Archibald S., Nickless A., Scholes R.J., Schulze R.
Natural Resources and the Environment, Council for Scientific and Industrial Research (CSIR), PO Box 395, Pretoria 0001, South Africa; Animal Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, Johannesburg 2050, South Africa; School of Bioresources Engineering and Environmental Hydrology, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
Archibald, S., Natural Resources and the Environment, Council for Scientific and Industrial Research (CSIR), PO Box 395, Pretoria 0001, South Africa, Animal Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, Johannesburg 2050, South Africa; Nickless, A., Natural Resources and the Environment, Council for Scientific and Industrial Research (CSIR), PO Box 395, Pretoria 0001, South Africa; Scholes, R.J., Natural Resources and the Environment, Council for Scientific and Industrial Research (CSIR), PO Box 395, Pretoria 0001, South Africa, Animal Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, Johannesburg 2050, South Africa; Schulze, R., School of Bioresources Engineering and Environmental Hydrology, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
In southern African savannas, grass production, and therefore the annual extent of fire, is highly dependent on rainfall. This response has repeatedly been noted in the literature but authors used different input variables and modelling approaches and the results are not comparable. Using long-term fire occurrence data from six protected areas in southern Africa we tested various methods for determining the relationship between antecedent rainfall and burned area. The types of regression model, the most appropriate index of accumulated rainfall, and the period over which to calculate annual burned area were all investigated. The importance of accumulating rainfall over more than one growing season was verified in all parks - improving the accuracy of the models by up to 30% compared with indices that only used the previous year's rainfall. Up to 56% of the variance in burned area between years could be explained by an 18-month accumulated rainfall index. Linear models and probit models performed equally well. The method suggested in this paper can be applied across southern Africa. This will improve our understanding of the drivers of interannual variation in burned area in this globally important fire region. © IAWF 2010.
