| Title | Diagnosing predated tags in telemetry survival studies of migratory fishes in river systems |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Authors | Buchanan, RA, Whitlock, SL |
| Volume | 10 |
| Issue | 1 |
| Pagination | 13 |
| Date Published | 2022/04/01 |
| ISBN Number | 2050-3385 |
| Abstract | Acoustic telemetry is a powerful tool for studying fish behavior and survival that relies on the assumption that tag detection reflects the presence of live study subjects. This assumption is violated when tag signals continue to be recorded after consumption by predators. When such tag predation is possible, it is necessary for researchers to diagnose and remove these non-representative detections. Past studies have employed a variety of data-filtering techniques to address the issue, ranging from rule-based algorithms that rely on expert judgements of behavior and movement capabilities of study subjects and their predators to automated pattern-recognition techniques using multivariate analyses. We compare four approaches for flagging suspicious tracks or detection events: two rule-based expert-opinion approaches of differing complexity and two unsupervised pattern-recognition approaches with and without data from deliberately tagged predators. We compare alternative approaches by applying these four filters to a case study of survival estimation of acoustic-tagged juvenile Chinook salmon (Oncorhynchus tshawytscha) in the San Joaquin River, California, United States. |
| URL | https://doi.org/10.1186/s40317-022-00283-1 |
| Short Title | Animal Biotelemetry |