Marcus A. Lashley

Do biological and bedsite characteristics influence survival of neonatal white-tailed deer?

Coyotes recently expanded into the eastern U.S. and potentially have caused localized white-tailed deer population declines. Research has focused on quantifying coyote predation on neonates, but little research has addressed the potential influence of bedsite characteristics on survival. In 2011 and 2012, we radiocollared 65 neonates, monitored them intensively for 16 weeks, and assigned mortality causes. We used Program MARK to estimate survival to 16 weeks and included biological covariates (i.e., sex, sibling status [whether or not it had a sibling], birth weight, and Julian date of birth). Survival to 16 weeks was 0.141 (95% CI = 0.075-0.249) and the top model included only sibling status, which indicated survival was lower for neonates that had a sibling. Predation was the leading cause of mortality (35 of 55; 64%) and coyotes were responsible for the majority of depredations (30 of 35; 86%). Additionally, we relocated neonates for the first 10 days of life and measured distance to firebreak, visual obstruction, and plant diversity at bedsites. Survival of predation to 10 days (0.726; 95% CI = 0.586-0.833) was weakly associated with plant diversity at bedsites but not related to visual obstruction. Our results indicate that neonate survival was low and coyote predation was an important source of mortality, which corroborates several recent studies from the region. Additionally, we detected only weak support for bedsite cover as a covariate to neonate survival, which indicates that mitigating effects of coyote predation on neonates may be more complicated than simply managing for increased hiding cover.

White-Tailed Deer Vigilance: The Influence of Social and Environmental Factors

Vigilance behavior may directly affect fitness of prey animals, and understanding factors influencing vigilance may provide important insight into predator-prey interactions. We used 40,540 pictures taken withcamera traps in August 2011 and 2012to evaluate factors influencing individual vigilance behavior of white-tailed deer (Odocoileus virginianus) while foraging at baited sites. We used binary logistic regression to determine if individual vigilance was affected by age, sex, and group size. Additionally, we evaluated whether the time of the day,moon phase,and presence of other non-predatorwildlife species impacted individual vigilance. Juveniles were 11% less vigilant at baited sites than adults. Females were 46% more vigilant when fawns were present. Males and females spent more time feeding as group size increased, but with each addition of 1 individual to a group, males increased feeding time by nearly double that of females. Individual vigilance fluctuated with time of day andwith moon phase but generally was least during diurnal and moonlit nocturnal hours, indicating deer have the ability to adjust vigilance behavior to changing predation risk associated with varyinglight intensity.White-tailed deer increased individual vigilance when other non-predator wildlife were present. Our data indicate that differential effects of environmental and social constraints on vigilance behavior between sexes may encourage sexual segregation in white-tailed deer.

Confirmation of Coyote Predation on Adult Female White-tailed Deer in the Southeastern United States

Abstract The recent expansion of Canis latrans (Coyote) into the eastern United States has generated interest among wildlife managers because of the potential impacts on Odocoileus virginianus (White-tailed Deer) populations. Coyotes have been reported as predators of adult and neonate White-tailed Deer in some parts of their range, but recent studies in the Southeast have documented only Coyote predation on neonates. We report 4 confirmed Coyote predation events on adult female White-tailed Deer that were radiocollared, implanted with vaginal implant transmitters, monitored every 4–8 hours, and apparently healthy. Field necropsies confirmed killing-bite wounds to the upper throat and base of the mandible, and feeding behavior on the carcasses was consistent with what has been observed for Coyotes. Further, we used swabs from bite wounds to confirm the presence of predator DNA, and the 3 carcasses that were swabbed tested positive for the presence of Coyote DNA. To our knowledge, our results represent the first scientifically documented Coyote predations on adult female White-tailed Deer in the Southeast.

Do coyotes Canis latrans influence occupancy of prey in suburban forest fragments

