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Urban green spaces (UGS) often support diverse bird assemblages. Current evidence suggests large UGS that are circular in shape and contain abundant tree canopy cover will support more bird species independent of UGS isolation. Here, we use bird occurrence information from the eBird citizen-science database over an 18-year period (2002–2019) to estimate annual and seasonal patterns of avian species richness in well-surveyed New York City green spaces. Area was the strongest correlate of annual (n = 102 UGS) and seasonal species richness (n = 43 UGS), whereas shape and isolation lacked significant relationships. Increasing area by 50% resulted in an 11.5% increase in annual and an 8.2% increase in seasonal species richness. There was no evidence that these relationships contained an upper limit. Tree canopy cover was weakly correlated with annual species richness. The richness of nocturnally migrating species was strongly correlated with area in the spring and autumn, especially for non-passerine species. The species richness of nocturnally migrating passerines was strongly correlated with tree canopy cover in the spring, where a 50% increase in canopy cover resulted in a 23.3% increase in species richness. Our findings emphasize the broad importance of area, the value of tree canopy cover for spring migrants, and the limited relevance of shape and isolation. Efforts to enhance area and tree canopy cover will increase the number of resident and migratory bird species, which will likely increase the number of other area-sensitive forest taxa that occur in urban environments.

Citizen-science projects engage volunteers to gather or process data to address scientific questions. But citizen-science projects vary in their ability to contribute usefully for science, conservation, or public policy. eBird has evolved from a basic citizen-science project into a collective enterprise, taking a novel approach to citizen science by developing cooperative partnerships among experts in a wide range of fields: population and distributions, conservation biologists, quantitative ecologists, statisticians, computer scientists, GIS and informatics specialists, application developers, and data administrators. The goal is to increase data quantity through participant recruitment and engagement, but also to quantify and control for data quality issues such as observer variability, imperfect detection of species, and both spatial and temporal bias in data collection. Advances at the interface among ecology, statistics, and computer science allow us to create new species distribution models that provide accurate estimates across broad spatial and temporal scales with extremely detailed resolution. eBird data are openly available and used by a broad spectrum of students, teachers, scientists, NGOs, government agencies, land managers, and policy makers. Feedback from this broad data use community helps identify development priorities. As a result, eBird has become a major source of biodiversity data, increasing our knowledge of the dynamics of species distributions, and having a direct impact on the conservation of birds and their habitats.