Dated perceptions of harvester ants as pests of crops and rangelands have been replaced with new understandings of the myriad beneficial roles they play in their native ecosystems.
Meet Mike Crossley, Ph.D., whose research applying ecoinformatics to insect abundance and diversity trends earned him a spot in the Early Career Professional Recognition Symposium at Entomology 2021. Learn more about Crossley and his work in the next installment of our "Standout Early Career Professionals" series.
An entomologist envisions a future in which non-fungible tokens (NFTs) could drive collecting of 3D virtual models of insect holotype specimens, thereby subsidizing increased digitization of entomological collections and discovery of new species.
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.