scholarly journals Accounting for correlated observations in an age-based state-space stock assessment model

2016 ◽  
Vol 73 (7) ◽  
pp. 1788-1797 ◽  
Author(s):  
Casper W. Berg ◽  
Anders Nielsen
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Age Groups ◽  
Assessment Model ◽  
Fish Stock ◽  
Confidence Bounds ◽  
Independence Assumption ◽  
Fish Stocks ◽  
Fish Stock Assessment ◽  
Improved Model

Abstract Fish stock assessment models often rely on size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics based on observations from many fishing hauls and subsamples of the size and age composition of the data. Although aggregation mitigates the strong intra-haul correlation between sizes/ages that is usually found in haul-by-haul data, violations of the independence assumption can have a large impact on the results and specifically on reported confidence bounds. A state-space assessment model that allows for correlations between age groups within years in the observation model for catches and surveys is presented and applied to data on several North Sea fish stocks using various correlation structures. In all cases the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased.

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.

scholarly journals Length-Based Stock Assessment of Smith's Barb, Puntioplites proctozystron (Bleeker, 1865) (Cyprinidae) and Asian Redtail Catfish, Hemibagrus nemurus, (Valenciennes, 1840), (Bagridae) in a Multipurpose Reservoir in Thailand

2021 ◽  
Vol 34 (2) ◽  
Author(s):  
KAJITPAN CHARERNNATE ◽  
PAVAROT NORANARTTRAGOON ◽  
TUANTONG JUTAGATE ◽  
Keyword(s):  
Growth Parameters ◽  
Stock Assessment ◽  
Relative Yield ◽  
Mesh Size ◽  
Fish Stock ◽  
Fish Stocks ◽  
The Status ◽  
Curvature Parameter ◽  
Spawning Potential Ratio ◽  
Fish Stock Assessment

Catches from inland fisheries in Thailand are about 200,000 tonnes annually and plays an important role in food security and subsidiary income. However, fish stocks are seldom assessed because of the lack of catch and effort data. In this study, two fish stock assessment models, viz., relative yield per recruit and length-based spawning potential ratio, were used to evaluate the status of two species as well as to highlight their applications to datalimited situation in Thailand. The study was conducted at Kangkrajan Reservoir, Thailand, for two targeted species, viz., Smith's barb, Puntioplites proctozystron (Bleeker, 1865) and Asian redtail catfish, Hemibagrus nemurus (Valenciennes, 1840) using length frequency data. The data were collected throughout 2019. Both species showed isometric growth. Von Bertalanffy growth parameters were estimated. Asymptotic length, curvature parameter and theoretical age at length zero were 36.2 cm TL, 0.39 yr-1 and -0.28 yr for P. proctozystron, respectively, and 63.2 cm TL, 0.37 yr-1 and -0.32 yr for H. nemurus. The exploitation rates reveal that both species are slightly overfished. Sizes at 50 % maturity and 50 % selectivities were 17.8 and 23.5 cm TL for P. proctozystron, respectively, and 15.6 and 20.8 cm TL for H. nemurus. Considering both parameters, the size at first capture to sustain the fisheries of P. proctozystron and H. nemurus should be >18 cm and >30 cm, respectively, which can be achieved by mesh-size regulations.

scholarly journals Systmod II: Approaching a real dynamic computer model for fish stock assessment and development of fishery strategies

2016 ◽  
Author(s):  
Kristin Hamre ◽  
Steinar Moen ◽  
Johannes Hamre
Keyword(s):  
Stock Assessment ◽  
Growth Function ◽  
Field Studies ◽  
Fish Growth ◽  
Fish Stock ◽  
Initial State ◽  
Fish Stocks ◽  
Spawning Stock ◽  
Fish Stock Assessment ◽  
In The Beginning

Simulating development of fish stocks may be as complex as calculation of the development of the atmosphere, which is treated in meteorology as an initial value problem in physics. This approach was first proposed by Abbe and Bjerknes in the beginning of the 20 th century and today huge systems of differential equations are used to predict the weather. A similar approach to fisheries biology and ecology requires a real dynamic population model, which calculates the development of fish stocks from an initial state with equations that are independent of time. Here we present Systmod II, which uses a length-based growth function with a parameter for environmental variation and length-based data structure. The model uses monthly time steps to integrate population growth by moving fish to higher length groups as they grow. Since fish growth and maturity correlate more with length than with age, this gives comprehensive and clear results. The model was validated for Norwegian Spring-Spawning herring, using observed data from ICES working groups, and correlations (R2) between simulated and observed stock (total stock, spawning stock and catchable stock, numbers and biomass) were above 0.93. At present, the model makes reliable predictions on the short term (3 year for herring). For long term forecasts, better predictions of recruitment are needed . Since length is the main variable of the growth function, the state of the fish stock, including variability in length per yearclass, can be measured in situ, using hydro-acoustic trawl surveys. Data for modelling of many of the relations are still lacking, but can be filled in from future field studies.

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

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.

Use and abuse of fishery models

2001 ◽  
Vol 58 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Jon T Schnute ◽  
Laura J Richards
Keyword(s):  
World Literature ◽  
Fishery Management ◽  
Stock Assessment ◽  
Management Practice ◽  
Fish Stock ◽  
Fish Stocks ◽  
Creative Thought ◽  
Modeling Process ◽  
Stock Biomass ◽  
Fish Stock Assessment

Recent failures of important fish stocks give mathematical models a poor reputation as tools for fishery management. This paper examines the role of models in fish stock assessment and identifies reasons why they can fail. Starting with laws of arithmetic, models attempt to relate observed data to unknown quantities, such as the stock biomass and abundance. Typically, the number of unknowns greatly exceeds the number of observations, and models must impose hypothetical constraints to give useful estimates. We use the word "fishmetic" (rhymes with arithmetic) to represent uncertainty in the conversion of arithmetic to practical fishery models. Arbitrary assumptions cannot be avoided, even though different choices can greatly influence the outcome of the analysis. We compare the modeling process in fisheries with that in other sciences. World literature also offers useful analogies. Potential reasons for failure suggest possible improvements to the application of fishery models. We recommend that modelers remain skeptical, expand their knowledge base, apply common sense, and implement robust strategies for fishery management. Particularly creative thought must be applied to the problem of translating scientific knowledge into management practice. Comparisons between fish stocks and financial stocks illustrate some possibilities.

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