No description available.

No description available.

White-tailed deer (Odocoileus virginianus) in the Big Cypress Basin of South Florida must cope with top-down and bottom-up forces, including frequent pyrogenic and hydrological disturbances and the threat of predation. These forces affect their space use, behavior, and survival. Recent changes to the regional hydrology and increased abundances the Florida panther (Puma concolor coryi), their primary predator in this system, call for a renewed look at how these forces affect this deer herd. To assess the effects of these forces on seasonal space use, behavior, and survival of deer, I analyzed GPS telemetry and camera trap data, highlighting the factors influencing deer space use across hydrological and biological seasons, and connected behavioral data captured on camera traps to female deer survival. Space use is primarily a function of intrinsic sex affects and landscape composition and configuration, and varies as resources and reproductive cycles fluctuate across seasons. Disturbance has little effect on space use, suggesting deer are well adapted to these disturbance regimes. Temperament in foraging behavior in female deer impacted survival, influencing prey catchability and potentially buffering prey populations against cycles of predation. / Master of Science / White-tailed deer (Odocoileus virginianus) in the Big Cypress Basin of South Florida must cope with a changing landscape of resources caused by frequent fire and flooding, while avoiding predation by their primary predator in this system, the Florida panther (Puma concolor coryi). Recent changes to water flow across this landscape and increasing numbers of Florida panthers call for a renewed look at how disturbance, landscape features, and predation influence the seasonal space use, behavior, and survival of deer in this system. Differences from sex and landscape features most explain seasonal space use of deer, while the influence of fire and flooding is limited. Variability in vigilance of female deer led to differences in female survival, suggesting a tradeoff between acquiring resource and safety when foraging under predation risk.

Three experiments were conducted to determine the effect of energy, protein, sex, and time on serum T4 and T3 concentrations. All sampling periods occurred at 28-day intervals. In the first experiment, (March-February) 7 adult bucks were placed on 2 feed levels, ad libitum or 25% restricted. Feed consumption of ad libitum deer was highest (P≤0.05) from June-October, fell in November, and remained low through March. Body weights of both groups were highest (P≤0.05) from September-October; lowest from March-April. Serum T4 was highest (P≤0.05) in May and July, and lowest in November. From November-February, restricted deer had lower T4 concentrations (P<0.01) than did ad libitum deer. Serum T3 was highest from May-August; lowest in November. Ad libitum had higher T3 concentrations (P<0.01) than the restricted animals. The second experiment compared the effects of energy and protein on body weight, and serum T4 and T3 of 24 fawns (12 male) from October-May. Feed intake fell gradually to low levels maintained from January-March, then increased slightly. Body weight gain was initially rapid (P<0.01), minimal from November-March, and slow through May. Serum T4 was highest in late April; lowest in October and February. Maximum serum T3 concentrations occurred in April; lowest values in February. Females had higher T4 and T3 values than did males. The third experiment involved 1 adult buck. Blood samples were drawn every 2 hours for a 24-hour period via a jugular catheter. Serum T4 and T3 concentrations were highest from 1600-2000 hours (EST), lowest at 1000 hours. / M.S.

Wildlife diseases often occur under quantifiable and consistent patterns, which can be understood to statistically predict their occurrence and spread across landscapes. Chronic wasting disease (CWD) is a neurodegenerative disease in the deer family Cervidae caused by a prion, a pathogenic and misfolded variant of a naturally occurring protein. Managing and controlling CWD is imperative for conservation of ecologically and economically important cervid species, but unclear transmission mechanisms within landscapes complicate evidence-based management. Gaps of information in the landscape ecology for CWD are particularly pronounced for areas with recent disease emergence and spread, such as within the CWD cluster in the Mid-Atlantic United States. Thus, I identified current gaps in information and sought to fill neglected areas of research, specifically focusing on landscape determinants for CWD occurrence and spread in the state of Virginia. In chapter 2, I conducted a scoping study that collected and synthesized decades of CWD research and identified trends with respect to statistical and mathematical modeling methods used, connectivity within the CWD research community, and the geographic areas from which studies were performed. In chapter 3, I investigated landscape determinants for CWD in Virginia using remote sensing landscape data and an epidemiological dataset from Virginia Department of Wildlife Resources (DWR) using diverse algorithms and model evaluation techniques. Finally, in chapter 4, I modeled landscape connectivity between confirmed CWD cases to examine potential paths and barriers to CWD spread across landscapes. My results indicate that landscape ecology was rarely incorporated throughout CWD's 50+ year history. I provide evidence that remotely-sensed landscape conditions can be used to predict the likelihood of CWD occurrence and connectivity in Virginia landscapes, suggesting plausible CWD spread. I suggest areas of future work by explicitly identifying gaps in CWD research and diagnostic methods from which models are based, and encourage further consideration of host's ecology in modeling. By integrating remotely-sensed data into my modeling framework, the workflow should be easily adaptable to new study areas or other wildlife diseases. / Master of Science / Understanding why diseases occur in some locations and not others can be a critical challenge for disease ecologists. One disease that has received significant attention from the media and scientific community is chronic wasting disease (CWD), which is caused by a misfolded protein called a prion. Virginia Department of Wildlife Resources (DWR) has identified a stark increase in the number of CWD cases since first discovered in 2009, which threatens white-tailed deer populations and a 500 million dollar industry used for conservation of Virginia wildlife species. Previous research found that CWD does not occur randomly on the landscape, but otherwise little is known about the landscape ecology of CWD. To provide insight on Virginia's CWD outbreak, I assessed methods used to investigate other CWD outbreaks in both space and time. Also, I used landscape data collected from satellites and data from CWD cases in Virginia, and applied statistical tools to identify patterns in the landscape that were linked with CWD cases. My results suggest that landscapes were rarely examined to understand CWD, and instead, researchers focused on understanding how populations will respond to the disease. I also provide evidence that, at least in Virginia, researchers can use satellite information with disease data to predict CWD on the landscape and estimate its spread. This information can be used by wildlife managers to control the disease. For example, disease surveillance can be increased in areas where CWD has been predicted, or herd sizes can be reduced in areas likely to promote disease spread. This information could also be used to tailor wildlife health regulations aimed to minimize the risk of other deer populations acquiring the disease. Ultimately, the landscape plays an important role in CWD, but research on this topic is limited; therefore, additional research is needed to understand and eventually control this disease affecting ecologically and culturally important game species.

