Estimating catch-at-age by combining data from different sources

Hirst, David; Storvik, Geir; Aldrin, Magne; Aanes, Sondre; Huseby, Ragnar Bang

doi:10.1139/f05-026

Cited by 11 publications

(11 citation statements)

References 9 publications

(8 reference statements)

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“…If the sampling error is known beforehand, then subject to some assumptions, the total error is the sum of sampling and process error (Lewy and Nielsen 2003). In the present paper, the sampling error (not shown) for the Norwegian catches were, on average, larger than the process error for all catches (estimated by modelling the sampling schemes; see Aanes and Pennington (2003) and Hirst et al (2004Hirst et al ( , 2005). However, because of the lack of data from other than Norwegian catches, we can not exclude the possibility that process error may be of more significant importance than the error related to sampling (see Lewy and Nielsen (2003) for an example on North Sea plaice).…”

Section: Discussionmentioning

confidence: 48%

“…The catch at age is estimated by combining biological samples with the reported landings given by the management authorities (e.g., Aanes and Pennington 2003;Hirst et al 2004Hirst et al , 2005. Because of the heterogeneous fishery for many fish stocks, possibly including a variety of fleet groups and fishing over large areas, the sampling schemes become rather complex.…”

Section: Data Sourcesmentioning

confidence: 99%

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

Aanes¹,

Engen²,

Sæther³

et al. 2007

Can. J. Fish. Aquat. Sci.

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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 catchat-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.Résumé : Les modèles fluctuation de la taille des stocks de poissons doivent inclure des paramètres qui décrivent la dynamique attendue ainsi que les influences stochastiques. De plus, des projections fiables de la population nécessitent une évaluation des incertitudes dans les estimations des paramètres vitaux. Nous mettons au point un modèle de la dynamique de la population structuré en fonction de l'âge qui est basé sur les données de captures en fonction de l'âge et les indices d'abondance dans lequel la mortalité naturelle et la mortalité due à la pêche sont séparées dans un modèle état-espace bayésien. Des méthodes de Monte Carlo par chaîne de Markov servent à ajuster le modèle aux données. Nous ajustons le modèle à une matrice de données récoltées sur 19 années chez la morue (Gadus morhua) du nord-est de l'Arctique. Par simulations du modèle ajusté, nous montrons que le modèle capture adéquatement le patron dynamique de la mortalité naturelle, bien que la taille absolue de la mortalité naturelle soit difficile à estimer. Il est nécessaire d'avoir accès à de longues séries chronologiques de données de haute qualité pour obtenir des estimations précises de tous les paramètres du modèle, mais certains paramètres ne peuvent être estimés sans l'inclusion de renseignements a priori. Néanmoins, notre modèle démontre que la variabilité temporelle de la mortalité naturelle affecte fortement la variabilité perçue des tailles des stocks. Ainsi, l'utilisation de procédures qui négligent les fluctuations temporelles de la mortalité naturelle peut donner des estimations erronées des fluctuations dans les tailles des stocks de poissons.[Traduit par la Rédaction] Aanes et al. 1142

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Section: Discussionmentioning

confidence: 48%

Section: Data Sourcesmentioning

confidence: 99%

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

Aanes¹,

Engen²,

Sæther³

et al. 2007

Can. J. Fish. Aquat. Sci.

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“…The workflow and transparency principles of StoX may be useful for other types of marine and terrestrial surveys, and new functions can be added to the function library. The next steps for the StoX project are to include methods for biodiversity indices, implement methods for fishery dependent data (Hirst et al, ), develop web services that can run StoX and associated R‐packages on a website, and ensure tighter integration with the ICES and IMR data processing pipelines. Since StoX and Rstox are fully open source, we also envision a closer interaction between other user groups and developers.…”

Section: Discussionmentioning

confidence: 99%

StoX: An open source software for marine survey analyses

et al. 2019

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Scientists across the globe conduct survey programs to monitor and characterize abundance, population structure, biodiversity and geographical distributions. To assess the state of marine fish and zooplankton, population surveys are often repeated annually using standardized sampling protocols and analysis techniques to establish trustworthy stock status. However, although transparency and repeatability are recognised as important principles of this process, it is often difficult to obtain comprehensive documentation of metadata and data processing steps. This is particularly challenging for workflows that include manual processing steps. StoX was principally built to process research‐vessel survey data, and we have included several standard survey estimation models. The software was developed to be robust and versatile and aimed at the open source community, such that users could easily build their own models. StoX is fully integrated with R to utilize the large number of R‐packages and enable any StoX function and stock estimation model to be controlled using R. There has been a large need for a freely available software for research–vessel survey estimation, and StoX is tested in surveys carried out in four continents and is the official tool for many important fish stock surveys. The basic workflow and transparency principles of StoX, together with a customizable GUI, makes StoX applicable for any geographically coded surveys. Future versions of StoX will include statistical models to estimate the catch composition in commercial fisheries. In fields such as conservation management, there is also a need to document the estimation methods, and additional estimation and analyses models, including biodiversity indices are currently implemented. In parallel, we envision a closer web service integration with existing international and national data centres.

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“…We also recommend that statistical methods based on best practice (ICES 2013b) should be used to estimate catch-atage for NSSH, along with estimates of sampling errors. The model (Hirst et al 2004(Hirst et al , 2005(Hirst et al , 2012, which is used by the Institute of Marine Research for estimating the catch-at-age of northeast Arctic cod and haddock, may also be applied to NSSH commercial fisheries data. If input data on catch-at-age and abundance indices are provided with sampling errors, then an SAM can be used to quantify the precision of the stock assessment (SSB and F).…”

Section: Discussionmentioning

confidence: 99%

Precision in estimates of density and biomass of Norwegian spring-spawning herring based on acoustic surveys

Stenevik

Vølstad

Høines

et al. 2015

Marine Biology Research

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The abundance and biomass of the Norwegian spring-spawning herring (NSSH) stock are assessed annually using a virtual population analysis (VPA) applied to catch-at-age data from the fishery and fishery-independent abundance indices derived from research vessel surveys for calibration ('tuning'). The most important of these surveys is the International Ecosystem Survey in the Nordic Seas (IESNS) and this is highly influential for the outcome of the assessment. Until now, the abundance indices from the IESNS have been reported without any measure of uncertainty. In this study, the sampling errors associated with the density estimates of NSSH from the IESNS for the years 2009-2012 are estimated using designbased survey sampling theory. The annual survey estimates of number and biomass of herring per square nautical mile (nm 2 ) were relatively precise for all age groups combined, with relative standard error (RSE) ranging from 8% to 15%, while for each individual age group (3-12) the RSE was less than 30% for most years. For age groups 1 and 2, and all age groups older than 12 years, the density estimates are highly imprecise, with RSE ranging from 30% to 100%. The precision in estimated density provided here indicates that the time series from the survey can be used to study trends in overall abundance and biomass of the stock. It is recommended that statistical assessment models that can account for sampling errors in input data from survey indices by age group and catch-at-age be tested in the assessments of the NSSH stock.

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Estimating catch-at-age by combining data from different sources

Cited by 11 publications

References 9 publications

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

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

StoX: An open source software for marine survey analyses

Precision in estimates of density and biomass of Norwegian spring-spawning herring based on acoustic surveys

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