Can machine learning be used for accurate species identification of beetles and other invertebrates? Researchers using carabid beetle data from the National Ecological Observatory Network created an algorithm that reached 85 percent accuracy on unidentified images. Eventually, they hope machine learning could one day be used to classify unidentified species in NEON bycatch and answer new questions about invertebrate diversity and abundance across North America.
A partnership between the National Ecological Observatory Network and the National Phenology Network makes deep troves of ecological and phenological data available for a variety of uses, including predicting populations and dynamics of insects such as mosquitoes.
The Biorepository created by the National Ecological Observatory Network program is a treasure trove for entomologists and others interested in insects, arthropods, and vector-borne diseases. Learn more about what's available and how it could enhance your research.