Abstract
Controlled burning is a necessary and regular activity in Mkuze Game Reserve, South Africa. Predicting the rate and extent of fire spread in controlled burning operations is, therefore, an important management objective. In this paper we evaluate a cellular automaton model for fire spread in terms of this objective using empirical data for two case studies in Mkuze Game Reserve. Incorporating data relating to factors such as temperature reduction in the early evening, subsequent dew formation and increased fuel moisture content, the model was found to closely resemble the observed fire behaviour.
Highlights
Mkuze Game Reserve (MGR) is a 37 000ha reserve located in northern KwaZulu-Natal (KZN), South Africa (Figure 1), managed by the KZN Wildlife
The region is characterised by an exceptionally high bio-diversity, which is attributed to the high spatial heterogeneity at the landscape level (Goodman, 1990)
Deciding how, where, and when to apply fire depends on the management objectives of the area concerned and the constraints that apply to that case
Summary
Mkuze Game Reserve (MGR) is a 37 000ha reserve located in northern KwaZulu-Natal (KZN), South Africa (Figure 1), managed by the KZN Wildlife. The primary management objectives for MGR is to maintain or enhance spatial heterogeneity, to ensure fodder flow to large mammals, to retard woody plant growth, and to reduce the risk of accidental or arson fires that will threaten the survival of plant species or destroy the composition or structure of a priority vegetation community (Goodman, 1990). Since both lightning and man-induced fire is believed to have played a major role in the development of the vegetation in MGR, fire is applied as a management tool with the intention that natural processes are allowed to prevail over those that are obviously artificial. We evaluate the predictive ability of a cellular automaton model for spatial fire spread (Berjak & Hearne, 2002) for two case studies in MGR
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