Record Details
Choosing Sampling Interval Durations for Remotely Classifying Rocky Mountain Elk Behavior
ScholarsArchive at Oregon State University
| Field | Value |
|---|---|
| Title | Choosing Sampling Interval Durations for Remotely Classifying Rocky Mountain Elk Behavior |
| Names |
Gaylord, Adam J.
(creator) Sanchez, Dana M. (creator) Van Sickle, John (creator) |
| Date Issued | 2016-06 (iso8601) |
| Note | This is the publisher’s final pdf. The article is published by the U.S. Fish & Wildlife Service and can be found at: http://fwspubs.org/. All material appearing in the Journal of Fish and Wildlife Management is in the public domain and may be reproduced or copied without permission unless specifically noted with the copyright symbol. |
| Abstract | Dual-axis accelerometer global positioning system collars can be used to remotely record the activity level and behavior of free-ranging animals, but inter- and intraspecific variations in motion among behaviors necessitate calibration for each species of interest. To date, little work has been done to determine the best duration for sampling intervals when using activity monitors that incorporate dual-axis accelerometers. However, we expected that the duration of behaviors relative to the duration of sampling intervals could affect the accuracy of calibration and behavior classification models. Furthermore, we considered the potential effect of winter diet supplementation (hay) on behavior classification. We used Lotek 4500 global positioning system collars featuring dual-axis accelerometer activity monitors to collect data for calibration and classification trials on Rocky Mountain elk Cervus elaphus nelsoni. We used discriminant function model structures to determine the number of accurately classifiable behaviors that could be derived from data sampled over three sampling interval durations (5 min, 152 s, and 64 s) while also considering the potential effect of hay supplementation on classification. Our results suggest that investigators should ascertain whether their focal elk herd accesses or might access supplemental hay before deployment and analysis of activity sensor data. Similarly, researchers must weigh priorities when choosing a sampling interval, because no optimal solution emerged from our investigation. For example, of our acceptable models, only those constructed using 64-s intervals were able to distinguish short bouts of running. However, only models constructed with 5-min intervals accurately classified browsing while also maximizing the number of behaviors identified. |
| Genre | Article |
| Topic | accelerometer |
| Identifier | Gaylord, A. J., Sanchez, D. M., & Van Sickle, J. (2016). Choosing sampling interval durations for remotely classifying elk behavior. Journal of Fish and Wildlife Management, 7(1), 213-221. doi:10.3996/042015-JFWM-034 |
