Abstract
Abstract. Soil organic carbon (SOC) sequestration across agroecosystems worldwide can contribute to mitigate the effects of climate change by reducing levels of atmospheric CO2. Stabilisation of organic carbon (OC) in the fine soil fraction (< 20 µm) is considered an important long-term store of SOC, and the saturation deficit (difference between measured OC and estimated maximum OC in the fine fraction) is frequently used to assess SOC sequestration potential following the linear regression equation developed by Hassink (1997). However, this approach is often taken without any assessment of the fit of the equation to the soils being studied. The statistical limitations of linear regression have previously been noted, giving rise to the proposed use of boundary line (BL) analysis and quantile regression (QR) to provide more robust estimates of maximum SOC stabilisation. The objectives of this work were to assess the suitability of the Hassink (1997) equation to estimate maximum fine-fraction OC in UK grassland soils of varying sward ages and to evaluate the linear regression, boundary line and quantile regression methods to estimate maximum fine-fraction OC. A chronosequence of 10 grasslands was sampled, in order to assess the relationship between sward age (time since the last reseeding event) and the measured and predicted maximum fine-fraction OC. Significantly different regression equations show that the Hassink (1997) equation does not accurately reflect maximum fine-fraction OC in UK grasslands when determined using the proportion of the fine soil fraction (< 20 µm, %) and measured fine-fraction OC (g C per kg soil). The QR estimate of maximum SOC stabilisation was almost double that of the linear regression and BL analysis (0.89 ± 0.074, 0.43 ± 0.017 and 0.57 ± 0.052 g C per kg soil, respectively). Sward age had an inconsistent effect on the measured variables and potential maximum fine-fraction OC. Fine-fraction OC across the grasslands made up 4.5 % to 55.9 % of total SOC, implying that there may be either high potential for additional C sequestration in the fine fraction of these soils or that protection in aggregates is predominant in these grassland soils. This work highlights the need to ensure that methods used to predict maximum fine-fraction OC reflect the soil in situ, resulting in more accurate assessments of carbon sequestration potential.
Highlights
Carbon (C) sequestration in soils offers a significant opportunity to remove CO2 from the atmosphere and store it in long-lived C pools (Lal, 2004; Powlson et al, 2011), with cobenefits for soil structure and functioning (Lorenz and Lal, 2018; Smith, 2012; Soussana et al, 2004)
The proportion of organic carbon (OC) stabilised in the fine fraction (< 20 μm) had high variability across the UK sites accounting for 4.5 % to 50.1 % of total soil organic carbon (SOC) with a median of 17.5 %
The proportion of total SOC stabilised in the fine fraction was not consistently higher in the oldest field and, in some instances, was significantly less, such as at Aberystwyth (Table A2)
Summary
Carbon (C) sequestration in soils offers a significant opportunity to remove CO2 from the atmosphere and store it in long-lived C pools (Lal, 2004; Powlson et al, 2011), with cobenefits for soil structure and functioning (Lorenz and Lal, 2018; Smith, 2012; Soussana et al, 2004). With respect to soil organic carbon (SOC) sequestration, organic carbon (OC) stabilised via adsorption to mineral surfaces in the fine soil fraction (< 20 μm) is often regarded as the most important due to its Published by Copernicus Publications on behalf of the European Geosciences Union. Paterson et al.: Estimating maximum fine-fraction organic carbon in UK grasslands longer residence time (Baldock and Skjemstad, 2000; Six et al, 2002). Potential SOC sequestration (or saturation deficit) can be estimated by subtracting the current fine-fraction OC from the estimated maximum fine-fraction OC (Angers et al, 2011)
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call