Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

doi:10.1371/journal.pone.0077566

Cited by 13 publications

(8 citation statements)

References 45 publications

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“…12 ISIS-FISH Mahevas & Pelletier, 2004;Pelletier et al, 2009;Drouineau, Mahévas, Pelletier, & Beliaeff, 2006;Drouineau, Mahévas, Bertignac, & Duplisea, 2010;Duplisea, 2010;Lehuta, Mahévas, Petitgas, & Pelletier, 2010;Rocklin, Pelletier, Mouillot, Tomasini, & Culioli, 2010;Lehuta, Mahévas, & Le Floc'h, 2013;Lehuta, Petitgas, et al, 2013;Lehuta, Holland, & Pershing, 2014;Lehuta, Vermard, & Marchal, 2015;Rochet & Rice, 2010;Marchal, Little, & Thebaud, 2011;Marchal, De Oliveira, Lorance, Baulier, & Pawlowski, 2013;Hussein et al, 2011a,b;Vermard et al, 2012;Gasche, Mahevas, & Marchal, 2013;Reecht et al, 2015. 13 BALTIC FLR-SMS Bastardie et al, 2009;Bastardie, Nielsen, & Kraus, 2010;Bastardie, Vinther, Nielsen, Ulrich, & Storr-Paulsen, 2010;Bastardie, Vinther, & Nielsen, 2012;Bastardie, Nielsen, & Vinther, 2015;Nielsen et al, 2011;Feekings et al, (submitted). Macher, Guyader, Talidec, & Bertignac, 2008;Macher et al, 2013;Merzéréaud, Biais, Lissardy, Bertignac, & Biseau, 2013;Merzéréaud et al, 2011;Simmonds et al, 2011;Raveau et al, 2012;Guillén et al, 2013;Guillén, Macher, Merzéréaud, Fifas, & Guyader, 2014;Guillén, Macher, Merzéréaud, Boncoeur, & Guyader, 2015;EU STECF, 2015a…”

Section: Stoch Hcr (Itq Wealth)mentioning

confidence: 99%

Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation

et al. 2017

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Marine ecosystems evolve under many interconnected and area-specific pressures. To fulfil society's intensifying and diversifying needs while ensuring ecologically sustainable development, more effective marine spatial planning and broader-scope management of marine resources is necessary. Integrated ecological-economic fisheries models (IEEFMs) of marine systems are needed to evaluate impacts and sustainability of potential management actions and understand, and anticipate ecological, economic and social dynamics at a range of scales from local to national and regional. To make these models most effective, it is important to determine how model characteristics and methods of communicating results influence the model implementation, the nature of the advice that can be provided and the impact on decisions taken by managers. This article presents a global review and comparative evaluation of 35 IEEFMs applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes although not all the models reviewed achieve that. Modellers must invest more time to make models user friendly and to participate in management fora where models and model results can be explained and discussed. Such involvement is beneficial to all parties, leading to improvement of models and more effective implementation of advice, but demands substantial resources which must be built into the governance process. It takes time to develop effective processes for using IEEFMs requiring a long-term commitment to integrating multidisciplinary modelling advice into management decision-making. K E Y W O R D Sbio-economic models, comparative model evaluation, fisheries management advice, integrated ecological-economic fisheries models, marine spatial planning and cross-sector management, performance criteria and scales and risks, use and acceptance and implementation and communication and flexibility and complexity | INTRODUCTIONThere is a growing need for tools to evaluate policies and assess tradeoffs in management of marine resources and provision of ecosystem services such as fishing, aquaculture, renewable energy, shipping, conservation and recreation (Cormier, Kannen, Elliott, & Hall, 2015;Degnbol & Wilson, 2008;EU 2014;Langlois, Fréon, Steyer, Delgenés, & Hélias, 2014;White et al., 2012). It is necessary to elaborate and apply common principles and broader, interdisciplinary management evaluation in the use of marine space involving several types of activities and sectors Soma et al., 2013;Stelzenmüller et al., 2013;Sundblad et al., 2014). Policymakers need to know the costs and benefits of conserving ecosystem goods and services to manage them sustainably. Moreover, according to an ecosystembased approach to management, specific pressures, associated uncertainties and risks need to be taken into account (Douvere, 2008;Ehler & Douvere, 2009;Gi...

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Section: Stoch Hcr (Itq Wealth)mentioning

confidence: 99%

Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation

et al. 2017

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“…In one example of coupled modelling, a full life-cycle model for fish (Rochette et al, 2013) (Huret et al, 2013) and to the spatially-explicit, multi-species, multi-fisheries dynamics model ISIS-Fish Pelletier, 2004 andPelletier et al, 2009). In that case, the coupled model approach, despite the lack of dynamic feedback, allowed management strategies (e.g., Total Allowable Catches, Marine Protected Areas) to be examined in terms of their effectiveness to conserve flatfish and benthic taxa in light of the cumulative impacts of fishing and aggregate extraction activities in coastal ecosystems (Gasche et al, 2013) Importantly, in some cases, existing tools will not be sufficient to capture all relevant processes and new tools will be required. A major issue confronting scientists charged with making predictions of future distribution and productivity is the ability of species to adapt to altered environmental conditions.…”

Section: Discussionmentioning

confidence: 99%

“…The robustness of model outputs can be explored by means of advanced sensitivity analysis techniques (Lehuta et al 2013b). Classification trees built from these simulations can be used to perform uncertainty analysis and assess the robustness of results to input parameter values (Gasche et al, 2013). The bounded parameterizations method considers the most pessimistic,…”

Section: Strengths and Weaknesses Of End-to-end Modelsmentioning

confidence: 99%

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

Peck¹,

Arvanitidis

Butenschön

et al. 2018

Estuarine, Coastal and Shelf Science

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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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“…Models in the second focus category investigate the effect of management on fishery outcomes by assessing different regulatory interventions, such as controls on catch (e.g. quotas (Gasche et al., 2013); gear‐dependent quotas (Sigurðardóttir, Johansson, Margeirsson, & Viðarsson, 2014); timing to reassess or adjust quotas (e.g. van Dijk, Haijema, Hendrix, Groeneveld, & van Ierland, 2013) effort limitations (e.g.…”

Section: Fisher Behaviour In Fisheries Sciencementioning

confidence: 99%

Behavioural diversity in fishing—Towards a next generation of fishery models

et al. 2020

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Despite improved knowledge and stricter regulations, numerous fish stocks remain overharvested. Previous research has shown that fisheries management may fail when the models and assessments used to inform management are based on unrealistic assumptions regarding fishers' decision‐making and responses to policies. Improving the understanding of fisher behaviour requires addressing its diversity and complexity through the integration of social science knowledge into modelling. In our paper, we review and synthesize state‐of‐the‐art research on both social science's understanding of fisher behaviour and the representation of fisher decision‐making in scientific models. We then develop and experiment with an agent‐based social–ecological fisheries model that formalizes three different fishing styles. Thereby we reflect on the implications of our incorporation of behavioural diversity and contrast it with the predominant assumption in fishery models: fishing practices being driven by rational profit maximizing. We envision a next generation of fisheries models and management that account for social scientific knowledge on individual and collective human behaviours. Through our agent‐based model, we demonstrate how such an integration is possible and propose a scientific approach for reducing uncertainty based on human behavioural diversity in fisheries. This study serves to lay the foundations for a next generation of social–ecological fishery models that account for human behavioural diversity and social and ecological complexity that are relevant for a realistic assessment and management of fishery sustainability problems.

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Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

Cited by 13 publications

References 45 publications

Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation

Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation

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

Behavioural diversity in fishing—Towards a next generation of fishery models

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