Abstract With the extirpation of apex predators from many North American systems, coyotes Canis latrans have become the de facto top predator and are ubiquitous members of most ecosystems. Keystone predators aid in maintaining ecosystem function by regulating the mammal community through direct predation and instilling the landscape of fear, yet the value of coyotes regulating systems to this capacity is understudied and likely variable across environments. Since coyotes are common in the Midwestern United States, we utilized camera traps and occupancy analyses to assess their role in regulating the distribution of mammalian herbivores in a fragmented suburban ecosystem. Forest cover was a strong positive predictor of white-tailed deer Odocoileus virginianus detection, while coyote occurrence had a negative effect. Coyotes exerted a negative effect on squirrel (Sciurus spp.) and eastern cottontail rabbit Sylvilagus floridanus occurrence, while urban cover was a positive predictor for the prey species’ occurrence. These results suggest all 3 species behaviorally avoid coyotes whereby deer seek denser forest cover and squirrels and cottontails mitigate risk by increasing use of urban areas. Although previous studies reveal limited influence of coyote on the rest of the carnivore guild in suburban systems, we suggest coyotes play an important role in regulating the herbivorous mammals and hence may provide similar ecological benefits in urban/suburban forest fragments through trophic cascades. Furthermore, since hunting may not be allowed in urban and suburban habitats, coyotes might also serve as the primary regulator of nuisance species occurring at high abundance such as white-tailed deer and squirrels.

The Effects of Extreme Drought on Native Forage Nutritional Quality and White-tailed Deer Diet Selection

Abstract Forage availability is often used as a measure of habitat quality for Odocoileus virginianus (White-tailed Deer; hereafter “Deer”). Many studies have evaluated treatment effects on forage availability, but the effects of other abiotic factors, such as drought, on native forages and Deer diet selection are poorly understood. We measured diet selection and nutritional quality of commonly occurring forages following extreme drought (2007) and normal rainfall years (2008) in 4 closed-canopied hardwood stands in the Central Hardwoods region. Deer selected 6 forage species in both years of the study. Within these 6 species, crude protein (CP) and acid detergent fiber (ADF) were not different, and neutral detergent fiber (NDF) increased during the year of normal rainfall. Thirteen other commonly occurring forages showed a different trend, with CP negatively affected by drought and ADF and NDF unaffected. Less-selected species in the drought year and a greater selection-index cut-off value suggest Deer were more selective of species consumed during extreme drought because fewer plants met their nutritional requirements. Our data support the selective quality hypothesis, predicting Deer become more selective of plant species to meet nutritional requirements when resources are limited. Our data suggest more frequent and intense droughts predicted as a result of global climate change may influence diet selection of deer and decrease forage quality enough to limit lactation during the late-summer stress period in the Southeast.

Poor soils and density-mediated body weight in deer: forage quality or quantity?

Cervid studies have demonstrated body weight and lactation may be limited in areas with poor-quality soils, with the underlying mechanism often attributed to poor forage quality resulting from poor soil quality. However, if highly nutritious foods are produced but in limited quantities, selective foraging may alleviate nutritional stressors associated with poor soil productivity when adequate quantities of high-quality forage are obtained. We tested whether poor soil productivity limits forage from being high quality or conversely limits the abundance of high-quality forages. To do so, we determined whether nutrient concentrations in selected and non-selected forages on our poor soil study site met the nutritional requirements of lactating white-tailed deer Odocoileus virginianus assuming adequate amounts of forage are obtained. Also, we compared body weight of yearling males at a high density (13–17 deer km-2) and low density (3–5 deer km-2), because previous studies concluded soils on the study site were too poor for morphometrics (e.g. body weight) to be density-mediated. Deer selected plant species from each of five forage classes that would meet their nutritional requirements (i.e. assuming adequate forage intake) but also selected for different nutrients across forage classes. Phosphorus was limited in most forages, but deer selected forages that met P-requirements 10 times more than expected. We demonstrated body weight was 7.3% greater when deer density was low than high. Contrary to previous reports from poor productivity soil regions, deer on our study site should be able to meet lactation requirements when the quantity of high-quality forage is not limiting, and similarly body weight should be density-mediated. Hence, management strategies that alter the amount of forage per animal (i.e. decreasing animal density and/or increasing forage abundance) are viable options to promote desirable ungulate morphometrics in poor soil regions.

