Carnivores play a critical role in maintaining ecosystem health but face global population threats such as habitat loss, persecution, and disease. Although some populations are recovering from historical declines due to conservation efforts, the ability to detect declines early remains crucial, as does monitoring the ongoing population threats. Estimating population abundance over time and investigating the factors which contribute to population trends enables timely intervention for effective conservation and management of carnivores. This research investigates the ecology and health of bobcats (Lynx rufus) in New York State through two complementary lenses: disease exposure and population abundance. Emerging infectious diseases pose a growing threat to wildlife health and conservation, particularly among carnivores. The first component of this thesis focuses on the emergence of highly pathogenic H5N1 influenza A virus (HP H5N1) in wild mammals, with carnivores representing the most affected mammalian order globally. Despite increasing reports of HP H5N1, the extent of the disease’s effect on morbidity and mortality in carnivores remains poorly understood. Here, I report a case of HP H5N1 infection in a bobcat and assess serological evidence of exposure in 16 live-captured individuals. In 2024, four bobcats (25%) tested positive for antibodies to H5 and N1. Two remained confirmed alive via GPS data until their collars dropped off automatically, while two others were alive as of June 2024, when their collars ceased transmitting. Another bobcat, negative for antibodies at capture, died from HP H5N1 infection within five weeks. These findings provide rare evidence of both survival and mortality following exposure, highlighting the importance of health surveillance, especially in species recovering from historical population declines or facing ongoing anthropogenic pressures. With such species, abundance monitoring is a critical aspect of understanding population response to dynamic environments and informing prompt management and conservation actions. However, monitoring carnivores is especially challenging due to their elusive nature, low densities, and large ranges. The second chapter of this thesis estimates abundance of bobcats, a species with historical declines in New York State, a study system with imperfect individual identifiability and sparse capture data. I employed a spatial capture-recapture model with random thinning and integrated auxiliary telemetry data to account for these challenges. Across five study areas averaging 652 km², mean bobcat density was estimated at 1.2 individuals per 100 km² (95% CI: 0.73–1.73). Density was positively associated with woody and herbaceous wetlands and easting, and negatively associated with northing, suggesting that population recovery remains concentrated in the southeastern portion of the state. These results indicate that bobcats are experiencing a slow recovery across western New York and point to potential ecological or anthropogenic barriers to full recovery. Additionally, these methods demonstrate the utility of integrating multiple data sources in a hierarchical modeling framework for estimating abundance of a low-density species to improve inference and guide evidence-based conservation and management decisions. Together, these chapters offer a unique view of bobcat ecology by investigating both individual health outcomes of a subset of the population from a novel disease, as well as population-level patterns in abundance. This work provides a foundation for future efforts to build upon and integrate spatially explicit abundance estimates with health data, enabling assessments of how pathogens like HP H5N1 influence individual survival and overall population viability.