2022 ESA Annual Meeting (August 14 - 19)

COS 154-3 Identifying engaging bird species and traits with citizen science data

10:30 AM-10:45 AM
516A
Ben R. Goldstein, UC Berkeley;Sara Stoudt,Bucknell University;Perry de Valpine,UC Berkeley;
Background/Question/Methods

Birders and amateur naturalists engage with different bird species at different rates. Species that are “charismatic” or more engaging are often prioritized in conservation, and previous researchers have used sociological experiments and digital records to estimate charisma indirectly. Quantifying species-specific biases held by naturalists can inform the impact and efficacy of conservation outreach and the scientific use of community collected biodiversity data. In this study, we view community science efforts as a record of human engagement with animals that can reveal patterns in observer engagement directly, which are in part driven by observer preference. We conduct a multi-stage analysis using generalized additive models (GAMs) to estimate spatial surfaces of user engagement with 472 species of birds across the contiguous United States in two community-contributed observational datasets, eBird and iNaturalist. We argue that eBird complete checklists represent the rate at which a species-agnostic observer detects different species, whereas the more opportunistic iNaturalist engagement surface represents selective engagement based on user preference along with logistical factors such as site selection and observer skill. Using a second-stage meta-analysis, we ask whether opportunistic birders contributing to iNaturalist engage more with larger, more colorful, and rarer birds relative to a baseline approximated from eBird contributors.

Results/Conclusions

We obtain an “overreporting index” for each of 472 species representing the median difference in engagement across space between iNaturalist and eBird. We find evidence that, across 472 modeled species, 52 species are significantly overreported and 158 are significantly underreported, indicating a wide variety of species-specific effects. We find that body mass, color contrast, and range size all predict a species’ overrepresentation in the opportunistic dataset. We find patterns in overreporting at the family level: songbirds (Passeriformes), doves/pigeons (Columbiformes), and gulls/waders (Charadriiformes) were underrepresented while owls (Strigiformes) and gamefowl (Galliformes) were overrepresented. Understanding which bird species are highly engaging can aid conservationists in creating impactful outreach materials and engaging new naturalists. The quantified differences between two prominent community science efforts may also be of use for researchers leveraging the data from one or both of them to answer scientific questions of interest.