Using fisheries‐independent survey data to reinforce China’s data‐limited fisheries management: Management strategy evaluation of survey‐based management procedures

2020 ◽  
Vol 28 (1) ◽  
pp. 40-52
Author(s):  
Ming Sun ◽  
Yunzhou Li ◽  
Yiping Ren ◽  
Yong Chen
Keyword(s):  
Survey Data ◽  
Fisheries Management ◽  
Management Strategy ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation ◽  
Management Procedures

scholarly journals Purported flaws in management strategy evaluation: basic problems or misinterpretations?

2010 ◽  
Vol 67 (3) ◽  
pp. 567-574 ◽  
Author(s):  
Douglas S. Butterworth ◽  
Nokome Bentley ◽  
José A. A. De Oliveira ◽  
Gregory P. Donovan ◽  
Laurence T. Kell ◽  
...  
Keyword(s):  
Fisheries Management ◽  
Management Strategy ◽  
Sampling Method ◽  
Parametric Bootstrap ◽  
Need For Care ◽  
Tail Probabilities ◽  
Management Level ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation ◽  
Management Procedures

Abstract Butterworth, D. S., Bentley, N., De Oliveira, J. A. A., Donovan, G. P., Kell, L. T., Parma, A. M., Punt, A. E., Sainsbury, K. J., Smith, A. D. M., and Stokes, T. K. 2010. Purported flaws in management strategy evaluation: basic problems or misinterpretations? – ICES Journal of Marine Science, 67: 567–574. Rochet and Rice, while recognizing management strategy evaluation (MSE) as an important step forward in fisheries management, level a number of criticisms at its implementation. Some of their points are sound, such as the need for care in representing uncertainties and for thorough documentation of the process. However, others evidence important misunderstandings. Although the difficulties in estimating tail probabilities and risks, as discussed by Rochet and Rice, are well known, their arguments that Efron's non-parametric bootstrap re-sampling method underestimates the probabilities of low values are flawed. In any case, though, the focus of MSEs is primarily on comparing performance and robustness across alternative management procedures (MPs), rather than on estimating absolute levels of risk. Qualitative methods can augment MSE, but their limitations also need to be recognized. Intelligence certainly needs to play a role in fisheries management, but not at the level of tinkering in the provision of annual advice, which Rochet and Rice apparently advocate, inter alia because this runs the risk of advice following noise rather than signal. Instead, intelligence should come into play in the exercise of oversight through the process of multiannual reviews of MSE and associated MPs. A number of examples are given of the process of interaction with stakeholders which should characterize MSE.

Using management strategy evaluation to establish indicators of changing fisheries

2019 ◽  
Vol 76 (9) ◽  
pp. 1653-1668 ◽  
Author(s):  
T.R. Carruthers ◽  
A.R. Hordyk
Keyword(s):  
Management Strategy ◽  
Statistical Power ◽  
Stock Assessment ◽  
Model Misspecification ◽  
Management Approach ◽  
Data Types ◽  
Quality Of Data ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation ◽  
Management Procedures

A new indicator is described that uses multivariate posterior predictive data arising from management strategy evaluation (MSE) to detect operating model misspecification (exceptional circumstances) due to changing system dynamics. The statistical power of the indicator was calculated for five case studies for which fishery stock assessments have estimated changes in recruitment, natural mortality rate, growth, fishing efficiency, and size selectivity. The importance of the component data types that inform the indicator was also calculated. The indicator was tested for multiple types of management procedures (e.g., catch limits by stock assessment, size limits, spatial closures) given varying qualities of data. The statistical power of the indicator could be high even over short time periods and depended on the type of system change and quality of data. Statistical power depended strongly on the type of management approach, suggesting that indicators should be established that rigorously account for feedbacks between proposed management and observed data. MSE processes should use alternative operating models to evaluate protocols for exceptional circumstances to ensure they are of acceptable statistical power.

