Discovering Hotspots and Coldspots of Species Richness in eBird Data

Quantifying biodiversity is an important task related to ecological research. One way to measure biodiversity is through species richness, which measures the number of unique species found in an area. Recently, citizen science biodiversity datasets such as eBird allow the calculation of species richness over an unprecedented spatial and temporal extent. However, several confounding factors associated with the unstructured observation process, such as observer effort, affect the number of species reported by citizen scientists. In this work, we develop an algorithm for discovering hotspots and coldspots of species richness using eBird data while accounting for these confounding factors.