Babesia bovis has been an important disease agent in the U.S. cattle industry for over a century. Recently, B. bovis-like parasites have been identified in white-tailed deer (WTD; Odocoileus virginianus) in Texas. If the parasites found in the WTD are B. bovis that are able to infect cattle, the disease could re-emerge. Susceptible adult cattle often die from this disease, which would result in severe production losses, as well as a decrease in carcass weights of disease survivors. The B. bovis-like parasite found in WTD was compared to B. bovis from cattle, by ribosomal DNA sequence analysis. Babesia isolated from WTD were found to have 99% identity to B. bovis from GenBank cattle sequences. No cattle samples in this study were found to be positive for B. bovis. On culture of WTD samples, a Babesia parasite could not be visualized based on common morphological features. Trypanosoma cervi has been studied for decades, but all the previous research identified this parasite solely by morphology. Trypanosoma species obtained from different host species was compared by ribosomal DNA sequence analyses. In this study, the Trypanosoma cultured from WTD had the morphological appearance of T. cervi. On sequence analysis, the cattle sequences aligned together with cattle isolates and the WTD sequences aligned closely with elk (Cervus canadensis) sequences, indicating that wild ungulates (WTD and elk) and cattle most likely have separate trypanosome species. On distribution analysis there was a trend in three South Texas counties, where the county with the highest occurrence of Trypanosoma had the lowest occurrence of Babesia; and vice versa. It is possible that Trypanosoma and Babesia blood parasites compete within the mammalian host, but the chi-squared test did not show a significant association between the two parasites in the different counties. On seasonal analysis, the correlation between positive samples and season could not be statistically confirmed, but it appears that Babesia infected animals are found in lowest numbers during hot, dry seasons. It also appears that there is another vector for Trypanosoma in South Texas besides the ked (Lipoptena mazamae) and tabanid fly (Tabanus spp.).

Thesis (M.S.)--Washington State University, 2004. / Title from PDF title page (viewed on May 22, 2005). Includes bibliographical references.

Thesis (Ph. D.)--Oregon State University, 1994. / Typescript (photocopy). Includes bibliographical references (leaves 108-121). Also available on the World Wide Web.

An understanding of the ecology and behavior of white-tailed deer (Odocoileus virginianus) is necessary for proper conservation and management, especially in the face of emerging infectious diseases. The objectives of my study were to estimate juvenile survival, compare methods of quantifying contact rates (simultaneous GPS locations vs. proximity loggers [PLs]), and investigate the impact of group depopulation on contact rates of remnant adult female and juvenile deer. To achieve these goals, I captured, radiotracked, and monitored adult female and juvenile white-tailed deer in southern Illinois during 2011-2014. Survival analysis of juveniles revealed that main causes of mortality were capture related and predation, though some dead animals also showed signs of hemorrhagic disease. Comparison between simultaneous GPS locations and PLs showed evidence that deer coming within the general vicinity of each other are less likely to come in close contact if they are in neighboring social groups than deer whose home ranges overlap little, if at all. Finally, experimental removal of group members caused few if any remnant adult females to alter their contact rates or space-use, but caused remnant juveniles to have lower space-use fidelity compared to control deer and to increase their direct contact rates with other groups temporarily. Using these results, I discuss the large effects that severe weather events can have on juvenile survival, the importance of social structure on the potential transmission of disease agents among female and juvenile deer, and the difference between adult females and juvenile deer in their need for social interactions. My research provides ecologists, wildlife biologists, and managers with valuable information concerning the potential impacts of the environment, infectious diseases, and management strategies on white-tailed deer populations.

White-tailed deer (Odocoileus virginianus) have considerable impacts on woody and herbaceous vegetation. Many oak-hickory forests in the eastern U.S. are experiencing a lack of oak (Quercus) and hickory (Carya) regeneration, with deer being a likely culprit. Furthermore, few have studied deer use of different herbaceous food plot mixtures. I addressed these gaps in the literature by assessing deer impacts on forest and herbaceous vegetation in southern Illinois. I established 150 paired plots (enclosed and control) in June 2015 and measured 25 habitat variables to assess impacts of deer herbivory from August 2015 to August 2016. Oak seedlings were present more often and in higher numbers within enclosed plots (F1,299 = 6.25, P < 0.050 and F1,387 = 4.50, P < 0.050, respectively). There were no differences in the height of oak seedlings or the presence, number, or height of hickory seedlings in enclosed versus control plots (F1,53 = 0.010, P = 0.938; F1,299 = 0.850, P = 0.357; F1,267 = 1.16, P = 0.282; and F1,15 = 0.030, P = 0.855; respectively). During September-November 2015, I counted and marked fallen acorns within 50 random paired plots; the number of acorns discovered or lost did not differ between enclosed and control plots (F1,94 = 0.310, P = 0.578 and F1,8 = 0.120, P = 0.736, respectively). I suggest managers incorporate potential deer impacts when designing management plans to best encourage oak regeneration. During September-November 2015, I established 16 food plots (half tilled; each 0.05 ha in size), planted to 4 food plot types. I compared Big Tine Buck Brunch, Evolved Harvest Throw & Gro, Antler King No Sweat, and a food plot mixture that I created. I measured deer use via 2 methods: vegetation growth in exclosures versus control (i.e., unfenced) areas and camera traps. Deer used all 4 food plot mixtures (n = 292 – 2,522 pictures/plot over 9 weeks), having a negative impact on mean vegetation height outside of exclosures (F3,1148 = 6.71, P < 0.001). Analysis of camera data indicated that deer did not preferentially use any one food plot mixture over the others (F3,12 = 0.090, P > 0.050). There also was no difference in the proportion of deer pictured in the process of eating within each food plot mixture (F3,12 = 0.592, P > 0.050). I suggest any of these 4 food plot varieties could be planted by a hunter or wildlife manager in the Midwest and observe similar use by deer.

