摘要：Dynamic process-based modelling is often proposed as a powerful tool to understand complex socio-environmental problems and to provide sustainable solutions as it allows disentangling cause and effect of human behaviour and environmental dynamics. However, the impact of such models in decision-making and to support policy-making has so far been very limited. In this paper, we want to take a critical look at the reasons behind this situation and propose steps that need to be taken to change it. We investigate a number of good practice examples from fields where models have influenced policy-making and management to identify the main aspects that promote or impede the application of these models. Specifically, we compare examples that differ in their extent to how explicitly they represent human behaviour as part of the model, ranging from purely environmental systems (including models for river management, honeybee colonies and animal diseases), where modelling techniques have long been established, to coupled socio-environmental systems (including models for land use, fishery management and sustainable water use). We use these examples to synthesise four key factors for successful modelling for policy and management support in socio-environmental systems. They cover (a) the specific requirements caused by modelling the human dimension, (b) the importance of data availability and accessibility, (c) essential elements of the partnership between modellers and decision-makers and (d) insights related to characteristics of the decision process. For each of these aspects, we give recommendations specifically to modellers, decision-makers or both to make the use of models for practice more effective. We argue that if all parties involved in the modelling and decision-making process take into account these suggestions during their collaboration, the full potential that socio-environmental modelling bears can increasingly unfold. A free Plain Language Summary can be found within the Supporting Information of this article.
