It is widely recognized that livestock industries are vulnerable to intentional or accidental introductions of Foreign Animal Diseases (FADs). Combating disease is difficult because of unknown wildlife-livestock interactions. Feral hogs (Sus scrofa) could harbor and shed disease in areas used by domestic livestock such as cattle (Bos taurus). Extent of risk logically depends on spatio-temporal interactions between species. I used Global Positioning System (GPS) collars on cattle and hogs in combination with a Geographic Information Systems (GIS) for detailed analysis on movement patterns of these 2 species on a ranch in southwestern Texas, USA. Motion-triggered video recorders were also utilized to determine interspecific activity patterns. I tested hypotheses that spatio-temporal distributions of domestic cattle and feral hogs on rangeland overlap and that interspecific contact occurs. If these posits are true, it is possible that introduced pathogens like foot-and-mouth disease (FMD) could be transmitted from feral hogs to cattle. Using a rate of 1 GPS fix/15 min (96 fixes/day), I found that spatial distribution of individual hogs and cattle overlapped on both the 95% and 50% kernel area use among 4 seasons. Both cows and feral hogs used Clay Flat, Clay Loam, and Rolling Hardland more so than other range sites. During Summer 2004, riparian zones were the most used feature, identified at 14% (2,760/19,365) of cattle and 70% (445/632) of hog fixes. Other than brush strips, cattle and feral hogs primarily interacted at riparian zones, fencelines, and roads. There were no direct interspecific contacts evident from GPS data, but 3 cases were recorded from video data. Indirect interspecific contacts that may be sufficient for disease transmission occurred much more frequently (GPS = 3.35 indirect contacts/day, video = cows follow hogs: 0.69 indirect contacts/day and hogs follow cows: 0.54 indirect contacts/day). Research results suggested that both species often travel along the same roads and fencelines to water and food sources, especially during extreme heat and low-precipitation conditions. This research provides basic information needed to improve models for management of FAD outbreaks in the U.S., based on specific knowledge of landscape usage and movement patterns of feral hogs and cattle.

White-tailed deer (Odocoileous virginianus) are an important game animal and provide intrinsic value to many people. However, disease has become of great concern within white-tailed deer populations. Frequency of contract drives the establishment and spread of infectious diseases among susceptible hosts. Supplemental feed provided to increase white-tailed deer survival or create hunting opportunities, as well as bait stations to aid in capture of deer, may increase contact opportunities and disease transfer. My objective was to quantify the effects of bait sites on indirect contact between deer. I examined data from global positioning system (GPS) collars placed on 27 deer near Carbondale, Illinois, USA, from 2002 to 2005. Location data from GPS collars were used to ensure that I quantified contacts between deer in separate social groups, based on the volume of intersection of their spatial utilization distributions and correlation of movements. I matched 35 bait site locations and control sites not containing bait based on local land cover composition. Pairwise indirect contacts between deer were tabulated within a 10, 25, 50, 75, or 100-m buffer around each bait and control site. Indirect contact frequencies between bait and control sites were compared using mixed-model Poisson regression with deer pair as a random-effect variable and bait, joint utilization distribution (JUD), and year as fixed-effect variables. Contact frequencies did not differ significantly (P<0.05) between bait sites and control sites at any buffer distance, implying that small bait piles used to capture deer have minimal effect on contact frequencies. However, the effect of more consistent and greater quantities of food distributed during supplemental feeding programs should be studied further to determine its impact on contact rates and spatial distribution of deer. Understanding the spatial distribution of white-tailed deer is important to implement effective disease and population management within localized areas. The objective of this study was to measure the home-range fidelity of female deer in an exurban deer herd in southern Illinois. I compared location data of 7 deer that had been collected in 2004-2005 and 2008. I used the volume of intersection (VI) and percent of home range overlap to statistically compare the two annual home ranges for each deer. Deer were located used ground-based radiotelemetry and home ranges were characterized using a fixed kernel utilization distribution. Comparing home ranges between years, the mean VI was 0.45 with little variation (range 0.35-0.55). I found the mean percent overlap of 50% isopleths to be 47.1% (range 31.3-71.7%) and the mean overlap of 95% isopleths to be 62.0% (range 44.3-68.6%). My results indicate that female white-tailed deer on our study area showed strong home-range fidelity, which could permit disease and population management by removing deer and reducing local deer densities.

