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DCF (Data Collection Framework): Stock assessment of European Eel (Anguilla anguilla) in German inland waters
Project
Project code: TI-FI-08-PID1557
Contract period: 01.03.2009
- 31.12.2020
Purpose of research: Inventory & Assessment
The status of the European Eel stock is considered critical. Yet, most of the required data are based on rough estimates or model assumptions. As part of a europe-wide network, we are working on the standardized collection of age-structure and growth in all relevant German inland waters in order to provide a solid data base for eel stock assesment and improve future management measures. Since the 1970s, the abundance of glass eels on European coasts drastically declined. In 2011, this trend reached an all-time low of one percent in the north sea region and five percent in other regions, in relation to values from the years 1960-1979. Albeit a slight increase in glass eel recruitment during the past three years, the stock situation of the European eel is still considered critical by the International Council for the Exploration of the Sea (ICES). However, due to a lack of fundamental stock assessment data an evaluation of recently applied managament measures is barely possible. Eel management is especially challenging, since there is only a single stock, which is scattered across the whole European continent and Northern Africa. To allow for a comprehensive collection of assessment data across the whole distributional range, the European eel was implemented in the EU Data Collection Framework in 2007. In this context, we focus our research on eel growth and maturation in german inland waters, in order to allow for the evaluation and optimization of current management measures. Up to 100 yellow- and silver eels, respectively, are sampled from commercial fisheries in all German river basin districts (according to the Water Framework Directive). In addition to the mandatory data on length, weight, age and sex, we also investigate the infestation of the swimbladder with the Nematode Anguillicola crassus and the contamination with pollutants, such as heavy metals and PCB's. These data allow for the identification of differences in habitat quality and will eventually result in recommendations concerning management measures, such as restocking.
Section overview
Subjects
- Freshwater fisheries
- Computer science
