Estimating the hatchery fraction of a natural population: a Bayesian approach
There is strong and growing interest in estimating the proportion of hatchery fish that are in a natural population (the hatchery fraction). In a sample of fish from the relevant population, some are observed to be marked, indicating their origin as hatchery fish. The observed proportion of marked fish is usually less than the actual hatchery fraction, since the observed proportion is determined by the proportion originally marked, differential survival (usually lower) of marked fish relative to unmarked hatchery fish, and rates of mark retention and detection. Bayesian methods can work well in a setting such as this, in which empirical data are limited but for which there may be considerable expert judgment regarding these values. We explored a Bayesian estimation of the hatchery fraction using Monte Carlo–Markov chain methods. Based on our findings, we created an interactive Excel tool to implement the algorithm, which we have made available for free.
Citation Information
| Publication Year | 2011 |
|---|---|
| Title | Estimating the hatchery fraction of a natural population: a Bayesian approach |
| DOI | 10.1080/02755947.2011.633687 |
| Authors | Jarrett Barber, Kenneth Gerow, Patrick J. Connolly, Sarabdeep Singh |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | North American Journal of Fisheries Management |
| Index ID | 70042256 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Western Fisheries Research Center |