scholarly journals Simulation-based management strategy evaluation: ignorance disguised as mathematics?

2009 ◽  
Vol 66 (4) ◽  
pp. 754-762 ◽  
Author(s):  
Marie-Joëlle Rochet ◽  
Jake C. Rice
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Management Strategy ◽  
Management Strategies ◽  
Stochastic Modelling ◽  
Alternative Methods ◽  
Risk Level ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation ◽  
Simulation Based

Abstract Rochet, M-J. and Rice, J. C. 2009. Simulation-based management strategy evaluation: ignorance disguised as mathematics? – ICES Journal of Marine Science, 66: 754–762. Simulation-based management strategy evaluations are increasingly developed and used for science advice in support of fisheries management, along with risk evaluation and decision analysis. These methods tackle the problem of uncertainty in fisheries systems and data by modelling uncertainty in two ways. For quantities that are difficult to measure accurately or are inherently variable, variables are replaced by probability distributions, and system dynamics are simulated by Monte Carlo simulations, drawing numbers from these distributions. For processes that are not fully understood, arrays of model formulations that might underlie the observed patterns are developed, each is assumed successively, and the results of the corresponding arrays of model results are then combined. We argue that these approaches have several paradoxical features. Stochastic modelling of uncertainty is paradoxical, because it implies knowing more than deterministic approaches: to know the distribution of a quantity requires more information than only estimating its expected value. To combine the results of Monte Carlo simulations with different model formulations may be paradoxical if outcomes of concern are unlikely under some formulations but very likely under others, whereas the reported uncertainty from combined results may produce a risk level that does not occur under any plausible assumed formulation. Moreover, risk estimates of the probability of undesirable outcomes are often statements about likelihood of events that were seldom observed and lie in the tails of the simulated distributions, where the results of Monte Carlo simulation are the least reliable. These potential paradoxes lead us to suggest that greater attention be given to alternative methods to evaluate risks or management strategies, such as qualitative methods and empirical post hoc analyses.

A management strategy evaluation of the commercial sockeye salmon fishery in Bristol Bay, Alaska

2019 ◽  
Vol 76 (9) ◽  
pp. 1669-1683 ◽  
Author(s):  
Curry J. Cunningham ◽  
Christopher M. Anderson ◽  
Jocelyn Yun-Ling Wang ◽  
Michael Link ◽  
Ray Hilborn
Keyword(s):  
Management Strategy ◽  
Sockeye Salmon ◽  
Estimation Error ◽  
Management Strategies ◽  
Fishing Effort ◽  
Time Varying ◽  
Bristol Bay ◽  
Traditional Methods ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation

Bristol Bay, Alaska, is home to the largest sockeye salmon (Oncorhynchus nerka) fishery in the world, harvesting an average of 25 million fish with an ex-vessel value exceeding US$100 million annually. Daily fishing effort is adaptively managed to achieve stock-specific escapement goals. Traditional methods for defining these goals relied on stock–recruitment analysis; however, this approach often ignores three fundamental sources of uncertainty: estimation error, implementation uncertainty, and time-varying recruitment dynamics. To compare escapement goal alternatives, we conducted a management strategy evaluation that simulated time-varying recruitment across production regimes and replicated the daily in-season management process. Results indicate (i) implementation uncertainty can be reasonably approximated with simple rules reflecting fishery managers’ daily decision process; (ii) despite implementation uncertainty, escapement goals are likely to be realized or exceeded, on average; and (iii) management strategies targeting escapement levels estimated by traditional methods to produce maximum sustainable yield may result in lower catch and greater variability in fishing opportunity compared with a strategy with defining high and low escapement goals that are targeted depending on assessed run size, which may maximize future catch while reducing the frequency of extremely low harvests.

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.

scholarly journals Comment on “Purported flaws in management strategy evaluation: basic problems or misinterpretation?” by Butterworth et al.

