Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.480
IF3.480
IF 5-year value: 4.194
IF 5-year
4.194
CiteScore value: 6.7
CiteScore
6.7
SNIP value: 1.143
SNIP1.143
IPP value: 3.65
IPP3.65
SJR value: 1.761
SJR1.761
Scimago H <br class='widget-line-break'>index value: 118
Scimago H
index
118
h5-index value: 60
h5-index60
Preprints
https://doi.org/10.5194/bg-2020-273
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2020-273
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Aug 2020

12 Aug 2020

Review status
A revised version of this preprint is currently under review for the journal BG.

Estimating maximum mineral associated organic carbon in UK grasslands

Kirsty C. Paterson1,2, Joanna M. Cloy1, Robert M. Rees1, Elizabeth M. Baggs2, Hugh Martineau3, Dario Fornara4, Andrew J. Macdonald5, and Sarah Buckingham1 Kirsty C. Paterson et al.
  • 1Scotland's Rural College, West Mains Road, Edinburgh, EH9 3JG, United Kingdom
  • 2Global Academy of Agricultureand Food Security, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, United Kingdom
  • 3Treberfydd Farm, Wales, United Kingdom
  • 4Agri-Food & Biosciences Institute (AFBI), Newforge Lane, BT9 5PX, Belfast, United Kingdom
  • 5Sustainable Agriculture Sciences Department, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, United Kingdom

Abstract. Soil organic carbon (SOC) sequestration across agroecosystems worldwide can contribute to mitigate the effects of climate change by reducing levels of atmospheric CO2. Mineral associated organic carbon (MAOC) is considered an important long-term store of SOC and the saturation deficit (difference between measured MAOC and estimated maximum MAOC) 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 MAOC in UK grassland soils of varying sward ages and to evaluate the linear regression, BL and QR methods to estimate maximum MAOC. A chronosequence of 10 grasslands was sampled, in order to assess the relationship between sward age (time since last reseeding event) and current and predicted maximum MAOC. Significantly different regression equations show that the Hassink (1997) equation does not accurately reflect maximum MAOC in UK grasslands when determined using the proportion of fine soil fraction and current MAOC. The QR estimate of maximum SOC stabilisation was almost double that of linear regression and BL analysis (0.89 ± 0.074, 0.43 ± 0.017 and 0.57 ± 0.052 g C kg−1 soil, respectively). Sward age had an inconsistent effect on the measured variables and potential maximum MAOC. MAOC 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 mineral fraction of these soils, or stabilisation in aggregates is predominant in these grassland soils. This work highlights the need to ensure that methods used to predict maximum MAOC reflect the soil in situ, resulting in more accurate assessments of carbon sequestration potential.

Kirsty C. Paterson et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Kirsty C. Paterson et al.

Kirsty C. Paterson et al.

Viewed

Total article views: 295 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
214 76 5 295 6 7
  • HTML: 214
  • PDF: 76
  • XML: 5
  • Total: 295
  • BibTeX: 6
  • EndNote: 7
Views and downloads (calculated since 12 Aug 2020)
Cumulative views and downloads (calculated since 12 Aug 2020)

Viewed (geographical distribution)

Total article views: 174 (including HTML, PDF, and XML) Thereof 169 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 23 Nov 2020
Publications Copernicus
Download
Short summary
Soil organic carbon sequestration across agroecosystems worldwide can contribute to mitigate the effects of climate change by reducing levels of atmospheric carbon dioxide. Maximum carbon sequestration potential is frequently estimated using the linear regression equation developed by Hassink (1997). This work examines the suitability of this equation for use in grasslands across the United Kingdom. The results highlight the need to ensure the fit of equations to the soils being studied.
Soil organic carbon sequestration across agroecosystems worldwide can contribute to mitigate the...
Citation
Altmetrics