scholarly journals Model averaging to streamline the stock assessment process

2014 ◽  
Vol 72 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Colin P. Millar ◽  
Ernesto Jardim ◽  
Finlay Scott ◽  
Giacomo Chato Osio ◽  
Iago Mosqueira ◽  
...  
Keyword(s):  
Large Scale ◽  
Stock Assessment ◽  
Model Averaging ◽  
Assessment Model ◽  
Assessment Process ◽  
Fish Stock ◽  
Assessment Procedure ◽  
Observation Error ◽  
Fishery Policy ◽  
Fishery Science

Abstract The current fish stock assessment process in Europe can be very resource- and time-intensive. The scientists involved require a very particular set of skills, acquired over their career, drawing from biology, ecology, statistics, mathematical modelling, oceanography, fishery policy, and computing. There is a particular focus on producing a single “best” stock assessment model, but as fishery science advances, there are clear needs to address a range of hypotheses and uncertainties, from large-scale issues such as climate change to specific ones, such as high observation error on young hake. Key to our discussion is the use of the assessment for all frameworks to translate hypotheses into models. We propose a change to the current stock assessment procedure, driven by the use of model averaging to address a range of plausible hypotheses, where increased collaboration between the varied disciplines within fishery science will result in more robust advice.

Impacts of outliers and mis-specification of priors on Bayesian fisheries-stock assessment

2000 ◽  
Vol 57 (11) ◽  
pp. 2293-2305 ◽  
Author(s):  
Y Chen ◽  
P A Breen ◽  
N L Andrew
Keyword(s):  
Normal Distribution ◽  
Stock Assessment ◽  
Management Strategies ◽  
Distribution Functions ◽  
Assessment Model ◽  
Fish Stock ◽  
Model Parameters ◽  
Prior Distributions ◽  
Likelihood Functions ◽  
Robust Likelihood

Bayesian inference is increasingly used in estimating model parameters for fish-stock assessment, because of its ability to incorporate uncertainty and prior knowledge and to provide information for risk analyses in evaluating alternative management strategies. Normal distributions are commonly used in formulating likelihood functions and informative prior distributions; these are sensitive to data outliers and mis-specification of prior distributions, both common problems in fisheries-stock assessment. Using a length-structured stock-assessment model for a New Zealand abalone fishery as an example, we evaluate the robustness of three likelihood functions and two prior-distribution functions, with respect to outliers and mis-specification of priors, in 48 different combinations. The two robust likelihood estimators performed slightly less well when no data outliers were present and much better when data outliers were present. Similarly, the Cauchy distribution was less sensitive to prior mis-specification than the normal distribution. We conclude that replacing the normal distribution with "fat-tailed" distributions for likelihoods and priors can improve Bayesian assessments when there are data outliers and mis-specification of priors, with relatively minor costs when there are none.

Contested stock assessment: two case studies

1998 ◽  
Vol 55 (2) ◽  
pp. 529-537 ◽  
Author(s):  
Paul Starr ◽  
John H Annala ◽  
Ray Hilborn
Keyword(s):  
Interest Groups ◽  
Peer Review ◽  
Case Studies ◽  
Oncorhynchus Tshawytscha ◽  
Pacific Salmon ◽  
Stock Assessment ◽  
Assessment Process ◽  
Commercial Fishing ◽  
Assessment Procedure ◽  
The Pacific

We describe two case studies where scientists representing alternative interest groups worked together to attempt to resolve scientific issues of fisheries assessments. In several fisheries in New Zealand, commercial fishing interests hired consultants to review governmental assessments. In some of these fisheries, the two sides provided alternative competing assessments; in other fisheries, there was a cooperative agreed-upon assessment. In the analysis of chinook salmon (Oncorhynchus tshawytscha) within the Pacific Salmon Treaty, scientists representing all parties agreed upon an assessment procedure and developed it over a number of years. Such contested assessments provide a number of benefits including (i) intense peer review, (ii) the ability to bring data from all parties into the assessment process, and (iii) better understanding and trust of the assessments by the different interest groups. Effective peer review requires repeating the calculations associated with data sources and assessment models. We suggest that contested assessments, despite the extra cost, are highly valuable, as they provide a substantially improved standard of assessment. Contested assessments will evolve towards cooperative analysis unless participating parties feel that the cooperative assessment is counter to their perceived interests.

scholarly journals “The Elephant in the Room”: Exploring Natural Mortality Uncertainty in Statistical Catch at Age Models

