Date of Award


Degree Type


Degree Name

Master of Science in Biological and Environmental Sciences (MSBES)

First Advisor

Brian D. Gerber


Current methods to model species habitat use through space and diel time are limited. Development of such models is critical when considering rapidly changing habitats where species are forced to adapt to anthropogenic change, often by shifting their diel activity across space. The first chapter of this manuscript focuses on redeveloping occupancy models to incorporate hypotheses on species diel habitat use. This alternative occupancy framework, called the multi-state diel occupancy model (MSDOM), can evaluate species diel activity against continuous response variables which may impact diel activity within and across seasons or years. We used two case studies on fosa, a mesocarnivore endemic to Madagascar, and coyote in Chicago, USA, to conceptualize the application of this model and to quantify the impacts of human activity on species’ spatial use in diel time. We found support that both species altered their diel activity across intensity of human disturbance—in and across years, and by degree of human disturbance. Our results exemplify the importance of understanding animal diel activity patterns and how human disturbance can lead to temporal habitat loss. This adapted model will allow future studies to answer explicit questions in regards to species diel habitat use and direct conservation efforts to protecting habitats over shorter, diel, periods. Chapter two of this manuscript focuses on incorporating human dimension research to understand relationships between people and wildlife. Human dimension research in ecology is especially needed in urban landscapes where more wildlife are living among and adapting to human dominated landscapes. Thus, we focus on understanding the complex drivers of human-wildlife relationships that have become increasingly important for managing both people and wildlife. A common approach to researching these drivers is via survey questionaries and the use of Likert items and scales, which require analytical techniques that handle their unique structure. Here, we apply a hierarchical Bayesian modeling framework to conduct ordinal regression that is well suited to Likert response data and allows the evaluation and comparison of model hypotheses. Our case study focuses on two objectives, understanding how people value coyotes and the frequency in which people interact with coyotes. We measured how people value coyotes with a Likert scale on peoples perceived risks and benefits of having coyotes on a landscape and measure frequencies of interactions with two Likert items on people’s sightings and incidents (growling, stalking attacking people or owned animals) with coyotes. We investigated how people’s demographics, knowledge of coyotes, and relationship with nature impacted the above response variables. We found strong support that decreasing connectedness to nature, fear of coyotes, and incidents between coyotes and owned animals (pets or livestock), negatively impacts people’s value of coyotes while pet ownership positively impacted peoples value of coyotes. Additionally, we found value of coyotes to vary across gender and counties; specifically, we found females to value coyotes more positively than males and found people from Bristol and Newport counties to have the most negative value coyotes. We found strong support that animal ownership and fear of coyotes, positively impacted coyote sightings and incidents. Coyote sightings and incidents also varied across counties and occurred most frequently in Bristol and Newport. These results highlight that human demographics and characteristics can shape people’s value and interactions with endemic wildlife. Through the application of ordinal regression, we were able to estimate how human demographics and characteristics impact people value of wildlife (positively or negatively) and how the frequency of interactions vary across groups of people. Through these findings, conservationists and wildlife managers can target mitigation and educational efforts to specific constituents which least value or most interact with coyotes. Importantly, this study highlights the importance of fear in shaping people’s value and interactions with coyotes, therefor we encourage more research on assuaging fear of local wildlife.



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