Effects of Nutrient Management Scenarios on Marine Food Webs: A Pan-European Assessment in Support of the Marine Strategy Framework Directive

Abstract

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.

Next-generation ensemble projections reveal higher climate risks for marine ecosystems

“…Our CMIP6 projections of twenty-first-century climate change impacts show steeper global biomass declines and thus greater climate risks for marine ecosystems than their CMIP5 counterparts forced by the same two ESMs, and emphasize the benefits of strong mitigation. Marked shifts in directional differences for many regions of the global ocean, probably driven by differences in ESM forcing, and in particular NPP, highlight the large uncertainties that still exist, suggesting that the readiness of ESM-forced global-scale MEMs to support country-level adaptation policies is still nascent, although these capabilities may be more advanced for regional models 38 . There remains an urgent need for model refinement to tackle uncertainty at all levels, including both climate and marine ecosystem projections.…”

Food web assessments in the Baltic Sea: Models bridging the gap between indicators and policy needs

“…In addition, we excluded studies where Baltic food web models were used as components of a geographically or thematically larger study (e.g. Piroddi et al 2021 ) or where different models were compared (e.g. Gårdmark et al 2013 ).…”

Making spatial-temporal marine ecosystem modelling better – A perspective

“…MEM ensemble modelling, where multiple MEMs, each with their strengths and weaknesses, are forced under shared drivers of change, is seen as another “gold standard” for projecting the magnitude and distribution of the impacts of changing environments and anthropogenic activities. Ensemble modelling is increasingly applied ( Lotze et al, 2019 ; Piroddi et al, 2021 ; e.g., Tittensor et al, 2018 ) and aims to side-step uncertainty related issues by obtaining average projections across a range of different ecosystem models – an approach that commonly outperforms any single model ( Rougier, 2016 ). However, Spence et al (2018) argue that using multiple model averages is not a guarantee to provide the best prediction, as discrepancies in each of the models are not independent.…”