Resource selection by southeastern fox squirrels in a fire-maintained forest system

Fire is essential to maintain the open forest structure required by the southeastern fox squirrel (Sciurus niger niger). In recent decades, managers of the longleaf pine (Pinus palustris) ecosystem have transitioned from dormant-season to growing-season burns, which more effectively limit midstory hardwood encroachment. Similarly, aggressive hardwood removal programs have been employed to further reduce hardwood midstory. However, fox squirrels are dependent on oaks (Quercus spp.) for food and cover; thus, it is unclear how growingseason burns and hardwood removal may affect habitat quality for fox squirrels. We used compositional analysis to investigate selection of home ranges within the study area by 48 radiocollared fox squirrels on the Fort Bragg Military Installation, North Carolina. We used resource utilization functions with growing-season fire history and other habitat covariates as explanatory variables to test whether growing-season fires influenced the selection of habitat components within home ranges. Lastly, using a sample of fox squirrel relocations and paired random points, we performed binomial logistic regression to test whether habitat selection by fox squirrels was influenced by the availability of oaks and longleaf pines and select forest stand structural characteristics. When establishing home ranges, fox squirrels selected southern yellow pine over other cover types. Within home ranges, fox squirrel use increased with decreasing distance to a riparian area but was not affected by the application of growing-season fires. At the population level, fox squirrels selected for greater densities of reproductively mature oak stems. Fox squirrels likely benefit from growing-season fires that maintain expansive upland pine stands but are negatively affected by homogeneous fire application and mechanical hardwood removal that reduce the occurrence of reproductively mature oaks across the landscape. Managers should strive to maintain oaks in riparian areas, fire shadows, and naturally occurring patches within pine stands when managing for fox squirrels.

How Emotion Trumps Logic in Climate Change Risk Perception: Exploring the Affective Heuristic Among Wildlife Science Students

Despite scientific support for the reality of climate change, public opinion remains polarized. Continued skepticism may be partially explained by lack of understanding of climate change science, and worldview and ideology, but factors contributing to risk perceptions also may differ depending on the subject of risk. This article compared how wildlife students in the eastern United States perceive climate change risk to wildlife versus humans. Left-leaning political ideology and acceptance of anthropogenic global warming predicted perceptions of climate change risks to humans. Contrastingly, scientific understanding was the most important predictor of wildlife-related risk perceptions. Students may have used an affective heuristic (i.e., emotions) in assessing climate change risks to society and a cognitive reasoning (i.e., logic and data) when considering climate change risks to wildlife, which suggests that climate change communicators should appeal to these different modes of thinking when considering risks to humans versus wildlife.

Evaluation of methods to estimate understory fruit biomass.

Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in wildlife habitat quality. Yet, designing a fruit sampling protocol that is executable on a frequent basis may be difficult, and knowledge of accuracy within monitoring protocols is lacking. We evaluated the accuracy and efficiency of 3 methods to estimate understory fruit biomass (Fruit Count, Stem Density, and Plant Coverage). The Fruit Count method requires visual counts of fruit to estimate fruit biomass. The Stem Density method uses counts of all stems of fruit producing species to estimate fruit biomass. The Plant Coverage method uses land coverage of fruit producing species to estimate fruit biomass. Using linear regression models under a censored-normal distribution, we determined the Fruit Count and Stem Density methods could accurately estimate fruit biomass; however, when comparing AIC values between models, the Fruit Count method was the superior method for estimating fruit biomass. After determining that Fruit Count was the superior method to accurately estimate fruit biomass, we conducted additional analyses to determine the sampling intensity (i.e., percentage of area) necessary to accurately estimate fruit biomass. The Fruit Count method accurately estimated fruit biomass at a 0.8% sampling intensity. In some cases, sampling 0.8% of an area may not be feasible. In these cases, we suggest sampling understory fruit production with the Fruit Count method at the greatest feasible sampling intensity, which could be valuable to assess annual fluctuations in fruit production.

Estimating wildlife activity curves: comparison of methods and sample size

Camera traps and radiotags commonly are used to estimate animal activity curves. However, little empirical evidence has been provided to validate whether they produce similar results. We compared activity curves from two common camera trapping techniques to those from radiotags with four species that varied substantially in size (~1 kg–~50 kg), diet (herbivore, omnivore, carnivore), and mode of activity (diurnal and crepuscular). Also, we sub-sampled photographs of each species with each camera trapping technique to determine the minimum sample size needed to maintain accuracy and precision of estimates. Camera trapping estimated greater activity during feeding times than radiotags in all but the carnivore, likely reflective of the close proximity of foods readily consumed by all species except the carnivore (i.e., corn bait or acorns). However, additional analyses still indicated both camera trapping methods produced relatively high overlap and correlation to radiotags. Regardless of species or camera trapping method, mean overlap increased and overlap error decreased rapidly as sample sizes increased until an asymptote near 100 detections which we therefore recommend as a minimum sample size. Researchers should acknowledge that camera traps and radiotags may estimate the same mode of activity but differ in their estimation of magnitude in activity peaks.