In:
Transactions of the American Fisheries Society, Wiley, Vol. 146, No. 4 ( 2017-07), p. 803-815
Abstract:
A series of estimates of the total mortality rate ( Z ) can be obtained by using the Beverton–Holt nonequilibrium‐based approach of Gedamke and Hoenig (2006) on observations of population mean length over time (ML model). In contrast, only relative mortality rates (not absolute values) can be obtained from a time series of catch rates. We derived the transitional behavior of the catch rate following a change in total mortality in the population. From this derivation, we developed a new method to estimate Z that utilizes both mean lengths and catch rates (MLCR model). Both the ML model and the MLCR model assume constant recruitment in the population. We used a simulation study to test performance when recruitment is variable. Simulations over various scenarios of Z and recruitment variability showed that there may be correlated residuals in the mean lengths and catch rates arising from fluctuations in recruitment. However, the root mean square errors of the Z estimates and the change point (i.e., the year when mortality changed) were smaller in the MLCR model than in the ML model, indicating that the MLCR model can better account for variable recruitment. Both methods were then applied to Mutton Snapper Lutjanus analis in Puerto Rico to illustrate their potential application to assess data‐limited stocks. The ML model estimated an increase in Z , but the MLCR model also estimated a subsequent reduction in Z when the catch rate data were considered. Received September 6, 2016; accepted March 14, 2017 Published online June 9, 2017
Type of Medium:
Online Resource
ISSN:
0002-8487
,
1548-8659
DOI:
10.1080/00028487.2017.1308881
Language:
English
Publisher:
Wiley
Publication Date:
2017
detail.hit.zdb_id:
2192460-0
SSG:
12
SSG:
21,3
