Distinguishing spatially correlated random variation in soil from a 'pure nugget' process

Geoderma

Volumn 185-186, Issue , 2012, Pages 102-109

  Lark, R M ^a  

^a BRITISH GEOLOGICAL SURVEY   (United Kingdom)

Author keywords

Linear mixed model; Log likelihood ratio; Nugget; Spatial dependence

Indexed keywords

CLASS MEAN; COVARIATES; ENGLAND; FIXED EFFECTS; FULL MODEL; KRIGING; LIKELIHOOD-RATIO TEST; LINEAR MIXED MODELS; LOG LIKELIHOOD-RATIO; MONTE CARLO SIMULATION; NUGGET; NUGGET-EFFECT; NULL MODEL; ORGANIC CARBON CONTENTS; RANDOM EFFECTS; RANDOM VARIATION; SAMPLING DISTRIBUTION; SAMPLING SCHEMES; SOIL MAP UNITS; SOIL SAMPLING; SOIL VARIATION; SPATIAL ANALYSIS; SPATIAL DEPENDENCE; SPATIAL PREDICTION;

MONTE CARLO METHODS; RANDOM PROCESSES; SOILS;

IMPORTANCE SAMPLING;

KRIGING; MONTE CARLO ANALYSIS; NUMERICAL MODEL; ORGANIC CARBON; SAMPLING; SOIL ANALYSIS; SOIL CARBON; SOIL DYNAMICS; SOIL ORGANIC MATTER; SPATIAL ANALYSIS; SUBSOIL; TOPSOIL;

ENGLAND; UNITED KINGDOM;

EID: 84861337165     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2012.03.029     Document Type: Article

References (29)

1. Akaike H. Information theory and an extension of the maximum likelihood principle. Second International Symposium on Information Theory 1973, 267-281. Akademiai Kiado, Budapest. B.N. Petrov, F. Csaki (Eds.).
2. Burgess T.M., Webster R. Optimal interpolation and isarithmic mapping of soil properties. I. The semi-variogram and punctual kriging. Journal of Soil Science 1980, 31:315-331.
3. Clayden B., Hollis J.M. Criteria for Differentiating Soil Series. Soil Survey of England and Wales Technical Monograph 1984, 17. Soil Survey of England and Wales, Harpenden.
4. Cox D.R., Hinkley D.V. Theoretical Statistics 1990, Chapman & Hall, London.
5. de Gruijter J., Brus D., Biekens M.F.P., Knotters M. Sampling for Natural Resource Monotoring 2006, Springer, Heidelberg.
6. Diggle P.J., Ribeiro P.J. Model-based geostatistics 2007, Springer, New York.
7. Haskard, K.A., 2007. An anisotropic Matérn spatial covariance model: REML estimation and properties. Ph.D. Thesis, University of Adelaide. http://hdl.handle.net/2440/47972.
8. Hassink J., Whitmore A.P. A model of the physical protection of organic matter in soils. Soil Science Society of America Journal 1997, 61:131-139.
9. Hodgson J.M. Soil Survey Field Handbook. Soil Survey of England and Wales Technical Monograph 1976, 5. Soil Survey of England and Wales, Harpenden.
10. IUSS Working Group W.R.B. World Reference Base for Soil Resources 2006. World Soil Resources Reports No. 103 2006, FAO, Rome. 2nd edition.
11. Lark R.M. Estimation of the variograms of soil properties by the method-of-moments and maximum likelihood; a comparison. European Journal of Soil Science 2000, 51:717-728.
12. Lark R.M. Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood. Geoderma 2002, 105:49-80.
13. Lark R.M., Cullis B.R. Model-based analysis using REML for inference from systematically sampled data on soil. European Journal of Soil Science 2004, 55:799-813.
14. Lark R.M., Webster R. Geostatistical mapping of geomorphic variables in the presence of trend. Earth Surface Processes and Landforms 2006, 31:862-874.
15. Lark R.M., Catt J.A., Stafford J.V. Towards the explanation of within-field variability of yield of winter barley: soil series differences. Journal of Agricultural Science 1998, 131:409-416.
16. Lark R.M., Cullis B.R., Welham S.J. On spatial prediction of soil properties in the presence of a spatial trend-the empirical best linear unbiased predictor (E-BLUP) with REML. European Journal of Soil Science 2006, 57:787-799.
17. Leenhardt D., Voltz M., Bomand M., Webster R. Evaluating soil maps for prediction of soil water properties. European Journal of Soil Science 1994, 45:293-301.
18. McBratney A.B., Mendonça Santos M.L., Minasny B. On digital soil mapping. Geoderma 2003, 117:3-52.
19. Patterson H.D., Thompson R. Recovery of inter-block information when block sizes are unequal. Biometrika 1971, 58:545-554.
20. Rawlins B.G., Webster R., Lister T.R. The influence of parent material on topsoil geochemistry in Eastern England. Earth Surface Processes and Landforms 2003, 28:1389-1409.
21. Rawlins B.G., Marchant B.P., Smyth D., Scheib C., Lark R.M., Jordan C. Airborne radiometric survey data and a DTM as covariates for regional scale mapping of soil organic carbon across Northern Ireland. European Journal of Soil Science 2009, 60:44-54.
22. Ribeiro P.J., Diggle P.J. geoR: a package for geostatistical analysis. R-NEWS 2001, 1:15-18.
23. Stacey K.F., Lark R.M., Whitmore A.P., Milne A.E. Using a process model to improve predictions of a soil variable by regression kriging. Geoderma 2006, 135:107-117.
24. Stram D.O., Lee J.W. Variance components testing in the longitudinal mixed effects setting. Biometrics 1994, 50:1171-1177.
25. Verbeke G., Molenberghs G. Linear Mixed Models for Longitudinal Data 2000, Springer, New York.
26. Wackernagel H. Multivariate geostatistics: an introduction with applications 2003, Springer, Berlin.
27. Walkley A., Black I.A. An examination of the Degtjareff method for determining organic carbon in soils: effect of variations in digestion conditions and of inorganic soil constituents. Soil Science 1934, 63:251-263.
28. Webster R., Beckett P.H.T. Quality and usefulness of soil maps. Nature 1968, 219:680-682.
29. Webster R., McBratney A.B. On the Akaike information criterion for choosing models for variograms of soil properties. Journal of Soil Science 1989, 40:493-496.