Abstract
1AbstractForest encroachment over savannas has been recurrently reported in the tropics over the last decades, especially in northern tropical Africa. However, process-based, spatially-explicit modelling of the phenomenon is still trailing broad scale empirical observations. In this paper, we used remotely-sensed diachronic data from Central Cameroon to calibrate a simple reaction-diffusion model, embodying dynamical interactions between grass and woody biomasses in the savanna biome. Landsat satellite image series over the Mpem and Djim National Park witnessed a dramatic extension of forest over the last five decades and our estimates of forest front speeds based on randomly sampled transects indeed yielded higher values (5-7 meters per year) than in the existing literature. We used simulations of the model to provide the first hitherto estimates of woody biomass dispersal coefficients. Since the region under study did not provide examples of savanna progression, estimates of grass dispersal proved inconsistent and we reverted to literature-based historical data to reach rough estimates. This paper demonstrates that broad scale remote sensing data allows for calibrating simple reaction-diffusion models of vegetation dynamics in the savanna biome. Once calibrated, such models become a general baseline of expected changes and a valuable tool to understand how spatial environmental factors (e.g., soil substrate) may locally modulate the overall dynamics.
Publisher
Cold Spring Harbor Laboratory