Alex Killion's Dissertation Defense
Title: Coexisting with Wildlife in Shared Landscapes: An Interdisciplinary Assessment to Inform Conservation
Chair: Dr. Neil Carter
Dr. Jacob Allgeier (EEB)
Dr. Meha Jain
Dr. Derek Van Berkel
Sustainable development is exceedingly difficult when multiple priorities conflict with each other. For example, while expanding or intensifying agriculture to increase crop yields can increase food security worldwide, the associated land clearing and resource competition can lead to habitat loss and population declines of wildlife species. On the other hand, interactions between humans and wildlife, like large carnivores or elephants, can sometimes lead to risks to human safety (e.g., attacks on people) and livelihoods (e.g., livestock depredation or crop-raiding), thereby reducing support for wildlife conservation in those circumstances. Indeed, facilitating the sustainable coexistence of humans and wildlife in shared landscapes — areas where people and wildlife frequently co-occur — is a major conservation challenge globally because interventions often promote one goal at the expense of others, leading to counterproductive outcomes. The interface between humans and wildlife populations continues to expand, with humans encroaching into wildlife habitats, and in some cases, wildlife populations recovering and expanding back into portions of their historic ranges that are now occupied by dense human settlements. Therefore, finding solutions that generate benefits for both humans and wildlife, or co-benefits, is urgently needed.
This work aims to better understand and address the social and ecological complexities of human-wildlife coexistence by leveraging large spatial and temporal data to create actionable insights. This dissertation captures human and wildlife dynamics over time, synthesizes and assesses effectiveness of interventions across diverse contexts, and predicts change to better inform decisions in shared landscapes. My first two chapters address these issues from a bottom-up perspective, focusing on human perceptions and adaptations to change. In contrast, the final two chapters come from the top-down, relying on synoptic and aggregate measurements to identify processes and predict change at a landscape scale.
In chapter one, I measure factors affecting the perceptions of the gray wolf (Canis lupus), a species that exemplifies human-wildlife conflict. Using Bayesian topic models, I track changes to wolf salience from local and national news outlets over 50 years, spanning numerous levels of wolf density and conflicting management policy. In chapter two, I conduct a global systematic review on the characteristics and effectiveness of human adaptations (e.g., lethal control) to wildlife-related risks. Random forest models indicate that the type of human adaptation is more important than any other factor, and identifies strategies capable of scaling across diverse contexts. In chapter three, I test the feasibility of new spaceborne data to measure 3D habitat structure and estimate wildlife occupancy. Results suggest that functional diversity indices of habitat structure provide different perspectives of wildlife habitat use compared to 2D variables. In chapter four, I look to the future to assess how livestock production can simultaneously reduce food insecurity and conserve wildlife in Sub-Saharan Africa. Using the Central African Republic as a case study, I generate spatial solutions for 2050 that prioritize livestock allocation targets to avoid co-occurrence with over 80% of wildlife ranges. While these four chapters differ in study location and purpose, they demonstrate the importance of capturing and integrating disparate social-ecological data across spatiotemporal scales to support the broad, multifaceted goal of coexistence in shared landscapes.