Abstract

Abstract. Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary – each cell either contains a tree or it is empty – and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.

Highlights

  • Landscapes are dynamic systems that reflect the complex interplay of many factors including climate, natural disturbance, natural succession, economic development and public policy

  • The Modified Forest Fire Model (MFFM) is able to reproduce the variability of the powerlaw parameters of actual fires in both the considered regions

  • As the case studies represent widely divergent, fire-adapted ecosystems (Mediterranean and Sub-tropical), these preliminary results suggest that the methodology developed for the MFFM is robust and promising for future analyses

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Summary

Introduction

Landscapes are dynamic systems that reflect the complex interplay of many factors including climate, natural disturbance, natural succession, economic development and public policy. Forecasts of anticipated future conditions required for landscape planning and public policy will improve as scientists come to understand the slow variables that constrain fast ecological and economic processes (Carpenter and Turner, 2000; Clark et al, 2001). Connectivity in anthropogenic fire regimes can be disrupted by fuel fragmentation (due to factors such as road building or conversion of forests to crop land) and fire suppression effort (Guyette et al, 2002). Because shifts in human cultural traditions cause substantive transitions in fire regimes, it is of great interest to develop methodologies that are capable of simulating the dynamic relationships between vegetation, wildfire, socio-economic factors and public policy. The goal of the modelling strategy is to provide a platform for investigating a suite of public policy issues related to land-use planning, fire management and climate change

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