WILDLIFE DISEASES OF ECONOMIC AND CONSERVATION IMPORTANCE

<b>Project Methods</b><br> For any disease system, establishing a strong surveillance and monitoring scheme is imperative, in other words, we cannot control what we do not know exists. Surveillance and monitoring should include constant collection, collation, and analysis of data related to animal health. In order to undertake the objectives of my research I will employ numerous methodologies (see below) which will include collaborations and buy-in from stakeholders at the local and national level. A brief description of research activities for each objective is given below.Determine disease threats posed by wildlife, especially abundant invasive and exotic species, to identify important disease threats at the wildlife-livestock interface, including diseases of biosecurity importance.An important consequence of the coexistence of wild and domestic animals is the possibility of pathogen transmission between species. Alteration of wildlife population densities, such as large deer and feral hog populations, increases the possibility for interspecies contact and pathogen transmission at the livestock-wildlife interface. Wild animals are a reservoir for many diseases affecting domestic animals. For example, feral hogs can carry numerous pathogens, but possibly the most threatening include brucellosis, pseudorabies and tularemia. Additionally, although bovine babesiosis is not currently found in the United States, white-tailed deer and nilgai antelope (Boselaphus tragocamelus) near the Texas-Mexico border have been found infested with ticks (Rhipicephalus microplus and R. annulatus) that cause bovine babesiosis (Babesia bovis and B. bigemina); this disease remains endemic in Mexico and poses an enormous threat to the United States. In Texas, diseases transmitted to cattle not only threaten the livelihood of cattle ranchers but the entire national beef industry. A primary goal of this research objective will be documenting wildlife demographics, contact rates with livestock, habitat use, infection status and vector infestation rates. The knowledge gained from these investigations will also be important for understanding the potential implications for many diseases, including those of biosecurity importance, including foot and mouth disease, African swine fever, and anthrax.Identifying disease threats to species of conservation concern.Species of conservation concern are particularly susceptible to disease introduction events which may cause significant negative impacts to populations. The goal of this research objective will be to identify potential pathogens that pose a threat to the persistence of these species. Species of particular interest from a disease standpoint include pronghorn (Antilocapra americana), bighorn sheep (Ovis canadensis nelsoni), ocelot (Leopardus pardalis), mountain lion (Puma concolor), and the black-tailed prairie dog (Cynomys ludovicianus). Often by the time diseases are recognized in wildlife populations, they are already at the point of posing significant threats to species. One of the goals for this portion of my research will be to utilize vector and intermediate host collections, as well as other noninvasive techniques, e.g. fecal analysis to detect potentially threatening pathogens on the landscape before populations are threatened.Investigating the influence of climate on the distribution of vectors and vector-borne diseases.Vectors and vector-borne diseases may be most impacted by changes in climate. A combination of predicted increasing temperature at higher altitudes, changes in precipitation patterns, increased climate fluctuation, and extreme weather events may have considerable effects on vectors of animal/wildlife health importance. Aspects of the vector life cycle and life history including activity rates, reproduction rates, interstadial development rates, and pathogen transmission. To better inform causes and consequences of disease occurrence, it will be important to understand where and why vectors and associated pathogens may or may not be detected. Monitoring the range, abundance, infection rates, and seasonal phenology of vector species will be important to my research.ToolDefinition/Explanation of UseEcological niche modelingEcological niche modeling or species distribution modeling uses various algorithms to predict the distribution of a species based on records of individuals. Of particular use are ecological niche models that use presence-only data instead of a logistic framework which requires presence and absence data because it is quite difficult to unequivocally show the absence of a species. I will utilize the Maxent modeling platform, which routinely out performs other presence-only methods. Ecological niche modeling is also valuable for understanding and predicting distribution shifts caused by changes in climate by using projected climate change models.GIS analyses and remote sensingGIS and remote sensing are important and powerful tools which incorporate ground-based measurements (location and attributes) and satellite and aerial photography data. Using these tools is useful for asking and answering many ecological questions at multiple scales across time and space. Spatial analyses using GIS can be useful for analyzing spatial trends and associations. Several spatial analysis tools are available in GIS and my applications of spatial modeling with GIS will include kriging, clustering algorithms, and inverse distance weighted, to name a few.Landscape geneticsLandscape genetics is a combination of population and landscape ecology and can provide information about interactions between the landscape and genetics including geneflow, genetic drift and selection. The goal of landscape genetics is to identify environmental features that influence gene flow among populations. My applications of this powerful tool will include assessing genetic diversity of vectors, pathogens and hosts and investigating movement and landscape features that may impede or enhance movement across landscapes.Mathematical and statistical modelingI will utilize a combination of traditional statistical methods including logistic, multivariate, and geographically-weighted regression and Bayesian forecasting to analyze pathogen data. I will also incorporate specialized, complex machine learning modeling platforms described below.Dynamical systems modeling including traditional Susceptible – Infected or Infectious – Removed (S-I-R) models to quantify:R0, the basic reproductive rate of a disease, i.e. how many secondary infections result from the introduction of a single infected individual into a naïve population.NT, the population threshold for establishment of a disease/pathogen.These types of models can also be useful to inform interventions such as immunization requirements, effect of addition or removal of barriers to movement, and vector/pathogen spread or establishment.Agent-based models are computational simulation tools that consider all components of a system to understand how system properties emerge from interactions. Essentially, these types of models emphasize interactions between individuals or agents and their environment. These types of models can also be useful to inform conditions necessary for vector/pathogen spread, establishment, and species interactions.