Biodiversity-focused contributory science platforms generate massive quantities of opportunistic records for research, but data are spatially, temporally, and taxonomically biased. While research attempting to quantify these biases abounds, less is known about how varied user motivations and behavior shapes how data accrue. Here, we compare how different iNaturalist user groups prioritize where and when they sample in the southeastern United States. We categorized users by participation level and traveler status, and examined how these groups differentially sample across land cover categories, urban and rural areas, protected land, urban parks, low-income urban neighborhoods, and weekends versus weekdays. We found that highly active users prioritize sampling in biodiversity-rich locations, filling data gaps in natural green spaces and rural areas while perpetuating biases toward protected areas and parks within urban areas. In contrast, casual users tend to primarily incorporate sampling into their daily lives, filling gaps within urban neighborhoods and on non-protected land while perpetuating biases toward developed areas. Local iNaturalist users, especially casual users, were the most likely to sample in low-income census tracts compared with travelers and are important for gap-filling in these underrepresented areas. Understanding how participants with different motivations shape opportunistic biodiversity data can inform contributory project planning and downstream data use. Our results emphasize the importance of recruiting new participants, retaining current participants, and engaging locals in contributory science programs. Further efforts to derive insight from opportunistic biodiversity data may benefit from accounting for variation in motivations of participants and resulting heterogeneity in biases across space and time.
Grady et al. (Thu,) studied this question.