We live in an era of global change, where emerging infectious diseases such as Ebola, Zika, bird flu, and white nose syndrome are affecting humans, wildlife, and domesticated species at an increasing rate. To understand and predict the dynamic spread of these infectious agents and other symbionts through host populations and communities, we need dynamic mathematical models that accurately portray host-symbiont transmission. But transmission is an inherently difficult process to measure or study, because it is actually a series of interacting processes influenced by abiotic and biotic factors at multiple scales, and thus empirical tests of the transmission function within epidemiological models are rare. Therefore, in this dissertation, I explore factors at the individual, population, and community-levels that influence host contact rates or symbiont transmission success in a common snail-symbiont system, providing a detailed description of the multi-faceted nature of symbiont transmission. From a review of the ecological literature, I found that most models assume that transmission is a linear function of host population density, whereas most empirical studies describe transmission as a nonlinear function of density. I then quantified the net nonlinear transmission-density relationship in a system where ectosymbiotic oligochaetes are directly transmitted among snail hosts, and I explored the ecological mechanisms underlying the nonlinear transmission-density relationship observed in the field via intraspecific transmission success and contact rate experiments in the laboratory. I found that the field results could be explained by heterogeneity in transmission success among snails with different characteristics and nonlinear contact-density relationships caused by non-instantaneous handling times. After I 'unpacked'population-level transmission dynamics into those individual-level mechanistic processes, I used this same approach to examine higher-level ecological organization by describing the mechanistic underpinnings of interspecific or community-level transmission in the same snail-symbiont system. I found that low interspecific transmission rates in the field were the product of opposing interactions between high population densities, high prevalences of infection, and very low interspecific transmission success caused by strong symbiont preferences for their current host species. Unpacking transmission in this way resulted in one of the most detailed empirical studies of transmission dynamics in a wildlife system, and yielded many surprising new insights in symbiont ecology that would not have been discovered with a purely phenomenological or holistic view of transmission. Though simple, linear, and holistic epidemiological models will always be important tools in disease ecology, 'unpacking'transmission rates and adding heterogeneity and nonlinearity to models, as I have done here, will become increasingly important as we work to maximize model prediction accuracy in this era of increased disease emergence. / Ph. D. / Parasites and pathogens can have important implications for wildlife conservation, the production of domesticated animals and crops, and human health, and thus ecologists and epidemiologists need effective tools for understanding, predicting, and managing the spread of these important pathogens. Mathematical models that represent the transmission of pathogens within single wildlife host species (e.g., Ebola transmission within bat populations) and between different host species (e.g., Ebola transmission between bats and humans) are one such tool, and these same models can be used to understand the spread of beneficial symbionts that actually help the host by being present. But despite being critical tools, these mathematical models are not yet perfect. In fact, in this dissertation work, I demonstrate that the most commonly used models are not well-supported by data from real host-parasite systems, and that the fundamental assumptions underlying these models are rarely tested, because measuring transmission among individuals is often difficult. Therefore, I developed experimental methods to test some of these fundamental assumptions in a system where tiny annelid worms live on aquatic snails, and are only transmitted from one snail to the next during direct contacts between snails. In particular, I first used field studies in a Virginia pond to describe how the rate of worm transmission within and between snail species depends on snail density. I then used laboratory experiments to understand how the rate of contacts between snails and worm preferences for particular snail characteristics (i.e., size, species) influence worm transmission rates. Taken together, this work represents one of the most detailed studies of transmission dynamics in a wildlife system, and yielded many important new insights regarding how to make epidemiological models more biologically realistic. Though the simplest epidemiological models that we have relied on for decades will continue to be useful, the more complicated, biologically-realistic models explored here will become increasingly important as we work towards improving our abilities to precisely and accurately predict and manage parasite transmission.

This thesis examines the space use, movement and contact rate patterns of a high- density, group-living, Eurasian badger (Meles meles) population in the UK naturally infected with bovine tuberculosis (bTB). Recently developed proximity logging devices were deployed on a representative sample of 51 badgers from eight different social groups to track their movements using radio-telemetry and to quantify their within- and between-group contact rates. Whilst interactions within social groups accounted for more than 90% of contacts, the entire study population was ultimately connected through interactions among individuals from neighbouring groups. Both within and between-group contacts, and also the use of denning sites, were heavily influenced by seasonal and demographic factors, which appear to be motivated to a large extent by reproductive behaviours. Nevertheless, by using social network analysis I found that badgers that tested positive for bTB were found to interact with fewer of their group members and for a shorter amount of time. Specifically these test-positive individuals were found to associate with test-negative group members significantly less than would be expected by chance. Those animals testing positive for bTB were also found to use outlying setts significantly more frequently than those that tested negative. The within and between-group contact rates of individuals were found to correlate with their sett use patterns. Those animals that spent less time interacting with group members and those that spent more time interacting with members of foreign social groups, were found to spend a greater proportion of their time at outlier setts. The findings in this thesis suggest a link between wider roaming behaviour and the disease status of an individual. This adds support to the argument that the social disruption of badger populations, for example through culling, may promote rather than alleviate the spread of bTB as a result of increased movement and contacts between groups. State-of-the-art technology has enabled me to demonstrate the strong influence that badger social organisation may have on the transmission of an economically significant infectious disease. My findings suggest that disease control measures might be enhanced by taking into account seasonal and individual-level variation in ranging behaviour and use of outlier setts, for example, by identifying and targeting functional groups of individuals, specific areas, or times of the year that contribute disproportionately to disease spread.