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dc.contributor.authorEvans, Karen
dc.contributor.authorBrown, Jaclyn N.
dc.contributor.authorSen Gupta, Alex
dc.contributor.authorNicol, Simon J.
dc.contributor.authorHoyle, Simon
dc.contributor.authorMatear, Richard
dc.contributor.authorArrizabalaga, Haritz
dc.date.accessioned2017-08-23T08:52:10Z-
dc.date.available2017-08-23T08:52:10Z-
dc.date.issued2015
dc.identifierISI:000351978700026
dc.identifier.citationDEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2015, 113, 312-322
dc.identifier.issn0967-0645
dc.identifier.urihttp://dspace.azti.es/handle/24689/267-
dc.description.abstractMulti-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty. (C) 2014 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipThe concepts for this manuscript were originally conceived in a workshop for the Targeted Tropical Tuna Research Program, held in Noumea in February 2013 and supported by the funding from the Pacific Australia Climate Change and Adaptation Program (2012/31051). The authors would like to thank two anonymous reviewers whose comments significantly improved this manuscript.
dc.language.isoeng
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.subjectEarth-system model
dc.subjectEcosystem model
dc.subjectFisheries
dc.subjectClimate
dc.subjectModel uncertainty
dc.subjectWESTERN TROPICAL PACIFIC
dc.subjectTUNA POPULATIONS
dc.subjectCHANGING CLIMATE
dc.subjectDYNAMICS MODEL
dc.subjectYELLOWFIN TUNA
dc.subjectTOP PREDATORS
dc.subjectBLUEFIN TUNA
dc.subjectSIZE SPECTRA
dc.subjectUPPER OCEAN
dc.subjectMANAGEMENT
dc.titleWhen 1+1 can be > 2: Uncertainties compound when simulating climate, fisheries and marine ecosystems
dc.typeArticle
dc.identifier.journalDEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY
dc.format.page312-322
dc.format.volume113
dc.contributor.funderPacific Australia Climate Change and Adaptation Program \[2012/31051]
dc.identifier.e-issn1879-0100
dc.identifier.doi10.1016/j.dsr2.2014.04.006
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