Direct estimates of gear selectivity from multiple tagging experiments
A new method is introduced for estimating selectivity of fishing gear from tagging data in which data from many experiments are combined. Selectivity is modeled as a multiplicative function of length and experiment effects using a generalized linear model with a log link function and a binomial erro...
| Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
|---|---|
| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Canadian Science Publishing
1997
|
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1139/f96-262 http://www.nrcresearchpress.com/doi/pdf/10.1139/f96-262 |
| Summary: | A new method is introduced for estimating selectivity of fishing gear from tagging data in which data from many experiments are combined. Selectivity is modeled as a multiplicative function of length and experiment effects using a generalized linear model with a log link function and a binomial error structure. We apply this method to 137 tagging experiments on Atlantic cod (Gadus morhua) conducted from 1954 to 1991. We show that the selectivity of otter trawls changed from the 1960s to the 1980s; during the earlier period the maximum probability of capture occurred at 55 cm and declined for longer fish, whereas in recent years the maximum probability is at approximately 60 cm and remains constant for longer fish. We discuss how selectivity estimates can be used to improve stock assessments.β & 23 |
|---|