-treatment effects, fire suppression, and prescribed fires. Fire behavior was parameterized with daily fire weather, ignition, and fire-boundary data. SCRPPLE was initially parameterized and developed for the Lake Tahoe Basin (LTB) in California and Nevada, USA although its behavior is general and could be applied worldwide. We demonstrate the behavior and utility of our model via four simple scenarios that emphasize the social dimensions of fire regimes: a) Recent Historical: simulated recent historical patterns of lightning and accidental fires and current patterns of fire suppression, b) Natural-Fire-Regime: simulated wildfire without suppression, accidental fires, or prescribed fires, holding all other factors the same as Recent Historical, c) Enhanced Suppression: simulated a doubling of the effectiveness of suppression, holding all other factors the same as Recent Historical, and d) Reduced Accidental Ignitions: within which the number of accidental fires was reduced by half, holding all other factors the same as Recent Historical. Results indicate that SCRPPLE can recreate past fire regimes, including size, intensity, and locations. Furthermore, our results indicate that the ‘Enhanced Suppression’ and ‘Reduced Accidental Ignitions’ scenarios had similar capacity to reduce fire and related tree mortality over time, suggesting that within the broad outlines of the scenarios, reducing accidental fires can be as effective as substantially increasing resources for suppression.
Rights
© 2019 Elsevier B.V. All rights reserved.
This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Locate the Document
DOI
10.1016/j.ecolmodel.2019.03.022
Persistent Identifier
https://archives.pdx.edu/ds/psu/28744
Citation Details
Scheller, R., Kretchun, A., Hawbaker, T. J., & Henne, P. D. (2019). A landscape model of variable social-ecological fire regimes. Ecological Modelling, 401, 85-93.