Electronic Theses and Dissertations



Document Type


Degree Name

Master of Science



Committee Chair

James Adelman

Committee Member

Cassandra Nuñez

Committee Member

Robert W. Klaver

Committee Member

Jaime L. Sabel


As humans continue to alter the environment, infectious diseases have become increasingly important challenges to wildlife populations and surveillance can play an important role in the management of such diseases. However, physiological surveillance is logistically and economically challenging, hampering our ability to detect disease incidence and spread. My work aimed to circumvent some of these challenges using an iconic species of North American wildlife as a model system: bighorn sheep (Ovis canadensis). For decades, Bighorn Sheep Respiratory Disease (BHSRD) has reduced lamb survival, decreased population growth and stability, and even led to local extinctions. As such, monitoring this disease is essential to the management and well-being of the species. Specifically, my research sought to 1) develop a surveillance program using clinical signs and behavioral sampling to predict infection in bighorn herds and 2) investigate whether community science is a viable method for monitoring behaviors indicative of wildlife disease. I observed bighorns in two sites with differing disease prevalence, the Little Belts (high disease prevalence) and Sun River (low disease prevalence), in Montana in the summers of 2021 and 2022 focusing largely on lamb behavior. Field technicians and I performed 20-minute focal behavioral sampling, focusing on one animal at a time and noting the time of inactivity and playing as well as any clinical signs of compromised health. These data showed that the Little Belts lambs spent more time inactive than did Sun River lambs in 2021, but not 2022. Further, the Little Belts lambs spent proportionally less time playing than did Sun River lambs in 2022, the year in which sufficient data were collected to assess this behavior. In both years, clinical signs (coughing, panting, lip-licking) were more prevalent among animals in the Little Belts herd. To test the viability of community science in behavior-based surveillance, in 2022, I trained 40 volunteers and paired them with biologists to perform 20-minute focal behavioral samples on bighorns throughout Glacier National Park. Each pair focused on a list of behaviors (paying particular attention to the time lambs spent inactive) that were identified as important indicators of bighorn health during the initial field season in summer 2021. Biologists and volunteers demonstrated similar ability to detect lamb inactivity, while the recording of other behaviors (feeding, walking, standing) and clinical signs (coughing, and lip-licking) were more variable. I also analyzed what factors best explained discrepancies in data collected by volunteers and found no strong effects of volunteer demographics on the accuracy of data collection. Few studies have focused on whether behavioral metrics can serve as reliable health indicators at the population level, and, to my knowledge, none has tested community science volunteers in this context. My study filled these knowledge gaps by 1) identifying behaviors and clinical signs in bighorn sheep that indicate BHSRD presence at the population level and 2) providing community science tools that managers, parks, and landowners can use to proactively monitor bighorn sheep populations for outbreaks of BHSRD.


Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest


Open Access