Body size varies according to nutritional availability, which is of ecological and evolutionary relevance. The purpose of this study is to test the hypothesis that differences in adult body size are realized by increasing juvenile growth rate for white-tailed deer (Odocoileus virginianus). Harvest records are used to construct growth rate estimates by empirical nonlinear curve fitting. Results are compared to those of previous models that include additional parameters. The rate of growth increases during the study period. Models that estimate multiple parameters may not work with harvest data in which estimates of these parameters are prone to error, which renders estimates from complex models too variable to detect inter-annual changes in growth rate that this simpler model captures

Tick-borne diseases cause in enormous burden on human, livestock, and wildlife health globally and are driven by the increasing abundance and geographic expansion of medically important tick species. More recently, tick-borne disease emergence is occurring in urban landscapes due to complex feedbacks between the environment, humans, wildlife, and ticks. In this dissertation, I focus on the ecological conditions that allow for tick-borne disease emergence in a city. I use a combination of spatial landscape modeling, empirical data collection, wildlife movement tracking to determine drivers of zoonotic hazards in New York City, NY, and employ vector genomics to examine vector dispersal in the northeastern United States. In chapter one, I pair tick collection throughout the five boroughs of New York City with landscape connectivity modeling to examine how green space connectivity and habitat availability affects the density and infection of questing nymphs – an important epidemiological measure of human risk for tick-borne diseases. I found that green spaces that were highly connected for deer had higher nymph density and infection prevalence for Borrelia burgdorferi sensu stricto, the etiologic agent of Lyme disease. In chapter two, I use camera trapping, live trapping, and tick collection on Staten Island, NY, to examine how landscape fragmentation – through changing habitat size and connectivity – shapes the host community available for questing Ixodes scapularis nymphs. Further, I examined whether patterns in host species abundance and activity correlate with the density of nymphs and their infection prevalence with three different pathogens that vary in host-specificity, B. burgdorferi, Babesia microti, and Anaplasma phagocytophilum. I found associations between host species and the size and connectivity of the park habitat, identified host species which amplified and removed ticks in the environment, and determined links between host activity and abundance and the infection prevalence of nymphs with host-specific pathogens. In chapter three, I utilize movement data from 59 white-tailed deer on Staten Island, NY, to assess the drivers of movement and its impact on tick-borne disease hazard across the landscape. I found that white-tailed deer avoid anthropogenic development at fine spatial scales when establishing home ranges but select for anthropogenic resources within their home range, increasing the potential to distribute ticks into environments that interface with humans. Finally in chapter four, I use double digest Restriction Associated DNA sequencing to examine the genetic differentiation of six I. scapularis populations across the Northeast region. I found high levels of gene flow across a spatial scale of 400 km, likely resulting from frequent host-mediated dispersal events combined with large I. scapularis populations. Taken together, this work emphasizes that host movement and ecology are critical determinants of urban tick-borne disease emergence through directing vector and pathogen dispersal, serving as pathogen reservoirs in urban habitats, and interfacing with humans in unique ways that increase human exposure to zoonotic hazards.

No description available.

