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Soil, land care and environmental research
RESEARCH ARTICLE

Towards cost-effective estimation of soil carbon stocks at the field scale

K. Singh A E , B. W. Murphy B and B. P. Marchant C D
+ Author Affiliations
- Author Affiliations

A Faculty of Agriculture and Environment, University of Sydney, Sydney, NSW 2006, Australia.

B Office of Environment and Heritage, Cowra, NSW 2794, Australia.

C Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK.

D Current address: British Geological Survey, Keyworth, Nottingham, NG12 5GG, UK.

E Corresponding author. Email: kanika.singh@sydney.edu.au

Soil Research 50(8) 672-684 https://doi.org/10.1071/SR12119
Submitted: 10 May 2012  Accepted: 1 January 2013   Published: 5 February 2013

Abstract

Accurate estimates of soil carbon stocks at the field scale are required to run market-based instruments for soil carbon, but the soil measurements required to make these estimates are expensive. Therefore, efficient sample designs are required. We explored the costs associated with estimating the mean soil carbon stocks within a 68-ha field on the old alluvial soils of the Macquarie River in central-west New South Wales (Red Chromosols or Red Luvisols). The sampling required to achieve a particular degree of accuracy depends upon the variability of soil carbon within the field. We conducted a 100-site geostatistical survey to estimate the variogram of soil carbon. We then used this variogram to consider the efficiency with which simple random and stratified sample designs can achieve a standard error <2 t/ha for the mean carbon stock to 30 cm. The stratifications considered were either purely spatial or based upon auxiliary information such as landform or sensor data. The effectiveness of localised clustering or quadrats within designs was also considered. Formulae were devised to determine the costs of implementing the different designs, based upon our experience from conducting the geostatistical survey. Only weak correlations between carbon stocks and the auxiliary information were evident, and hence the stratifications were largely ineffective. Some benefits of using quadrats were evident, since analytical and field survey costs were reduced. However, the cost (AU$2500) required to achieve the target accuracy is still considerable. The sampled field has complex pedology, and we therefore expect that these costs are larger than average. Similar studies are required to calculate sampling requirements in different locations and to determine whether these requirements can be related to factors such as soil type, parent material, or land management history.

Additional keywords: costs, measurement, paddock scale, soil carbon, uncertainty.


References

Allen DE, Pringle MJ, Page KL, Dalal RC (2010) A review of sampling designs for the measurement of soil organic carbon in Australian grazing lands. The Rangeland Journal 32, 227–246.
A review of sampling designs for the measurement of soil organic carbon in Australian grazing lands.Crossref | GoogleScholarGoogle Scholar |

Bock M, Böhner J, Conrad O, Köthe R, Ringeler A (2007) Methods for creating functional soil databases and applying digital soil mapping with SAGA GIS. In ‘Status and prospect of soil information in south-eastern Europe: soil databases, projects and applications’. EUR 22646. (Eds T Hengl, P Panagos, A Jones, G Toth) pp. 149–162. (EN Scientific and Technical Research Series, Office for Official Publications of the European Communities: Luxemburg)

Bowman G, Chapman GA, Murphy BW, Wilson BR, Jenkins BR, Koen T, Gray JM, Morand DT, Atkinson G, Murphy C, Murrell A, Milford HB (2009) ‘Protocols for soil condition and land capability monitoring.’ NSW Natural Resources Monitoring, Evaluation and Reporting Program. (Department of Environment, Climate Change and Water NSW: Sydney) Available at: www.environment.nsw.gov.au/resources/soils/SoilsProtocols.pdf

Bricklemyer RS, Miller PR, Paustian K, Keck T, Nielsen GA, Antle JM (2005) Soil organic carbon variability and sampling optimization in Montana dryland wheat fields. Journal of Soil and Water Conservation 60, 42–51.

Brus DJ, Spatjens LEEM, Gruijter JJ (1999) A sampling scheme for estimating the mean extractable phosphorus concentration of fields for environmental regulation. Geoderma 89, 129–148.
A sampling scheme for estimating the mean extractable phosphorus concentration of fields for environmental regulation.Crossref | GoogleScholarGoogle Scholar |

Conant RT, Paustian K (2002) Spatial variability of soil organic carbon in grasslands: implications for detecting change at different scales. Environmental Pollution 116, S127–S135.
Spatial variability of soil organic carbon in grasslands: implications for detecting change at different scales.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XhsFCh&md5=d7cc99d046df78b0ff4a3737578d30c7CAS |

Davis AA, Stolt MH, Compton JE (2004) Spatial distribution of soil carbon in southern New England hardwood forest landscapes. Soil Science Society of America Journal 68, 895–903.
Spatial distribution of soil carbon in southern New England hardwood forest landscapes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXktV2gurw%3D&md5=e543d98e3e23b151d310dfd39f8ef296CAS |

de Gruijter J, Brus D, Bierkens M, Knotters M (2006) ‘Sampling for natural resource monitoring.’ (Springer-Verlag: Berlin)

Domburg P, de Gruijter JJ, Brus DJ (1994) A structured approach to designing soil sampling schemes with prediction of sampling error from variograms. Geoderma 62, 151–164.
A structured approach to designing soil sampling schemes with prediction of sampling error from variograms.Crossref | GoogleScholarGoogle Scholar |

Duncan D, Wooldridge A, Brennan N, Agar B, Murphy B, Welch A, Andersson K, Kellett J, Lawrie J, Kew G, Andersson K (2008) Soil Information Package, Nyngan 1 : 250 000 Sheet. Central West Catchment Management Authority and NSW Department of Environment and Climate Change.

