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Volume 23, Issue 4 p. 742-754
Article

Biological ensemble modeling to evaluate potential futures of living marine resources

Anna Gårdmark,

Corresponding Author

Swedish University of Agricultural Sciences, Department of Aquatic Resources, Institute of Coastal Research, Skolgatan 6, SE-742 42 Öregrund, Sweden

E-mail: anna.gardmark@slu.seSearch for more papers by this author
Martin Lindegren,

Technical University of Denmark, National Institute of Aquatic Resources, Charlottenlund Castle, 2920 Charlottenlund, Denmark

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Stefan Neuenfeldt,

Technical University of Denmark, National Institute of Aquatic Resources, Charlottenlund Castle, 2920 Charlottenlund, Denmark

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Thorsten Blenckner,

Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden

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Outi Heikinheimo,

Finnish Game and Fisheries Research Institute, P.O. Box 2, Viikinkaari 4, FIN-00791 Helsinki, Finland

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Bärbel Müller-Karulis,

Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden

Institute of Food Safety, Animal Health and Environment (BIOR), Fish Resources Research Department, 8 Daugavgrivas Str., Riga LV 1048 Latvia

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Susa Niiranen,

Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden

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Maciej T. Tomczak,

Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden

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Eero Aro,

Finnish Game and Fisheries Research Institute, P.O. Box 2, Viikinkaari 4, FIN-00791 Helsinki, Finland

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Anders Wikström,

Department of Biology (Theoretical Population Ecology and Evolution Group), Ecology Building, Lund University, SE-22362 Lund, Sweden

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Christian Möllmann,

Institute of Hydrobiology and Fisheries Science, KLIMACAMPUS, University of Hamburg, Grosse Elbstrasse 133, D-2276 Hamburg, Germany

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First published: 01 June 2013
Citations: 58

Corresponding Editor: S. S. Heppell.

Abstract

Natural resource management requires approaches to understand and handle sources of uncertainty in future responses of complex systems to human activities. Here we present one such approach, the “biological ensemble modeling approach,” using the Eastern Baltic cod (Gadus morhua callarias) as an example. The core of the approach is to expose an ensemble of models with different ecological assumptions to climate forcing, using multiple realizations of each climate scenario. We simulated the long-term response of cod to future fishing and climate change in seven ecological models ranging from single-species to food web models. These models were analyzed using the “biological ensemble modeling approach” by which we (1) identified a key ecological mechanism explaining the differences in simulated cod responses between models, (2) disentangled the uncertainty caused by differences in ecological model assumptions from the statistical uncertainty of future climate, and (3) identified results common for the whole model ensemble. Species interactions greatly influenced the simulated response of cod to fishing and climate, as well as the degree to which the statistical uncertainty of climate trajectories carried through to uncertainty of cod responses. Models ignoring the feedback from prey on cod showed large interannual fluctuations in cod dynamics and were more sensitive to the underlying uncertainty of climate forcing than models accounting for such stabilizing predator–prey feedbacks. Yet in all models, intense fishing prevented recovery, and climate change further decreased the cod population. Our study demonstrates how the biological ensemble modeling approach makes it possible to evaluate the relative importance of different sources of uncertainty in future species responses, as well as to seek scientific conclusions and sustainable management solutions robust to uncertainty of food web processes in the face of climate change.