Land-use changes have been suggested as one major driver of the observed honeybee decline (Apis mellifera L.). With the current reform of the Common Agricultural Policy (CAP) for 2014-2020, the European Commission aims to promote the environmental sustainability of agricultural systems in the European Union. Therefore, the EU funds several obligatory measures, such as Ecological Focus Areas (EFAs). However, empirical evaluations of such current CAP standards are challenging. We therefore demonstrate that modelling frameworks are a valuable tool for evaluating the success of these CAP implementations and other mitigation measures. So, we developed a landscape generator to design EFA scenarios. Here, we implemented covers of EFAs on total agricultural landscape area of 3, 5, 7 and 10% according to current and claimed CAP obligations. We complied data of flowering phenology of the following EFA types: set-asides, nitrogen-fixing crops, hedgerows and field margins. We then determined honeybee colony performance under these EFA regimes by using the recently developed and well-tested model BEEHAVE that links in-hive dynamics to foraging in realistic landscapes.
Results/Conclusions
We found that flower strips and phacelia set-asides had most positive effects on colony performance depending on their cover. For 3% up to 7% cover on total agricultural area the colony success strongly depends on spatial arrangement of these EFA types in the agricultural landscape. For example, when flower strips occupy 10% of the agricultural area, the colony is able to convert about 60 kg honey per year into production of worker bees for developing and maintaining a sufficient force of foragers and nurse bees. We used the honeybee colony to demonstrate that the effectiveness of mitigation measures can be assessed with well-tested simulation models. Using such modelling frameworks for representative species and types of agricultural systems could improve our understanding how mitigation measures are related to the needs and behavior of specific species and could help in achieving the aim of policy instruments.