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Abstract. American bison (Bison bison L.) have recovered from the brink ofextinction over the past century. Bison reintroduction creates multipleenvironmental benefits, but impacts on greenhouse gas emissions are poorlyunderstood. Bison are thought to have produced some 2 Tg yr−1 of theestimated 9–15 Tg yr−1 of pre-industrial enteric methane emissions,but few measurements have been made due to their mobile grazing habits andsafety issues associated with measuring non-domesticated animals. Here, wemeasure methane and carbon dioxide fluxes from a bison herd on an enclosedpasture during daytime periods in winter using eddy covariance. Methaneemissions from the study area were negligible in the absence of bison(mean ± standard deviation = −0.0009 ± 0.008 µmol m−2 s−1) and were significantly greater than zero,0.048 ± 0.082 µmol m−2 s−1, with a positively skeweddistribution, when bison were present. We coupled bison location estimatesfrom automated camera images with two independent flux footprint models tocalculate a mean per-animal methane efflux of 58.5 µmol s−1 per bison, similar to eddy covariance measurements ofmethane efflux from a cattle feedlot during winter. When we sum theobservations over time with conservative uncertainty estimates we arrive at81 g CH4 per bison d−1 with 95 % confidence intervalsbetween 54 and 109 g CH4 per bison d−1. Uncertainty wasdominated by bison location estimates (46 % of the total uncertainty),then the flux footprint model (33 %) and the eddy covariance measurements(21 %), suggesting that making higher-resolution animal location estimatesis a logical starting point for decreasing total uncertainty. Annualmeasurements are ultimately necessary to determine the full greenhouse gasburden of bison grazing systems. Our observations highlight the need tocompare greenhouse gas emissions from different ruminant grazing systems anddemonstrate the potential for using eddy covariance to measure methaneefflux from non-domesticated animals. 

ABSTRACT The lack of energy balance closure in Eddy‐Covariance (EC) measurements is a well‐known, still unresolved challenge in micrometeorology, with energy balance closure (EBC) rates typically ranging between 60% and 80%. While numerous hypotheses have been proposed to explain this imbalance, the relative contributions of neglected energy storage terms, data quality and flux processing options remain insufficiently disentangled. Using standardized ICOS and NEON datasets, we show that a significant portion of the observed energy imbalance can be attributed to overlooked or inconsistently handled energy components and turbulent flux quality control. Using data drawn from 84 sites, we show that comprehensive energy accounting—including soil heat flux, storage terms (soil, air, biomass), photosynthetic energy demand, and strict quality filtering of turbulent fluxes—improved EBC by 16% on average, with site‐specific gains up to 40%. However, we also identify a persistent residual imbalance that is unlikely to be resolved through methodological refinements or additional measurements alone, pointing to fundamental physical processes that are not accounted for in the standard measurement and processing. We argue that this unresolved imbalance should be explicitly acknowledged and bounded, rather than implicitly absorbed into correction schemes, and we outline practical guidance for diagnosing and interpreting EBC in standardized flux networks. This perspective evaluates methodological advances and residual uncertainties, providing an actionable framework for the appropriate use of EC energy fluxes in carbon, water, and climate research. 

Abstract The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features. 

Abstract Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.