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Uncertainties in a Baltic Sea Food-Web Model Reveal Challenges for Future Projections

Models that can project ecosystem dynamics under changing environmental conditions are in high demand. The application of such models, however, requires model validation together with analyses of model uncertainties, which are both often overlooked. We carried out a simplified model uncertainty and sensitivity analysis on an Ecopath with Ecosim food-web model of the Baltic Proper (BaltProWeb) and found the model sensitive to both variations in the input data of pre-identified key groups and environmental forcing. Model uncertainties grew particularly high in future climate change scenarios. For example, cod fishery recommendations that resulted in viable stocks in the original model failed after data uncertainties were introduced. In addition, addressing the trophic control dynamics produced by the food-web model proved as a useful tool for both model validation, and for studying the food-web function. These results indicate that presenting model uncertainties is necessary to alleviate ecological surprises in marine ecosystem management.
Baltic States, Food Chain, Oceans and Seas, Fisheries, Uncertainty, Models, Theoretical, Seawater, Biomass
Baltic States, Food Chain, Oceans and Seas, Fisheries, Uncertainty, Models, Theoretical, Seawater, Biomass
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).28 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
