SEAwise Report on how integration of ecological indicators in multispecies-multifleet management evaluation models changes impacts of management strategies on fished stocks
Creators: name: Travers-Trolet, Morgane
name: Hernvann, Pierre-Yves
name: Lehuta, Sigrid
name: Gernez, Maël
name: Sánchez-Maroño, Sonia
name: Ibaibarriaga, Leire
name: García, Dorleta
name: Citores, Leire
name: Andrés, Marga
name: Bitetto, Isabella
name: Romagnonia, Giovanni
name: Sgardeli, Vasiliki
name: Tsoukali, Stavroula
name: Giannoulaki, Marianna
name: Papantoniou, Georgia
name: Tsagarakis, Konstantinos
name: Vassilopoulou, Celia
name: Kempf, Alexander
name: Kühn, Bernhard
name: Taylor, Marc
name: van de Wolfshaar, Karen
name: Potier, Mikaela
name: Heath, Mike
name: Melià, Paco
name: Binch, Logan
name: Rindorf, Anna
Publisher: name: Technical University of Denmark
Year: 2025
Subjects: classificationCode: 410402
subject: Environmental assessment and monitoring
classificationCode: 410401
subject: Conservation and biodiversity
classificationCode: 410404
subject: Environmental management
classificationCode: 410102
subject: Ecological impacts of climate change and ecological adaptation
classificationCode: 410103
subject: Human impacts of climate change and human adaptation

description: The SEAwise project works to deliver a fully operational tool that will allow fishers, managers, and policy makers to easily apply Ecosystem Based Fisheries Management. Evaluating fishing management strategies in relation to stock sustainability and ecosystem health under changing environmental condition requires integration of ecological processes into predictive models. This SEAwise report describes the work aiming at integrating key environmental drivers into enhanced multi-stock multi-fleet models, that will allow evaluating the impacts of management strategies on stock and ecosystem indicators under climate change as conducted in the first 30 months of SEAwise.Different modelling frameworks were used to explore the impacts of abiotic (defined here as environment, climate change and their impacts on e.g. plankton) and biotic factors (predation interactions, density-dependence) on stocks dynamics and management strategy evaluations. The Mediterranean Sea, Westerns Waters and the North Sea were modelled using both multi-stock multi-fleet models (FLBEIA, BEMTOOL) and food web models (StrathE2E, EwE, OSMOSE). Using different types of models proved to be useful to explore environmental effects on stocks dynamics, provide wider ecosystem implication of management strategies and investigate the impact of model structure on predicted effects. First, knowledge from other SEAwise WPs was compiled and integrated in the formulation of some ecological processes within simulation models. Environmentally mediated processes were mainly related to recruitement, but integration of environmental conditions was also performed for growth and consumption rate and attempted for predation mortality. Second, future projections of environmental variables were used to simulate the impact of several management strategies on stocks and ecosystem dynamics. Management scenarios were similar to those already studied within SEAwise, and corresponded to status quo situation, to a perfect implementation of the landing obligation, to a pretty good yield situation and to a case-specific scenario. From some simulations covering the three case studies, results indicated that considering environmental drivers leads to worse projected stock status for the majority of stocks compared to the reference situation with no environmental change. However, the relative ranking of management scenarios in terms of stock biomass did not seem to change.Future work will involve more models, and will integrate biotic and abiotic factors in additional ecological processes. Model coupling and comparison were informative and such approach will be pursued in the future deliverable too. This will allow investigation of the uncertainty linked to model structure, process formulation and environmental projections.Read more about the SEAwise project at https://seawiseproject.org/