Neighborhood Ethnicity is Related to Occupancy of Mammals Across a Diverse Metropolitan Area

More people live in cities or metropolitan areas than ever before, which encompass many types of urbanization. These areas are culturally diverse and densely populated heterogeneous landscapes that are shaped by socio-ecological patterns. Cities support human and wildlife populations that are influenced indirectly and directly by human decisions. This process can result in unequal access to environmental services and accessible green spaces. Additionally, biodiversity distribution is influenced by human decisions. Although neighborhood income can drive biodiversity in metropolitan areas (i.e., the ‘luxury effect’), other socio-cultural factors may also influence the presence and abundance of wildlife beyond simple measures of wealth. To understand how additional social factors shape distributions of wildlife, I ask, are patterns of wildlife distribution associated with neighborhood ethnicity, in addition to income and ecological landscape characteristics within metropolitan areas? Utilizing data from 38 wildlife cameras deployed in neighborhood public parks and non-built spaces in metro Phoenix, AZ (USA), I estimated occupancy and activity patterns of coyotes (Canis latrans), desert cottontail rabbits (Sylvilagus audubonii), and domestic cats (Felis catus) across gradients of median household income and neighborhood ethnicity, estimated by the proportion of Latinx residents. Neighborhood ethnicity appeared in the top models for all species, and neighborhood % of Latinx residents was inversely associated with presence of native Sonoran Desert animals (coyotes and cottontail rabbits). Furthermore, daily activity patterns of coyotes differed in neighborhoods with higher vs. lower proportion of Latinx residents. My results suggest that socio-cultural variables beyond income are associated with wildlife distributions, and that factors associated with neighborhood ethnicity may be an informative correlate of city-wide ecological patterns. In this research, I unraveled predictive social variables and differentiated wildlife distribution across neighborhood gradients of income and ethnic composition, bringing attention to the potentially unequal distribution of mammals in cities.