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Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II

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  • Sturtevant, Brian R.
  • Scheller, Robert M.
  • Miranda, Brian R.
  • Shinneman, Douglas
  • Syphard, Alexandra

Abstract

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common.

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  • Sturtevant, Brian R. & Scheller, Robert M. & Miranda, Brian R. & Shinneman, Douglas & Syphard, Alexandra, 2009. "Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II," Ecological Modelling, Elsevier, vol. 220(23), pages 3380-3393.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:23:p:3380-3393
    DOI: 10.1016/j.ecolmodel.2009.07.030
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    References listed on IDEAS

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    1. Meg Krawchuk & Steve Cumming & Mike Flannigan, 2009. "Predicted changes in fire weather suggest increases in lightning fire initiation and future area burned in the mixedwood boreal forest," Climatic Change, Springer, vol. 92(1), pages 83-97, January.
    2. Didion, M. & Fortin, M.-J. & Fall, A., 2007. "Forest age structure as indicator of boreal forest sustainability under alternative management and fire regimes: A landscape level sensitivity analysis," Ecological Modelling, Elsevier, vol. 200(1), pages 45-58.
    3. Scheller, Robert M. & Domingo, James B. & Sturtevant, Brian R. & Williams, Jeremy S. & Rudy, Arnold & Gustafson, Eric J. & Mladenoff, David J., 2007. "Design, development, and application of LANDIS-II, a spatial landscape simulation model with flexible temporal and spatial resolution," Ecological Modelling, Elsevier, vol. 201(3), pages 409-419.
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    Cited by:

    1. Simons-Legaard, Erin & Legaard, Kasey & Weiskittel, Aaron, 2015. "Predicting aboveground biomass with LANDIS-II: A global and temporal analysis of parameter sensitivity," Ecological Modelling, Elsevier, vol. 313(C), pages 325-332.
    2. Gianluigi Busico & Elisabetta Giuditta & Nerantzis Kazakis & Nicolò Colombani, 2019. "A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    3. Conlisk, Erin & Syphard, Alexandra D. & Franklin, Janet & Regan, Helen M., 2015. "Predicting the impact of fire on a vulnerable multi-species community using a dynamic vegetation model," Ecological Modelling, Elsevier, vol. 301(C), pages 27-39.
    4. Inglis, Nicole C. & Vukomanovic, Jelena, 2020. "Climate change disproportionately affects visual quality of cultural ecosystem services in a mountain region," Ecosystem Services, Elsevier, vol. 45(C).
    5. Lucash, Melissa S. & Marshall, Adrienne M. & Weiss, Shelby A. & McNabb, John W. & Nicolsky, Dmitry J. & Flerchinger, Gerald N. & Link, Timothy E. & Vogel, Jason G. & Scheller, Robert M. & Abramoff, Ro, 2023. "Burning trees in frozen soil: Simulating fire, vegetation, soil, and hydrology in the boreal forests of Alaska," Ecological Modelling, Elsevier, vol. 481(C).
    6. Bart, Ryan R. & Kennedy, Maureen C. & Tague, Christina L. & McKenzie, Donald, 2020. "Integrating fire effects on vegetation carbon cycling within an ecohydrologic model," Ecological Modelling, Elsevier, vol. 416(C).
    7. Shruti Sachdeva & Tarunpreet Bhatia & A. K. Verma, 2018. "GIS-based evolutionary optimized Gradient Boosted Decision Trees for forest fire susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(3), pages 1399-1418, July.
    8. Scheller, Robert & Kretchun, Alec & Hawbaker, Todd J. & Henne, Paul D., 2019. "A landscape model of variable social-ecological fire regimes," Ecological Modelling, Elsevier, vol. 401(C), pages 85-93.
    9. Cécile C. Remy & Alisa R. Keyser & Dan J. Krofcheck & Marcy E. Litvak & Matthew D. Hurteau, 2021. "Future fire-driven landscape changes along a southwestern US elevation gradient," Climatic Change, Springer, vol. 166(3), pages 1-20, June.
    10. Kinley Tshering & Phuntsho Thinley & Mahyat Shafapour Tehrany & Ugyen Thinley & Farzin Shabani, 2020. "A Comparison of the Qualitative Analytic Hierarchy Process and the Quantitative Frequency Ratio Techniques in Predicting Forest Fire-Prone Areas in Bhutan Using GIS," Forecasting, MDPI, vol. 2(2), pages 1-23, March.
    11. de Bruijn, Arjan & Gustafson, Eric J. & Sturtevant, Brian R. & Foster, Jane R. & Miranda, Brian R. & Lichti, Nathanael I. & Jacobs, Douglass F., 2014. "Toward more robust projections of forest landscape dynamics under novel environmental conditions: Embedding PnET within LANDIS-II," Ecological Modelling, Elsevier, vol. 287(C), pages 44-57.

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