Management Strategy Evaluation: Allowing the Light on the Hill to Illuminate More Than One Species

Kaplan, Isaac C.; Gaichas, Sarah; Stawitz, Christine C.; Lynch, Patrick D.; Marshall, Kristin N.; Deroba, Jonathan J.; Masi, Michelle; Brodziak, Jon K. T.; Aydin, Kerim; Holsman, Kirstin K.; Townsend, Howard; Tommasi, Désirée; Smith, James A.; Koenigstein, Stefan; Weijerman, Mariska; Link, Jason S.

doi:10.3389/fmars.2021.624355

Cited by 38 publications

(23 citation statements)

References 97 publications

(147 reference statements)

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“…Duplisea et al (2021) proposed the use of empirical or phenomenological models to provide broad predictive capacity to quantify future states to manage risks associated with management decisions under plausible future environmental conditions and fishery objectives. Similar to environmentally conditioned MSEs (Kaplan et al, 2021; Punt et al, 2022), Monte Carlo simulations based on the underlying environmental effect on population response provide projections of the probability of achieving the objectives through time while allowing an assessment of the importance of environmental change on stock dynamics but without the complexity of an MSE. Successive and consistent departures from projections can serve to assess whether other factors may be driving stock dynamics or that changes in baseline conditions may require a re‐evaluation of the stock's production potential and fishery objectives.…”

Section: Discussionmentioning

confidence: 99%

Incorporating knowledge of changes in climatic, oceanographic and ecological conditions in Canadian stock assessments

et al. 2022

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Environmental impacts on fisheries are pervasive, yet methods to account for them in stock assessments and management decisions vary in rigour and quality. The prevalence and efficacy of methods to account for environmental impacts are not well documented, limiting our ability to adequately respond to future environmental and climate changes for adaptive resource management. In Canada, legislation now requires that environmental conditions are considered in the management of fish stocks, yet the current extent of implementation in assessment processes is poorly understood. We assessed the use of climate, oceanographic and ecological considerations in science advisory processes for 178 stock assessments by Fisheries and Oceans Canada. We evaluated whether these considerations were included in conceptual hypotheses about broad‐scale mechanisms, quantitative or qualitative analyses, and the development of management advice on current or future stock status. Conceptual hypotheses were included in 46% of assessments; quantitative inclusions occurred in 21% of assessments, while qualitative interpretations appeared in 31% of assessments; and 27% of assessments included climate, oceanographic and/or ecological considerations in the advice. Assessments of salmonids, invertebrates and pelagic taxa more frequently made use of environmental data than those for groundfish and elasmobranchs. Comparing our findings with assessments in other jurisdictions highlighted a gap in Canada's ability to respond to environmental changes and a need to develop integrated management approaches, such as regional ecosystem assessments and approaches that combine modelling and empirical analyses, with socio‐economic analysis within interdisciplinary teams.

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Section: Discussionmentioning

confidence: 99%

Incorporating knowledge of changes in climatic, oceanographic and ecological conditions in Canadian stock assessments

et al. 2022

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“…Both simulators as currently implemented assume a single population of a single species, which can be limiting. Extension to multiple populations of the same species, or multiple species (Punt et al, 2020b;Kanaji et al, 2021;Kaplan et al, 2021) are potential extensions of the operating models within the simulators. In particular, consideration of migration between populations would account for potential sink-source dynamics.…”

Section: Discussionmentioning

confidence: 99%

“…A management strategy is an agreed-upon set of rules for determining thresholds beyond which a CO runs the risk of not being met with unacceptably high probability (Punt, 2006;Winship, 2009;Bunnefeld et al, 2011;Kaplan et al, 2021). This strategy defines management objectives in the form of thresholds that managers can monitor from available data, with the management objectives that these thresholds are not exceeded.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Strategies for Managing Anthropogenic Mortality on Marine Mammals: An R Implementation With the Package RLA

