Behavioural, physiological and community-level responses of wildlife to human disturbance

As human pressure on natural habitats continues to intensify, understanding how human activities impact wildlife fitness and survival has become a central focus in contemporary ecology. This PhD project aims to fill current knowledge gaps by examining the effects of human activities on wildlife at multiple biological levels, providing a comprehensive perspective on how species adapt—or fail to adapt—to anthropogenic pressures at different biological levels. The thesis is divided into three objectives, each addressing a specific scale and aspect of human-wildlife interactions: (1) investigating short-term spatio-temporal adjustments of wildlife in response to human activities in a small private reserve dedicated to ecotourism, (2) establishing whether wildlife populations show consistently elevated glucocorticoid concentrations (GCCs) in human-disturbed areas and exploring the role of disturbance type and species traits in shaping these responses, and (3) exploring how anthropogenic and environmental factors shape urban avian communities by identifying species assemblages with different tolerances to urbanization and mapping their distribution across the urban matrix. Chapter II focuses on fine-scale, short-term behavioral responses of wildlife to dynamic human disturbance patterns in a small private reserve. Using an extensive camera-trapping study, we modeled species detection/non-detection as a function of temporally and spatially explicit proxies of human pressure, revealing how mammalian species adjust their spatial and temporal patterns in response to unpredictable human activities. Chapter III shifts to a global perspective, examining the physiological responses of wildlife to anthropogenic stressors through a phylogenetic meta-analysis of glucocorticoid concentrations (GCCs). By synthesizing data from 121 studies across 114 terrestrial vertebrate species, we investigated how disturbance type and species traits—such as body size, diet, and migratory behavior—modulate GCC shifts. Finally, Chapter IV explores the community-level effects of urbanization on avian communities in the metropolitan area of Rome. Using extensive acoustic monitoring and deep neural network algorithms (BirdNet), we classified bird calls and identified species assemblages with varying tolerance to urbanization. By analyzing urban and environmental variables, we investigate the determinants of the assemblages' occurrence, and map their distribution across the urban landscape.