2020 ◽  
Vol 7 ◽  
Author(s):  
Alessandro Mannini ◽  
Cecilia Pinto ◽  
Christoph Konrad ◽  
Paraskevas Vasilakopoulos ◽  
Henning Winker
Keyword(s):  
Stock Assessment ◽  
Assessment Process ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Food And Agriculture ◽  
Stock Assessments ◽  
The Mediterranean ◽  
The Impact

The natural mortality rate (M) of a fish stock is typically highly influential on the outcome of age-structured stock assessment models, but at the same time extremely difficult to estimate. In data-limited stock assessments, M usually relies on a range of empirically or theoretically derived M estimates, which can vary vastly. This article aims at evaluating the impact of this variability in M using seven Mediterranean stocks as case studies of statistical catch-at-age assessments for information-limited fisheries. The two main bodies carrying out stock assessments in the Mediterranean and Black Seas are European Union’s Scientific Technical Economic Committee for Fisheries (STECF) and Food and Agriculture Organization’s General Fisheries Commission for the Mediterranean (GFCM). Current advice in terms of fishing mortality levels is based on a single “best” M assumption which is agreed by stock assessment expert working groups, but uncertainty about M is not taken into consideration. Our results demonstrate that not accounting for the uncertainty surrounding M during the assessment process can lead to strong underestimation or overestimation of fishing mortality, potentially biasing the management process. We recommend carrying out relevant sensitivity analyses to improve stock assessment and fisheries management in data-limited areas such as the Mediterranean basin.

Comparison of the frequentist properties of Bayes and the maximum likelihood estimators in an age-structured fish stock assessment model

2002 ◽  
Vol 59 (1) ◽  
pp. 136-143 ◽  
Author(s):  
Anders Nielsen ◽  
Peter Lewy
Keyword(s):  
Maximum Likelihood ◽  
Stock Assessment ◽  
Process Variations ◽  
Bayes Estimator ◽  
Assessment Model ◽  
Fish Stock ◽  
The North ◽  
The North Sea ◽  
Age Structured ◽  
Fish Stock Assessment

A simulation study was carried out for a separable fish stock assessment model including commercial and survey catch-at-age and effort data. All catches are considered stochastic variables subject to sampling and process variations. The results showed that the Bayes estimator of spawning biomass is a useful but slightly biased estimator for which the frequentist variance can be estimated by the posterior variance. Comparisons further show that the Bayes estimator is better than the maximum likelihood in the sense that it is less biased and, surprisingly, has a much lesser variance. The catch simulations were based on the North Sea plaice (Pleuronectes platessa) stock and fishery data.

A recipe for Bayesian network driven stock assessment

2004 ◽  
Vol 61 (9) ◽  
pp. 1647-1657 ◽  
Author(s):  
T R Hammond
Keyword(s):  
Bayesian Network ◽  
Stock Assessment ◽  
Assessment Model ◽  
Fish Stock ◽  
Posterior Density ◽  
Discrete Random Variables ◽  
Analytic Integration ◽  
Network Propagation ◽  
A New Technique ◽  
Fish Stock Assessment

Markov Chain Monte Carlo (MCMC), the most widely used algorithm in Bayesian statistics, can fail to converge. Although convergence is tested by various diagnostics, these can only reveal failure, never success. To avoid these difficulties, this paper suggests a recipe for using Bayesian network propagation (BNP) to compute posterior results for fish stock assessment. Bayesian networks employ discrete random variables and specify relationships between them with conditional probability tables. Therefore, the recipe uses a new technique called "fuzzy discretization" to convert a continuous Bayesian model into a discrete Bayesian network. The technique is illustrated on a Schaefer assessment model by showing how model equations can be converted to probability tables. Posterior density estimates for carrying capacity (K) from both MCMC and BNP were compared with exact results (obtained by analytic integration and grid search) under three scenarios. BNP outperformed MCMC (as implemented in WinBUGS) in all scenarios, though MCMC diagnostics previously deemed sufficient reported no problems. Tightening the grid resolution of discrete numeric variables over regions of high posterior probability greatly improved BNP performance, so a grid selection heuristic is included in the recipe. In summary, this recipe may provide an effective alternative to MCMC for similar Bayesian problems.

