BUSCADOR RECOLECTA

Digital.CSIC. Repositorio Institucional del CSIC

oai:digital.csic.es:10261/242057

18 pages, 7 figures, 2 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2021.596797/full#supplementary-material.-- The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s, Eutrophication is one of the most important anthropogenic pressures impacting coastal seas. In Europe, several legislations and management measures have been implemented to halt nutrient overloading in marine ecosystems. This study evaluates the impact of freshwater nutrient control measures on higher trophic levels (HTL) in European marine ecosystems following descriptors and criteria as defined by the Marine Strategy Framework Directive (MSFD). We used a novel pan-European marine modeling ensemble of fourteen HTL models, covering almost all the EU seas, under two nutrient management scenarios. Results from our projections suggest that the proposed nutrient reduction measures may not have a significant impact on the structure and function of European marine ecosystems. Among the assessed criteria, the spawning stock biomass of commercially important fish stocks and the biomass of small pelagic fishes would be the most impacted, albeit with values lower than 2.5%. For the other criteria/indicators, such as species diversity and trophic level indicators, the impact was lower. The Black Sea and the North-East Atlantic were the most negatively impacted regions, while the Baltic Sea was the only region showing signs of improvement. Coastal and shelf areas were more sensitive to environmental changes than large regional and sub-regional ecosystems that also include open seas. This is the first pan-European multi-model comparison study used to assess the impacts of land-based measures on marine and coastal European ecosystems through a set of selected ecological indicators. Since anthropogenic pressures are expanding apace in the marine environment and policy makers need to use rapid and effective policy measures for fast-changing environments, this modeling framework is an essential asset in supporting and guiding EU policy needs and decisions, BM-K acknowledges funding from EU-H2020 project ClimeFish (grant agreement 677039), CL received support from the project CAMPUS funded by the Natural Environment Research Council and Defra (grant agreement NERC UK NE/RE007241/1). FM was funded by the SOMBEE project of the joint BiodivERsA and Belmont Forum call “BiodivScen 2018” (ANR-18-EBI4-0003-01). KD received support from the National Academies of Sciences Engineering and Medicine Gulf Research Program (Early Career Research Fellowship). MC acknowledges partial funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no 869300 (FutureMARES project). This work acknowledges institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed