Considerations for management strategy evaluation for small pelagic fishes

Management strategy evaluation (MSE) is the state-of-the-art approach for testing and comparing management strategies in a way that accounts for multiple sources of uncertainty (e.g. monitoring, estimation, and implementation). Management strategy evaluation can help identify management strategies that are robust to uncertainty about the life history of the target species and its relationship to other species in the food web. Small pelagic fish (e.g. anchovy, herring and sardine) fulfil an important ecological role in marine food webs and present challenges to the use of MSE and other simulation-based evaluation approaches. This is due to considerable stochastic variation in their ecology and life history, which leads to substantial observation and process uncertainty. Here, we summarize the current state of MSE for small pelagic fishes worldwide. We leverage expert input from ecologists and modellers to draw attention to sources of process and observation uncertainty for small pelagic species, providing examples from geographical regions where these species are ecologically, economically and culturally important. Temporal variation in recruitment and other life-history rates, spatial structure and movement, and species interactions are key considerations for small pelagic fishes. We discuss tools for building these into the MSE process, with examples from existing fisheries. We argue that model complexity should be informed by management priorities and whether ecosystem information will be used to generate dynamics or to inform reference points. We recommend that our list of considerations be used in the initial phases of the MSE process for small pelagic fishes or to build complexity on existing single-species models.publishedVersio

Overfishing or environmental change: Establishing the frequency of changes in productivity of marine fish stocks

Thesis (Master's)--University of Washington, 2013The relative importance of environmental conditions and stock abundance in determining the productivity of fish stocks has been a subject of an on-going debate. The controversy can be formulated as four competing hypotheses: 1) productivity is driven by fishing pressure, which affects abundance, subsequent recruitment; 2) productivity is regime-driven, with periods of good and bad productivity unrelated to abundance; 3) productivity is random from year to year and unrelated to abundance and is temporally uncorrelated; and 4) both stock abundance and regimes of good and bad conditions interact to affect productivity. The goals of this study are (1) to evaluate the support for each of these hypotheses by examining the productivity of marine species using a large number of stocks, and (2) to evaluate the same hypotheses with respect to recruitment. This project uses historic data from about 230 assessments from the RAM Legacy Database. Each of the four hypotheses will be formulated as alternative models, and the support for the hypotheses evaluated using model selection via AICc and AICc weights. The specific models are (1) a biomass-dynamic model relating surplus production to stock size, (2) a regime shift model accounting for temporal shifts in productivity; (3) a model that assumes productivity to be random and (4) a biomass-dynamics model that has regime changes in productivity parameters. Then a similar analysis was performed on recruitment. I found that when considering production the Abundance Hypothesis best explains 18.3% of stocks, the Regimes Hypothesis 38.6%, the Mixed Hypothesis 30.5%, and the Random Hypothesis 12.6%. When considering recruitment, the stock-recruitment Hypothesis best explains 17% of stocks, the Regimes Hypothesis 45%, the Mixed Hypothesis 21% and the Random Hypothesis 18%. If the production of a stock is determined by periodic regimes and the assessment of the stock does not recognize the shift in regimes, then the management system with respect to sustainable yield is incorrect. I do not suggest that we should abandon the goal of maintaining fish stocks at high abundance. Rather I simply show that it is unlikely that such policies will assure high and sustained recruitment. Thus, future work should identify and evaluate management strategies that would be robust to irregular jumps in average productivity

Rejection sampling and agent-based models for data limited fisheries

Many of the world’s fisheries are “data-limited” where the information does not allow precise determination of fish stock status and limits the development of appropriate management responses. Two approaches are proposed for use in data-limited stock management strategy evaluations to guide the evaluations and to understand the sources of uncertainty: rejection sampling methods and the incorporation of more complex socio-economic dynamics into management evaluations using agent-based models. In rejection sampling (or rejection filtering) a model is simulated many times with a wide range of priors on parameters and outcomes are compared multiple filtering criteria. Those simulations that pass all the filters form an ensemble of feasible models. The ensemble can be used to look for robust management strategies, robust to both model uncertainties. Agent-based models of fishery economics can be implemented within the rejection framework, integrating the biological and economic understanding of the fishery. A simple artificial example of a difference equation bio-economic model is given to demonstrate the approach. Then rejection sampling is applied to an agent-based model for the hairtail (Trichiurus japonicas) fishery, where an operating model is constructed with rejection/agent-based methods and compared to known data and analyses of the fishery. The usefulness of information and rejection filters are illuminated and efficacy examined. The methods can be helpful for strategic guidance where multiple states of nature are possible as a part of management strategy evaluatio

Which design elements of individual quota fisheries help to achieve management objectives?

Individual quota (IQ) management systems in commercial marine fisheries are highly diverse, differing in the security, durability and exclusivity of the harvesting privilege and the transferability of quota units. This diversity in the degree of harvest rights may influence the effectiveness of IQ fisheries to meet management objectives. We conducted a global meta-analysis of 167 stocks managed under IQs to test whether the strength of harvest rights impacts the conservation status of stocks in terms of catch, exploitation rate and biomass relative to management targets. We used non-parametric methods to assess non-linear relationships and linear regression models to explicitly consider interactions among predictors. Most IQ fisheries consistently met fleet-wide quota limits (94% of stocks had recent catches below or within 10% of quotas), but only 2/3 of IQ fisheries adhered to sustainable management targets for biomass and exploitation rate (68% of stocks had exploitation rates below or within 10% of targets and 63% of stocks had biomass above or within 10% of biomass targets). Strikingly, when exclusivity of the harvesting privilege was low, exploitation rates depended on whether IQ implementation was industry-driven (exploitation below targets) or government-mandated (exploitation above targets). At high levels of exclusivity, exploitation rates converged to just below management targets. Transferability of quota units was associated with stock biomass closer to and slightly above target levels than stocks with non-transferable quota. However, regional differences had the strongest effect on biomass, suggesting that other management or biological attributes of regional fishery systems have greater influence on marine populations.Fil: Melnychuk, Michael C.. University of Washington; Estados UnidosFil: Essington, Timothy E.. University of Washington; Estados UnidosFil: Trevor, Branch A.. University of Washington; Estados UnidosFil: Heppell, Selina S.. Oregon State Universit; Estados UnidosFil: Jensen, Olaf P.. University of Washington; Estados UnidosFil: Link, Jason S.. Northeast Fisheries Science Center; Estados UnidosFil: Martell, Steven J. D.. International Pacific Halibut Commission; Estados UnidosFil: Parma, Ana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Smith, Anthony D. M.. Oceans and Atmosphere Flagship; Australi