Influence of Growth and Recruitment Parameters in the Assessment and Management Variables of the Yellow Squat Lobster (Cervimunida johni)

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 ( L a = 1 ) and the coefficient of variation at age ( c v a ) were tested for six combinations of values for the steepness parameter (h) and the recruitment variance ( σ R 2 ). We also investigated the reliability of these estimates using an operating model. Our findings indicate that the parameter related to growth, L a = 1 , has the greatest impact on the assessment and management variables of this fishery resource, with c v a having a lesser effect. Recruitment and fishing mortality estimates were the main variables affected. Parameters h and σ R 2 did not profoundly impact the variables assessed. In addition, 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.

GROUPS WITH SUBNORMAL NORMALIZERS OF SUBNORMAL SUBGROUPS

We consider the class of solvable groups in which all subnormal subgroups have subnormal normalizers, a class containing many well-known classes of solvable groups. Groups of this class have Fitting length three at most; some other information connected with the Fitting series is given.

Fixed-point free action of an abelian group of odd non-squarefree exponent

Let A be a finite group acting fixed-point freely on a finite (solvable) group G. A longstanding conjecture is that if (|G|, |A|) = 1, then the Fitting length of G is bounded by the length of the longest chain of subgroups of A. It is expected that the conjecture is true when the coprimeness condition is replaced by the assumption that A is nilpotent. We establish the conjecture without the coprimeness condition in the case where A is an abelian group whose order is a product of three odd primes and where the Sylow 2-subgroups of G are abelian.

Using length data in the Schnute Model to describe growth in a metapenaeid from waters off Australia

This paper presents a novel approach for fitting length data to the Schnute growth model. Cohorts were fitted manually to a time series of length distributions from two stocks (Clarence and Hunter Rivers) of Metapenaeus macleayi and considered analogous to individuals from tag–recapture data, in order to estimate growth parameters. Data for Clarence males best fitted the three-parameter Schnute Model (L∞ = 21.3 mm CL, κ = 0.025 day–1 and γ = –1.35), whereas those for Hunter males were best fitted to a two-parameter version of the model (L∞ = 33.5 mm CL, κ = 0.009 day–1 and γ = 0 fixed). The equivalent to the von Bertalanffy growth function was the best fit to female data from both stocks (L∞ = 36.6 and 40.2 mm CL, κ = 0.004 and 0.005 day–1 and γ = 1 fixed for Clarence and Hunter respectively). Females grew larger than males and took longer to achieve their maximum size. No significant differences in female growth were found between stocks; however, males from the Hunter grew to a longer mean maximum length but at a slower rate than those from the Clarence. This study shows how the Schnute Model can be fitted to length based data and thus include the flexibility of comparing fits between asymptotic and non-asymptotic growth functions.