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Wild bovids are a diverse group of typically large, hoofed ruminant mammals that play crucial functions in ecosystems as seed transporters and prey for predators to maintain biodiversity. However, their conservation status varies from least concern to critically endangered with extinction, depending on the regions and remaining population. The expansion of agricultural areas and livestock farming has led to habitat loss and natural resource sharing, likely increasing the risk of disease transmission and pathogen circulation between humans, wildlife, and domestic animals at the shared habitats or the interface areas. This thesis aims to identify the habitat suitability of five wild bovids remaining in Thailand, understand the consequences of introducing infectious disease into the population, and identify where there is a risk of disease transmission. Therefore, three main studies were conducted: 1) identifying suitable areas for five wild bovid species, including gaur, banteng, wild water buffalo, mainland serow and Chinese goral in Thailand; 2) simulating the impact of infectious diseases of cattle on wild bovid populations, and; 3) mapping potential risk areas between wild bovids and cattle. Initially, I used ecological niche modelling to identify the habitat suitability of five wild bovids remaining in Thailand. Due to poor model predictions for two species (mainland serow and Chinese goral), I excluded these two models from further analyses. The results indicated that over 50% of the potentially suitable areas for the three modelled species (gaur, banteng, wild water buffalo) were located outside protected areas close to human populations and agricultural areas. Then, I simulated the number of animals in a model gaur population with and without infections over 100 years with 100 repetitions using stochastic mathematical models. I selected six bovine infectious diseases with different traits, such as incubation and infectious periods or fatality probabilities, including anthrax, bovine tuberculosis, haemorrhagic septicaemia, lumpy skin disease, foot and mouth disease and brucellosis. I introduced an individual infected animal into a closed population for each infectious disease. The disease-free gaur population grew over time, with infections with different traits having different impacts. The populations infected with chronic diseases (e.g. bovine tuberculosis and bovine brucellosis) showed the greatest decline, while diseases with high mortality but acute disease or high transmission rates with low mortality had less impact on the populations. Finally, I mapped the potential risk areas for disease transmission, assuming that high cattle density and habitat suitability increased transmission risk between wild bovids and livestock. The results also indicated that the potential high-risk areas were at the interface areas at the forest edges where interactions between wildlife and cattle occur. All my studies and findings will require further investigation and validation to gain a deeper and better understanding of the complexity of infectious diseases within wildlife populations and the dynamics of their distributions, but they contribute to supporting wildlife conservation and implementing disease mitigation measures to prevent disease transmission among the populations by highlighting where wild bovids might have suitable habitat, what types of infections may be problems and where mitigation may be better targeted.

The wildlife and livestock interface is vital for wildlife conservation and habitat management. Infectious diseases maintained by domestic species may impact threatened species such as Asian bovids, as they share natural resources and habitats. To predict the population impact of infectious diseases with different traits, we used stochastic mathematical models to simulate the population dynamics over 100 years for 100 times in a model gaur (Bos gaurus) population with and without disease. We simulated repeated introductions from a reservoir, such as domestic cattle. We selected six bovine infectious diseases; anthrax, bovine tuberculosis, haemorrhagic septicaemia, lumpy skin disease, foot and mouth disease and brucellosis, all of which have caused outbreaks in wildlife populations. From a starting population of 300, the disease-free population increased by an average of 228% over 100 years. Brucellosis with frequency-dependent transmission showed the highest average population declines (-97%), with population extinction occurring 16% of the time. Foot and mouth disease with frequency-dependent transmission showed the lowest impact, with an average population increase of 200%. Overall, acute infections with very high or low fatality had the lowest impact, whereas chronic infections produced the greatest population decline. These results may help disease management and surveillance strategies support wildlife conservation.

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