Population estimates derived from aerial surveys of ungulates are biased by imperfect detection, where probability of sighting groups is influenced by variables specific to terrain features and vegetation communities. Therefore, methods for bias-correction must be validated for the region to which they will be applied. Our objectives were to quantify factors affecting detection probability of mule deer (Odocoileus hemionus) during helicopter surveys in Texas, USA, rangelands, and develop a detection probability model to reduce bias in deer population estimates. We placed global positioning system (GPS) collars on 215 deer on 6 sites representative of mule deer range in the southern Great Plains and the Chihuahuan Desert during 2008-2010. We collected data during aerial surveys in January-March and fit logistic regression models to predict detection probability of mule deer based on ecological and behavioral covariates. We evaluated the model using independent estimates of population size derived from a markresight procedure. Detection of mule deer was negatively related to distance from the transect, increasing brush cover, sunlight, and increasing terrain ruggedness (P < 0.01). Probability of detection in brush cover was greater if deer were active (P ¼ 0.02). Population estimates corrected for visibility bias using our detection probability model or mark-resight models averaged 2.1 AE 0.49 (SD; n ¼ 50) and 2.2 AE 0.62 times larger, respectively, than uncorrected counts. Estimates of population size derived from the detection probability model averaged 101 AE 26% of mark-resight estimates. However, the detection probability model did not improve precision of population estimates, probably because of unmodeled variation in availability of deer during surveys. Our detection probability model is a simple and effective means to reduce bias in estimates of mule deer population size in southwestern rangelands. Availability bias may be a persistent issue for surveys of mule deer in the Southwest, and appears to be a primary influence of variance of population estimates. Ó 2016 The Wildlife Society.
Habitat quality is an important factor that can greatly affect wildlife populations. Pronghorn (Antilocapra americana) habitat in the Texas Panhandle, USA has been lost through growth of human settlements and agricultural lands. We determined the most pertinent environmental variables affecting habitat selection using multiple methods, including a search of peer‐reviewed literature, expert opinion ranking, and habitat suitability modeling. We determined quality and extent of pronghorn habitat in the Texas Panhandle using the MAXENT modeling environment to build a presence‐only habitat suitability model based on global positioning system (GPS) locations collected via aerial surveys. Our habitat suitability model indicated that woodlands, agricultural land, and summer precipitation had the greatest contributions to the overall model. Areas with greatest habitat suitability are associated with high pronghorn population densities, particularly in the northwestern corner of the Panhandle. This probabilistic model may serve as a useful tool for pronghorn conservation primarily because it provides insight into what factors are most predictive of their presence, which areas are most suitable for pronghorn, and as a simple, replicable process to identify and evaluate pronghorn habitat. © 2016 The Wildlife Society.
The greater kudu Tragelaphus strepsiceros, a large African herbivore, occupies the browser trophic niche. This species has been introduced into selected areas of Texas inhabited by the white-tailed deer Odocoileus virginianus, a native browser. Based on similar trophic function, potential interspecific competition could exist between these two species. The objectives of our study were to: 1) describe the seasonal diets of greater kudu in Texas and 2) determine if greater kudu show preference for plants that might create competition with white-tailed deer. We documented the seasonal diet and forage preference of greater kudu at Mason Mountain Wildlife Management Area from 15 May 2001 to 25 February 2002 by identifying epidermal fragments of plants in faecal pellets. We identified and quantified 49 species of plants eaten by greater kudu. Annually, browse made up 80.2% o ft h ed i e t ,w h i l e7 . 6 % mast, 6.5% grasses, 3% forbs and 2.7% unidentified material comprised the remaining parts of their diet. Important browse species included Texas/blackjack oak Quercus buckleyi/Q. marilandica, plateau live oak Q. fusiformis,AshejuniperJuniperus ashei,mesquite Prosopis glandulosa, prickly pear Opuntia sp., flameleaf sumac Rhus lanceolata, and Texas persimmon Diospyros texana. We measured availability of forage plants by quadrat and line intercept methods concurrent with faecal pellet collection. We compared plant use (dietary composition) with plant availability and assessed forage preference by greater kudu using loglikelihood x 2 -tests with Bonferroni corrected confidence intervals and Manly's alpha indices. We detected statistically significant differences between plant use and availability (P , 0.05). Purple horsemint Monarda citriodora, Canada wildrye Elymus canadensis, mesquite, flameleaf sumac, Texas/blackjack oak and Ashe juniper were preferred species. Relative preference of general forage categories by greater kudu in Texas was similar to that reported from Africa. Basedon our findings, greater kudu could compete with white-tailed deer for browse forage.
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