Use of artificial landscapes to isolate controls on burn probability |
| |
| Authors: | Marc-André Parisien Carol Miller Alan A Ager Mark A Finney |
| |
| Institution: | (1) Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320 122nd Street, Edmonton, AB, T5H 3S5, Canada;(2) Present address: Department of Environmental Science, Policy and Management, University of California, Berkeley, 137 Mulford Hall 3114, Berkeley, CA 94720, USA;(3) Aldo Leopold Wilderness Research Institute, Rocky Mountain Research Station, USDA Forest Service, 790 E Beckwith Avenue, Missoula, MT 59801, USA;(4) Western Wildlands Environmental Threat Assessment Center, Pacific Northwest Research Station, USDA Forest Service, 3160 NE 3rd Street, Prineville, OR 97754, USA;(5) Missoula Fire Sciences Laboratory, Rocky Mountain Research Station, USDA Forest Service, 5775 W US Highway 10, Missoula, MT 59808, USA |
| |
| Abstract: | Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with
sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite
the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of environmental
factors on BP patterns is not well understood. This study examined the relative effects of ignitions, fuels, and weather on
mean BP and spatial patterns in BP (i.e., BP variability) using highly simplified artificial landscapes and wildfire simulation
methods. Our results showed that a limited set of inputs yielded a wide range of responses in the mean and spatial patterning
of BP. The input factors contributed unequally to mean BP and to BP variability: so-called top-down controls (weather) primarily
influenced mean BP, whereas bottom-up influences (ignitions and fuels) were mainly responsible for the spatial patterns of
BP. However, confounding effects and interactions among factors suggest that fully separating top-down and bottom-up controls
may be impossible. Furthermore, interactions among input variables produced unanticipated but explainable BP patterns, hinting
at complex topological dependencies among the main determinants of fire spread and the resulting BP. The results will improve
our understanding of the spatial ecology of fire regimes and help in the interpretation of patterns of fire likelihood on
real landscapes as part of future wildfire risk assessments. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
