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Calibration Strategies for Detecting Macroscale Patterns in NEON Atmospheric Carbon Isotope Observations
Author(s) -
Fiorella Richard P.,
Good Stephen P.,
Allen Scott T.,
Guo Jessica S.,
Still Christopher J.,
Noone David C.,
Anderegg William R. L.,
Florian Christopher R.,
Luo Hongyan,
PinginthaDurden Natchaya,
Bowen Gabriel J.
Publication year - 2021
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2020jg005862
Subject(s) - neon , isotopologue , atmospheric sciences , carbon cycle , environmental science , isotopes of carbon , isotope , calibration , chemistry , ecosystem , ecology , geology , environmental chemistry , physics , statistics , biology , total organic carbon , mathematics , organic chemistry , quantum mechanics , argon , molecule
Carbon fluxes in terrestrial ecosystems and their response to environmental change are a major source of uncertainty in the modern carbon cycle. The National Ecological Observatory Network (NEON) presents the opportunity to merge eddy covariance (EC)‐derived fluxes with CO 2 isotope ratio measurements to gain insights into carbon cycle processes. Collected continuously and consistently across >40 sites, NEON EC and isotope data facilitate novel integrative analyses. However, currently provisioned atmospheric isotope data are uncalibrated, greatly limiting ability to perform cross‐site analyses. Here, we present two approaches to calibrating NEON CO 2 isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO 2 isotopologues independently yields a lower δ 13 C bias (<0.05‰) and higher precision (<0.40‰) than directly correcting δ 13 C with linear regression (bias: <0.11‰, precision: 0.42‰), but with slightly higher error and lower precision in calibrated CO 2 mole fraction. The magnitude of the corrections to δ 13 C and CO 2 mole fractions vary substantially by site, underscoring the need for users to apply a consistent calibration framework to data in the NEON archive. Post‐calibration data sets show that site mean annual δ 13 C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO 2 and δ 13 C than other sites, particularly during the summer and at night. The overview and analysis tools developed here will facilitate cross‐site analysis using NEON data, provide a model for other continental‐scale observational networks, and enable new advances leveraging the isotope ratios of specific carbon fluxes.