Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

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Peck, Myron A. | Arvanitidis, Christos | Butenschön, Momme | Canu, Donata Melaku | Chatzinikolaou, Eva | Cucco, Andrea | Domenici, Paolo | Fernandes, Jose A. | Gasche, Loïc | Huebert, Klaus B. | Hufnagl, Marc | Jones, Miranda C. | Kempf, Alexander | Keyl, Friedemann | Maar, Marie | Mahevas, Stéphanie | Marchal, Paul | Nicolas, Delphine | Pinnegar, John K. | Rivot, Etienne | Rochette, Sébastien | Sell, Anne F. | Sinerchia, Matteo | Solidoro, Cosimo | Somerfield, Paul J. | Teal, Lorna R. | Travers-Trolet, Morgan | Wolfshaar, Karen E., van De

Edité par CCSD ; Elsevier -

The research leading to these results has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration (FP7/2007-2013) within the Ocean of Tomorrow call under Grant Agreement No.266445 for the project Vectors of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS). This work is also a contribution to the EU Cost Action FA1004 "Conservation Physiology". PS acknowledges support from the UK Natural Environment Research Council and Department for Environment, Food and Rural Affairs [grant number NE/L003279/1, Marine Ecosystems Research Programme. The authors wish to thank Drs. Jason Link, Elizabeth Fulton and Oivind Fiksen as well as an anonymous reviewer for their helpful comments on an earlier version of this manuscript. This work also benefitted from discussions among members of the ICES Working Group on Integrated Physical biological and Ecosystem Modelling (WGIPEM) and the ICES-PICES Strategic Initiative on Climate Change Impacts on Marine Ecosystems (SICCME). Academic press ltd- elsevier science ltd London Si Marine & Freshwater Biology; Oceanography Iences, v367, p2979 Iences, v367, p1607. International audience. We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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