2006
DOI: 10.1007/s00442-006-0497-x
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Introducing inter-individual growth variability in the assessment of a cephalopod population: application to the English Channel squid Loligo forbesi

Abstract: A new approach is presented here to better take into account inter-individual growth variability in age-structured models used for stock assessment. Cohort analysis requires knowledge of the age structure of the catch, generally derived from an age-length key and length-structure information. Age distribution at length is estimated by applying conditional quantile regression to a data set of lengths and ages estimated from calcareous parts. A "stochastic" age-length key that describes the probability of age-at… Show more

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Cited by 9 publications
(4 citation statements)
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References 49 publications
(66 reference statements)
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“…Individual variability in growth has been observed in many taxa, including cephalopods (Domain et al 2000), gastropods (Hughes & Roberts 1980) and teleosts (Searcy & Sponaugle 2000), resulting in intraspecific size-at-age data often being highly variable (Challier et al 2006). Under these conditions, understanding population dynamics and changes in population size structure becomes challenging (Gurney & Veitch 2007), especially for exploited species.…”
Section: Introductionmentioning
confidence: 99%
“…Individual variability in growth has been observed in many taxa, including cephalopods (Domain et al 2000), gastropods (Hughes & Roberts 1980) and teleosts (Searcy & Sponaugle 2000), resulting in intraspecific size-at-age data often being highly variable (Challier et al 2006). Under these conditions, understanding population dynamics and changes in population size structure becomes challenging (Gurney & Veitch 2007), especially for exploited species.…”
Section: Introductionmentioning
confidence: 99%
“…Some exercises with cohort analysis (Royer et al 2002;Challier et al 2006a) and depletion methods (Young et al 2004) have been conducted for loliginid squids, but for the most part, conventional models used in the assessment of fin fish stocks are not applicable (Pierce & Guerra 1994). Nevertheless, if stock size predictions are to partly rely on temperature data (Robin & Denis 1999;Pierce & Boyle 2003;Chen et al 2006), the understanding of age structure, growth, and its variability under fluctuating environmental conditions is of fundamental relevance.…”
Section: Introductionmentioning
confidence: 99%
“…However, it is worth noting that one constraint of this type of growth analysis is that without the availability of age data on the study samples, and because the smoothing graphs are composites of a collection of animals at different developmental points in the life cycle, it is impossible to follow the individual growth trajectories of single animals, and so inferences must be made from the population regarding growth processes (as has been done in previous research, e.g. Challier et al, 2006). As with previous results for male L. forbesii (and to a lesser extent, females) in Scotland and Spain Collins et al, 1999;Smith et al, 2005), for L. vulgaris from the Iberian Peninsula (Coelho et al, 1994; and Loligo reynaudii off South Africa (Hanlon et al, 2002;Olyott et al, 2006), the Dashed lines represent 95% confidence intervals around the main effects existence of two to three size-at-maturity categories within the animals sampled, each potentially having a characteristic gonad weight-body length relationship, would tend to give the appearance of a weaker positive relationship between the variables than exists within each group alone.…”
Section: Body Lengthmentioning
confidence: 99%