Predator-prey interactions are among one of the most important community-structuring interspecific relationships. It is well known that predators have direct (i.e., consumptive) effects (CEs), influencing population density [1] and survival [2, 3], and indirect (i.e., non-consumptive) effects (NCEs) on prey. Typically, NCEs are caused by the prey's antipredator behaviors, and can range from changes in distribution and habitat use [4-8] to changes in morphology [9] and decreased reproductive success and recruitment [10-13] to increased vigilance and group size [14, 15]. Based on their strength, CEs and NCEs can scale up to affecting entire ecosystems through trophic cascades [16, 17]. Antipredator behaviors are often tied to the prey's perception of predation risk, which is the probability of prey encountering a predator and/or being killed [7] and varies across space and time [18, 19]. Prey perception of predation risk is based on predator identity and hunting style [20-23], and prey often connect the risk of being killed by an ambush predator to specific habitat features [4], while the risk of being killed by a wide-ranging predator is often not tied to habitat features [17], although these types of predators might find more success in open habitats [24]. This suggests that prey will use different antipredator strategies to avoid different predators. Whereas prey might avoid risky habitats when avoiding ambush predators, prey might avoid being active and/or increase vigilance during risky hours when coursing predators might be active and hunting [25]. While many studies focus on the effect of a single predator on prey [i.e., 8], in most ecological communities, there are often multiple predators preying on the same species [26-28]. The number of predatory species in an ecological community can influence the strength of predator effects on prey [27, 29]. If the antipredator strategies that prey use to reduce predation risk by one predator indirectly increases its chance of being killed by another predator [i.e., predator faciliation; 30], predators can more effectively suppress prey populations [29, 31]. Prey in multi-predator systems often seem unable to completely avoid all predators, and instead focus their energies on using antipredator behaviors meant to avoid predators in order of lethality [32]. The interactions between predators, and the interactions between predators and humans, can also influence predation pressure on prey [33]. A comprehensive study on antipredator behavior and survival in a multi-predator system would determine not only the spatiotemporal distributions, antipredator behavior, and survival probability of the prey, but the spatiotemporal distributions of the predators. The white-tailed deer (Odocoileus virginianus) are culturally and economically important species across much of the United States [34] in Pennsylvania. The number one cause of mortality in white-tailed deer fawns is predation [3, 35]; in Pennsylvania, black bears (Ursus americanus), coyotes (Canis latrans), and bobcats (Lynx rufus; Vreeland et al. 2004, McLean et al. 2005) are all known to prey on fawns. All three predators use different habitats [37-39], can be active at different times [40-42], and have different hunting styles [43, 44], creating a landscape of predation risk that varies spatially and temporally [45]. In addition, these predators--particularly coyotes and bobcats [46-48]--can compete with and influence the habitat use and activity patterns of the other predators, further complicating the landscape that fawns must navigate to survive. While this landscape of multi-predator predation risk has been characterized before for white-tailed deer fawns [see 49, 50], no one has attempted to do so in Pennsylvania. In this dissertation, I examine how habitat relationships (Chapter 1) and spatiotemporal interactions of and between humans, fawns, black bears, coyotes, and bobcats influence the vigilance (Chapter 2) and survival (Chapter 3) of fawns during their first three months of life. In Chapter 1, I find that differing matrix types can influence the similarity of coyote and fawn habitat use. In Chapter 2, I posit that the risk allocation hypothesis can explain why a number of studies--including my own--have found that, in more anthropogenically disturbed habitats, species that would normally avoid spatiotemporal overlap with each other increase in spatiotemporal overlap. In Chapter 3, I estimate fawn survival, examine its relationship to fawn antipredator behavior and habitat, and find that data from camera trap surveys could be a feasible alternative to radio-collaring when the goal is to estimate fawn survival. My research provides new insights into species interactions are influenced by anthropogenic disturbance and a template for noninvasively and inexpensively examining these interactions.