Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches Ecosphere

A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30-yr horizon of the network. In contrast to NEON ’s extensive use of automated instruments to collect environmental data, NEON ’s biodiversity surveys are almost entirely conducted using traditional human-centric field methods. We believe that the combination of instrumentation for remote data collection and machine learning models to process such data represents an important opportu-nity for NEON to expand the scope, scale, and usability of its biodiversity data collection while potentiallyreducing long-term costs. In this manuscript, we first review the current status of instrument-based biodi- versity surveys within the NEON project and previous research at the intersection of biodiversity, instru- mentation, and machine learning at NEON sites. We then survey methods that have been developed at