Suchergebnisse

Chapter 1. Bridging the Ggap. Experiments in the Heart of the Transition Zone (Mackinson and Holm) -- Chapter 2. Knowledge for Fisheries Governance. Participation, Integration and Institutional Reform (Linke et al) -- Chapter 3. Fishermen and Scientists in the Same Boat. A Story of Collaboration in the UK South Devon Crab Fishery (Pearson, et al.) -- Chapter 4. Getting Choosy About Whitefish in Lake Vättern. Using Participatory Approaches to Improve Fisheries Selectivity (Sandström, et al.) -- Chapter 5. Understanding Fishermen-Scientist Collaboration in Galician Small-Scale Fisheries (NW Spain). Validating a Methodological Toolbox Through a Process-Oriented Approach (Vidal, et al.) -- Chapter 6. Information is the Jam of the Western Baltic Herring Sandwich. Bridging Gaps Between Policy, Stakeholders and Science (Clausen, et al.) -- Chapter 7. Aiming for By-Catch. Collaborative Monitoring of Rare and Migratory Species in the Wadden Sea (Wätjen and Ramírez-Monsalve) -- Chapter 8. The Italian Job. Navigating the (Im)perfect Storm of Participatory Fisheries Research in the Northern Adriatic Sea (Raicevich, et al.) -- Chapter 9. Trapped in the TAC Machine. Making a Fisheries Based Indicator System for Coastal Cod in Steigen, Norway (Holm, et al.) -- Chapter 10. When Fishermen Take Charge. The Development of a Management Plan for the Red Shrimp Fishery in Mediterranean Spain (Bjørkan, et al.) -- Chapter 11. Does Slow-Burn Collaboration Deliver Results? Towards Collaborative Development Multiannual Multispecies Management Plans in North Sea Mixed Demersal Fisheries (Mackinson, et al.) -- Chapter 12. Action Research in Tropical Tuna Purse Seine Fisheries. Thoughts and Perspectives (Airaud, et al.) -- Chapter 13. From Planning for Society to Planning with Society. Integration of Coastal Fisheries into the Maritime Spatial Planning (Aps, et al.) -- Chapter 14. Implementing the Landing Obligation. An Analysis of the Gap Between Fishers and Policy Makers in the Netherlands (Kraan and Verweij) -- Chapter 15. Taking the Initiative on Maltese Trawl Industry Management. Industry and Science Collaboration on Identifying Nursery and Spawning Areas for Trawl Fisheries Target Species (Martin) -- Chapter 16. People, Sharks and Science. What can it take for Industry-led Research to make a Difference to the Management of Elasmobranchs of Conservation Concern in UK waters? (Hetherington and Bendall) -- Chapter 17. Bridging Gaps, Reforming Fisheries (Holm, et al.) -- Chapter 18. Conclusion (Mackinson, et al.). .

WKNSMSE (Workshop on North Sea stocks Management Strategy Evaluation) took place over two physical meetings (19-21 November 2018 and 26-28 February 2019, but at ICES HQ, Copenhagen) and several WebEx meetings, was chaired by José De Oliveira (UK) and included 30 participants from Denmark, Germany, Netherlands, Norway, Sweden, UK and the European Commission, and two reviewers from South African and New Zealand. The purpose of this process was to evaluate long-term management strategies for jointly-managed stocks in the North Sea (cod, haddock, whiting, saithe and autumn-spawning herring) between the European Union and Norway, following a request from EU-Norway. The first physical meeting provided an ICES interpretation of the EU-Norway request, agreed the specifications of the MSE, decided on the tools and approaches to use, and developed a work plan, while the second meeting (and subsequent follow-up WebEx meetings) discussed results, developed conclusions, ensured the minimum requirements for conducting MSEs (developed by WKGMSE2) were met, and finalised the report. ICES were tasked to find "optimal" combinations of harvest control rule parameters (Ftarget and Btrigger) for management strategies with or without stability mechanisms (TAC constraints and banking and borrowing scenarios). "Optimal" combinations were defined as those combinations of Ftarget and Btrigger that simultaneously maximised long-term yield while being precautionary (long-term risk3≤5%). The request also asked for sensitivity tests once the management strategies were "optimised". The approach adopted for all stocks was to include the assessment and forecast in a full-feedback MSE simulation, and to condition the baseline operating model on the benchmarked ICES assessment. The one exception was haddock, where it was not possible to include TSA in the full-feedback simulation because it was too slow to converge and requires manual intervention; SAM was used instead as a reasonable approximation. The approach also considered alternative operating models to capture a broader range of uncertainties. Full-feedback simulations were computationally challenging and required the use of parallelisation and high-performance computing; it also meant that the time-frame for the work was extremely tight, and in some cases, analyses were restricted. Nonetheless, the work was completed for all stocks, and "optimal" combinations for most management strategies were found. There were some notable issues that arose through this suite of MSEs, including that some management strategies that were precautionary in the long-term could have unsavoury and avoidable features in the short term (depending on the management strategy), and that reference points estimated by EqSim were, in many cases, no longer found to be precautionary in the MSE.