scholarly journals Integrating management strategy evaluation into fisheries management: advancing best practices for stakeholder inclusion based on an MSE for Northeast US Atlantic herring,

2019 ◽  
Vol 76 (7) ◽  
pp. 1103-1111 ◽  
Author(s):  
R.G. Feeney ◽  
D.V. Boelke ◽  
J.J. Deroba ◽  
S. Gaichas ◽  
B.J. Irwin ◽  
...  
Keyword(s):  
Best Practices ◽  
New England ◽  
Fisheries Management ◽  
Management Strategy ◽  
Fishery Management ◽  
Lessons Learned ◽  
Clupea Harengus ◽  
Atlantic Herring ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation

The New England Fishery Management Council used management strategy evaluation (MSE) to evaluate possible harvest control rules for Atlantic herring (Clupea harengus), the first MSE in the US and perhaps globally to use open-invitation, public workshops for input. Stakeholder inclusion can increase both realism and likelihood of use by managers, but inclusivity is not achieved easily. Here, self-selected participants had diverse backgrounds and differing levels of interest and preparedness. We describe some challenges with directly engaging the public in MSE and offer broader insights for obtaining effective public participation during a decision-making process. Conducting an open MSE aligns well with publicly driven management but requires clear goals and communication. Investment in effective organizers, impartial facilitators, and knowledgeable analysts can improve communication and understanding of MSE to the betterment of fisheries management. We aim to further MSE best practices on integrating stakeholders and hope that our lessons learned on communication, engagement, and integration of MSE into an existing management arena will be useful to other practitioners.

Management strategy evaluation of a multi-indicator adaptive framework for data-limited fisheries management

2016 ◽  
Vol 92 (4) ◽  
pp. 423-445 ◽  
Author(s):  
WJ Harford ◽  
T Gedamke ◽  
EA Babcock ◽  
R Carcamo ◽  
G McDonald ◽  
...  
Keyword(s):  
Fisheries Management ◽  
Management Strategy ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation ◽  
Adaptive Framework

scholarly journals Fisheries management for regime-based ecosystems: a management strategy evaluation for the snow crab fishery in the eastern Bering Sea

2012 ◽  
Vol 70 (5) ◽  
pp. 955-967 ◽  
Author(s):  
Cody S. Szuwalski ◽  
André E. Punt
Keyword(s):  
Fisheries Management ◽  
Bering Sea ◽  
Management Strategy ◽  
Management Strategies ◽  
Regime Shifts ◽  
Snow Crab ◽  
Management Strategy Evaluation ◽  
Eastern Bering Sea ◽  
Strategy Evaluation ◽  
Spawning Biomass

Abstract Szuwalski, C., and Punt A. E. 2013. Fisheries management for regime-based ecosystems: a management strategy evaluation for the snow crab fishery in the eastern Bering Sea. – ICES Journal of Marine Science, 70: 955–967. Regime shifts are a prominent feature of the physical environment of some ecosystems and have the potential to influence stock productivity. However, few management strategies or harvest control rules (HCRs) consider the possibility of changes in stock productivity. A management strategy evaluation is conducted for the snow crab (Chionoecetes opilio) fishery in the eastern Bering Sea, an ecosystem influenced by regime shifts. Operating models that project recruitment as a single average (i.e. the current basis for management advice), regime-based with no relationship between recruitment and spawning biomass, and regime-based with control of recruitment oscillating between environmental conditions and spawning biomass are considered. An HCR that accounts for shifts in recruitment regime is compared with the status quo HCR for each operating model. The regime-based HCR increases yield and decreases variability in yield at the cost of a higher probability of overfishing in regime-based systems. However, the regime-based HCR slightly decreases yield (no change in variability) and increases the probability of overfishing in non-regime-based systems. Identifying changes in productivity that are definitely driven by environmental regime rather than fishing pressure is the largest difficulty in implementing these rules.

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