Assessing the reliability of avian biodiversity measures of urban greenspaces using eBird citizen science data

Urban greenspaces are important areas for biodiversity, serving multiple uses, sometimes including conservation and biodiversity management. Citizen science provides a cheap and potentially effective method of assisting biodiversity management in urban greenspaces. Despite this potential, the minimum amount of citizen science data required to adequately represent a community is largely untested. We used eBird data to test the minimum sampling effort required to be confident in results for three biological metrics, species richness, Shannon diversity, and community composition (Bray-Curtis similarity). For our data, from 30 urban greenspaces in North America, for a 90% threshold level, a minimum mean number of 210, 33, and 58 checklists were necessary for species richness, Shannon diversity, and community composition, respectively. However, when we eliminated those species that were present in fewer than 5% of checklists at a given site, there was a marked decrease in mean minimum number of checklists required (17, 9, and 52, respectively). Depending on the ecological questions of interest, eBird data may be a potentially reliable data source in urban greenspaces. We provide a validation methodology using eBird data, with its associated code in the R statistical environment, to provide confidence for land managers and community groups managing urban greenspaces.