@article {Challier_etal2006,
	title = {{Introducing inter-individual growth variability in the assessment of a cephalopod population: application to the English Channel squid Loligo forbesi}},
	journal = {Oecologia},
	volume = {150},
	number = {1},
	year = {2006},
	pages = {17{\textendash}28},
	abstract = {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-length is applied to the English Channel squid <i>Loligo forbesi</i>. Age distribution at length from quantile regression proved to be considerably less biased than that resulting from both polymodal decomposition (PD) and two separate slicing methods. Both catch-at-age and stock size were underestimated using classical methods. Estimations of fishing mortalities from classical methods were higher causing underestimation in yield simulations. Quantile regression offers a more complete statistical analysis of the stochastic relationships among random variables than mean regression and PD.},
	doi = {10.1007/s00442-006-0497-x},
	author = {Challier, L and Orr, P and Jean-Paul Robin}
}
