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RESEARCH ARTICLE

Scale-dependent correlations between soil properties and environmental factors across the Loess Plateau of China

Zhi-Peng Liu A C , Ming-An Shao B D and Yun-Qiang Wang B
+ Author Affiliations
- Author Affiliations

A State Key Laboratory of Soil Erosion and Dry-land Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences, Ministry of Water Resources, Yangling Shaanxi 712100, P.R. China.

B Key Laboratory of Ecosystem Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R. China.

C Graduate School of Chinese Academy of Sciences, Beijing 100049, P.R. China.

D Corresponding author. Email: shaoma@igsnrr.ac.cn

Soil Research 51(2) 112-123 https://doi.org/10.1071/SR12190
Submitted: 13 July 2012  Accepted: 12 March 2013   Published: 22 April 2013

Abstract

Traditional statistical analysis of the correlations between spatially distributed variables takes no account of their regionalised nature. Factorial kriging analysis (FKA) was developed and widely used to overcome this problem. In our study, we applied FKA to investigate scale-dependent correlations between selected soil properties and environmental factors across the Loess Plateau of China. Surface soil samples were collected from 382 sampling sites throughout the region, and soil organic carbon (SOC), soil total nitrogen (STN), soil total phosphorus (STP), soil total potassium (STK), soil pH, bulk density (BD), and clay and silt contents were determined. Five environmental factors (elevation, precipitation, temperature, land-use type, and soil type) were also included in the FKA to identify influential processes. A linear model of co-regionalisation, including a nugget effect and two spherical structures (effective ranges of 200 and 400 km), was fitted to the experimental auto- and cross-variograms of the variables. Scale-dependent correlations were calculated for nugget-effect scale (<30–50 km), short-range scale with a range of 200 km, and long-range scale with a range of 400 km. Principal component analysis was conducted to clearly illustrate the correlations at each spatial scale. The scale-dependent correlations were different from the general correlations and varied at different scales. Generally, SOC and STN were strongly correlated at the nugget-effect scale and the long-range scale, but not at the short-range scale. Precipitation and clay content showed close correlations with STP at the nugget-effect scale and long-range scale. The STK was weakly correlated with the other variables at each spatial scale, and closely correlated with soil type at the long-range scale. Soil pH was closely correlated with BD, soil type, and elevation at the nugget-effect, short, and long spatial scales, respectively. Close correlations were found between BD and land-use type at each spatial scale. Land use and soil type were considered to be the important factors controlling spatial variation of soil properties at the short-range scale, while at the long-range scale the likely factors were identified as precipitation, temperature, and elevation. Our study provided an insight into the spatial-dependent correlations between soil properties and environmental factors from a regional perspective.

Additional keywords: environmental factors, factorial kriging, Loess Plateau, soil properties, multivariate geostatistics.


References

Abdul-Wahab SA, Bakheit CS, Al-Alawi SM (2005) Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environmental Modelling & Software 20, 1263–1271.
Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations.Crossref | GoogleScholarGoogle Scholar |

Bai Y, Wang Y (2011) Spatial variability of soil chemical properties in a Jujube slope on the Loess Plateau of China. Soil Science 176, 550–558.
Spatial variability of soil chemical properties in a Jujube slope on the Loess Plateau of China.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXht1Cqu7bK&md5=64919b7085f62d97a3302537ae625616CAS |

Bocchi S, Castrignan A, Fornarò F, Maggiore T (2000) Application of factorial kriging for mapping soil variation at field scale. European Journal of Agronomy 13, 295–308.
Application of factorial kriging for mapping soil variation at field scale.Crossref | GoogleScholarGoogle Scholar |

Boon SD (1945) ‘Vlam-Fotmetrie.’ (Centen: Amsterdam)

Bronson KF, Zobeck TM, Chua TT, Acosta-Martinez V, van Pelt RS, Booker JD (2004) Carbon and nitrogen pools of southern high plains and grassland soils. Soil Science Society of America Journal 68, 1695–1704.
Carbon and nitrogen pools of southern high plains and grassland soils.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXns1Smt7o%3D&md5=0081ffb3a9d6deb400d0779f1170527dCAS |

Bremner JM, Tabatabai MA (1972) Use of an ammonia electrode for determination of ammonia in Kjeldahl. Communications in Soil Science and Plant Analysis 3, 159–165.
Use of an ammonia electrode for determination of ammonia in Kjeldahl.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaE38XksVOit7k%3D&md5=63f4c839f387367d1b900020adc9948cCAS |

Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994) Field-scale variability of soil properties in Central Iowa soils. Soil Science Society of America Journal 58, 1501–1511.
Field-scale variability of soil properties in Central Iowa soils.Crossref | GoogleScholarGoogle Scholar |

Caruso JC, Cliff N (1997) Empirical size, coverage, and power of confidence intervals for Spearman’s Rho. Educational and Psychological Measurement 57, 637–654.
Empirical size, coverage, and power of confidence intervals for Spearman’s Rho.Crossref | GoogleScholarGoogle Scholar |

Castrignanò A, Goovaerts P, Lulli L, Bragato G (2000) A geostatistical approach to estimate probability of occurrence of Tuber melanosporum in relation to some soil properties. Geoderma 98, 95–113.
A geostatistical approach to estimate probability of occurrence of Tuber melanosporum in relation to some soil properties.Crossref | GoogleScholarGoogle Scholar |

Committee of Remote Sensing Maps of the Environment and Resources on the Loess Plateau (1992) 1 : 500000 digital soil map of the Loess Plateau region. (Seismological Press: Beijing)

Gao L, Shao MA (2012) The interpolation accuracy for seven soil properties at various sampling scales on the Loess Plateau, China. Journal of Soils and Sediments 12, 128–142.
The interpolation accuracy for seven soil properties at various sampling scales on the Loess Plateau, China.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhtFGitrk%3D&md5=da20a37e5f1ec5beca07e768ab6bd464CAS |

Gong ZT (2003) ‘Chinese Soil Taxonomy: theory, method, practice.’ (Science Press: Beijing)

Goovaerts P (1992) Factorial kriging analysis: a useful tool for exploring the structure of multivariate spatial soil information. Journal of Soil Science 43, 597–619.
Factorial kriging analysis: a useful tool for exploring the structure of multivariate spatial soil information.Crossref | GoogleScholarGoogle Scholar |

Goovaerts P (1999) Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89, 1–45.
Geostatistics in soil science: state-of-the-art and perspectives.Crossref | GoogleScholarGoogle Scholar |

Goovaerts P, Webster R (1994) Scale-dependent correlation between topsoil copper and cobalt concentrations in Scotland. European Journal of Soil Science 45, 79–95.
Scale-dependent correlation between topsoil copper and cobalt concentrations in Scotland.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2cXltVOgsL0%3D&md5=f14a48eff61ee8223dd6cde3059ac861CAS |

Gray JM, Humphreys GS, Deckers JA (2009) Relationships in soil distribution as revealed by a global soil database. Geoderma 150, 309–323.
Relationships in soil distribution as revealed by a global soil database.Crossref | GoogleScholarGoogle Scholar |

Hagedorn F, Spinnler D, Siegwolf R (2003) Increase N deposition retards mineralization of old soil organic matter. Soil Biology & Biochemistry 35, 1683–1692.
Increase N deposition retards mineralization of old soil organic matter.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXosVyiur0%3D&md5=83199141612c3de2ae6aae47eb42a913CAS |

He XB, Li ZB, Hao MD, Tang KL, Zheng FL (2003) Down-scale analysis for water scarcity in response to soil-water conservation on Loess Plateau of China. Agriculture, Ecosystems & Environment 94, 355–361.
Down-scale analysis for water scarcity in response to soil-water conservation on Loess Plateau of China.Crossref | GoogleScholarGoogle Scholar |

Heuvelink GBM, Webster R (2001) Modelling soil variation: past, present and future. Geoderma 100, 269–301.
Modelling soil variation: past, present and future.Crossref | GoogleScholarGoogle Scholar |

Hu W, Shao MA, Wang QJ, Fan J, Horton R (2009) Temporal changes of soil hydraulic properties under different land uses. Geoderma 149, 355–366.
Temporal changes of soil hydraulic properties under different land uses.Crossref | GoogleScholarGoogle Scholar |

Imrie CE, Korre A, Munoz-Melendez G, Thornton I, Durucan S (2008) Application of factorial kriging analysis to the FOREGS European topsoil geochemistry database. The Science of the Total Environment 393, 96–110.
Application of factorial kriging analysis to the FOREGS European topsoil geochemistry database.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXitFarsb8%3D&md5=ca4db0dac0abfa621b18f34a02e32830CAS | 18222529PubMed |

