Selection and estimation of sequential catch-at-age models

2012 ◽  
Vol 69 (11) ◽  
pp. 1760-1772 ◽  
Author(s):  
Gudmundur Gudmundsson ◽  
Thorvaldur Gunnlaugsson
Keyword(s):  
Measurement Errors ◽  
Gadus Morhua ◽  
Likelihood Function ◽  
Marginal Likelihood ◽  
Stock Assessment ◽  
Fish Stock ◽  
Natural Mortality ◽  
Selectivity Estimation ◽  
Time Series Modelling ◽  
Simplifying Assumptions

Fish stock assessment by catch-at-age and survey data is affected by many stochastic elements: measurement errors; sampling variations; natural variations in mortality, catchability and migrations; technological and social effects on fishing intensity and selectivity. Estimation of simulated models shows that the bias in estimation by linear approximation of the Kalman filter or automatic approximation of the marginal likelihood function is much smaller than the errors produced by the stochastic elements. In time series modelling, they are represented by residuals in the equations. Strong simplifying assumptions about these effects are common in catch-at-age analysis, but estimation of models for Icelandic cod ( Gadus morhua ) and pollock ( Pollachius virens , herein referred to as saithe) demonstrates that the relative importance of different random elements can vary greatly between stocks. These assumptions include exact catch-at-age measurements, no irregular migrations or variations in natural mortality, separable fishing mortality rates, and no permanent variations in survey catchability. Inappropriate simplificactions can have a strong effect on stock estimates. It is possible and important to test simplifying assumptions by comparison with more general models. Estimation of the magnitude of natural mortality is also examined.

scholarly journals Estimation of the parameters of fish stock dynamics from catch-at-age data and indices of abundance: can natural and fishing mortality be separated?

2007 ◽  
Vol 64 (8) ◽  
pp. 1130-1142 ◽  
Author(s):  
Sondre Aanes ◽  
Steinar Engen ◽  
Bernt-Erik Sæther ◽  
Ronny Aanes
Keyword(s):  
Gadus Morhua ◽  
State Space Model ◽  
Population Projections ◽  
Quality Data ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Absolute Size ◽  
Data Set ◽  
Long Time

Models for fluctuations in size of fish stocks must include parameters that describe expected dynamics, as well as stochastic influences. In addition, reliable population projections also require assessments about the uncertainties in estimates of vital parameters. Here we develop an age-structured model of population dynamics based on catch-at-age data and indices of abundance in which the natural and fishing mortality are separated in a Bayesian state–space model. Markov chain Monte Carlo methods are used to fit the model to the data. The model is fitted to a data set of 19 years for Northeast Arctic cod (Gadus morhua). By simulations of the fitted model we show that the model captures the dynamical pattern of natural mortality adequately, whereas the absolute size of natural mortality is difficult to estimate. Access to long time series of high-quality data are necessary for obtaining precise estimates of all the parameters in the model, but some parameters cannot be estimated without including some prior information. Nevertheless, our model demonstrates that temporal variability in natural mortality strongly affects perceived variability in stock sizes. Thus, using estimation procedures that neglect temporal fluctuations in natural mortality may therefore give biased estimates of fluctuations in fish stock sizes.

scholarly journals Non-linearity in stock–recruitment relationships of Atlantic cod: insights from a multi-model approach

2019 ◽  
Vol 77 (4) ◽  
pp. 1492-1502 ◽  
Author(s):  
Camilla Sguotti ◽  
Saskia A Otto ◽  
Xochitl Cormon ◽  
Karl M Werner ◽  
Ethan Deyle ◽  
...  
Keyword(s):  
Environmental Variables ◽  
Gadus Morhua ◽  
Fishery Management ◽  
Atlantic Cod ◽  
Stock Assessment ◽  
Fish Stock ◽  
Recovery Potential ◽  
Stock Recruitment ◽  
Model Approach ◽  
Non Parametric

Abstract The stock–recruitment relationship is the basis of any stock prediction and thus fundamental for fishery management. Traditional parametric stock–recruitment models often poorly fit empirical data, nevertheless they are still the rule in fish stock assessment procedures. We here apply a multi-model approach to predict recruitment of 20 Atlantic cod (Gadus morhua) stocks as a function of adult biomass and environmental variables. We compare the traditional Ricker model with two non-parametric approaches: (i) the stochastic cusp model from catastrophe theory and (ii) multivariate simplex projections, based on attractor state-space reconstruction. We show that the performance of each model is contingent on the historical dynamics of individual stocks, and that stocks which experienced abrupt and state-dependent dynamics are best modelled using non-parametric approaches. These dynamics are pervasive in Western stocks highlighting a geographical distinction between cod stocks, which have implications for their recovery potential. Furthermore, the addition of environmental variables always improved the models’ predictive power indicating that they should be considered in stock assessment and management routines. Using our multi-model approach, we demonstrate that we should be more flexible when modelling recruitment and tailor our approaches to the dynamical properties of each individual stock.

scholarly journals Detecting regime shifts in fish stock dynamics

2015 ◽  
Vol 72 (11) ◽  
pp. 1619-1628 ◽  
Author(s):  
Tommi Perälä ◽  
Anna Kuparinen
Keyword(s):  
Gadus Morhua ◽  
Atlantic Cod ◽  
Stock Assessment ◽  
Detection Algorithm ◽  
Regime Shifts ◽  
Change Point Detection ◽  
Fish Stock ◽  
Fish Stocks ◽  
Data Generating Process ◽  
Change In Mean

Environmental factors such as water temperature, salinity, and the abundance of zooplankton can have major effects on certain fish stocks’ ability to produce juveniles and, thus, stock renewal ability. This variability in stock productivity manifests itself as different productivity regimes. Here, we detect productivity regime shifts by analyzing recruit-per-spawner time series with Bayesian online change point detection algorithm. The algorithm infers the time since the last regime shift (change in mean or variance or both) as well as the parameters of the data-generating process for the current regime sequentially. We demonstrate the algorithm’s performance using simulated recruitment data from an individual-based model and further apply the algorithm to stock assessment estimates for four Atlantic cod (Gadus morhua) stocks obtained from RAM legacy database. Our analysis shows that the algorithm performs well when the variability between the regimes is high enough compared with the variability within the regimes. The algorithm found several productivity regimes for all four cod stocks, and the findings suggest that the stocks are currently in low productivity regimes, which have started during the 1990s and 2000s.

