click The National Science Foundation’s National Ecological Observatory Network (NEON) is a continental-scale observation facility operated by Battelle and designed to collect long-term open access ecological data to better understand how U.S. ecosystems are changing. The comprehensive data, spatial extent and remote sensing technology provided by NEON will enable a large and diverse user community to tackle new questions at scales not accessible to previous generations of ecologists.
viagra in uk NEON collects data and archival samples that characterize plant, animals, soil, nutrients, freshwater and atmosphere from 81 field sites strategically located in terrestrial and freshwater ecosystems across the U.S.
- Collection methods are standardized across field sites to provide high quality datasets from in situ automated instrument measurements, observational sampling and airborne remote sensing surveys.
- Over 175 open access data products are available on the NEON data portal in addition to open access data tutorials, code packages and other resources to enable use of NEON data.
- NEON also archives over 100,000 biological, genomic and geological samples each year which are available upon request from the NEON Biorepository.
pandora drug ingredients viagra In addition to data, samples and educational resources, NEON also serves as an infrastructure for Principal Investigator-driven research to advance understanding of ecological processes. Through the NEON Assignable Assets program, researchers can 1) Request access to NEON field sites to conduct their own research; 2) Request that NEON field scientists collect additional observations and samples; 3) Add their own data collection sensors to field site infrastructure; 4) Request airborne remote sensing surveys customized to a geographic area of their choice; and, 5) Request access to NEON’s Mobile Deployment Platforms (MDPs). MDPs are quick set up mobile sensor arrays that can be outfitted with atmospheric, soil and aquatic sensors for PI-driven monitoring projects such as data collection during and after stochastic ecological events (e.g. fires, floods and pest outbreaks).