Integrated Survey Team of Chinese Academy of Sciences on the Loess Plateau (1991) ‘Soil resources and its rational use on the Loess Plateau.’ pp. 171–173. (Chinese Science and Technology Press: Beijing)

Jenny (1941) ‘Factors of soil formation: a system of quantitative pedology.’ (McGraw-Hill: New York) (Reprinted by Dover Publications: New York)

Jia XX, Shao MA, Wei XR, Horton R, Li XZ (2011) Estimating total net primary productivity of managed grasslands by a state-space modeling approach in a small catchment on the Loess Plateau, China. Geoderma 160, 281–291.
Estimating total net primary productivity of managed grasslands by a state-space modeling approach in a small catchment on the Loess Plateau, China.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXit1KktA%3D%3D&md5=520af55db59a8570ff44ff9e95f4e62fCAS |

Li YS, Huang MB (2008) Pasture yield and soil water depletion of continuous growing alfalfa in the Loess Plateau of China. Agriculture, Ecosystems & Environment 124, 24–32.
Pasture yield and soil water depletion of continuous growing alfalfa in the Loess Plateau of China.Crossref | GoogleScholarGoogle Scholar |

Lin JS, Shi XZ, Lu XX, Yu DS, Wang HJ, Zhao YC, Sun WX (2009) Storage and spatial variation of phosphorus in paddy soils of China. Pedosphere 19, 790–798.
Storage and spatial variation of phosphorus in paddy soils of China.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsFOmtbvI&md5=6fa3bcd546bcb6cd0e3f4dd453d56f8bCAS |

Liu G (1999) Soil conservation and sustainable agriculture on the Loess Plateau: challenges and prospects. Ambio 28, 663–668.

Liu ZP, Shao MA, Wang YQ (2011) Effect of environmental factors on regional soil organic carbon stocks across the Loess Plateau region, China. Agriculture, Ecosystems & Environment 142, 184–194.
Effect of environmental factors on regional soil organic carbon stocks across the Loess Plateau region, China.Crossref | GoogleScholarGoogle Scholar |

Matheron G (1963) Principles of geostatistics. Economic Geology and the Bulletin of the Society of Economic Geologists 58, 1246–1266.
Principles of geostatistics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaF2cXltFKiug%3D%3D&md5=a7aabaf85451a80b3c67ca618f47d583CAS |

McBratney AB, Webster R (1986) Choosing functions for semivariograms of soil properties and fitting them to sampling estimates. Journal of Soil Science 37, 617–639.
Choosing functions for semivariograms of soil properties and fitting them to sampling estimates.Crossref | GoogleScholarGoogle Scholar |

McLean EO (1982) Soil pH and lime requirement. In ‘Methods of soil analysis. Part 2’. 2nd edn. Agronomy Monograph Vol. 9. (Eds AL Page, RH Miller, DR Keeney) pp. 199–224. (ASA and SSSA: Madison, WI)

Meersmans J, Wesemael BV, Molle MV (2009) Determining soil organic carbon for agricultural soils: a comparison between the Walkley-Black and the dry combustion methods (north Belgium). Soil Use and Management 25, 346–353.
Determining soil organic carbon for agricultural soils: a comparison between the Walkley-Black and the dry combustion methods (north Belgium).Crossref | GoogleScholarGoogle Scholar |

Murphy J, Riley JP (1962) A modified single solution method for the determination of phosphate in natural water. Analytica Chimica Acta 27, 31–36.
A modified single solution method for the determination of phosphate in natural water.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaF38XksVyntr8%3D&md5=603c87a43a9461fcfd5e49e620af594bCAS |

Nelson DW, Sommers LE (1982) Total carbon, organic carbon and organic matter. In ‘Methods of soil analysis, Part 2’. 2nd edn. Agronomy Monograph Volume 9. (Eds AL Page, RH Miller, DR Keeney) pp. 534–580. (ASA and SSSA: Madison, WI)

Nielsen DR, Bouma J (1985) ‘Soil spatial variability.’ (Pudoc: Wageningen, the Netherlands)

Ostwald M, Chen D (2006) Land-use change: Impacts of climate variation and policies among small-scale farmers in the Loess Plateau, China. Land Use Policy 23, 361–371.
Land-use change: Impacts of climate variation and policies among small-scale farmers in the Loess Plateau, China.Crossref | GoogleScholarGoogle Scholar |

Pebesma EJ (2004) Multivariable geostatistics in S: the gstat package. Computers & Geosciences 30, 683–691.
Multivariable geostatistics in S: the gstat package.Crossref | GoogleScholarGoogle Scholar |

