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The development of soil organic matter in restored biodiverse Jarrah forests of South-Western Australia as determined by ASE and GCMS

Lin, D. S., Greenwood, P. F., George, S., Somerfield, P. J. and Tibbett, M. ORCID: (2011) The development of soil organic matter in restored biodiverse Jarrah forests of South-Western Australia as determined by ASE and GCMS. Environmental Science and Pollution Research, 18 (7). pp. 1070-1078. ISSN 1614-7499

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To link to this item DOI: 10.1007/s11356-010-0433-9


Background, aim and scope Soil organic matter (SOM) is known to increase with time as landscapes recover after a major disturbance; however, little is known about the evolution of the chemistry of SOM in reconstructed ecosystems. In this study, we assessed the development of SOM chemistry in a chronosequence (space for time substitution) of restored Jarrah forest sites in Western Australia. Materials and methods Replicated samples were taken at the surface of the mineral soil as well as deeper in the profile at sites of 1, 3, 6, 9, 12, and 17 years of age. A molecular approach was developed to distinguish and quantify numerous individual compounds in SOM. This used accelerated solvent extraction in conjunction with gas chromatography mass spectrometry. A novel multivariate statistical approach was used to assess changes in accelerated solvent extraction (ASE)-gas chromatography-mass spectrometry (GCMS) spectra. This enabled us to track SOM developmental trajectories with restoration time. Results Results showed total carbon concentrations approached that of native forests soils by 17 years of restoration. Using the relate protocol in PRIMER, we demonstrated an overall linear relationship with site age at both depths, indicating that changes in SOM chemistry were occurring. Conclusions The surface soils were seen to approach native molecular compositions while the deeper soil retained a more stable chemical signature, suggesting litter from the developing diverse plant community has altered SOM near the surface. Our new approach for assessing SOM development, combining ASE-GCMS with illuminating multivariate statistical analysis, holds great promise to more fully develop ASE for the characterisation of SOM.

Item Type:Article
Divisions:Life Sciences > School of Agriculture, Policy and Development > Department of Sustainable Land Management > Centre for Agri-environmental Research (CAER)
ID Code:42817

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