Landscape and Ecological Engineering

, Volume 15, Issue 2, pp 215–221 | Cite as

Geostatistical estimation of surface soil carbon stock in Mt. Wakakusa grassland of Japan

  • Khairun N. Kamarudin
  • Mayu Tomita
  • Keiko Kondo
  • Susumu S. AbeEmail author
Short Communication


Although nation-wide assessments on the grassland soil carbon storage have been conducted in Japan, the uncertainty of the estimation accuracy remains with its local variability. In the present study, using geostatistical approach, we assessed the spatial variability and distribution pattern of organic carbon (OC) and estimated its total stock in the surface soils (0–5 cm) over Mt. Wakakusa grassland (30.2 ha) of Central Japan. The exploratory statistics indicated that the surface soils had 1.88 ± 0.28 kg C m−2 of soil OC density on average (n = 147) with a moderate variability (CV = 18.8%), while the geostatistical analysis unveiled that its semivariogram was well fitted by a spherical model (R2 = 0.93, RSS = 1.15E−05) and had a strong spatial dependency (nugget–sill ratio = 0.31). Based on these results, we constructed an interpolated map and estimated total OC stock to 552 Mg C in the surface soil of Mt. Wakakusa grassland.


Ordinary kriging Semivariogram Soil organic carbon density 



The present study was carried out on the authority of the Agency for Cultural Affairs and the Nara Prefecture, and was made possible by the financial support from the Japan Society for the Promotion of Science (Kakenhi no. 16K18669). The authors would like to extend their gratitude to the Nara Park Management Office and the colleges at the Laboratory of Ecological Engineering, Kindai University for the assistance during the field survey. Khairun N. Kamarudin enjoyed the scholarship from the Ministry of Education, Culture, Sports, Science and Technology of Japan.


