Combining Observational Data and Language for Species Range Estimation Max Hamilton 1 Christian Lange 2 Elijah Cole 3 Alexander Shepard 4

Neural Information Processing Systems 

Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management. However, traditional SRMs rely on the availability of environmental covariates and high-quality species location observation data, both of which can be challenging to obtain due to geographic inaccessibility and resource constraints. We propose a novel approach combining millions of citizen science species observations with textual descriptions from Wikipedia, covering habitat preferences and range descriptions for tens of thousands of species.

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