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 CO₂ 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 CO₂ isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO₂ isotopologues independently yields a lower δ¹³C bias (<0.05‰) and higher precision (<0.40‰) than directly correcting δ¹³C with linear regression (bias: <0.11‰, precision: 0.42‰), but with slightly higher error and lower precision in calibrated CO₂ mole fraction. The magnitude of the corrections to δ¹³C and CO₂ 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 δ¹³C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO₂ and δ¹³C 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.

中文翻译：

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在NEON大气碳同位素观测中检测宏观模式的校准策略

陆地生态系统中的碳通量及其对环境变化的响应是现代碳循环中不确定性的主要来源。美国国家生态观测站网络（NEON）提供了将源自涡度协方差（EC）的通量与CO ₂同位素比率测量值相结合的机会，以深入了解碳循环过程。NEON EC和同位素数据在超过40个地点连续不断地收集，有助于进行新颖的整合分析。但是，当前提供的大气同位素数据尚未校准，这极大地限制了进行跨站点分析的能力。在这里，我们介绍了两种校准NEON CO ₂同位素比率的方法，以及用于校准NEON数据的R封装。我们发现校准CO ₂同位素异独立地产生较低的δ ¹³不是直接校正Ç偏压（<0.05‰）和更高的精度（<0.40‰）δ ¹³下用线性回归（偏压：<0.11‰，精度：0.42‰），但具有略微更高的错误和校准的CO ₂摩尔分数的精度较低。更正的幅度δ ¹³ C和CO ₂的摩尔分数由现场显着变化，强调需要用户在归档NEON应用一致的校准框架数据。校准后的数据集显示该网站的年平均δ ¹³C与降水，温度和干旱呈负相关，而与海拔呈正相关。森林和农业生态系统中的CO表现出更大的梯度₂和δ ¹³比其他网站C，尤其是在夏天，晚上。此处开发的概述和分析工具将有助于使用NEON数据进行跨站点分析，为其他大陆尺度的观测网络提供模型，并利用特定碳通量的同位素比实现新的进展。