24 
Fishery Bulletin 1 15(1) 
A B 
Observation Observation 
Figure 4 
Probabilities (p,) derived according to Kullback-Leibler divergence criteria for the (A) 
log-normal and (B) power log-skew-t models. The dotted lines are the probabilities of 
0.51, 0.55, 0.60, and 0.70. 
length-at-age data (Quiroz et al., 2010; Montenegro 
and Branco, 2016). This framework is particularly rel- 
evant when dealing with harvested fish populations for 
which length-at-age data collected from fishing opera- 
tions usually contain missing observations and indicate 
bias toward fast-growing individuals of each age class. 
A correct specification of the VBGF is critical because 
growth is an important aspect of contemporary stock 
assessment models (Zhu et al., 2016) upon which bio- 
mass estimates and conservation measures are based. 
Acknowledgments 
The authors are grateful to the Institute de Fomento 
Pesquero (Valparaiso, Chile) for providing access to 
the data used in this work. The research of F. Lopez 
Quintero was supported partially by a doctoral grant 
from Pontificia Universidad Catolica de Valparaiso 
(Valparaiso, Chile). The research of J. Contreras-Reyes 
was supported partially by Comision Nacional de In- 
vestigacion Cientifico y Tecnologico (CONICYT) doc- 
toral scholarship 2016 number 21160618 (Res. Ex. 
4128/2016). R. Wiff was funded by Fondo Nacional de 
Desarrollo Cientifico y Tecnologico (FONDECYT) post- 
doctoral project number 3130425 and by the Center of 
Applied Ecology and Sustainability (CAPES) project 
CONICYT FB 0002. R. Arellano-Valle was funded by 
FONDECYT (Chile) grants 1120121 and 1150325. We 
are sincerely grateful to 3 anonymous reviewers for 
their comments and suggestions that greatly improved 
an early version of this manuscript. 
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