Big data and AI are being utilized to model hidden patterns in nature across entire ecological communities, not just for individual bird species. These models track each species' full annual life cycle, from breeding to migration, 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 understanding species diversity and composition in various regions.

The researchers plan to release new biodiversity data products on species richness that will be publicly available in 2024. Additionally, they aim to extend their models to estimate bird abundance and incorporate various data modalities, such as visual and audio observations, to enhance the accuracy of their findings.