Goidts E, Van Wesemael B, Crucifix M (2009) Magnitude and sources of uncertainties in soil organic carbon (SOC) stock assessments at various scales. European Journal of Soil Science 60, 723–739.
Magnitude and sources of uncertainties in soil organic carbon (SOC) stock assessments at various scales.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXht1ylsLbL&md5=a62577324c7061d5385466108614d26bCAS |

Holmes KW, Wherret A, Keating A, Murphy DV (2011) Meeting bulk density sampling requirements efficiently to estimate soil carbon stocks. Soil Research 49, 680–695.
Meeting bulk density sampling requirements efficiently to estimate soil carbon stocks.Crossref | GoogleScholarGoogle Scholar |

Huang X, Senthilkumar S, Kravchenko A, Thelen K, Qi J (2007) Total carbon mapping in glacial till soils using near-infrared spectroscopy, Landsat imagery and topographical information. Geoderma 141, 34–42.
Total carbon mapping in glacial till soils using near-infrared spectroscopy, Landsat imagery and topographical information.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXosVSju7s%3D&md5=68a1f1b15ea3f1e4977f1f9c96d41ac2CAS |

Knowles TA, Singh B (2003) Carbon storage in cotton soils of northern NSW. Australian Journal of Soil Research 41, 889–903.
Carbon storage in cotton soils of northern NSW.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXnt1Crt74%3D&md5=5c8c68cc474cce50a134741dd88490aeCAS |

Kravchenko AN, Robertson GP, Bullock DG (2006) Management practice effects on surface total carbon: Differences in spatial variability patterns. Agronomy Journal 98, 1559–1568.

Lachlan Catchment Management Authority (2011) Soil Carbon Pilot Project. Lachlan Catchment Management Authority, NSW, Australia. Available at: www.lachlan.cma.nsw.gov.au/downloads/Soil_Carbon_Pilot/Fact_Sheets/Fact_Sheet_1_Soil_Carbon_Pilot_Overview.pdf, and www.lachlan.cma.nsw.gov.au/downloads/Soil_Carbon_Pilot/Fact_Sheets/Fact_Sheet_3_Soil_Carbon_calculations_for_the_pilot.pdf

Lark RM (2009) Estimating the regional mean status and change of soil properties: two distinct objectives for soil survey. European Journal of Soil Science 60, 748–756.
Estimating the regional mean status and change of soil properties: two distinct objectives for soil survey.Crossref | GoogleScholarGoogle Scholar |

McKenzie N, Ryan P, Fogarty P, Wood J (2000) Sampling, measurement and analytical protocols for carbon estimation in soil, litter and coarse woody debris. National Carbon Accounting System Technical Report No. 14, Australian Greenhouse Office, Canberra.

Miklos M, Short MG, McBratney AB, Minasny B (2010) Mapping and comparing the distribution of soil carbon under cropping and grazing management practices in Narrabri, north west NSW. Australian Journal of Soil Research 48, 248–257.
Mapping and comparing the distribution of soil carbon under cropping and grazing management practices in Narrabri, north west NSW.Crossref | GoogleScholarGoogle Scholar |

Minty B, Franklin R, Milligan P, Richardson M, Wilford J (2009) The radiometric map of Australia. Exploration Geophysics 40, 325–333.
The radiometric map of Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsFagsbrP&md5=17da25e842ad865fe21f12fd70b621f0CAS |

Murphy B, Badgery W, Simmons A, Rawson A, Warden E, Andersson K (2013) Soil testing protocols at the paddock scale for contracts and audits. Market Based Instruments for Soil Carbon (CAMBI). Version 5.3. New South Wales Department of Primary Industries, Orange, Australia.

Qin C-Z, Zhu A-X, Qiu W-L, Lu Y-J, Li B-L, Pei T (2012) Mapping soil organic matter in small low-relief catchments using fuzzy slope position information. Geoderma 171–172, 64–74.
Mapping soil organic matter in small low-relief catchments using fuzzy slope position information.Crossref | GoogleScholarGoogle Scholar |

Sanderman J, Farquhason R, Baldock J (2010) Soil carbon sequestration potential: A review for Australian agriculture. Report for the Australian Department of Climate Change and Energy and Efficiency. CSIRO, Division of Land and Water, Urrbrae, S. Aust.

Shukla MK, Slater BK, Lal R, Cepuder P (2004) Spatial variability of soil properties and potential management classification of a chernozemic field in Lower Austria. Soil Science 169, 852–860.
Spatial variability of soil properties and potential management classification of a chernozemic field in Lower Austria.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXis1Sjug%3D%3D&md5=35c7a6d0e18e31ed55be44a8094fb347CAS |

Simbahan GC, Dobermann A, Goovaerts P, Ping JL, Haddix ML (2006) Fine resolution mapping of soil carbon based on multivariate secondary data. Geoderma 132, 471–489.
Fine resolution mapping of soil carbon based on multivariate secondary data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XksFaqtr8%3D&md5=fe80a63fec52566500868203279dbabcCAS |

Walvoort DJJ, Brus DJ, de Gruijter JJ (2010) An R package for spatial coverage sampling and random sampling from compact geographical strata by k-means. Computers & Geosciences 36, 1261–1267.
An R package for spatial coverage sampling and random sampling from compact geographical strata by k-means.Crossref | GoogleScholarGoogle Scholar |

Webster R, Oliver MA (2007) ‘Geostatistics for environmental scientists.’ (Wiley: Chichester, UK)

WRB (2006) ‘World reference base for soil resources 2006.’ 2nd edn. IUSS Working Group. World Soil Resources Reports No. 103. (FAO: Rome)