Using Bayesian decision analysis to help achieve a precautionary approach for managing developing fisheries

1998 ◽  
Vol 55 (12) ◽  
pp. 2642-2661 ◽  
Author(s):  
M K McAllister ◽  
G P Kirkwood
Keyword(s):  
Decision Analysis ◽  
Probability Distributions ◽  
Bayesian Decision ◽  
Catch Per Unit Effort ◽  
Precautionary Approach ◽  
Control Rules ◽  
Trade Offs ◽  
Management Procedures ◽  
Resource Data ◽  
Few Data

Bayesian decision analysis offers a useful framework for helping to achieve a precautionary approach to managing developing fisheries. With few data on the resource, data and experience from ecologically similar fish populations (or prior information) can also be used to quantitatively evaluate alternative procedures for managing the resource and to provide management advice. We applied Bayesian decision analysis to a hypothetical developing fishery in which a logistic model was fitted to catch per unit effort data. We evaluated the trade-offs in yield and the risk of depletion of catch and effort control rules. Effort control rules yielded average catches nearly 40% larger for levels of risk similar to those given by catch control rules. Management procedures designed to reduce the risks of implementing high harvest rates and to promote resource recovery at low stock sizes reduced the risks of overexploitation and caused only very small reductions in average catch. However, -50 and +100% biases in prior probability distributions for some parameters and the use of overly precise priors (CV < 0.5) in stock assessments caused large increases in the risk of overexploitation.

scholarly journals Generic management procedures for data-poor fisheries: forecasting with few data

2014 ◽  
Vol 72 (1) ◽  
pp. 251-261 ◽  
Author(s):  
H. F. Geromont ◽  
D. S. Butterworth
Keyword(s):  
Scientific Management ◽  
Fish Stocks ◽  
Control Rules ◽  
Management Procedure ◽  
Key Characteristics ◽  
Management Procedures ◽  
Wide Range ◽  
Generic Management ◽  
Few Data ◽  
Index Of Abundance

Abstract The majority of fish stocks worldwide are not managed quantitatively as they lack sufficient data, particularly a direct index of abundance, on which to base an assessment. Often these stocks are relatively “low value”, which renders dedicated scientific management too costly, and a generic solution is therefore desirable. A management procedure (MP) approach is suggested where simple harvest control rules are simulation tested to check robustness to uncertainties. The aim of this analysis is to test some very simple “off-the-shelf” MPs that could be applied to groups of data-poor stocks which share similar key characteristics in terms of status and demographic parameters. For this initial investigation, a selection of empirical MPs is simulation tested over a wide range of operating models (OMs) representing resources of medium productivity classified as severely depleted, to ascertain how well these different MPs perform. While the data-moderate MPs (based on an index of abundance) perform somewhat better than the data-limited ones (which lack such input) as would be expected, the latter nevertheless perform surprisingly well across wide ranges of uncertainty. These simple MPs could well provide the basis to develop candidate MPs to manage data-limited stocks, ensuring if not optimal, at least relatively stable sustainable future catches.

scholarly journals Valuation-Based Systems for Bayesian Decision Analysis

1992 ◽  
Vol 40 (3) ◽  
pp. 463-484 ◽  
Author(s):  
Prakash P. Shenoy
Keyword(s):  
Decision Analysis ◽  
Bayesian Decision

scholarly journals A Multicriteria Decision Model for Assessment of Failure Consequences in the RCM Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Marcelo H. Alencar ◽  
Adiel T. de Almeida
Keyword(s):  
Failure Mode ◽  
Decision Model ◽  
Probability Distributions ◽  
Maintenance Planning ◽  
Multiattribute Utility ◽  
Five Dimensions ◽  
Multicriteria Decision ◽  
Reliability Centered Maintenance ◽  
Trade Offs ◽  
And Behavior

This paper proposes a multicriteria decision model based on MAUT (Multiattribute Utility Theory) incorporated into an RCM (Reliability Centered Maintenance) approach in order to provide a better assessment of the consequences of failure, allowing a more effective maintenance planning. MAUT provides an evaluation of probability distributions on each attribute as well as trade-offs involving lotteries. The model proposed takes advantage of such evaluations and it also restructures consequence groups established in an RCM approach into new five dimensions. As a result, overall indices of utility are computed for each failure mode analyzed. With these values, the ranking of the alternatives is established. The decision-maker’s preferences are taken into account so that the final result for each failure mode incorporates subjective aspects based on the decision-maker’s perceptions and behavior.

Lessons learned from data-limited evaluations of data-rich reef fish species in the Gulf of Mexico: implications for providing fisheries management advice for data-poor stocks

2019 ◽  
Vol 76 (9) ◽  
pp. 1624-1639 ◽  
Author(s):  
Skyler R. Sagarese ◽  
William J. Harford ◽  
John F. Walter ◽  
Meaghan D. Bryan ◽  
J. Jeffery Isely ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Reef Fish ◽  
Fish Species ◽  
Stock Assessment ◽  
Lessons Learned ◽  
Management Objectives ◽  
Trade Offs ◽  
Data Limitations ◽  
Management Procedures ◽  
Reef Fish Species

Specifying annual catch limits for artisanal fisheries, low economic value stocks, or bycatch species is problematic due to data limitations. Many empirical management procedures (MPs) have been developed that provide catch advice based on achieving a stable catch or a historical target (i.e., instead of maximum sustainable yield). However, a thorough comparison of derived yield streams between empirical MPs and stock assessment models has not been explored. We first evaluate trade-offs in conservation and yield metrics for data-limited approaches through management strategy evaluation (MSE) of seven data-rich reef fish species in the Gulf of Mexico. We then apply data-limited approaches for each species and compare how catch advice differs from current age-based assessment models. MSEs identified empirical MPs (e.g., using relative abundance) as a compromise between data requirements and the ability to consistently achieve management objectives (e.g., prevent overfishing). Catch advice differed greatly among data-limited approaches and current assessments, likely due to data inputs and assumptions. Adaptive MPs become clearly viable options that can achieve management objectives while incorporating auxiliary data beyond catch-only approaches.

