Resilience of tropical forest and savanna: bridging theory and observation

This thesis explores the hypothesis that tropical forest and savanna can be alternative stable states. Feedbacks of tree cover with fire across the tropics, and with rainfall in the Amazon basin, are studied by linking modelling to the analysis of broad-scale remote-sensing data. Time series of tree cover and fire observations are used to quantify the strength of the fire-tree cover feedback loop along climatic gradients. From these empirical results a spatially explicit and stochastic fire-tree cover model is developed. The model predicts that forest and savanna are fire-driven alternative stable states across rainfall conditions, but the exact rainfall range depends strongly on rainfall seasonality. Next, regional-scale effects of tree cover on rainfall in the Amazon basin are presented. Forest transpiration is estimated and the trajectories of that transpired water through the atmosphere are simulated. It is found that one-third of all rainfall in the Amazon basin originates from the basin; two-thirds of that water has been transpired by trees at least once. Forests in the southern half of the basin contribute most to the resilience of other forests, whereas forests in the south-western Amazon are most dependent on transpiration from forests elsewhere in the basin. The relative contribution of forest transpiration to rainfall is higher in drier months and in drier years. In conclusion, tree cover will not change smoothly with climate change and possible transitions between forest and savanna will likely be relatively abrupt. The main mechanism behind such tipping points is a feedback between tree cover and fire. Increasing rainfall seasonality will strengthen that feedback and in the Amazon at least, reduced forest transpiration resulting from tree-cover loss will enhance that seasonality.