Evaluating a fish monitoring protocol using state-space hierarchical models
Open Fish Science Journal
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Abstract
Using data collected from three river reaches in Montana, we evaluated our ability to detect population trends and predict fish future fish abundance. Data were collected as part of a long-term monitoring program conducted by Montana Fish, Wildlife and Parks to primarily estimate rainbow (Oncorhynchus mykiss) and brown trout (Salmo trutta) abundance in numerous rivers across Montana. We used a hierarchical Bayesian mark-recapture model to estimate fish abundance over time in each of the three river reaches. We then fit a state-space Gompertz model to estimate current trends and future fish populations. Density dependent effects were detected in 1 of the 6 fish populations. Predictions of future fish populations displayed wide credible intervals. Our simulations indicated that given the observed variation in the abundance estimates, the probability of detecting a 30% decline in fish populations over a five-year period was less than 50%. We recommend a monitoring program that is closely tied to management objectives and reflects the precision necessary to make informed management decisions.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Evaluating a fish monitoring protocol using state-space hierarchical models |
| Series title | Open Fish Science Journal |
| DOI | 10.2174/1874401X01205010001 |
| Volume | 5 |
| Year Published | 2012 |
| Language | English |
| Publisher | Bentham Open |
| Publisher location | Oak Park, IL |
| Contributing office(s) | Montana Cooperative Fishery Research Unit, National Wildlife Health Center |
| Description | 8 p. |
| First page | 1 |
| Last page | 8 |
| Country | United States |
| State | Montana |
| Google Analytic Metrics | Metrics page |