scholarly journals A decision analysis framework for stakeholder involvement and learning in groundwater management

2013 ◽  
Vol 10 (7) ◽  
pp. 8747-8780 ◽  
Author(s):  
T. P. Karjalainen ◽  
P. M. Rossi ◽  
P. Ala-aho ◽  
R. Eskelinen ◽  
K. Reinikainen ◽  
...  
Keyword(s):  
Decision Analysis ◽  
Groundwater Management ◽  
Stakeholder Participation ◽  
Scientific Information ◽  
Stakeholder Involvement ◽  
Resource Planning ◽  
Assessment Process ◽  
Analysis Framework ◽  
Practical Applications ◽  
Trade Offs

Abstract. Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of an MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assess their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context, and the critical issues for the further process.

scholarly journals Evaluating deepwater fisheries management strategies using a mixed-fisheries and spatially explicit modelling framework

2013 ◽  
Vol 70 (4) ◽  
pp. 768-781 ◽  
Author(s):  
Paul Marchal ◽  
Youen Vermard
Keyword(s):  
Fisheries Management ◽  
Management Strategies ◽  
Spatially Explicit ◽  
Catch Per Unit Effort ◽  
Modelling Framework ◽  
Control Rules ◽  
Bioeconomic Modelling ◽  
Stock Assessments ◽  
Fleet Dynamics

Abstract Marchal, P., and Vermard, Y. 2013. Evaluating deepwater fisheries management strategies using a mixed-fisheries and spatially explicit modelling framework. – ICES Journal of Marine Science, 70: 768–781. We have used in this study a spatially explicit bioeconomic modelling framework to evaluate management strategies, building in both data-rich and data-limited harvest control rules (HCRs), for a mix of deepwater fleets and species, on which information is variable. The main focus was on blue ling (Molva dypterygia). For that species, both data-rich and data-limited HCRs were tested, while catch per unit effort (CPUE) was used either to tune stock assessments, or to directly trigger management action. There were only limited differences between the performances of both HCRs when blue ling biomass was initialized at the current level, but blue ling recovered more quickly with the data-rich HCR when its initial biomass was severely depleted. Both types of HCR lead, on average, to a long-term recovery of both blue ling and saithe (Pollachius virens) stocks, and some increase in overall profit. However, that improvement is not sufficient to guarantee sustainable exploitation with a high probability. Blue ling CPUE did not always adequately reflect trends in biomass, which mainly resulted from fleet dynamics, possibly in combination with density-dependence. The stock dynamics of roundnose grenadier (Coryphaenoides rupestris), black scabbardfish (Aphanopus carbo) and deepwater sharks (Centrophorus squamosus and Centroscymnus coelolepis) were little affected by the type of HCR chosen to manage blue ling.

OP58 Testing Of A Multiple Criteria Decision Analysis Value Framework With Decision Makers Across Europe

2017 ◽  
Vol 33 (S1) ◽  
pp. 25-26
Author(s):  
Aris Angelis ◽  
Mark Linch ◽  
Gilberto Montibeller ◽  
Teresa Molina-Lopez ◽  
Anna Zawada ◽  
...  
Keyword(s):  
Decision Analysis ◽  
Relative Weight ◽  
Value Theory ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Multiple Criteria Decision Analysis ◽  
Model Assessment ◽  
Value Assessment ◽  
Therapeutic Impact ◽  
Trade Offs

INTRODUCTION:We test in practice a Multiple Criteria Decision Analysis (MCDA) framework for the value assessment of a set of therapeutic options for the indication of hormone relapsed metastatic prostate cancer (mPC) through a series of simulation exercises with the participation of decision makers from different Health Technology Assessment (HTA)/insurance agencies across Europe, including TLV (Sweden), AETSA (Andalusia-Spain), INAMI-RIZIV (Belgium) and AOTMiT (Poland). The drugs evaluated were abiraterone, cabazitaxel and enzalutamide.METHODS:Using a multi-attribute value theory framework, past research outcomes and literature findings, an mPC-specific value tree was constructed incorporating relevant concerns as criteria. By adopting the MACBETH approach the different drugs were scored against the criteria through the development of value functions, relative weights were assigned to the criteria using a swing weighting technique, scores and weights were combined using an additive aggregation technique, and sensitivity analysis of results was conducted. All stages were informed through the participation of a small group of experts from each HTA/insurance agency at a series of decision conferences taking place in each country.RESULTS:Value parameters considered spanned the dimensions of therapeutic impact, safety profile, innovation level and socioeconomic impact. Overall weighted preference value scores were produced reflecting the performance of the treatments against the criteria while considering their relative importance. Order of treatments’ rankings was identical across all agencies, with enzalutamide scoring highest and cabazitaxel lowest. Therapeutic impact criteria always produced the greatest relative weight. Hypothetical priority setting decisions were made based on “value-for-money” grounds through the use of “cost per unit of value” metrics by incorporating purchasing costs.CONCLUSIONS:The MCDA framework tested possesses a number of characteristics that could facilitate decision making, including the systematic and explicit incorporation of value trade-offs as part of model assessment and the transparency throughout all its stages. Therefore, it has the prospects to act as a practical evaluation tool for value assessment and communication during the HTA process.

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