White-tailed deer (Odocoileus virginianus) dispersal and excursion movements impact gene flow, population dynamics, and disease spread. Knowledge of movement characteristics and habitat selection during dispersal could provide the ability to predict how deer may relocate themselves within the landscape while providing managers valuable information regarding corridors for gene flow and disease spread. My objectives were to 1) test the hypothesis that extra-home-range movements occur as a strategy to broaden mating opportunities or as a means of searching for higher quality resources in this fragmented landscape, 2) compare occurrence rates and path movement metrics for dispersal and excursion movements to determine if underlying differences in behavior exist that would allude to mechanisms for accepting the risk of leaving a home range, 3) create and test the performance of expert opinion and step selection function resistance models at predicting deer dispersal movements, and 4) fit single and multiple random walk models to dispersal path data to determine movement states occurring within this behavior. During 2011-2014, I placed GPS collars programmed to take hourly locations on 49 fawn and yearling white-tailed deer in agricultural east-central Illinois to record dispersal and excursion movement paths. Linear mixed effects models were used to test for differences in path characteristics between sexes and ages (e.g., distance, straightness, duration, and speed). I used known-fate models, with demographic, temporal, and home range variables as covariates, to obtain dispersal and excursion occurrence rate estimates. Ten dispersal and 54 excursion movement paths were recorded during the study. Dispersal paths were longer and straighter (P < 0.001), and trended toward being longer in duration (P = 0.080) and faster in speed (P = 0.085), than excursion paths. Dispersal rates differed by sex (annual estimate ± SE with ages pooled: males 0.81 ± 0.12, females 0.16 ± 0.15) and were greatest during the breeding season (14-day estimates for males: winter 0.00 ± 0.01, fawning 0.02 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.31 ± 0.15, and females: winter 0.00 ± 0.01, fawning 0.01 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.04 ± 0.03). In contrast, I found no evidence that excursion rates were influenced by demographic, temporal, or home range variables (annual: 0.78 ± 0.06). I compared 2 methods of resistance modeling for predicting deer dispersal paths. I created an expert opinion survey and calculated a dispersal step selection function (SSF) to rank habitat variables and create 2 types of resistance maps to dispersal movements. I created least-cost paths with the starting and ending points coinciding with recorded dispersal paths within these 2 resistance maps. I compared the created paths to actual paths and a null straight line path using a path deviation index (PDI), path straightness, and path cost/m as variables of interest. Experts ranked land cover variables differently by season, applying a lower resistance value to agriculture cover during the summer/fall period, so 2 versions of the expert opinion resistance maps were created. For the SSF, I found that both forest cover and streams had significant nonlinear effects on deer dispersal movements. Assuming that all other factors remained constant, deer were more likely (≥ 0.50 probability) to move toward forested habitat when located < 335 m and when > 2795 m away. Deer dispersal movement behavior relating to streams followed a similar trend but with deer always having > 0.56 probability to move toward a stream than away. For least-cost path comparison, I conducted 3 ANOVAs (α = 0.05 throughout) to test for mean differences in calculated path metrics for all paths with path type as a within-subjects effect. I found no difference between the expert opinion survey model, the SSF model, and the null straight line model at predicting dispersal paths. PDI values were similar among all models (F1,9 = 0.004, P = 0.99). The SSF paths (0.91 ± 0.02) were significantly straighter then both the expert opinion (0.57 ± 0.03) and actual deer paths (0.44 ± 0.06; F1, 9 = 32.65, P < 0.001), but the expert opinion path did not differ from the actual path (P = 0.08). Path costs differed within the expert opinion survey resistance map (F1, 9 = 14.21, P < 0.001) with the expert opinion least cost paths (23.64 ± 3.14) having lower resistance/m than both the actual (46.15 ± 3.85) and straight line paths (48.74 ± 3.94; P < 0.001 for both). However, the actual and straight line paths did not differ (P = 0.872). There were no difference in path costs between the actual, SSF least-cost path, and straight line paths within the SSF resistance map (F1, 9 = 0.454, P = 0.64). I constructed and attempted to fit single and multiple random models to collected dispersal locations using WinBUGS v. 1.4.3. I was able to fit a single random walk model to deer dispersal paths but the more complex random walk models did not converge. I used the average parameter values derived from the single model to simulate deer dispersal paths and compared them to observed Net Squared Displacement. My simulated paths underpredicted deer displacement for 0.90 of individuals. Deer in east-central Illinois are very mobile and commonly make excursion movements throughout the year. The fact that I recorded differing dispersal rates within the same study area over a temporally short period from a previous study highlight the need for managers to obtain recent estimates of population parameters when making management decisions. The frequency of excursion movements should not be overlooked by managers as it is a behavior that can influence gene flow and potentially spread disease across the landscape at a localized scale. The preference for forest and stream habitats during dispersal can allow managers to focus surveillance or culling efforts around these types of habitats. The application of the least-cost path modeling technique appears to be ineffective at predicting deer dispersal paths, which emphasizes the importance of validating these types of models with actual data. The results from the random walk analysis highlight the need to collect as many locations as possible during temporally-short movements to understand the mechanisms acting upon them.

Planted pine (Pinus spp.) comprises nearly 10% of the total land cover in the state of Mississippi. Often, understory structure is limited in this system. Thus, managers use a variety of management practices to improve understory biomass and structure. I assessed the impacts of common forest management practices (canopy reduction, prescribed fire, and selective herbicide application) and their combined effects on aspects of community structure. More specifically, I assessed impacts of disturbance intensity on non-native plant invasions, and evaluated how microscale vegetation characteristics influenced use by white-tailed deer (Odocoileus virginianus) and wild turkey (Mealagris gallopavo). Combining canopy reductions with prescribed fire, which closely mimicked historical intermediate disturbance intensities in this vegetation type, led to the greatest invasion resistance due to high abundances of native plants. Both deer and turkey increased use in areas with high levels of understory cover. Coupling canopy reductions with prescribed fire created the most favorable conditions for both species.