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The Berry College campus has a population of white-tailed deer habituated to the presence of humans. One area of the campus contains residential houses, and apartments for faculty and staff. In this area, there have been numerous anecdotal reports, as well as photographic and video evidence, of white-tailed deer exhibiting aggressive behavior, particularly toward dogs being walked on leashes. In addition, deer following individuals or circling humans at a distance, making them uncomfortable, have been reported. The objective of this study was to document and establish the locations, frequency, and types of behaviors exhibited by deer in response to humans walking with and without leashed dogs. During the summer of 2019, a total of 13 instances of aggressive behavior were encountered by residents of the area and the investigators. In a majority of the events, (n = 12), deer would follow individuals with their dogs an average distance of 212.7 m ± 24.8 (100%), circle in front of the individuals, and stop in the walking path (50%), forcing them to turn another direction or be subjected to warning snorts or grinding teeth (33%), and/or pawing behavior (33%). We had proposed to administer a negative reinforcement stimulus in the form of impact of a needleless paint-marking dart delivered by a tranquilizer dart gun. It was hypothesized that the negative reinforcement might reduce the likelihood of individual deer repeating the aggressive behavior. However, no deer presented the aggressive behavior when researchers were carrying the tranquilizer dart gun. The investigators are planning on continuation of this project in 2020.

The objective of this study was to determine the importance of visual verification in the behavioral response of white-tailed deer to an auditory alert recording. We utilized a portable, remote-controlled sound system to play recordings of the white-tailed deer alert “blow.” In Phase I, the sound treatment was administered from a single location in a 1.3-ha grass lawn surrounded by wooded areas and roads with limited visibility, to free-ranging white-tailed deer on the Berry College campus during day and night hours. In Phase II, sound treatments were administered from varying locations in open lawn and hay fields. Recordings of deer activity were obtained from a digital camcorder and a FLIR thermal imagery camera. Behavior of white-tailed deer in response to the audio recording was classified as Passive (no altered behavior), Alert (actively observing and/or listening toward the recorded sound), Active (slow to moderate intentional movement toward or away from the recorded sound), or Flight (running away from the recorded sound). Six 10-sec periods of activity were evaluated. The pretreatment period (Pre Treat) began one minute prior to activation of the alert sound. The next four time periods [Sound (T1-T3)] represent the four consecutive 10-sec time frames from initiation of the sound treatment. A post-treatment (Post Trt) period was approximately 60 sec following the T3 period. In both phases, deer exhibited decreased Passive Behavior and increased Alert Behavior and Active Behavior following administration of the sound treatment. In the more confined area (Phase I) at night, deer tended to exhibit Alert and Active Behaviors longer than during the day. In the more open areas (Phase II), the degree of Active Behavior was diminished, with deer in the day tending to seek out the location of the sound. The results indicate that the use of visual verification to the auditory alert influenced behavioral response of white-tailed deer, and may be more critical in the areas where that process is limited compared to more open landscapes.

Evaluation of harvest data remains one of the most important sources of information in the development of strategies to manage regional populations of white-tailed deer. While descriptive statistics and simple linear models are utilized extensively, the use of artificial neural networks for this type of data analyses is unexplored. Linear model was compared to Artificial Neural Networks (ANN) models with Levenberg–Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms, to evaluate the relative accuracy in predicting antler beam diameter and length using age and dressed body weight in white-tailed deer. Data utilized for this study were obtained from male animals harvested by hunters between 1977–2009 at the Berry College Wildlife Management Area. Metrics for evaluating model performance indicated that linear and ANN models resulted in close match and good agreement between predicted and observed values and thus good performance for all models. However, metrics values of Mean Absolute Error and Root Mean Squared Error for linear model and the ANN-BR model indicated smaller error and lower deviation relative to the mean values of antler beam diameter and length in comparison to other ANN models, demonstrating better agreement of the predicted and observed values of antler beam diameter and length. ANN-SCG model resulted in the highest error within the models. Overall, metrics for evaluating model performance from the ANN model with BR learning algorithm and linear model indicated better agreement of the predicted and observed values of antler beam diameter and length. Results of this study suggest the use of ANN generated results that are comparable to Linear Models of harvest data to aid in the development of strategies to manage white-tailed deer. [ABSTRACT FROM AUTHOR]

Basic knowledge of white-tailed deer (Odocoileus virginianus) hearing can improve understanding of deer behavior and may assist in the development of effective deterrent strategies. Using auditory brainstem response testing, we determined that white-tailed deer hear within the range of frequencies we tested, between 0.25-30 kilohertz (kHz), with best sensitivity between 4-8 kHz. The upper limit of human hearing lies at about 20 kHz, whereas we demonstrated that white-tailed deer detected frequencies to at least 30 kHz. This difference suggests that research on the use of ultrasonic (frequencies 20 kHz) auditory deterrents is justified as a possible means of reducing deer-human conflicts. [ABSTRACT FROM AUTHOR]

We evaluated the behavioral responses of white-tailed deer (Odocoileus virginianus) to 4 colors of wildlife warning reflectors (red, white, blue-green, and amber) that are purported to reduce the incidence of deer-vehicle collisions. We observed white-tailed deer behaviors relative to roads before and after installation of wildlife warning reflectors using a forward-looking infrared camera during 90 observation nights. We concluded that wildlife warning reflectors were ineffective in changing deer behavior such that deer-vehicle collisions might be prevented. [ABSTRACT FROM AUTHOR]

We hypothesized that free-ranging white-tailed deer (Odocoileus virginianus) could be conditioned to associate an audible sound cue (electronic metronome) with a negative stimulus (electric shock) as a means of damage control. Three plots with two feed stations each, were established in a pasture. Feed stations consisted of plastic trays with electric fence wire attached to the top creating grids, mounted on boxes housing an electric fence charger and an electronic metronome. Infrared game monitors were also utilized to monitor deer activity at each feeder. Consumption rate of corn (2.27 kg/day) and deer activity were recorded daily. The experiment consisted of alternating 5-day periods where the wire grid was electrified and the metronome activated in one feed station at each plot (EM), followed by periods where only the metronome remained functional (M) for a total of three replicates. During EM periods, corn consumption decreased (P<0.001) to virtually zero. During M periods, corn consumption decreased (P<0.01) by about 30% at treatment feeders compared to controls. Deer activity was similar during all treatment periods. Results of this experiment indicate the conditioning treatment had limited effectiveness using this experimental protocol. [Copyright &y& Elsevier]