  1. Abe SS, Harada T, Okumura H, Wakatsuki T (2019) Comparing rates of rock weathering and soil formation between two temperate forest watersheds differing in parent rock and vegetation type. Jpn Agric Res Q (in press) Google Scholar
  2. Cambardella CA, Moorman TB, Novak JM et al (1994) Field-scale variability of soil properties in central Iowa soils. Soil Sci Soc Am J 58:1501–1511CrossRefGoogle Scholar
  3. Chilès JP, Delfiner P (2012) Geostatistics: modeling spatial uncertainty, 2nd edn. Wiley, New YorkCrossRefGoogle Scholar
  4. Cobo JG, Dercon G, Yekeye T et al (2010) Integration of mid-infrared spectroscopy and geostatistics in the assessment of soil spatial variability at landscape level. Geoderma 158:398–411CrossRefGoogle Scholar
  5. Cressie N, Hawkins DM (1980) Robust estimation of the variogram. Math Geol 12:115–125CrossRefGoogle Scholar
  6. Davidson A, Csillag F (2003) A comparison of three approaches for predicting C4 species cover of northern mixed grass prairie. Remote Sens Environ 86:70–82CrossRefGoogle Scholar
  7. Fukushima K, Ishii K, Yoshioka T (2017) Effects of deer grazing on soil C and N dynamics in Miscanthus sinensis grassland and Quercus serrata forest in Ashiu research forest, Japan. J For Res 22:309–313Google Scholar
  8. Kamarudin KN, Tomita M, Kondo K, Abe SS (2019) Spatial variability and geostatistical mapping of selected soil properties in Mt. Wakakusa grassland of Japan. Jpn Agric Res Quart (in press) Google Scholar
  9. Kerry R, Oliver MA (2007) Determining the effect of asymmetric data on the variogram. I. Underlying asymmetry. Comput Geosci 33:1212–1232CrossRefGoogle Scholar
  10. Lark RM (2000) A comparison of some robust estimators of the variogram for use in soil survey. Eur J Soil Sci 51:137–157CrossRefGoogle Scholar
  11. Leys C, Ley C, Klein O, Bernard P, Licata L (2013) Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol 49:764–766CrossRefGoogle Scholar
  12. Maesako Y, Nanami S, Kanzaki M (2007) Spatial distribution of two invasive alien species, Podocarpus nagi and Sapium sebiferum, spreading in a warm-temperate evergreen forest of the Kasugayama Forest Reserve, Japan. Veg Sci 24:103–112Google Scholar
  13. Matsuura S, Sasaki H, Kohyama K (2012) Organic carbon stocks in grassland soils and their spatial distribution in Japan. Grassl Sci 58:79–93CrossRefGoogle Scholar
  14. Nakagami K, Hojito M, Itano S et al (2009) Soil carbon stock in typical grasslands in Japan. Grassl Sci 55:96–103CrossRefGoogle Scholar
  15. Olea RA (2006) A six-step practical approach to semivariogram modeling. Stoch Environ Res Risk Assess 20:307–318CrossRefGoogle Scholar
  16. Oliver MA, Webster R (2014) A tutorial guide to geostatistics: computing and modeling and kriging. CATENA 113:56–69CrossRefGoogle Scholar
  17. Pebesma EJ (2004) Multivariable geostatistics in S: the gstat package. Comput Geosci 30:683–691CrossRefGoogle Scholar
  18. Reimann C, Filzmoser P (2000) Normal and lognormal data distribution in geochemistry: death of a myth. Consequences for the statistical treatment of geochemical and environmental data. Environ Geol 39:1001–1014CrossRefGoogle Scholar
  19. Rossi RE, Mulla DJ, Journel AG, Franz EH (1992) Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecol Monogr 62:277–314CrossRefGoogle Scholar
  20. Shimoda S, Takahashi Y (2009) Differences in soil carbon storage due to mowing, burning and uncontrolled management practices of a grassland at the foot of Mount Sanbe, Japan. Grassl Sci 55:175–180CrossRefGoogle Scholar
  21. Spiess AN, Neumeyer N (2010) An evaluation of R 2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach. BMC Pharmacol 10:6CrossRefGoogle Scholar
  22. Takahashi R, Maenaka H (1977) Relationship between recreational densities and vegetational types on the grassland of Wakakusayama Hill, Nara Park. J Jpn Inst Landsc Archit 40(3):24–37 (in Japanese with English summary) CrossRefGoogle Scholar
  23. Tamura K, Higashi T, Nagatsuka S (2001) Soils in Wakakusayama. Grassl Ecol 32(33):25–32 (in Japanese) Google Scholar
  24. Tate KR, Giltrap DJ, Claydon JJ et al (1997) Organic carbon stocks in New Zealand’s terrestrial ecosystems. J R Soc N Z 27:315–335CrossRefGoogle Scholar
  25. Watson RT, Noble IR, Bolin B et al (eds) (2000) Land use, land-use change, and forestry. IPCC Special Report, Cambridge University Press, CambridgeGoogle Scholar
  26. Yamamoto Y, Shindo K, Hagino K et al (2002) Changes in vegetation due to the stopped controlled burns in the semi-natural grassland of Aso region. Grassl Sci 48:416–420 (in Japanese) Google Scholar
  27. Yan X, Cai Z (2008) Number of soil profiles needed to give a reliable overall estimate of soil organic carbon storage using profile carbon density data. Soil Sci Plant Nutr 54:819–825CrossRefGoogle Scholar

Copyright information

© International Consortium of Landscape and Ecological Engineering 2019

Authors and Affiliations

  • Khairun N. Kamarudin
    • 1
  • Mayu Tomita
    • 1
    • 2
  • Keiko Kondo
    • 1
  • Susumu S. Abe
    • 1
    Email author
  1. 1.Faculty of AgricultureKindai UniversityNaraJapan
  2. 2.Graduate School of Life and Environmental SciencesKyoto Prefectural UniversityKyotoJapan

Personalised recommendations