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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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10799437 | PMC |
http://dx.doi.org/10.1186/s40462-024-00450-4 | DOI Listing |
Microbiome
December 2024
College of Life Sciences, Shihezi University, Shihezi, Xinjiang, 832003, China.
J Zoo Wildl Med
December 2024
Texas Parks and Wildlife Department, Austin, Texas, 78744 USA.
Wildlife species are routinely captured for translocation, general health monitoring, and research-based pursuits to guide wildlife management. Mule deer () were captured for various research projects and management actions in the Trans-Pecos and Panhandle regions of Texas from 2015 to 2019. The objective of this study was to develop hematologic and biochemical parameters for free-ranging mule deer in Texas and to develop a health monitoring system for current and future mule deer population management.
View Article and Find Full Text PDFFront Vet Sci
November 2024
Department of Veterinary Pathobiology, College of Veterinary Medicine, University of Missouri, Columbia, MO, United States.
Introduction: Chronic wasting disease (CWD) among cervids in Kansas has seen a consistent rise over the years, both in terms of the number of infections and its geographical spread. In this study, we assessed the occupancy patterns of CWD among white-tailed deer and mule deer across the state.
Methods: Using surveillance data collected since 2005, we applied a dynamic patch occupancy model within a Bayesian framework, incorporating various environmental covariates.
Nat Ecol Evol
December 2024
Laboratoire d'Écologie Alpine, UMR UGA-USMB-CNRS 5553, Université de Savoie Mont-Blanc, Le Bourget-du-Lac, France.
J Wildl Dis
November 2024
Southeastern Cooperative Wildlife Disease Study, 589 D. W. Brooks Dr., Athens, Georgia 30602, USA.
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