Estimating multifleet catchability coefficients and natural mortality from fishery catch and effort data: comparison of Bayesian state–space and observation error models

2011 ◽  
Vol 68 (7) ◽  
pp. 1171-1181 ◽  
Author(s):  
Shijie Zhou ◽  
André E. Punt ◽  
Roy Deng ◽  
Janet Bishop
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Observation Error ◽  
Natural Mortality ◽  
Posterior Median ◽  
Median Estimate ◽  
Penaeus Semisulcatus ◽  
Process Error ◽  
Two Parameters ◽  
Delay Difference

Catchability and natural mortality are key quantities in fisheries stock assessment. However, it is difficult to estimate these two parameters simultaneously using only fishery catch and effort data. A Bayesian state–space modified delay–difference model is outlined that can estimate time series of catchability by fleet as well as natural mortality. This model, and three variants thereof, is fitted to data for grooved tiger prawns ( Penaeus semisulcatus ) in Australia’s Northern Prawn Fishery during the period of the year when there is little recruitment. A model that allows for both observation and process error and estimates natural mortality is best, in terms of model selection criteria as well as fit diagnostics. The posterior median estimate for catchability for the primary target fleet ranges from 6.15 × 10−4 to 1.09 × 10−4 during 1980–2007, while the posterior median estimate for catchability for a fleet with P. semisulcatus as its byproduct is about 20% of that for the primary fleet. Fishing efficiency increased at approximately 2% annually during 1980–2007, while the weekly natural mortality is estimated to be 0.053 week–1.

Natural mortality diagnostics for state-space stock assessment models

2021 ◽  
Vol 243 ◽  
pp. 106062
Author(s):  
Andrea M.J. Perreault ◽  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Natural Mortality

Bayesian stock assessment using a state–space implementation of the delay difference model

1999 ◽  
Vol 56 (1) ◽  
pp. 37-52 ◽  
Author(s):  
Renate Meyer ◽  
Russell B Millar
Keyword(s):  
State Space ◽  
Bayesian Approach ◽  
Stock Assessment ◽  
State Space Model ◽  
Random Errors ◽  
Difference Model ◽  
Spawning Stock ◽  
The Common ◽  
Biomass Dynamics ◽  
Delay Difference

This paper presents a Bayesian approach to fisheries stock assessment using the delay difference model to describe nonlinear population dynamics. Given a time series of annual catch and effort data, models in the Deriso-Schnute family predict exploitable biomass in the following year from biomass in the current and previous year and from past spawning stock. A state-space model is used, as it allows incorporation of random errors in both the biomass dynamics equations and the observations. Because the biomass dynamics are nonlinear, the common Kalman filter is generally not applicable for parameter estimation. However, it is demonstrated that the Bayesian approach can handle any form of nonlinear relationship in the state and observation equations as well as realistic distributional assumptions. Difficulties with posterior calculations are overcome by the Gibbs sampler in conjunction with the adaptive rejection Metropolis sampling algorithm.

scholarly journals A state-space stock assessment model for northern cod, including under-reported catches and variable natural mortality rates

2016 ◽  
Vol 73 (2) ◽  
pp. 296-308 ◽  
Author(s):  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Gadus Morhua ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Assessment Model ◽  
Data Sources ◽  
Natural Mortality ◽  
Similar Data ◽  
Subjective Data ◽  
Northern Cod

A state-space assessment model for the northern cod (Gadus morhua) stock off southern Labrador and eastern Newfoundland is developed here. The model utilizes information from offshore trawl surveys, inshore acoustic surveys, fishery catch age compositions, partial fishery landings, and tagging. This is done using an approach that avoids the use of subjective data-weighting. Estimates of fishing mortality rates (F) are usually conditional on assumptions about natural mortality rates (M) in stock assessment models. However, by integrating much of the information on northern cod, it is possible to estimate F and M separately. It is also possible to estimate a change in the offshore survey catchability by including inshore acoustic biomass estimates. The proposed model also accounts for biased total catch statistics, which is a common problem in stock assessments. The main goal of the model is to provide realistic projections of the impacts of various levels of future fishery catches on the recovery of this stock. The projections incorporate uncertainty about M and catch. This is vital information for successful future fisheries. The model has been developed for the specific data sources available for northern cod, but it could be adapted to other stocks with similar data sources.

scholarly journals Disentangling risks to an endangered fish: using a state-space life cycle model to separate natural mortality from anthropogenic losses

2021 ◽  
Author(s):  
William Everett Smith ◽  
Leo Polansky ◽  
Matthew L. Nobriga
Keyword(s):  
Life Cycle ◽  
State Space ◽  
Process Variation ◽  
Estuarine Fish ◽  
Observation Error ◽  
Natural Mortality ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Multiple Sources ◽  
Delta Smelt

State-space population models are becoming a common tool to guide natural resource management, because they address the statistical challenges arising from high observation error and process variation while improving inference by integrating multiple, disparate datasets. A hierarchical state-space life cycle model was developed, motivated by delta smelt (Hypomesus transpacificus), an estuarine fish experiencing simultaneous risks of entrainment mortality from out-of-basin water export and natural mortality. Notable model features included a covariate-dependent instantaneous rates formulation of survival, allowing estimation of multiple sources of mortality, and inclusion of relative observation bias parameters, allowing integration of differently scaled abundance indices and entrainment estimates. Simulation testing confirmed that two sources of mortality, process variation, and data integration parameters could be estimated. Delta smelt entrainment mortality was associated with environmental conditions used to manage entrainment, and recruitment and natural mortality were related to temperature, outflow, food, and predators. Although entrainment mortality was reduced in recent years, ecosystem conditions did not appear to support robust spawning or over-summer survival of new recruits, manifesting as a 98% reduction of adults during 1995-2015.

