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Purpose The estimations of greenhouse gas (GHG) field emissions from fertilization and soil carbon changes are challenges associated with calculating the carbon footprint (CFP) of agricultural products. At the regional level, the IPCC Guidelines for National Greenhouse Gas Inventories (2006a) Tier 1 approach, based on default emission factors, insufficiently accounts for emission variability resulting from pedo-climatic conditions or management practices. However, Tier 2 and 3 approaches are usually considered too complex to be practicable. In this paper, we discuss different readily available medium-effort methods to improve the accuracy of GHG emission estimates. Methods We present four case studies-two wheat crops in Germany and two peach orchards in Italy-to test the performance of Tier 1, 2, and 3 methodologies and compare the estimated results with available field measurements. The methodologies selected at Tier 2 and Tier 3 level are characterized by simple implementation and data collection, for which only a medium level of effort for stakeholders is required. The Tier 2 method consists of calculating direct and indirect N 2 O, emissions from fertilization with a multivariate empirical model which accounts for pedo-climatic and crop management conditions. The Tier 3 method entails simulation of soil carbon stock change using the Rothamsted carbon model. Results and discussion Relevant differences were found among the tested methodologies: in all case studies, the Tier 1 approach exceeded the Tier 2 estimations for fertilizer-induced emissions (up to +50 %) and the measurements. Using this higher Tier approach reduced the estimated CFP calculation of annual crops by 4 and 21 % and that of the perennial crop by 7 %. Removals related to positive soil carbon change calculated using the Tier 1 approach also exceeded the Tier 3 calculations for the studied annual crops (up to +90 %) but considerably underrated the Tier 3 estimations and measurements for perennial crops (−75 %). In this case, the impact of the selected Tier method on the final CFP results was even more relevant: an increase of 194 and 88 % for the studied annual crops and a decrease of 67 % for the perennial crop case study. Conclusions The use of higher Tiers for the estimation of land-based emissions is strongly recommended to improve the accuracy of the CFP results. The suggested mediumeffort methods tested in this study represent a good compromise between complexity reduction and accuracy improvement and can be considered reliable for the assessment of GHG mitigation potentials.

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Deadwood (woody debris (WD), standing dead trees (snags), stumps, and buried deadwood) abundance was estimated in Labrador humid high-boreal black spruce (Picea mariana (Mill.) BSP) forests regrown following natural and anthropogenic disturbances. Aboveground deadwood (DW) abundance in Labrador was similar to values observed in other boreal forests experiencing drier or warmer climates. Clear-cut harvest generated large amounts of WD, which had almost completely decomposed 34–36 years following harvesting, with a fitted volume reduction rate of –0.058 year–1. Total WD in all harvested stands was composed of predominantly <10 cm pieces, which should be included in DW inventories of disturbed coniferous boreal forests. Postfire WD likely peaked ∼20 years following disturbance, as a result of the collapse of snags, and was dominated by large amounts of medium-sized logs (10.0–19.9 cm). Buried DW stocks considerably exceeded total aboveground DW stocks in old-growth, middle-aged, and older harvested stands. Old-growth stands contained 179.3 m3·ha–1 of buried DW, a vast amount indicative of long-term accumulation requiring significantly depressed rates of WD decomposition following burial. DW stocks could be significantly underestimated if buried DW is excluded from DW inventories in cool and moist coniferous forests with long fire-return intervals.

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Manual closed‐chamber measurements are commonly used to quantify annual net CO2 ecosystem exchange (NEE) in a wide range of terrestrial ecosystems. However, differences in both the acquisition and gap filling of manual closed‐chamber data are large in the existing literature, complicating inter‐study comparisons and meta analyses. The aim of this study was to compare common approaches for quantifying CO2 exchange at three methodological levels. (1) The first level included two different CO2 flux measurement methods: one via measurements during mid‐day applying net coverages (mid‐day approach) and one via measurements from sunrise to noon (sunrise approach) to capture a span of light conditions for measurements of NEE with transparent chambers. (2) The second level included three different methods of pooling measured ecosystem respiration (RECO) fluxes for empirical modeling of RECO: campaign‐wise (19 single‐measurement‐day RECO models), season‐wise (one RECO model for the entire study period), and cluster‐wise (two RECO models representing a low and a high vegetation status). (3) The third level included two different methods of deriving fluxes of gross primary production (GPP): by subtracting either proximately measured RECO fluxes (direct GPP modeling) or empirically modeled RECO fluxes from measured NEE fluxes (indirect GPP modeling). Measurements were made during 2013–2014 in a lucerne‐clover‐grass field in NE Germany. Across the different combinations of measurement and gap‐filling options, the NEE balances of the agricultural field diverged strongly (–200 to 425 g CO2‐C m−2). NEE balances were most similar to previous studies when derived from sunrise measurements and indirect GPP modeling. Overall, the large variation in NEE balances resulting from different data‐acquisition or gap‐filling strategies indicates that these methodological decisions should be made very carefully and that they likely add to the overall uncertainty of greenhouse gas emission factors. Preferably, a standard approach should be developed to reduce the uncertainty of upscaled estimates.