Positive relationships between age, sexually selected traits, and male reproductive success have been reported for a number of polygynous ungulates; however, relatively little is known about the factors influencing male reproductive success in ungulate species whose mating system is characterized by tending‐bond behaviors. Broad interest in the genetic consequences of selective harvest supports a greater understanding of the role of these factors as determinants of male reproductive success in important game species (e.g., white‐tailed deer [Odocoileus virginianus]), that exhibit tending‐bond behaviors. We investigated male reproductive success in white‐tailed deer across a range of sex ratios and age structures using a known population of deer housed in a 175‐ha enclosure in central Alabama, USA. We measured age, annual antler size, and annual body size of male white‐tailed deer and assigned paternity to 143 known‐age offspring during 2007–2014. Reproductive success was attributed to a high proportion of males during each of the 6 breeding seasons. Our most supported model indicated that annual body size and antler size of the individual were positively associated with annual male breeding success. The effects of annual antler size were sensitive to changes in mean male age of the herd, with antler size having the greatest effect on male reproductive success under older male age structures. Young (≤1.5 yr) males reproduced most frequently when male age structure was youngest (which correlated with female‐biased sex ratios in this population). Our results suggest that male age structure and sex ratio played a key role in establishing patterns of male reproductive success in white‐tailed deer. Management practices that encourage balanced adult sex ratios and older male age structures (e.g., Quality Deer Management) may promote a highly competitive environment where sexually selected traits are of increased importance to male breeding success. However, the ability of managers to alter herd genetics in a positive or negative direction through selective harvest is limited in white‐tailed deer because of the high proportion of reproducing males. © 2016 The Wildlife Society.

Drones equipped with thermal sensors have shown ability to overcome some of the limitations often associated with traditional human‐occupied aerial surveys (e.g., low detection, high operational cost, human safety risk). However, their accuracy and reliability as a valid population technique have not been adequately tested. We tested the effectiveness of using a miniaturized thermal sensor equipped to a drone (thermal drone) for surveying white‐tailed deer (Odocoileus virginianus) populations using a captive deer population with a highly constrained (hereafter, known) abundance (151–163 deer, midpoint 157 [87–94 deer/km2, midpoint 90 deer/km2]) at Auburn University's deer research facility, Alabama, USA, 16–17 March 2017. We flew 3 flights beginning 30 minutes prior to sunrise and sunset (1 morning and 2 evening) consisting of 15 nonoverlapping parallel transects (18.8 km) using a small fixed‐wing aircraft equipped with a nonradiometric thermal infrared imager. Deer were identified by 2 separate observers by their contrast against background thermal radiation and body shape. Our average thermal drone density estimate (69.8 deer/km2, 95% CI = 52.2–87.6), was 78% of the mean known value of 90.2 deer/km2, exceeding most sighting probabilities observed with thermal surveys conducted using human‐occupied aircraft. Thermal contrast between animals and background was improved during evening flights and our drone‐based density estimate (82.7 deer/km2) was 92% of the mean known value. This indicates that time of flight, in conjunction with local vegetation types, determines thermal contrast and influences ability to distinguish deer. The method provides the ability to perform accurate and reliable population surveys in a safe and cost‐effective manner compared with traditional aerial surveys and is only expected to continue to improve as sensor technology and machine learning analytics continue to advance. Furthermore, the precise replicability of autonomous flights at future dates results in methodology with superior spatial precision that increases statistical power to detect population trends across surveys. © 2020 The Wildlife Society.

No abstract

Camera traps are widely used to monitor wildlife, with important management decisions often relying on interpretation of these data. Animal misidentifications are known to be an important source of error in wildlife surveys that require the identification of unique individuals from camera-trap data; however, the practice of broadly classifying animal images according to sex or age has received less critical attention despite the significant potential for misidentification error under certain circumstances. From 19 January to 1 April 2017, we solicited a group of 726 participants, consisting of both wildlife professionals and nonprofessionals from across the United States, to take an online survey that tested their ability to classify images of known white-tailed deer (Odocoileus virginianus) according to sex and age. Our goal was to determine the relative influence of tested observer (i.e., experience and familiarity with classifying deer images) and image-based factors (i.e., distance of deer from camera, day vs. night image) on accuracy of deer classifications. Our results indicated that respondents that were wildlife biologists and those with greater levels of experience viewing deer images were more accurate than others when classifying posthunting season images of deer as adult male, adult female, or fawn. However, the sex-age group of the deer was the most influential predictor of classification reliability, with branched-antlered adult males being classified more accurately by all respondent groups than were adult females and fawns. Our findings emphasized that animal misidentifications may be an important source of survey error not only when identifying unique individuals, but also under any circumstance where comparative groups lack definitive traits. We suggest that those using camera traps to evaluate wildlife populations should select survey periods that maximize differences among classification groups, when possible, and develop species-specific image training for observers to improve the reliability of results. Further, population demographics should be considered when evaluating the overall reliability of survey results for species where classification accuracy varies among sex-age groups.

Vaginal implant transmitters (VITs) are increasingly used to facilitate capture of neonatal ungulates. Environmental conditions potentially have a significant influence on performance of VITs; however, effects on VIT performance largely are unknown. We exposed VITs to conditions reflective of those present during white‐tailed deer fawning season in Alabama and examined effects of ambient air temperature and vegetative structure on their performance. Performance of VITs was inversely related to ambient air temperature, and VIT performance increased along with increasing amounts of shade provided by vegetation. Current devices likely will perform relatively well if expelled in areas where ambient air temperatures are below the user‐defined pulse switch point and habitat conditions provide shade. Performance of VITs will be severely compromised if expulsion occurs in areas where ambient air temperatures are above the user‐defined pulse switch point and devices are exposed to direct sun. Individuals interested in utilizing VITs should consider local climate and vegetative characteristics prior to initiating projects to evaluate if devices will meet performance requirements.