scholarly journals Effects of process and observation errors on effective sample size of fishery and survey age and length composition using variance ratio and likelihood methods

2011 ◽  
Vol 68 (7) ◽  
pp. 1548-1557 ◽  
Author(s):  
Peter-John F. Hulson ◽  
Dana H. Hanselman ◽  
Terrance J. Quinn
Keyword(s):  
Sample Size ◽  
Likelihood Function ◽  
Stock Assessment ◽  
Age Distribution ◽  
Multinomial Distribution ◽  
Effective Sample Size ◽  
Observation Error ◽  
Variance Ratio ◽  
Likelihood Methods ◽  
Process Error

Abstract Hulson, P-J. F., Hanselman, D. H., and Quinn, T. J. II. 2011. Effects of process and observation errors on effective sample size of fishery and survey age and length composition using variance ratio and likelihood methods. – ICES Journal of Marine Science, 68: 1548–1557. Observations of age or length composition from fisheries or research surveys are modelled frequently with the multinomial distribution. Violations of multinomial assumptions in data collection usually cause overdispersion of observations and consequent underestimation of uncertainty. This has led to the adoption of an effective sample size less than the actual sample size to approximate the likelihood function for age or length composition better in, for example, fishery stock assessment models. The behaviour of effective sample size is examined under different scenarios for population age distribution and sampling design. Effective sample size was approximated with three approaches: (i) the ratio of multinomial to empirical variance; (ii) sampling estimation; and (iii) the Dirichlet likelihood. The most significant changes in effective sample size were attributable to process error involving aggregation of ages within schools. In terms of observation error, effective sample size can be increased by increasing the number of tows from which samples are obtained for age or length composition, then, because of the reduced uncertainty in effective sample size, the Dirichlet likelihood can be integrated into the objective function of fishery stock assessment models to estimate the effective sample size in future assessments.

scholarly journals Getting all information out of logbooks: estimating banana prawn fishable biomass, catchability, and fishing power increase, with a focus on natural mortality

2014 ◽  
Vol 72 (1) ◽  
pp. 54-61 ◽  
Author(s):  
Shijie Zhou ◽  
Rik C. Buckworth ◽  
Nick Ellis ◽  
Roy A. Deng ◽  
Sean Pascoe
Keyword(s):  
Stock Assessment ◽  
Fish Stock ◽  
Unexpected Result ◽  
Observation Error ◽  
Natural Mortality ◽  
Power Increase ◽  
Aggregation Behaviour ◽  
Random Variability ◽  
Fishery Data ◽  
Fish Stock Assessment

Abstract Biomass, catchability, and natural mortality are key parameters in fish stock assessment. Yet, it is difficult to estimate these quantities, especially natural mortality, when only fishery data are available. Using a method of population depletion analysis, we estimated these population and biological quantities for the white banana prawn (Penaeus merguiensis) in Australia's valuable Northern Prawn Fishery. In addition, we directly included fishing power change over time. The models were implemented in a Bayesian framework by incorporating process error, observation error, and random variability for the underlying parameters. The posterior median initial fishable biomass ranged from ∼2000 to 7000 t year−1, and the median catchability varied from ∼3.8 × 10−4 to 7.3 × 10−4 boat-day−1, resulting in an average fishing power increase of 2.6% per year. An unexpected result is the estimate of exponential natural mortality rate of ∼0.03 week−1. This value is substantially lower than an earlier estimate of 0.05 week−1, which was based on a single year's fishery data in one stock region and has been widely used for over four decades without validation. We attribute this low natural mortality estimate mainly to prawn aggregation behaviour.

scholarly journals Impact of survey design changes on stock assessment advice: sea scallops

2013 ◽  
Vol 71 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Stephen J. Smith ◽  
Brad Hubley
Keyword(s):  
Nova Scotia ◽  
Survey Design ◽  
Stock Assessment ◽  
Error Component ◽  
Assessment Model ◽  
Observation Error ◽  
Design Changes ◽  
Process Error ◽  
Survey Estimates ◽  
Sea Scallops

Abstract Smith, S. J., and Hubley, B. 2014. Impact of survey design changes on stock assessment advice: sea scallops. – ICES Journal of Marine Science, 71: 320–327. Annual surveys of marine resources are used to monitor changes in population composition and abundance. Improvements in the performance and coverage of these surveys can readily be evaluated for the surveys themselves but should also be considered in the context of the stock assessment models that use the estimates from these surveys. For those surveys based on a probability design, improvements in the probability design are usually evaluated with respect to the resultant increase in precision of the survey estimates. Survey precision estimates can be included in many stock assessment models as observation error, as long as the process error component of the model is also identified. Advice on catch levels for sea scallop populations (Placopecten magellanicus) around Nova Scotia is developed using a Bayesian state space assessment model in which both observation and process error terms have been defined. Information on survey estimates of precision are included in the observation error component of the assessment model and the impacts of changes in survey precision on the provision of advice can be evaluated in terms of reference points and management advice. The sensitivity of stock assessment advice to changes in the level of precision of survey estimates was evaluated for three scallop fisheries around Nova Scotia. The results indicated that the impact of the changes depended upon the degree of concurrence between the annual changes in biomass as observed from the survey and those predicted by the model.

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