Utilization of Spatial Capture-recapture and Non-invasive Sampling Methods for Monitoring Ungulate Populations
- ISBN-10
- 0438930436
- ISBN-13
- 9780438930438
- Language
- English
- Published
- 2018
- Author
- Jennifer L. Brazeal
Description
Historically, abundance and density of mule deer and elk in North America has been estimated using a combination of biased indices and aerial surveys. Non-invasive genetic sampling and spatially explicit capture-recapture (SCR) models provide a robust alternative for estimating population parameters of large ungulates, but these methods are relatively new. We demonstrate the effectiveness, utility, and robustness of such methods for estimating density and abundance of deer and elk. We used fecal DNA samples and SCR models to estimate density, sex ratio, and habitat correlates to density for a mule deer (Odocoileus hemionus) population across its critical summer range (~500 km2) in the central Sierra Nevada Range, California, USA during 2013 and 2014. We estimated density at 5.0 (95% CI = 2.3–7.8) deer/km2 in 2013 and 5.1 (95% CI = 3.1–7.2) deer/km2 in 2014. The estimated sex ratio was 62 (95% CI = 41–93) males/100 females in 2013 and 65 (95% CI = 45–94) males/100 females in 2014. We found that density was effectively homogeneous throughout the study area. In September 2014, our sampling was cut short by a mega-fire, the King Fire, which burned a large area (359 km2) adjacent to our study area, and over large portions of the population’s annual range. Having conducted sampling before the fire, we continued sampling in the two months following the fire, and in the summer of 2015 to discover if displacement from the fire zone increased density on our study area or if a lack of resources on the burn area impacted apparent survival and per-capita recruitment on our study area. We used SCR models to estimate density and non-spatial Pradel robust-design recruitment models to estimate survival and recruitment rates. We observed a non-significant increase in deer density immediately after the fire, while per-capita recruitment rates increased significantly and survival rates exhibited no detectable change, suggesting displacement of deer to the study area in response to the fire. These changes did not carry over into the following year, indicating that deer returned to their original home ranges, or deer originally on the burn area moved to alternative areas. To evaluate the robustness and accuracy of these methods, and to assess the utility of an alternative non-invasive method for estimating density of wild ungulates, we compared density estimates from fecal genetic sampling and SCR to estimates from camera trapping and the random encounter model (REM) of a tule elk (Cervus canadensis nannodes) population of known size within a 3.49 km2 fenced enclosure on the San Luis National Wildlife Refuge in Los Banos, CA. We also subsampled the SCR detection histories, which included detections from all individuals, to explore the effects of varying search effort and elk density on the precision and accuracy of results. We found that SCR outperformed REM methods in the full datasets, and reliably provided accurate (relative bias 10%) and reasonably precise (relative standard error 20%) estimates of density at moderately low to high densities (6–17 elk/km2), when the subsampling scenarios yielded a minimum average of 20 recaptures. The REM estimate of density was much larger than the true density of elk in the enclosure (|D - D̂| elk/km2), and had lower precision. We also found that the number of samples used to construct detection histories was a reliable predictor of precision, and could be used to establish a minimum sampling goal in future population surveys of elk. Our results suggest that SCR and non-invasive genetic sampling are promising tools for future population studies and monitoring of North American ungulates.
