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Applied and Environmental Soil Science
Volume 2012 (2012), Article ID 241535, 13 pages
http://dx.doi.org/10.1155/2012/241535
Research Article

Spectral Estimation of Soil Properties in Siberian Tundra Soils and Relations with Plant Species Composition

1Centre for Geo-Information, Wageningen University, 6708 PB Wageningen, The Netherlands
2Institute of Evolutionary Biology and Environmental Studies, University of Zürich, 8006 Zurich, Switzerland
3Nature Conservation and Plant Ecology, Wageningen University, 6708 PB Wageningen, The Netherlands
4Institute of Biological Problems of the Cryolithozone, 677980 Yakutsk, Russia
5Institute of Physicochemical and Biological Problems of Soil Science, 142290 Pushchino, Russia

Received 13 February 2012; Accepted 18 June 2012

Academic Editor: Raphael Viscarra Rossel

Copyright © 2012 Harm Bartholomeus et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Predicted global warming will be most pronounced in the Arctic and will severely affect permafrost environments. Due to its large spatial extent and large stocks of soil organic carbon, changes to organic matter decomposition rates and associated carbon fluxes in Arctic permafrost soils will significantly impact the global carbon cycle. We explore the potential of soil spectroscopy to estimate soil carbon properties and investigate the relation between soil properties and vegetation composition. Soil samples are collected in Siberia, and vegetation descriptions are made at each sample point. First, laboratory-determined soil properties are related to the spectral reflectance of wet and dried samples using partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR). SMLR, using selected wavelengths related with C and N, yields high calibration accuracies for C and N. PLSR yields a good prediction model for K and a moderate model for pH. Using these models, soil properties are determined for a larger number of samples, and soil properties are related to plant species composition. This analysis shows that variation of soil properties is large within vegetation classes, but vegetation composition can be used for qualitative estimation of soil properties.