Socio-environmental drivers of human-nature interactions in urban green spaces

Abstract

Online platforms have broadened the opportunities of people to interact with nature through community/citizen science, especially in urban areas. However, there is a lack of comprehensive understanding of the social and environmental factors that influence nature interactions in cities. Here, we aim to identify the social and environmental predictors that impact nature interactions, by combining citizen science data with environmental and demographic data in New York City. We applied generalized linear models to identify which of 12 social and environmental factors influence nature interactions in public parks (n = 355) in the Borough of Queens, New York, New York (USA) in two scenarios, small-medium sized parks only (n = 355) and all parks (n = 359). We used iNaturalist records, including the number of users (Observers), Observations, Observed Biodiversity, and a calculated interaction effect (number of users × observations, Interaction), as metrics of nature interactions. For small-medium parks, all nature interactions were significantly influenced by park area, canopy cover, percent population with blood pressure and asthma conditions, noise, and summer mean temperature. Observers and Interaction were positively associated with median income. Observers, Observations, and Interaction were predicted by percent water cover, impervious cover, distance to public transportation, and ethnic diversity. In the analysis that included all parks, the results were similar with minor differences. This study demonstrates a holistic approach to a very specific type of human-nature interaction newly made available with technological advances, seen through an interdisciplinary lens and will help inform planners, residents, and city government on creating more interactive and socio-environmentally beneficial urban green spaces.