Life Sciences Commons^™

Using Low-Fix Rate Gps Telemetry To Expand Estimates Of Ungulate Reproductive Success, Nathan D. Hooven, Kathleen E. Williams, John T. Hast, Joseph R. Mcdermott, R. Daniel Crank, Gabe Jenkins, Matthew T. Springer, John J. Cox

Forestry and Natural Resources Faculty Publications

Background

Population parameters such as reproductive success are critical for sustainably managing ungulate populations, however obtaining these data is often difficult, expensive, and invasive. Movement-based methods that leverage Global Positioning System (GPS) relocation data to identify parturition offer an alternative to more invasive techniques such as vaginal implant transmitters, but thus far have only been applied to relocation data with a relatively fine (one fix every  < 8 h) temporal resolution. We employed a machine learning method to classify parturition/calf survival in cow elk in southeastern Kentucky, USA, using 13-h GPS relocation data and three simple movement metrics, training a random forest on cows that successfully reared their calf to a week old.

Results

We developed a decision rule based upon a predicted probability threshold across individual cow time series, accurately classifying 89.5% (51/57) of cows with a known reproductive status. When used to infer status of …