et al. 2021

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Bycatch, the undesirable and non-intentional catch of non-target species in marine fisheries, is one of the main causes of mortality of marine mammals worldwide. When quantitative conservation objectives and management goals are clearly defined, computer-based procedures can be used to explore likely population dynamics under different management scenarios and estimate the levels of anthropogenic removals, including bycatch, that marine mammal populations may withstand. Two control rules for setting removal limits are the Potential Biological Removal (PBR) established under the US Marine Mammal Protection Act and the Removals Limit Algorithm (RLA) inspired from the Catch Limit Algorithm (CLA) developed under the Revised Management Procedure of the International Whaling Commission. The PBR and RLA control rules were tested in a Management Strategy Evaluation (MSE) framework. A key feature of PBR and RLA is to ensure conservation objectives are met in the face of the multiple uncertainties or biases that plague real-world data on marine mammals. We built a package named RLA in the R software to carry out MSE of control rules to set removal limits in marine mammal conservation. The package functionalities are illustrated by two case studies carried out under the auspices of the Oslo and Paris convention (OSPAR) (the Convention for the Protection of the Marine Environment of the North-East Atlantic) Marine Mammal Expert Group (OMMEG) in the context of the EU Marine Strategy Framework Directive. The first case study sought to tune the PBR control rule to the conservation objective of restoring, with a probability of 0.8, a cetacean population to 80% of carrying capacity after 100 years. The second case study sought to further develop a RLA to set removals limit on harbor porpoises in the North Sea with the same conservation objective as in the first case study. Estimation of the removals limit under the RLA control rule was carried out within the Bayesian paradigm. Outputs from the functions implemented in the package RLA allows the assessment of user-defined performance metrics, such as time to reach a given fraction of carrying capacity under a given level of removals compared to the time needed given no removals.

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“…The success of this approach has been demonstrated in many fisheries applications. As yet, it has had only limited application across polar regions (but see Hollowed et al, 2020;Kaplan et al, 2021). Nevertheless, results from validated high-resolution ecological and social system models for the Bering Sea and Barents Sea provided much greater insight into the expected trajectories of climate change in the region (Hansen et al, 2019b;Holsman et al, 2020).…”

Section: Projections Of Ecosystem Responsesmentioning

confidence: 99%

Climate Change Impacts on Polar Marine Ecosystems: Toward Robust Approaches for Managing Risks and Uncertainties

Ottersen¹,

Constable²,

Hollowed³

et al. 2022

Front. Clim.

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The Polar Regions chapter of the Intergovernmental Panel on Climate Change's Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) provides a comprehensive assessment of climate change impacts on polar marine ecosystems and associated consequences for humans. It also includes identification of confidence for major findings based on agreement across studies and weight of evidence. Sources of uncertainty, from the extent of available datasets, to resolution of projection models, to the complexity and understanding of underlying social-ecological linkages and dynamics, can influence confidence. Here we, marine ecosystem scientists all having experience as lead authors of IPCC reports, examine the evolution of confidence in observed and projected climate-linked changes in polar ecosystems since SROCC. Further synthesis of literature on polar marine ecosystems has been undertaken, especially within IPCC's Sixth Assessment Report (AR6) Working Group II; for the Southern Ocean also the Marine Ecosystem Assessment for the Southern Ocean (MEASO). These publications incorporate new scientific findings that address some of the knowledge gaps identified in SROCC. While knowledge gaps have been narrowed, we still find that polar region assessments reflect pronounced geographical skewness in knowledge regarding the responses of marine life to changing climate and associated literature. There is also an imbalance in scientific focus; especially research in Antarctica is dominated by physical oceanography and cryosphere science with highly fragmented approaches and only short-term funding to ecology. There are clear indications that the scientific community has made substantial progress in its ability to project ecosystem responses to future climate change through the development of coupled biophysical models of the region facilitated by increased computer power allowing for improved resolution in space and time. Lastly, we point forward—providing recommendations for future advances for IPCC assessments.

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Management Strategy Evaluation: Allowing the Light on the Hill to Illuminate More Than One Species

Cited by 38 publications

References 97 publications

Incorporating knowledge of changes in climatic, oceanographic and ecological conditions in Canadian stock assessments

Incorporating knowledge of changes in climatic, oceanographic and ecological conditions in Canadian stock assessments

Evaluating Strategies for Managing Anthropogenic Mortality on Marine Mammals: An R Implementation With the Package RLA

Climate Change Impacts on Polar Marine Ecosystems: Toward Robust Approaches for Managing Risks and Uncertainties

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