Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models

Abstract

The forest, savanna, and grassland biomes, andthe transitions between them, are expected to undergo majorchanges in the future due to global climate change. Dynamicglobal vegetation models (DGVMs) are very useful for understandingvegetation dynamics under the present climate,and for predicting its changes under future conditions. However,several DGVMs display high uncertainty in predictingvegetation in tropical areas. Here we perform a comparativeanalysis of three different DGVMs (JSBACH, LPJ-GUESSSPITFIREand aDGVM) with regard to their representationof the ecological mechanisms and feedbacks that determinethe forest, savanna, and grassland biomes, in an attempt tobridge the knowledge gap between ecology and global modeling.The outcomes of the models, which include differentmechanisms, are compared to observed tree cover along amean annual precipitation gradient in Africa. By drawing onthe large number of recent studies that have delivered new insightsinto the ecology of tropical ecosystems in general, andof savannas in particular, we identify two main mechanismsthat need improved representation in the examined DGVMs