Cited by 383Fire effects on ecosystemsSpecies Distribution and Climate ChangeRangeland and Wildlife Management

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Environmental controls on the distribution of wildfire at multiple spatial scales

Parisien, Marc-André, Moritz, Max A.·2009·Ecological Monographs

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Abstract

Despite its widespread occurrence globally, wildfire preferentially occupies an environmental middle ground and is significantly less prevalent in biomes characterized by environmental extremes (e.g., tundra, rain forests, and deserts). We evaluated the biophysical “environmental space” of wildfire from regional to subcontinental extents, with methods widely used for modeling habitat distributions. This approach is particularly suitable for the biogeographic study of wildfire, because it simultaneously considers patterns in multiple factors controlling wildfire suitability over large areas. We used the Maxent and boosted regression tree algorithms to assess wildfire–environment relationships for three levels of complexity (in terms of inclusion of variables) at three spatial scales: the conterminous United States, the state of California, and five wildfire‐prone ecoregions of California. The resulting models were projected geographically to obtain spatial predictions of wildfire suitability and were also applied to other regions to assess their generality and spatial transferability. Predictions of the potential range of wildfire had high classification accuracy; they also highlighted areas where wildfires had not recently been observed, indicating the potential (or past) suitability of these areas. The models identified several key variables that were not suspected to be important in the large‐scale control of wildfires, but which might indirectly affect control by influencing the presence of flammable vegetation. Models transferred to different areas were useful only when they overlapped appreciably with the target area's environmental space. This approach should allow exploration of the potential shifts in wildfire range in a changing climate, the potential for restoration of wildfire where it has been “extirpated,” and, conversely, the “invasiveness” of wildfire after changes in plant species composition. Our study demonstrates that habitat distribution models and related concepts can be used to characterize environmental controls on a natural disturbance process, but also that future work is needed to refine our understanding of the direct causal factors controlling wildfire at multiple spatial scales.

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Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
Maximum entropy modeling of species geographic distributions
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2005.03.026 · Cited by 15,396
Novel methods improve prediction of species’ distributions from occurrence data
Elith*, J., H. Graham*, C., P. Anderson, R., Dudík, M., Ferrier, S., Guisan, A., J. Hijmans, R., Huettmann, F., R. Leathwick, J., Lehmann, A., et al. (2006) · Ecography · doi:10.1111/j.2006.0906-7590.04596.x · Cited by 9,088
Stochastic gradient boosting
Friedman, J. H. (2002) · Computational Statistics & Data Analysis · doi:10.1016/s0167-9473(01)00065-2 · Cited by 7,067
A review of methods for the assessment of prediction errors in conservation presence/absence models
FIELDING, A. H., & BELL, J. F. (1997) · Environmental Conservation · doi:10.1017/s0376892997000088 · Cited by 6,956
Predicting species distribution: offering more than simple habitat models.
Guisan, A., & Thuiller, W. (2005) · Ecology Letters · doi:10.1111/j.1461-0248.2005.00792.x · Cited by 6,844
A working guide to boosted regression trees
Elith, J., Leathwick, J. R., & Hastie, T. (2008) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2008.01390.x · Cited by 6,484
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
Phillips, S. J., & Dudík, M. (2008) · Ecography · doi:10.1111/j.0906-7590.2008.5203.x · Cited by 5,890
Warming and earlier spring increase western U.S. forest wildfire activity.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., & Swetnam, T. W. (2006) · Science · doi:10.1126/science.1128834 · Cited by 5,176
Fingerprints of global warming on wild animals and plants
Root, T. L., Price, J. T., Hall, K. R., Schneider, S. H., Rosenzweig, C., & Pounds, J. A. (2003) · Nature · doi:10.1038/nature01333 · Cited by 4,774

Show all 132 references

Research works printed but not linked: 16

Bureau of Land Management., 2006, Wildland fire history
Davis F. W., 1998, The California gap analysis project final report
ESRI., 2005, ArcGIS 9.1
Fire and Resource Assessment Program., 2006, Fire perimeters
Griffin J. R., 1972, The distribution of forest trees in California. USDA, Forest Service. Research Paper PSW-82
Kuchler A. W., 1964, American Geographical Society, Special Publication No. 36
10.1130/0091-7613(2000)28<211:VIFFAC>2.0.CO;2 · DOI
PRISM Group., 2004, Climate normals, 1971−2000
Pyne S. J., 1996, Introduction to wildfire. Second edition
10.1023/A:1021584519109 · DOI
Rothermel R. C., 1972, General Technical Report INT-115
Schmidt K. M., 2002, General Technical Report RMRS-GTR-87
Skinner C. N., 1996, Sierra Nevada ecosystem project: final report to Congress, Volume II, Chapter 38, Assessments and scientific basis for management options, 1041
U.S. Geological Survey., 2000, Global 30 arc-second elevation data set
van Wagtendonk J. W., Fire Ecology
10.1111/j.1654-1103.2002.tb02094.x · DOI

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Authors: Parisien, M.-A., & Moritz, M. A.
Affiliations: Canadian Forest Service (CA)
University of California, Berkeley (US)
Corresponding author: Parisien, Marc-André
ORCID: Parisien, Marc-André
Moritz, Max A.
Venue: Ecological Monographs
Publisher: Wiley
Published: 2009-02
Volume: 79
Issue: 1
Pages: 127-154
ISSN: 0012-9615 (ISSN-L)
1557-7015
DOI: 10.1890/07-1289.1
OpenAlex: W2065509880
Cited by: 383
References: 132
Citations by year: 2026: 16 · 2025: 22 · 2024: 13 · 2023: 19 · 2022: 28 · 2021: 32 · 2020: 13 · 2019: 39 · 2018: 22 · 2017: 25 · 2016: 29 · 2015: 24 · 2014: 20 · 2013: 26 · 2012: 20
FWCI: 15.76
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Ecological Monographs (publishedVersion)
Topics: Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
Keywords: forest fires, habitat suitability, spatial scale, climate change, fire restoration, ecoregions, California, spatial transferability, MaxEnt, boosted regression trees

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Environmental controls on the distribution of wildfire at multiple spatial scales

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