期刊
AGRICULTURE ECOSYSTEMS & ENVIRONMENT
卷 85, 期 1-3, 页码 145-161出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/S0167-8809(01)00181-5
关键词
land-use change; land-cover change; Sahel; desertification; modelling
This paper presents a simulation model to project land-cover changes at a national scale for Sudano-sahelian countries. The aim of this study is to better understand the driving forces of land-use change and to reconstruct past changes. The structure of our model is heavily determined by its spatially aggregated level. This model represents, in a dynamic way, a simplified version of our current understanding of the processes of land-use change in the Sudano-sahelian region of Africa. For any given year, the land demand is calculated under the assumption that there should be an equilibrium between the production and consumption of basic resources derived from different land-uses. The exogenous variables of the model are human population (rural and urban), livestock, rainfall and cereals imports. The output are the areas allocated to fuelwood extraction, crops, fallow and pasture for every year. Pressure indicators are also generated endogenously by the model (rate of overgrazing and land degradation, labour productivity, average household budget). The parameters of the model were derived on the basis of a comprehensive review of the literature, mostly of local scale case studies of land-use changes in the Sahel. In agreement with farming system research, the model simulates two processes of land-use change: agricultural expansion at the most extensive technological level, followed by agricultural intensification once some land threshold is reached. The model was first tested at a national scale using data from Burkina Faso. Results simulate land-use changes at two time frequencies: high frequency, as driven by climatic variability, and low frequency, as driven by demographic trends. The rates of cropland expansion predicted by the model are consistent with rates measured for several case studies, based on fine spatial resolution remote sensing data. (C) 2001 Elsevier Science B.V. All rights reserved.
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