Fleksibest—an age–length structured fish stock assessment model

2002 ◽  
Vol 55 (1-3) ◽  
pp. 87-101 ◽  
Author(s):  
Kristin Guldbrandsen Frøysa ◽  
Bjarte Bogstad ◽  
Dankert W. Skagen
Keyword(s):  
Stock Assessment ◽  
Assessment Model ◽  
Fish Stock ◽  
Fish Stock Assessment

Application of the bomb radiocarbon chronometer to the validation of redfish Centroberyx affinis age

1995 ◽  
Vol 52 (7) ◽  
pp. 1399-1405 ◽  
Author(s):  
John M. Kalish
Keyword(s):  
Age Estimation ◽  
Stock Assessment ◽  
Estimation Method ◽  
Assessment Process ◽  
Estimation Methods ◽  
Fish Stock ◽  
Critical Element ◽  
Bomb Radiocarbon ◽  
Radiocarbon Data ◽  
Fish Stock Assessment

Validation of methods used to estimate fish age is a critical element of the fish stock assessment process. Despite the importance of validation, few procedures are available that provide unbiased estimates of true fish age and those methods that are available are seldom used. The majority of these methods are unlikely to provide an indication of the true age of individual fish, data that are best suited to the validation process. Accelerator mass spectrometry analyses of radiocarbon in selected regions of Centroberyx affinis otoliths were used to validate the age estimation method for this species. Radiocarbon data from the otoliths of C. affinis with presumed birth dates between 1955 and 1985 described the increase in ocean radiocarbon attributable to the atmospheric detonation of nuclear weapons in the 1950s and 1960s. The results confirm the longevity of C. affinis and demonstrate the effectiveness of the bomb radiocarbon chronometer for the validation of age-estimation methods.

Detecting and correcting underreported catches in fish stock assessment: trial of a new method

2010 ◽  
Vol 67 (8) ◽  
pp. 1247-1261 ◽  
Author(s):  
Nicolas Bousquet ◽  
Noel Cadigan ◽  
Thierry Duchesne ◽  
Louis-Paul Rivest
Keyword(s):  
Gadus Morhua ◽  
Stock Assessment ◽  
Population Analysis ◽  
Assessment Model ◽  
Fish Stock ◽  
Stock Biomass ◽  
Stock Assessments ◽  
Spawning Stock ◽  
Age Structured ◽  
Fish Stock Assessment

Landings from fisheries are often underreported, that is, the true landings are greater than those reported. Despite this bias, reported landings are widely used in fish stock assessments, and this might lead to overoptimistic exploitation strategies. We construct a statistical stock assessment model that accounts for underreported landings using the theory of censoring with sequential population analysis (SPA). The new model is developed and implemented specifically for the cod stock ( Gadus morhua ) from the southern Gulf of St. Lawrence (Canada). This stock is known to have unreported overfishing during 1985–1992. We show in simulations that for this stock, the new censored model can correctly detect the problematic landings. These corrections are nearly insensitive to subjective boundaries placed on real catches and robust to modifications imposed in the simulation of landings. However, when surveys are too noisy, the new SPA for censored catches can result in increased uncertainty in parameters used for management such as spawning stock biomass and age-structured stock size.

scholarly journals Using survey data independently from commercial data in stock assessment: an example using haddock in ICES Division VIa

2005 ◽  
Vol 62 (5) ◽  
pp. 996-1005 ◽  
Author(s):  
D.J. Beare ◽  
C.L. Needle ◽  
F. Burns ◽  
D.G. Reid
Keyword(s):  
Survey Data ◽  
Stock Assessment ◽  
Assessment Process ◽  
Fish Stock ◽  
Trawl Survey ◽  
Commercial Catch ◽  
Spatially Resolved ◽  
Abundance Estimates ◽  
Class Strength ◽  
Downward Spiral

Abstract Currently standard fish stock biomass estimates are based most directly on commercial catch-at-age data. The main contribution made by research-vessel trawl survey data to the stock assessment process is to “tune” trends in the commercial data and provide estimates of incoming year-class strength. In this process much of the information contained with the survey data (e.g. spatial detail) is lost because the data are first aggregated into numbers-at-age indices for given areas. Another problem is that increasingly restrictive total allowable catches (TACs) imposed on the fishing industry have led to what is suspected to be widespread misreporting, i.e. the scientists do not know how many fish have been landed. This leads to negative biases in the catch data, low stock abundance estimates by scientists, even lower TACs, followed by even more misreporting. One potential way to escape this downward spiral is to explore scientific trawl survey data in more detail since trawl surveys are more straightforward to regulate. Traditionally, there has been resistance to this idea since, in comparison to commercial catch-at-age data, trawl survey data are very sparse in space and time. In this study, the potential for using trawl survey data independently in stock assessments is explored for the case of ICES Area VIa haddock, using two different tools. Findings suggest that it is possible to get qualitatively useful information from trawl survey data alone as well as quantitative, spatially resolved, estimates of fish abundance by making simple swept-area assumptions. In addition, interesting differences between survey and commercial data are highlighted by the study. The mean age of fish reported by the commercial fleet, for example, is higher than that reflected by the survey data, while fishing mortality estimates tend to be higher when estimated from survey data alone.

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