Evaluating a fish monitoring protocol using state-space hierarchical models

Open Fish Science Journal
By: , and 



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.

Additional publication details

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) National Wildlife Health Center, Montana Cooperative Fishery Research Unit
Description 8 p.
First page 1
Last page 8
Country United States
State Montana