MareFrame publications in Fisheries Research Special Issue: Advancing Ecosystem Based Fisheries Management
Edited by Gunnar Stefansson, Javier Ruiz, Sveinn Agnarsson, Ingrid van Putten
Implementing the ecosystem based approach for fisheries management requires the development and use of innovative tools and processes. The importance of the EBFM has been highlighted worldwide by EU, FAO, ICES, NOAA, and IWC among others. After a long history of large research projects focused on establishing the scientific basis for an EBFM, many ecosystem models have been developed and extended, data have been collected, and a considerable amount of scientific knowledge has been created. However, very little of this has been utilized to support planning and decision-making. While the scientific basis for multi-species and ecosystem management exists, in practice both the stock management and scientific advice to support management decisions provided are on a single-species basis. With a significant amount of scientific knowledge already established, but little implementation carrying that forward, it is clear that substantial barriers exist that are preventing the required uptake. Some of these barriers are that scientific knowledge, models, methods and data are insufficient, but it is becoming increasingly clear that this is only part of the problem. Barriers to adopting EAFM clearly also exist relating to a lack of scientific cooperation, lack of stakeholder engagement and ownership, lack of documented benefits as well as institutional and organizational obstacles. This Special Issue feature development and use of scientific methods, tools and technologies, statistical modelling tools and assessment methods that go beyond the single-species approach,. The emphasis will be on how these tools can be made relevant in a management context, in which stakeholder involvement becomes increasingly important. In other words, the focus is on how the scientific basis for EBFM can be made relevant to the needs of stakeholder and decision makers.