Qiu Y, Fu BJ, Wang J, Chen LD (2001) Spatial variability of soil moisture content and its relation to environmental indices in a semi-arid gully catchment of the Loess Plateau, China. Journal of Arid Environments 49, 723–750.
Spatial variability of soil moisture content and its relation to environmental indices in a semi-arid gully catchment of the Loess Plateau, China.Crossref | GoogleScholarGoogle Scholar |

R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available at: www.R-project.org/

Rodgers SE, Oliver MA (2007) A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation. Geographical Analysis 39, 195–216.
A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation.Crossref | GoogleScholarGoogle Scholar |

Saporta A (1990) ‘Probabilités, Analyse des Données et Statistique.’ (Technip: Paris)

Shi H, Shao MA (2000) Soil and water loss from the Loess Plateau in China. Journal of Arid Environments 45, 9–20.
Soil and water loss from the Loess Plateau in China.Crossref | GoogleScholarGoogle Scholar |

Tan ZX, Lal R, Smeck NE, Calhoun FG (2004) Relationship between surface soil organic carbon pool and site variables. Geoderma 121, 187–195.
Relationship between surface soil organic carbon pool and site variables.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXlsFWqtLc%3D&md5=737124084fae2794f7304cd678facd9dCAS |

Tang KL (1991) ‘Soil erosion on the Loess Plateau: Its regional distribution and control.’ (China Sciences and Technology Press: Beijing)

Trangmar BB, Yost RS, Uehara G (1986) Application of geostatistics to spatial studies of soil properties. Advances in Agronomy 38, 45–94.
Application of geostatistics to spatial studies of soil properties.Crossref | GoogleScholarGoogle Scholar |

van Meirvenne M, Goovaerts P (2002) Accounting for spatial dependence in the processing of multi-temporal SAR images using factorial kriging. International Journal of Remote Sensing 23, 371–387.
Accounting for spatial dependence in the processing of multi-temporal SAR images using factorial kriging.Crossref | GoogleScholarGoogle Scholar |

Wackernagel H (1998) ‘Multivariate geostatistics.’ 2nd edn (Springer-Verlag: Berlin)

Wang YQ, Zhang XC, Huang CQ (2009) Spatial variability of soil total nitrogen and soil total phosphorus under different land uses in a small watershed on the Loess Plateau, China. Geoderma 150, 141–149.
Spatial variability of soil total nitrogen and soil total phosphorus under different land uses in a small watershed on the Loess Plateau, China.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXjt1Kis7g%3D&md5=bd48765c45097c946ae3de7e40dff0f4CAS |

Wang YQ, Shao MA, Zhu YJ, Liu ZP (2011) Impact of land use and plant characteristics on dried soil layers in different climatic regions on the Loess Plateau of China. Agricultural and Forest Meteorology 151, 437–448.
Impact of land use and plant characteristics on dried soil layers in different climatic regions on the Loess Plateau of China.Crossref | GoogleScholarGoogle Scholar |

Webster R, Atteia O, Dubois JP (1994) Coregionalization of trace metal in the soil in the Swiss Jura. European Journal of Soil Science 45, 205–218.
Coregionalization of trace metal in the soil in the Swiss Jura.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2cXmt12ltLw%3D&md5=0196a9fb3daf3232302f71ca569d070eCAS |

Xu S, Tao S (2004) Coregionalisation analysis of heavy metals in the surface soil of Inner Mongolia. The Science of the Total Environment 320, 73–87.
Coregionalisation analysis of heavy metals in the surface soil of Inner Mongolia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhsV2mu7Y%3D&md5=a185490fb547fb14985c3dcd6088cb9fCAS | 14987928PubMed |

Yang WZ, Shao MA (2000) ‘Soil water research on the Loess Plateau.’ (Science Press: Beijing) [in Chinese with English abstract]

Zhang C, Selinus O, Kjellstrom G (1999) Discrimination between natural background and anthropogenic pollution in environmental geochemistry – exemplified in an area of south-eastern Sweden. The Science of the Total Environment 243–244, 129–140.
Discrimination between natural background and anthropogenic pollution in environmental geochemistry – exemplified in an area of south-eastern Sweden.Crossref | GoogleScholarGoogle Scholar |

Zhao JB, Huang CC, Zhu XM (1999) Formation and development of Loess Plateau. Journal of Desert Research 19, 333–337. [in Chinese with English abstract]