Bird Observation Data Enhances Predictions of Wild Bee Diversity

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A new study published in PLOS One shows that combining bird observation data with land cover information leads to more accurate predictions of wild bee species richness than using either data source alone.

This breakthrough could play a critical role in guiding conservation strategies for wild bees, which are experiencing significant population declines despite their essential role in maintaining healthy ecosystems and supporting agricultural production. Unlike honeybees managed by beekeepers, wild bees are vital pollinators that thrive without human intervention.

Led by scientists from the Cornell Lab of Ornithology and the Cornell Atkinson Center for Sustainability, the study aimed to address the lack of comprehensive data on wild bee distribution across the United States.

"Our understanding of where bees live is seriously limited by insufficient data, which hampers conservation planning," said Josée Rousseau, the study’s lead author and a postdoctoral researcher at the Cornell Lab of Ornithology.

To bridge these data gaps, the research team turned to bird observations from the Cornell Lab’s eBird program, a massive database of sightings contributed by birdwatchers worldwide.

"Birds are excellent ecological indicators and can sometimes reveal more about environmental quality than satellite data alone," explained Amanda Rodewald, faculty director of the Center for Avian Population Studies at the Cornell Lab of Ornithology. "Thanks to eBird participants, we had a unique opportunity to explore whether bird data could also inform our understanding of wild bees."

The researchers combined eBird data with publicly available land cover information across the eastern and central United States. They then compared these predictions to bee survey data from the Global Biodiversity Information Facility and the Symbiota Collections of Arthropods Network, which included 476,584 bee records covering 792 wild bee species alongside observations of 79 bird species.

Their results demonstrated that using both bird and environmental data produced more accurate predictions of bee richness across large geographic areas compared to relying on land cover data alone.

"Until now, most predictions of bee populations have only used land cover information," Rousseau said. "By adding bird data, we gained a more detailed understanding of the types of landscapes likely to support higher bee diversity, providing better guidance for conservation planning."

Birds and bees often respond to habitat features in similar ways, although they operate at different scales, Rodewald added. Birds can reflect environmental details that satellite imagery might miss, such as the presence of flowering plants or land management practices.

For instance, the presence of Gray Catbirds, which feed on fruits from understory trees and shrubs, can signal habitats rich in flowering plants important for bees. Similarly, Orchard Orioles often indicate the presence of open woodlands and orchards, environments that support a high diversity of wild bee species.

By tapping into the rich dataset provided by birdwatchers, researchers have opened a new path for better understanding and conserving wild bee populations across the United States.