How do changing economic conditions affect the performance of fishing fleets? This question can be answered by analysing the economic data that is collected by the Thünen-Institute as part of the European Data Collection Framework (DCF). With this data historical trends can be analysed and future projections can be made.
Based on logbook, landing and VMS (Vessel Monitoring System) data, the fishing effort, catch and revenues of fishing fleets can be mapped and presented on a fine scale level. In a next step we are using these data to evaluate future and alternative fisheries management strategies (see VECTORS and COEXIST). Thereby we integrate biological and economic components of a fishing system into a spatially explicit, bio-economic model (see scheme of FishRent model above). With such a model we are able to simulate the spatiotemporal interplay between various fishing fleets and targeted fish stocks.
Nowadays there is a growing interest in developing bio-economic models as tools for understanding how fishers will response to management plans, but also to ecological and economic changes that might occur simultaneously. This is essential for assessing the potential impact of alternative polices on natural resources. FishRent is such a model and its biological component was further developed within the Thünen-Institute. Compared with other models it is one of the most advanced models that can be used for fisheries management evaluations. It is a model system that takes into account:
Moreover, the model includes fuel and fish prices, costs, fishing behaviour, in terms of investments and fishing effort distributions between fleets for a long period of time. The integrated age-structured population model accounts for stock-recruitment relationships and seasonal migrations of species.
The explicit and balanced representation of biological and economic dynamics allows the model to be used to help clarify the implications of ecological changes not only for the fish stocks and fleets but also for effective forms of fisheries management, topics which are of growing concern for resource managers.
For instance, the FishRent model was used to analyse the potential impact of the upcoming discard ban on fleets and fish stocks. The aim of such a discard ban is that fish is no longer thrown over board. However, who will be the winner and loser of such a ban? In the case of the North Sea saithe fishery model results showed that although such a discard ban seemed to be beneficial for the cod stock, it caused a spatial shift of fishing effort which resulted in catches of predominantly juvenile saithe prior to spawning. Subsequently the spawning stock of saithe was negatively impacted in the longer term, when the low number of juveniles reached older age classes. Moreover, the economic consequences of the low cod catch due to missing quotas included up to 23% profit reductions for saithe fleets. Thus, the decision of who will be a winner or loser under the future conditions depends highly on the quota availability for the individual fleets.