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Plant-atmosphere exchange fluxes of CO2 measured with the Eddy covariance method are used extensively for the assessment of ecosystem carbon budgets worldwide. The present paper describes eddy flux measurements for a managed upland grassland in Central France studied over two decades (2003–2021). We present the site meteorological data for this measurement period, and we describe the pre-processing and post-processing approaches used to overcome issues of data gaps, commonly associated with long-term EC datasets. Recent progress in eddy flux technology and machine learning now paves the way to produce robust long-term datasets, based on normalised data processing techniques, but such reference datasets remain rare for grasslands. Here, we combined two gap-filling techniques, Marginal Distribution Sampling (short gaps) and Random Forest (long gaps), to complete two reference flux datasets at the half-hour and daily-scales respectively. The resulting datasets are valuable for assessing the response of grassland ecosystems to (past) climate change, but also for model evaluation and validation with respect to future global change research with the carbon-cycle community. [ABSTRACT FROM AUTHOR]

Many studies have assessed the potential of agricultural practices to sequester carbon (C). A comprehensive evaluation of impacts of agricultural practices requires not only considering C storage but also direct and indirect emissions of greenhouse gases (GHG) and their side effects (e.g., on the water cycle or agricultural production). We used a high‐resolution modeling approach with the Simulateur mulTIdisciplinaire pour les Cultures Standard soil‐crop model to quantify soil organic C (SOC) storage potential, GHG balance, biomass production and nitrogen‐ and water‐related impacts for all arable land in France for current cropping systems (baseline scenario) and three mitigation scenarios: (i) spatial and temporal expansion of cover crops, (ii) spatial insertion and temporal extension of temporary grasslands (two sub‐scenarios) and (iii) improved recycling of organic resources as fertilizer. In the baseline scenario, SOC decreased slightly over 30 years in crop‐only rotations but increased significantly in crop/temporary grassland rotations. Results highlighted a strong trade‐off between the storage rate per unit area (kg C ha−1 year−1) of mitigation scenarios and the areas to which they could be applied. As a result, while the most promising scenario at the field scale was the insertion of temporary grassland (+466 kg C ha−1 year−1 stored to a depth of 0.3 m compared to the baseline, on 0.68 Mha), at the national scale, it was by far the expansion of cover crops (+131 kg C ha−1 year−1, on 17.62 Mha). Side effects on crop production, water irrigation and nitrogen emissions varied greatly depending on the scenario and production situation. At the national scale, combining the three mitigation scenarios could mitigate GHG emissions of current cropping systems by 54% (−11.2 from the current 20.5 Mt CO2e year−1), but the remaining emissions would still lie far from the objective of C‐neutral agriculture. [ABSTRACT FROM AUTHOR]

The agriculture, forestry and other land use sector are responsible for 24% (10–12 Pg CO 2 e per year) of anthropogenic greenhouse gas (GHG) emissions worldwide, with concomitant opportunities for mitigation. A scientific panel used deliberative methods to identify ten technical measures comprising 26 sub-measures to reduce GHG emissions from agriculture in France. Their abatement potential and cost are compared. The proposed measures concern nitrogen (N) management, management practices that increase carbon stocks in soils and biomass, livestock diets, and energy production and consumption on farms. Results show that the total abatement potential can be divided into three parts. One third of the cumulated abatement potential corresponds to sub-measures that can be implemented at a negative technical cost. These sub-measures focus on increased efficiency in input use including N fertilisers, animal feed and energy. The second third are sub-measures with moderate cost (<€25 per metric Mg of avoided CO 2 e). These sub-measures require specific investments or changes to cropping systems, but additional costs or lower incomes are partially compensated for by a reduction in other costs or by the production of other marketable products. The remaining third are high-cost sub-measures (>€25 per metric Mg of avoided CO 2 e). These require investment with no direct financial return, the purchase of particular inputs, dedicated labour time or involve production losses. Assuming additivity, the cumulated abatement is 32.3 Tg CO 2 e per year in 2030, but only 10 Tg (i.e. 10% of current agricultural emissions) when calculated under current inventory rules. This study confirms that a significant abatement potential exists in the agricultural sector, with two thirds of this potential at low or even negative cost. This is likely to be an underestimated as it is based on a status quo of the current agricultural system. Results also emphasise the need to upgrade inventory rules so that efforts to reduce emissions can be accounted for. [ABSTRACT FROM AUTHOR]

• Twenty-three models estimated carbon fluxes in croplands and grasslands worldwide. • Vegetation data were needed as a minimum data requirement for model calibration. • C flux simulation improved with a multi-model approach (multi-model median). Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO 2 , and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (Int C = -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods). [ABSTRACT FROM AUTHOR]