Date

Spring 2023

Document Type

Master's Thesis (Open Access)

Degree Name

Master of Science (M.S.)

Department

Applied Environmental Science

Abstract

As anthropogenic activity such as urbanization and agriculture destroys and fragments wildlife habitat, some patches may grow too small or isolated to support apex predators, which may allow mesopredator populations to flourish in the absence of predation and competition pressure. In areas where mesopredator occupancy is high, increased predation pressure may be placed on mesopredator prey species such as songbirds, which are already experiencing declines due to habitat loss. Here I used camera traps to collect occupancy data of the region’s most commonly occurring apex predators (coyotes) and three mesopredator species (bobcats, gray foxes, and domestic cats) at 35 sites along an urbanization gradient prominently featuring agriculture in California’s Salinas Valley, and I conducted avian point counts to estimate passerine richness at 70 sites along the same gradient. I evaluated the influence of apex predators on mesopredators with single-season occupancy models, and I assessed the potential impact of mesopredators on passerine richness with Random Forest regression analysis. Gray foxes displayed a strong negative relationship with coyote activity and a strong positive relationship with mountain lion presence, while coyotes were negatively associated with mountain lions. Distance to wildland patches was the top predictor for both felid species, neither of which were notably impacted by coyotes. While natural landscape and topography predictors had the greatest explanatory power for passerine richness, domestic cat activity also had a notable adverse effect on passerines, with more explanatory power than all other carnivore and human-related metrics. Agricultural metrics typically displayed only moderate or weak predictive power in all models despite having higher carnivore and passerine richness than all other landscape classes, suggesting that there is greater complexity to how wildlife use agricultural habitat than I captured in this study.

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