Abstract. Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilience of the climate system to vegetation disturbance at regional to global scales. We hypothesize that by starting with two extreme initialisations of biomass, positive vegetation-climate feedbacks will keep the vegetation-atmosphere system within different attraction domains. Indeed, model integrations starting from different initial biomass distributions diverged to clearly distinct climate-vegetation states in terms of abiotic (precipitation and temperature) and biotic (biomass) variables. Moreover, we found that between these states there are several other steady states which depend on the scale of perturbation. From here global susceptibility maps were made showing regions of low and high resilience. The model results suggest that mainly the boreal and monsoon regions have low resiliences, i.e. instable biomass equilibria, with positive vegetation-climate feedbacks in which the biomass induced by a perturbation is further enforced. The perturbation did not only influence single vegetation-climate cell interactions but also caused changes in spatial patterns of atmospheric circulation due to neighbouring cells constituting in spatial vegetation-climate feedbacks. Large perturbations could trigger an abrupt shift of the system towards another steady state. Although the model setup used in our simulation is rather simple, our results stress that the coupling of feedbacks at multiple scales in vegetation-climate models is essential and urgent to understand the system dynamics for improved projections of ecosystem responses to anthropogenic changes in climate forcing.