2010 ◽  
Vol 67 (3) ◽  
pp. 575-576 ◽  
Author(s):  
Marie-Joëlle Rochet ◽  
Jake C. Rice
Keyword(s):  
Management Strategy ◽  
Marine Science ◽  
Technical Aspects ◽  
Management Strategy Evaluation ◽  
Incomplete Knowledge ◽  
Strategy Evaluation ◽  
Simulation Based ◽  
Population Processes

Abstract Rochet, M-J., and Rice, J. C. 2010. Comment on “Purported flaws in management strategy evaluation: basic problems or misinterpretation?” by Butterworth et al. – ICES Journal of Marine Science, 67: 575–576. Simulation-based management strategy evaluation is a valuable tool, when appropriately implemented. Implementation, however, may not always have been appropriate, and some reasons are provided why perhaps there is incomplete faith in certain of its technical aspects, such as knowing the distribution of the parameters of population processes from the information in limited datasets. A management strategy that has been evaluated by simulation should not be used as an “autopilot”, because even the most competent of experts can develop autopilots with imperfect and incomplete knowledge of reality, and all information should be incorporated when decisions have to be made.

Review of progress in the introduction of management strategy evaluation (MSE) approaches in Australia's South East Fishery

2001 ◽  
Vol 52 (4) ◽  
pp. 719 ◽  
Author(s):  
André E. Punt ◽  
Anthony D. M. Smith ◽  
Gurong Cui
Keyword(s):  
Performance Indicators ◽  
Management Strategy ◽  
Stock Assessment ◽  
Management Strategy Evaluation ◽  
Management Objectives ◽  
Strategy Evaluation ◽  
Simulation Based ◽  
Stock Assessments ◽  
Research Programmes ◽  
Different Levels

The MSE approach provides a simulation-based framework within which harvest strategies, stock assessment methods, performance indicators and research programmes can be compared. This approach has been used in the Australian South East Fishery (SEF) to assess harvest strategies for the over-exploited eastern gemfish resource and to compare different levels of discard monitoring for blue grenadier. The main challenges to use of the MSE approach in the SEF are poorly specified management objectives and the lack of quantitative stock assessments on which to build operating models for many of the species.

When does hypoxia affect management performance of a fishery? A management strategy evaluation of Dungeness crab (Metacarcinus magister) fisheries in Hood Canal, Washington, USA

2017 ◽  
Vol 74 (6) ◽  
pp. 922-932 ◽  
Author(s):  
Halley E. Froehlich ◽  
Timothy E. Essington ◽  
P. Sean McDonald
Keyword(s):  
Management Strategy ◽  
Fishery Management ◽  
Management Strategies ◽  
Puget Sound ◽  
Ecosystem Approach ◽  
Dungeness Crab ◽  
Management Strategy Evaluation ◽  
Hood Canal ◽  
Strategy Evaluation ◽  
Alternative Scenarios

Management strategies for fisheries typically do not account for environmental stressors, such as hypoxia (dissolved oxygen < 2 mg·L−1). Hypoxia can lead to shoaling of organisms into normoxic habitats, enhancing catchability, which could reduce the performance of fishery management strategies. Here, we conducted a management strategy evaluation of Dungeness crab (Metacarcinus magister) fisheries in Hood Canal, Washington, a seasonally hypoxic fjord in Puget Sound. Specifically, we asked whether the current management strategy was robust to hypoxia-induced catchability changes under alternative scenarios of illegal take, incidental capture mortality, and reproductive limitation. We find that the management strategy performed well to changes in catchability when illegal and incidental fishing mortality was low and fishing did not lead to reproductive limitation. However, the performance eroded markedly (reduced long-term catch and (or) population and higher catch variation) under the alternative scenarios. These findings underscore the benefit of applying an ecosystem approach to fisheries management because it identifies potential risks to management strategies in systems subject to environmental change.

scholarly journals Considerations for management strategy evaluation for small pelagic fishes

2021 ◽  
Author(s):  
Margaret C. Siple ◽  
Laura E. Koehn ◽  
Kelli F. Johnson ◽  
André E. Punt ◽  
T. Mariella Canales ◽  
...  
Keyword(s):  
Management Strategy ◽  
Management Strategy Evaluation ◽  
Pelagic Fishes ◽  
Strategy Evaluation

scholarly journals Bio-economic management strategy evaluation of deepwater stocks using the FLBEIA model

2013 ◽  
Vol 26 (4) ◽  
pp. 365-379 ◽  
Author(s):  
Dorleta Garcia ◽  
Agurtzane Urtizberea ◽  
Guzman Diez ◽  
Juan Gil ◽  
Paul Marchal
Keyword(s):  
Management Strategy ◽  
Economic Management ◽  
Management Strategy Evaluation ◽  
Strategy Evaluation

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.

Sign in / Sign up

Export Citation Format

Share Document