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.

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.

In what direction should the fishing mortality target change when natural mortality increases within an assessment?

2016 ◽  
Vol 73 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Christopher M. Legault ◽  
Michael C. Palmer
Keyword(s):  
Mortality Rate ◽  
Empirical Evidence ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Stock Assessment ◽  
Total Mortality ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Limanda Ferruginea ◽  
Trade Offs

Traditionally, the natural mortality rate (M) in a stock assessment is assumed to be constant. When M increases within an assessment, the question arises how to change the fishing mortality rate target (FTarget). Per recruit considerations lead to an increase in FTarget, while limiting total mortality leads to a decrease in FTarget. Application of either approach can result in nonsensical results. Short-term gains in yield associated with high FTarget values should be considered in light of potential losses in future yield if the high total mortality rate leads to a decrease in recruitment. Examples using yellowtail flounder (Limanda ferruginea) and Atlantic cod (Gadus morhua) are used to demonstrate that FTarget can change when M increases within an assessment and to illustrate the consequences of different FTarget values. When a change in M within an assessment is contemplated, first consider the amount and strength of empirical evidence to support the change. When the empirical evidence is not strong, we recommend using a constant M. If strong empirical evidence exists, we recommend estimating FTarget for a range of stock–recruitment relationships and evaluating the trade-offs between risk of overfishing and forgone yield.

Ovulatory Rhythm and a Method to Determine the Stage of Spawning in Atlantic Cod (Gadus morhua)

1990 ◽  
Vol 47 (6) ◽  
pp. 1185-1193 ◽  
Author(s):  
O. S. Kjesbu ◽  
P. R. Witthames ◽  
P. Solemdal ◽  
M. Greer WalKer
Keyword(s):  
Standard Deviation ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Stock Assessment ◽  
Growth Period ◽  
Fish Stock ◽  
Oocyte Growth ◽  
Size Frequency Distribution ◽  
Fish Stock Assessment ◽  
Linear Regressions

The size frequency distribution of the vitellogenic oocytes in Atlantic cod (Gadus morhua) changes in a predictable manner as spawning progresses. This change was studied by sampling successive batches of eggs from reared cod kept in the laboratory. The shape of the vitellogenic oocyte mode was described by measuring the diameter, standard deviation, and skewness and kurtosis. Linear regressions were derived which related the portion of the total number of eggs spawned per season (PES) to the number of vitellogenic oocytes per gram of the ovary and in relation to the standard deviation of the distribution. This method which allows the PES in a spawning fish to be estimated has the following applications. For fish stock assessment purposes fecundity estimates can be made on spawning rather than prespawning fish and residence times on spawning grounds can be calculated. In addition successive batches of eggs can be identified and studied. This is important in hormonal and larval studies. A detailed description is given of the oocyte growth during the ovulatory rhythm. The rhythm consists of four periods: arrest, final growth, hydration, and ovulation. It is suggested that the egg size is determined during the final growth period.

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 It’s elemental, my dear Watson: validating seasonal patterns in otolith chemical chronologies

2020 ◽  
Author(s):  
Karin Hüssy ◽  
Maria Krüger-Johnsen ◽  
Tonny Bernt Thomsen ◽  
Benjamin Dominguez Heredia ◽  
Tomas Naeraa ◽  
...  
Keyword(s):  
Age Estimation ◽  
Gadus Morhua ◽  
Stock Assessment ◽  
Early Spring ◽  
Fish Stock ◽  
Late Winter ◽  
Seasonal Patterns ◽  
Traditional Age ◽  
Eastern Baltic ◽  
Baltic Cod

Accurate age data is essential for reliable fish stock assessment. Yet many stocks suffer from inconsistencies in age interpretation. A new approach to obtain age makes use of the chemical composition of otoliths. This study validates the periodicity of recurrent patterns in 25Mg, 31P, 34K, 55Mn, 63Cu, 64Zn, 66Zn, 85Rb, 88Sr, 138Ba, and 208Pb in Baltic cod (Gadus morhua) otoliths from tag-recapture and known-age samples. Otolith P concentrations showed the highest consistency in seasonality over the years, with minima co-occurring with otolith winter zones in the known-age otoliths and in late winter/early spring when water temperatures are coldest in tagged cod . The timing of minima differs between stocks, occurring around February in western Baltic cod and one month later in eastern Baltic cod; seasonal maxima are also stock-specific, occurring in August and October, respectively. The amplitude in P is larger in faster-growing western compared to eastern Baltic cod. Seasonal patterns with minima in winter/late spring were also evident in Mg and Mn, but less consistent over time and fish size than P. Chronological patterns in P, and to a lesser extent Mg and Mn, may have the potential to supplement traditional age estimation or to guide the visual identification of translucent and opaque otolith patterns used in traditional age estimation

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.

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