Summary: | Healthy carnivore populations are important to maintaining ecosystem balance, but many species are declining globally at disturbing rates due to anthropogenic causes. To effectively manage and conserve carnivores, wildlife managers must be able to obtain reliable estimates of population parameters. Noninvasive genetic sampling (NGS) methods such as hair or scat collection offer new and exciting alternatives to traditional carnivore research methods involving capture, drugging, and handling of animals; however, the potential of NGS methods to answer applied ecological questions has not been fully realized. The main objective of my doctoral research was to develop and apply NGS methods to estimate demographic and genetic parameters for large carnivore populations in the Rocky Mountains. First, I evaluated two NGS methods, hair snares and snow tracking, for cougars (Puma concolor) in Yellowstone National Park. I developed a method to collect hair while following cougar tracks in snow to bed sites and natural hair snags (e.g. thorn bushes, branch tips) from which I demonstrated that samples collected using NGS can provide reliable information on cougar population abundance. Next, I compared the ability of two NGS methods, hair traps and bear rub surveys, to estimate population abundance and trend of grizzly (Ursus arctos) and black bears (U. americanus) in Banff National Park. I found that bear rubs performed better than hair traps for estimating grizzly bear abundance and population growth rates, whereas hair traps worked better than bear rubs for black bears. I then used NGS to examine demographic and genetic connectivity at wildlife crossing structures along the Trans-Canada Highway that bisects Banff National Park. I compared genetic data collected from the bear populations surrounding the highway to data collected at the crossing structures using a novel hair sampling system. This comparison allowed me to show that wildlife crossing structures provided demographic connectivity for bear populations and ...
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