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Poster Short Abstract

We study the spatial pattern in iNaturalist observations across four different cities from the Global North and South. Our finding shows that while some patterns are similar, the spatial biases are not the same across cities, and are rather context-based.

Poster Abstract

We explore the spatial biases in biodiversity observations on iNaturalist across four cities, representing both the Global South (Colombo, Sri Lanka; La Paz, Bolivia) and the Global North (Greater London, UK; San Francisco Bay Area, USA). We ask if the data patterns we observe in different areas are the same, and if they are impacted by common factors such as population density and environmental factors. In our study, we try to understand whether the observations are randomly distributed, shaped by population density, or influenced by the presence/extent of green and blue spaces (factors that are noted in the literature). We present three models: (1) a random baseline to identify initial “hot” and “cold” spots of observations; (2) a population-based model to understand the influence of population density on contributions; and (3) a mixed model combining population density with the presence of green and blue spaces, to test our main hypothesis. Using the chi-square test, the observed (actual) value is compared to the expected values for each model, and the Pearson correlation is used to assess relationships between observations, population density, and green/blue space.

Our findings show that while certain patterns are similar across cities, biases vary across cities by context. In some cities, the hotspots are driven by green/blue spaces, while in other cities it is driven by single-user behavior. These results show that spatial biases are created by both environmental factors (green/blue space) and social factors (users' behavior).