Resumen
Fitting length data in age-structured stock assessment is a common method for evaluating hard-to-age animals, such as crustaceans. Growth specification and the uncertainty in the stock recruitment relationship are key issues in length-based assessment models. We conducted sensitivity analyses to evaluate the impact of growth and recruitment parameters on the stock assessment and management variables of the yellow squat lobster (Cervimunida johni) caught off the Chilean coast. Nine different scenarios of the length at first capture (La=1" role="presentation">????=1La=1
L
a
=
1
) and the coefficient of variation at age (cva" role="presentation" style="position: relative;">??????cva
c
v
a
) were tested for six combinations of values for the steepness parameter (h) and the recruitment variance (σR2" role="presentation" style="position: relative;">??2??sR2
s
R
2
). We also investigated the reliability of these estimates using an operating model. Our findings indicate that the parameter related to growth, La=1" role="presentation" style="position: relative;">????=1La=1
L
a
=
1
, has the greatest impact on the assessment and management variables of this fishery resource, with cva" role="presentation" style="position: relative;">??????cva
c
v
a
having a lesser effect. Recruitment and fishing mortality estimates were the main variables affected. Parameters h and σR2" role="presentation" style="position: relative;">??2??sR2
s
R
2
did not profoundly impact the variables assessed. In addition, La=1" role="presentation" style="position: relative;">????=1La=1
L
a
=
1
was the most biased estimated parameter. We discuss that the high influence of growth parameters is related to model structure, and thus implications for determination of the status of yellow squat lobster should be addressed in the future. We recommended developing simulation protocols for the selection of growth parameters when using an age-structured model with length observations, and we believe that our findings are relevant for all Chilean fisheries with a similar stock assessment framework.