Canadian Forest Service Publications

Comparison of spatially explicit forest landscape fire disturbance models. 2008. Li, Chao; Hans, H.; Barclay, H.J.; Liu, J.; Carlson, G.; Campbell, D. Forest Ecology and Management 254(3): 499-510.

Year: 2008

Issued by: Northern Forestry Centre

Catalog ID: 28085

Language: English

Availability: Order paper copy (free), PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1016/j.foreco.2007.07.022

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Abstract

Comparisons of model behaviors are an efficient way of understanding the differences amongst various models and thus providing guidance to model users for selecting suitable models for their own purposes. This study focuses on a comparison of the most commonly used fire spread algorithms used in scenario fire regime models. This paper provides an overview of fire regime modeling and describes a simulation model, Ecological Disturbance Model, as a simulation shell for such a comparison using the Fort A La Corne forest area in central Saskatchewan, Canada, as the study area. Simulation results suggested that for a fire scenario modeling approach, various fire spread algorithms such as DISPATCH, percolation, and cellular automata (CA) may not result in significant differences between user-defined and simulated fire frequencies; however, significant differences in simulated forest dynamics could result when using different fire spread algorithms. The simulation results from DISPATCH and CA are more similar than those from the percolation algorithm; however, the latter appeared to be a better representative of observed fire spread processes due to its underlying assumption of fire spread mechanisms. Simulation results also suggested that the fire spread algorithms that replicate four or eight direction fire spread in percolation and CA will not make a significant difference in simulated fire regimes or forest dynamics. It is thus recommend that using simulation shells as a tool to take alternative assumptions or models into account to narrow down the uncertainty parameters and avoid the paradoxes in the modeling of natural resource management.