Coupling a physiological grazer population model with a generalized model for vegetation dynamics

We coupled a generalized model for the population dynamics of large mammalian grazers, based on animal physiology, with a plant-physiological model for vegetation dynamics and ecosystem processes, applicable at local to global scales (LPJ-GUESS). To our knowledge, this is the first attempt to combine process-based grazer population and vegetation modelling in a single generalized modelling framework, applicable at regional to continental scales. The capability of the coupled model to reproduce real-world grazer densities was tested by comparing modelled biomass densities with empirical data from African game parks, where semi-natural grazer populations still exist. The model reproduced inter-park differences in long-term average grazer biomass densities and yielded similar dependencies between major environmental drivers (e.g. precipitation, annual net primary productivity [NPP], dry season length) and grazer population densities as found in other more empirical studies. Amongst the potential environmental drivers, modelled NPP and dry season length were most strongly correlated with empirical and modelled biomass densities. Major discrepancies between modelled and empirical densities occurred for individual parks, but this was expected because the model did not include all factors that influence grazer populations (e.g. nutrient dynamics and poaching).

The dataset includes the model code, bin data for running the grazer model in African savannahs and R scripts for evaluation.