New research from Cornell University is using big data and artificial intelligence (AI) to model hidden patterns in nature, not just for one bird species, but for entire ecological communities across continents. And the models follow each species’ full annual life cycle, from breeding to fall migration to non-breeding grounds, and back north again during spring migration.
This groundbreaking work is being led by the Cornell Lab of Ornithology and the Cornell Institute for Computational Sustainability. It relies on data from eBird, one of the world’s largest biodiversity science projects, which has over 900,000 birders reporting their sightings.
The new AI models can help us to identify and prioritize landscapes of high conservation value, which is vital in this era of ongoing biodiversity loss. They can also help us to better understand the impacts of climate change and other threats on bird populations. This research is a great example of how cross-disciplinary collaboration can lead to innovative solutions for some of our most pressing environmental challenges.
