Evaluating movement-based methods for estimating the frequency and timing of parturition in mule deer

Tabitha A Hughes; Randy T Larsen; Kent R Hersey; Madelon van de Kerk; Brock R McMillan

doi:10.1186/s40462-024-00450-4

Evaluating movement-based methods for estimating the frequency and timing of parturition in mule deer

Mov Ecol. 2024 Jan 19;12(1):6. doi: 10.1186/s40462-024-00450-4.

Authors

Tabitha A Hughes¹, Randy T Larsen², Kent R Hersey³, Madelon van de Kerk⁴, Brock R McMillan²

Affiliations

¹ Department of Plant and Wildlife Sciences, Brigham Young University, 4105 Life Sciences Building, Provo, UT, 84602, USA. tabbyhughes98@gmail.com.
² Department of Plant and Wildlife Sciences, Brigham Young University, 4105 Life Sciences Building, Provo, UT, 84602, USA.
³ Utah Division of Wildlife Resources, 1594 W North Temple, Suite 2110, Salt Lake City, UT, 84116, USA.
⁴ School of Environment and Sustainability, Western Colorado University, Kelley Hall 144, Gunnison, CO, 81231, USA.

Abstract

Background: Information on reproduction of harvested species such as mule deer (Odocoileus hemionus) is vital for conservation and management. Furthermore, parturition in ungulates may be detected using patterns of movement logged by GPS transmitters. Several movement-based methods have been developed to detect parturition in ungulates including the Peterson method, behavioral change point analysis (BCPA), rolling minimum convex polygons (rMCP), individual-based method (IBM), and population-based method (PBM). Our objectives were to (1) test the accuracy and the precision of each previously described method and (2) develop an improved method optimized for mule deer that incorporated aspects of the other methods.

Methods: We determined parturition timing and status for female mule deer fitted with GPS collars and implanted with vaginal implant transmitters (VITs). We used movement patterns before and after parturition to set movement thresholds for each movement-based method. Following model training, we used location and birth date data from an external dataset to test the effectiveness of each movement-based method. Additionally, we developed a novel method for detecting parturition called the analysis of parturition indicators (API). We used two regression analyses to determine the accuracy and precision of estimates generated by each method.

Results: The six methods we employed varied in accuracy, with the API, rMCP, and BCPA being most accurate. Precision also varied among methods, with the API, rMCP, and PBM generating the most precise estimates of parturition dates. The API and the rMCP performed similarly and better overall than any of the other existing methods.

Conclusions: We found that movement-based methods could be used to accurately and precisely detect parturition in mule deer. Further, we determined that the API and rMCP methods had the greatest overall success at detecting parturition in mule deer. The relative success of the API and rMCP may be attributed to the fact that both methods use home range size to detect parturition and are validated using known parturition dates of collared deer. We present the API as an efficient method of estimating birth status and timing of parturition of mule deer fitted with GPS transmitters, as well as affirm the effectiveness of a previously developed method, rMCP.

Keywords: Global positioning system; Movement; Mule deer; Odocoileus hemionus; Parturition timing; Pregnancy rate; Ungulate; Utah.

Abstract

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