neonSoilFlux: An R package for continuous sensor‐based estimation of soil <scp> CO ₂ </scp> fluxes

Abstract Accurate quantification of soil carbon fluxes is essential to reduce uncertainty in estimates of the terrestrial carbon sink. However, these fluxes vary over time and across ecosystem types and so, it can be difficult to estimate them accurately across large scales. The flux‐gradient method estimates soil carbon fluxes using co‐located measurements of soil CO 2 concentration, soil temperature, soil moisture and other soil properties. The National Ecological Observatory Network (NEON) provides such data across 20 ecoclimatic domains spanning the continental U.S., Puerto Rico, Alaska and Hawai‘i. We present an R software package ( neonSoilFlux ) that acquires soil environmental data to compute half‐hourly soil carbon fluxes for each soil replicate plot at a given terrestrial NEON site. To assess the computed fluxes, we visited six focal NEON sites and measured soil carbon fluxes using a closed‐dynamic chamber approach. Outputs from the neonSoilFlux showed agreement with measured fluxes ( R 2 between measured and neonSoilFlux outputs ranging from 0.12 to 0.77 depending on calculation method used); measured outputs generally fell within the range of calculated uncertainties from the gradient method. Calculated fluxes from neonSoilFlux aggregated to the daily scale exhibited expected site‐specific seasonal patterns. While the flux‐gradient method is broadly effective, its accuracy is highly sensitive to site‐specific inputs, including the extent to which gap‐filing techniques are used to interpolate missing sensor data and to estimates of soil diffusivity and moisture content. Future refinement and validation of neonSoilFlux outputs can contribute to existing databases of soil carbon flux measurements, providing near real‐time estimates of a critical component of the terrestrial carbon cycle.