WKNSMSE (Workshop on North Sea stocks Management Strategy Evaluation) took place over two physical meetings (19-21 November 2018 and 26-28 February 2019, but at ICES HQ, Copenhagen) and several WebEx meetings, was chaired by José De Oliveira (UK) and included 30 participants from Denmark, Germany, Netherlands, Norway, Sweden, UK and the European Commission, and two reviewers from South African and New Zealand. The purpose of this work was to evaluate long-term management strategies for jointly-managed stocks in the North Sea (cod, haddock, whiting, saithe and autumn-spawning herring) between the European Union and Norway, following a request from EU-Norway. The first physical meeting provided an ICES interpretation of the EU-Norway request, agreed the specifications of the MSE, decided on the tools and approaches to use, and developed a work plan, while the second meeting (and subsequent follow-up WebEx meetings) discussed results, developed conclusions, ensured the minimum requirements for conducting MSEs (developed by WKGMSE2) were met, and finalised the report. ICES were tasked to find "optimal" combinations of harvest control rule parameters (F target and B trigger ) for management strategies with or without stability mechanisms (TAC constraints and banking and borrowing scenarios). "Optimal" combinations were defined as those combinations of F target and B trigger that simultaneously maximised long-term yield while being precautionary (long-term risk3≤5%). The request also asked for sensitivity tests once the management strategies were "optimised". The approach adopted for all stocks was to include the assessment and forecast in a full-feedback MSE simulation, and to condition the baseline operating model on the benchmarked ICES assessment. The one exception was haddock, where it was not possible to include TSA in the full-feedback simulation because it was too slow to converge and requires manual intervention; SAM was used instead as a reasonable approximation. The approach also considered alternative operating models to capture a broader range of uncertainties. Full-feedback simulations were computationally challenging and required the use of parallelisation and high-performance computing; it also meant that the time-frame for the work was extremely tight, and in some cases, analyses were restricted. Nonetheless, the work was completed for all stocks, and "optimal" combinations for most management strategies were found. There were some notable issues that arose through this suite of MSEs, including that some management strategies that were precautionary in the long-term could have unsavoury and avoidable features in the short term (depending on the management strategy), and that reference points estimated by EqSim were, in many cases, no longer found to be precautionary in the MSE.

6 pages, 5 figures, supporting information https://doi.org/10.1073/pnas.1900194116.-- All data reported in this paper are archived and publicly available at http://dataservices.gfz-potsdam.de/pik/showshort.php?id=escidoc:2956913. ; While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends ; Financial support was provided by the German Federal Ministry of Education and Research through ISI-MIP (Grant01LS1201A1), the European Union's Horizon 2020 Research and Innovation Program (Grant 678193), and the Ocean Frontier Institute (Module G). We acknowledge additional financial support as follows: to H.K.L., W.W.L.C., and B.W. from the Natural Sciences and Engineering Research Council (NSERC) of Canada; to D.P.T. from the Kanne Rasmussen Foundation Denmark; to A.B.-B. from the NSERC Transatlantic Ocean Science and Technology Program; to W.W.L.C. and T.D.E. from the Nippon Foundation-Nereus Program; to E.D.G., M.C. and J. Steenbeek from the European Union's Horizon 2020 Re-search and Innovation Program (Grants 682602 and 689518); to E.A.F., J.L.B., andT.R. from Commonwealth Scientific and Industrial Research Organization and the Australian Research Council; to N.B., L.B., and O.M. from the French Agence Nationale de la Recherche and Pôle de Calcul et de Données pour la Mer; and to S.J. from the UK Department of Environment, Food and Rural Affairs ; Peer Reviewed