DIASPARA: DIAdromous Species: moving towards new PARadigms to achieve holistic scientific Advice

Objectives

Improving scientific knowledge on the European eel and Atlantic/Baltic salmon to strengthen the science-basis of management decisions under the Common Fisheries Policy

Summary

Despite legal commitments for their conservation, the Atlantic salmon and the European eel are currently endangered. This is partly due to their ecological characteristics. First, the two species share their life cycle between marine and continental ecosystems, in and outside Europe. Despite behaving like independent units during their continental phase, they are biologically mixed during their marine phases, requiring to orchestrate regional and international management and assessment process (data collection and availability, use of appropriate assessment methods). Moreover, the species are submitted to many human impacts (e.g. fisheries, habitat degradation and fragmentation). In this context, building on pre-existing roadmaps, DIASPARA aims at providing tools to enhance the coherence of the scientific assessment process from data collection to assessment, with the final objective of supporting more holistic advice and to better inform a regional management. First, DIASPARA will undergo an inventory of available data and make recommendations for potential improvement in the collection, based on a spatiotemporal analysis of key biological parameters. Then, DIASPARA will develop database structures in order to store data required for the assessment. This will include biological data, fisheries data, but also data to monitor the impact of dams and hydropower plants. This work on dams will support the river continuity restoration targeted by other EU Regulations (e.g. WFD, free-flowing rivers target of the EU Biodiversity Strategy). Finally, the stock assessment methods should explicitly handle the complex spatial structure and the life cycle specificities of the species. This results in complex and time-consuming models. DIASPARA will benchmark different tools and statistical assumptions to enhance the performance of the analytical methods to enhance the quality of the data and to allow more comprehensive robustness tests and short-term forecasts exploration.