Identifying resting locations of a small elusive forest carnivore using a two-stage model accounting for GPS measurement error and hidden behavioral states
Movement Ecology
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Abstract
Studies of animal movement using location data are often faced with two challenges. First, time series of animal locations are likely to arise from multiple behavioral states (e.g., directed movement, resting) that cannot be observed directly. Second, location data can be affected by measurement error, including failed location fixes. Simultaneously addressing both problems in a single statistical model is analytically and computationally challenging. To both separate behavioral states and account for measurement error, we used a two-stage modeling approach to identify resting locations of fishers (Pekania pennanti) based on GPS and accelerometer data.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Identifying resting locations of a small elusive forest carnivore using a two-stage model accounting for GPS measurement error and hidden behavioral states |
| Series title | Movement Ecology |
| DOI | 10.1186/s40462-021-00256-8 |
| Volume | 9 |
| Year Published | 2021 |
| Language | English |
| Publisher | Springer Nature |
| Contributing office(s) | Western Fisheries Research Center |
| Description | 17, 22 p. |
| Country | United States |
| State | California, Oregon |
| Google Analytic Metrics | Metrics page |