Pellet group surveys were conducted on 21 transects in February-March, 1985, and January-March, 1986, to estimate relative deer densities on eleven study areas on the Jefferson National Forest, southwestern Virginia. Habitat data were collected on the same transects in July-September, 1985. Additional habitat information was measured from aerial photographs and USDA Forest Service compartment maps. These data were used to develop eleven multiple linear regression models and one pattern recognition (PATREC) model for predicting deer winter habitat quality, based on the assumption that relative density of deer is a good indicator of habitat quality. The densities of evergreen broad-leaved shrubs and"Nonforage" shrubs, basal area, mean distance to a field, and percent slope were among the most important variables selected in the regression model building process. Six variables were selected for use in the PATREC model: mean tree diameter, oak basal area, basal area of"Other Winter Forage" tree species, density of"Nonforage" shrubs, mean distance to a gated gravel road, and mean canopy closure. Spearman's rank correlations were used to compare the model outputs with estimated pellet group densities. All of the models had correlation coefficients ≥ 0.60, four had correlation coefficients > 0.80. The models need to be validated, i.e. tested with independent data from areas outside the study sites. These tests will help refine the models and assess their effectiveness in other regions of the southern Appalachian Mountains. / Master of Science

no abstract provided by author / Master of Science

A habitat suitability index (HSI) model for white-tailed deer (Odocoileus virginianus) was tested to determine the relationship between habitat quality predicted by the model and habitat quality suggested by the condition of 1.5 year-old bucks on Quantico Marine Corps Base, Virginia. Additionally, new models were developed that predict the response of habitat variables important to a variety of species to succession and management. Habitat quality predicted by the white-tailed deer HSI model for 11 different deer management units was not strongly correlated with body weight (Spearman's r = -0.40, f = 0.221, n = 11), beam diameter (rs = 0.06, f = 0.851, n = 11), beam length (rs = 0.37, f = 0.265, n = 11), and number of points (rs = -0.24, f = 0.473, n = 11). The area within each management unit with HSI > 0.5 was weakly correlated (rs = 0.48, P = 0.13) with beam diameter and beam length. We attempted to model the response of vegetation to succession and management. The strength of the relationship between habitat changes and stand age (succession) varied depending on the variable and cover type being modeled. R2adj values were highest on average for habitat parameters associated with overstory trees, including basal area, dbh, density, and height. R2adj values were low (R2a~ < 0.5) and regressions nonsignificant (f > 0.10) for models associated with shrubs and herbaceous vegetation. In general, the response of habitat parameters was most predictable in loblolly-shortleaf pine plantations that were hand planted and not subject to the same variation associated with naturally regenerated stands. / Master of Science

Master of Science

The mixed oak-pine cover type was evaluated as white-tailed deer range on four study areas by measuring dry matter production of key forages and determining their nutrient composition. Composite diets containing plant species which represented the major portions of each seasonal diet as indicated by food habits studies, were mixed for the summer, fall and winter seasons. For the spring flush and spring seasons, individual key forages were analysed. All samples were assayed for soluble carbohydrates, lignin, phosphorus, gross energy, proximate composition, and in vitro dry matter digestibility. Digestible energy production in kcal/ha/day was calculated seasonally for key forages. The ratios of digestible energy available in key forages to that required by the estimated deer herd were 3.01, 5.94, 0.96, 2.14, and 1.23, for the spring flush, spring, summer, fall, and winter, respectively. These ratios indicate the potential of the study areas to support the estimated population density of 1 deer per 16.4 ha. The mixed oak-pine cover type appears to be adequate to support the estimated deer herd if 50 percent of the key forages are consumed seasonally but inadequate if only 25 percent are used. During all seasons, forage protein appeared to be adequate and phosphorus was possibly lower than that required for optimal animal performance. / Master of Science