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Statistical Catch‐Free Age‐Structured Assessment to Estimate Year‐Class Strength for Inland Recreational Fisheries: A Largemouth Bass Example
Author(s) -
Feltz Nicholas G.,
Catalano Matthew J.
Publication year - 2017
Publication title -
north american journal of fisheries management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 72
eISSN - 1548-8675
pISSN - 0275-5947
DOI - 10.1080/02755947.2016.1240119
Subject(s) - fishing , fishery , electrofishing , stock assessment , micropterus , bass (fish) , geography , recreational fishing , environmental science , statistics , biology , fish <actinopterygii> , mathematics
Statistical catch‐at‐age analysis (SCAA) is commonly used to estimate recruitment and mortality for large‐scale, economically important fish stocks, but fishery‐dependent catch‐at‐age data are often unavailable for smaller‐scale inland fisheries, thus limiting the use of SCAA. In these systems, a catch‐free approach to age‐structure modeling may be useful for estimating recruitment and mortality rates solely from a time series of survey age composition and catch rate data by estimating recruitment as a relative index of year‐class strength ( R t ). Here, we demonstrate a statistical catch‐free age‐structured assessment (SCFASA) model for small‐scale inland fish stocks as an alternative to traditional catch curve approaches by using Largemouth Bass Micropterus salmoides as an example. We fitted the SCFASA to fishery‐independent survey age composition and catch‐per‐effort data from Largemouth Bass stocks in three Alabama reservoirs to estimate R t , annual fishing mortality rates, and age‐specific electrofishing survey vulnerability; we compared R t to catch curve residual estimates and performed a sensitivity analysis under a variety of model assumptions. Model estimates of R t and temporal trends in fishing mortality were robust to changes in assumptions about the effective sample size of multinomial age samples, natural mortality rate, and temporal variability in fishing mortality. However, the magnitude of instantaneous fishing mortality rates at two of the three reservoirs was somewhat higher than empirical estimates for similar stocks and was sensitive to model assumptions. Our application of the SCFASA to survey data sets routinely collected by management agencies for Largemouth Bass potentially provides a comprehensive approach to estimating R t , mortality, and sampling vulnerability for these stocks without increasing sampling effort. Future investigations of SCFASA's utility for small‐scale inland stocks should address the potential for bias in the magnitude of fishing mortality estimates due to incorrectly specified vulnerability schedules. Received October 5, 2015; accepted September 19, 2016 Published online December 21, 2016