Fisheries stock assessment and decision analysis: the Bayesian approach

Punt, André E.; Hilborn, Ray

doi:10.1023/a:1018419207494

Cited by 475 publications

(350 citation statements)

References 49 publications

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“…Mortality and survival A fish in length class k after growth has been completed has three possibilities: to die naturally, be caught, or to survive (ρ t ,k , γ t ,k , and p t ,k , respectively), with respective probabilities given by Baranov (Baranov, 1976;Quinn and Deriso, 1998) as follows:…”

Section: Figurementioning

confidence: 99%

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Embedding the effect of environmental conditions on recruitment and survival of the European anchovy (Engraulis encrasicolus): a Bayesian model with dual-time resolution

Rincón

Catalán

Mäntyniemi³

et al. 2017

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Abstract-Many studies underscore the importance of incorporating the effect of environmental data within a life-history-stage-specific framework for determining the recruitment and survival of small pelagic fish. The recruitment of anchovy (Engraulis encrasicolus) in the Gulf of Cádiz (NE Atlantic) is sensitive to the effect of intense easterlies, stratification of the water column, and discharges from the Guadalquivir River on early life stages. As a proof of concept, we have developed the basis for a new Bayesian model with a dual time step resolution: monthly for juveniles and adults, and weekly for earlier life stages. This dual time step resolution resolves environmental effects on prerecruits while simulating the effect of fishing on recruits. Our estimates for juvenile abundances are validated with field data. The Bayesian framework accounts for the uncertainty, thus providing consistent length-frequency estimates and a plausible environmentally driven stock-recruitment relationship.

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Section: Figurementioning

confidence: 99%

“…The second one, the observation model describes how the population state is observed and with what uncertainty. The linking of these two stochastic models provides consistent simulation of stock dynamics and computes uncertainty as a natural output (Punt and Hilborn, 1997;Millar and Meyer, 2000).…”

mentioning

confidence: 99%

Embedding the effect of environmental conditions on recruitment and survival of the European anchovy (Engraulis encrasicolus): a Bayesian model with dual-time resolution

Rincón

Catalán

Mäntyniemi³

et al. 2017

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show abstract

“…The high complexity is required both to use the data fully and to address changing management and fishing patterns, especially a shift from summer to winter fisheries in the mid 1990s. The approach is Bayesian, in line with evolving assessment practice worldwide (Walters & Ludwig 1994;Punt & Hilborn 1997).…”

Section: Assessmentmentioning

confidence: 99%

Can additional abundance indices improve harvest control rules for New Zealand rock lobster (Jasus edwardsii) fisheries?

Bentley¹,

Breen²,

Kim

et al. 2005

New Zealand Journal of Marine and Freshwater Research

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Although New Zealand rock lobster (Jasus edwardsii) fisheries can be assessed with a sophisticated Bayesian length-based model, these assessments are expensive and time consuming; they cannot be conducted for each area every year. Harvest control rules are increasingly important management tools in New Zealand rock lobster fisheries. Recent work has developed and evaluated procedures for rebuilding or maintaining lobster stocks based on criteria agreed by stakeholders. Most management procedures depend on a single abundance index, often catch per unit of effort (CPUE). When management procedures react slowly to changes in vulnerable biomass, allowable catches get out of phase with the stock, causing large oscillations in both catches and CPUE. Lags between data and management actions and "latent years" are features of rules that reduce responsiveness. This study explores ways to improve the responsiveness of harvest control rules by using additional data to predict changes in vulnerable biomass. Four data sets are examined: CPUE trends, pre-recruit indices, puerulus settlement indices, and size frequencies. Only pre-recruit indices, which were explored with a simple delay-difference model based on parameter estimates from recent assessments, appeared to have immediate potential for use in improving management procedures.

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“…Of course not, but that is the usual quantitative outcome of a standard statistical test, because the null hypothesis of no relationship cannot be rejected. More appropriate methods for addressing uncertainties in a decisionmaking context, such as those based on assessment of likelihoods or using Bayesian methods, have been utilized for many years in other risk assessment fields related to management of chemicals and fisheries (Ellison, 1996;Hill, 1996;Punt and Hilborn, 1997;Thompson, 1992). These methods are equally well-suited to LMO risk assessment and should be seriously considered in all cases where data are highly uncertain.…”

Section: Lesson 1: Account For Uncertaintymentioning

confidence: 99%

General principles for risk assessment of living modified organisms: Lessons from chemical risk assessment

Hill¹,

Sendashonga²

2003

Environ. Biosafety Res.

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Modern biotechnology has led to the development and use of Living Modified Organisms (LMOs) for agriculture and other purposes. Regulators at the national level are increasingly depending on risk assessment as a tool for assessing potential adverse effects of LMOs on the environment and human health. In addition, the Cartagena Protocol on Biosafety, an international agreement expected to enter into force in the near future, requires risk assessment as the basis for decision-making regarding import of some LMOs. While LMO risk assessment is relatively new, there are other risk assessment disciplines which have developed over longer time periods. The field of assessment of the environmental and human health risks of chemicals is particularly well developed, and is similar in application to LMO risk assessment. This paper aims to draw lessons for LMO risk assessment from the vast experience with chemical risk assessment. Seven general principles are outlined which should serve as a useful checklist to guide assessments of risks posed by LMOs.

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Fisheries stock assessment and decision analysis: the Bayesian approach

Cited by 475 publications

References 49 publications

Embedding the effect of environmental conditions on recruitment and survival of the European anchovy (Engraulis encrasicolus): a Bayesian model with dual-time resolution

Embedding the effect of environmental conditions on recruitment and survival of the European anchovy (Engraulis encrasicolus): a Bayesian model with dual-time resolution

Can additional abundance indices improve harvest control rules for New Zealand rock lobster (Jasus edwardsii) fisheries?

General principles for risk assessment of living modified organisms: Lessons from chemical risk assessment

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