Big data and AI are being utilized to model hidden patterns in nature, focusing not just on individual bird species but on entire ecological communities across continents. These models track each species’ full annual life cycle, providing insights into biodiversity and the environmental conditions that influence species interactions.

The participation of over 900,000 birders in the Cornell Lab of Ornithology's eBird program has significantly enhanced data collection. This citizen science initiative helps fill data gaps and provides a large-scale observational dataset that is crucial for identifying patterns of bird biodiversity and prioritizing conservation landscapes.

The team plans to release new biodiversity data products on species richness, which will be freely available to the public. Additionally, they aim to enhance the models to estimate bird abundance and incorporate audio observations, further improving the understanding of bird populations and their ecological dynamics.