4.5 Article Proceedings Paper

Using simulation to map fire regimes: an evaluation of approaches, strategies, and limitations

期刊

INTERNATIONAL JOURNAL OF WILDLAND FIRE
卷 12, 期 3-4, 页码 309-322

出版社

CSIRO PUBLISHING
DOI: 10.1071/WF03017

关键词

mapping; GIS; LANDSUM; FIRESCAPE; simulation modelling; landscape modelling.

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Spatial depictions of fire regimes are indispensable to fire management because they portray important characteristics of wildland fire, such as severity, intensity, and pattern, across a landscape that serves as important reference for future treatment activities. However, spatially explicit fire regime maps are difficult and costly to create requiring extensive expertise in fire history sampling, multivariate statistics, remotely sensed image classification, fire behaviour and effects, fuel dynamics, landscape ecology, simulation modelling, and geographical information systems (GIS). This paper first compares three common strategies for predicting fire regimes ( classification, empirical, and simulation) using a 51 000 ha landscape in the Selway-BitterrootWilderness Area of Montana, USA. Simulation modelling is identified as the best overall strategy with respect to developing temporally deep spatial fire patterns, but it has limitations. To illustrate these problems, we performed three simulation experiments using the LANDSUM spatial model to determine the relative importance of ( 1) simulation time span; ( 2) fire frequency parameters; and ( 3) fire size parameters on the simulation of landscape fire return interval. The model used to simulate fire regimes is also very important, so we compared two spatially explicit landscape fire succession models ( LANDSUM and FIRESCAPE) to demonstrate differences between model predictions and limitations of each on a neutral landscape. FIRESCAPE was developed for simulating fire regimes in eucalypt forests of south-eastern Australia. Finally, challenges for future simulation and fire regime research are presented including field data, scale, fire regime variability, map obsolescence, and classification resolution.

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