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

Summary: Estimating catch-at-age by combining data from
different sources
David Hirst, Geir Storvik, Magne Aldrin, Sondre Aanes, and Ragnar Bang Huseby
Abstract: Estimating the catch-at-age of commercial fish species is an important part of the quota-setting process for
many different species and almost all countries with a fishing fleet. Current procedures are usually very time-
consuming and somewhat ad hoc, and the estimates have no measure of uncertainty. We previously developed a method
for catch-at-age of Norwegian Atlantic cod (Gadus morhua), but this only considered aged fish sampled randomly from
random hauls. In most countries, the sampling scheme is not so simple. There are usually a very large number of
length-only samples from which the age must be estimated using an age­length relationship, and often some or all of
the age samples are collected from data that are first stratified by length. This adds considerably to the difficulties in
the estimation. In this paper, we model the three different kinds of data simultaneously using a development of our ear-
lier Bayesian hierarchical model. This enables us to obtain estimates of the catch-at-age with appropriate uncertainty
and also to provide advice on how best to sample data in the future. The data types are random samples of age, length,
and weight; age and weight stratified by length; and length only.
Résumé : L'estimation de la récolte en fonction de l'âge est une étape importante du processus de définition des quo-
tas pour plusieurs espèces et dans presque tous les pays qui possèdent une flotte de pêche. Les méthodes courantes
exigent beaucoup de temps et elles sont ajustées à des situations particulières et elles ne comportent pas de mesure
d'incertitude. Nous avons développé antérieurement une méthode pour estimer la capture en fonction de l'âge chez la
morue franche (Gadus morhua) de Norvège, mais elle ne tient compte que des poissons d'âge connu échantillonnés au
hasard dans des récoltes aléatoires. Dans la plupart des pays, le plan d'échantillonnage est loin d'être aussi simple. Il y

  

Source: Aldrin, Magne - Norsk Regnesentral
Storvik, Geir - Matematisk institutt, Universitetet i Oslo

 

Collections: Biology and Medicine; Mathematics