Rapid prediction of particulate, humus and resistant fractions of soil organic carbon in reforested lands using infrared spectroscopy. (15th May 2017)

• Record Type: Journal Article
• Authors: Madhavan, Dinesh B.; Baldock, Jeff A.; Read, Zoe J.; Murphy, Simon C.; Cunningham, Shaun C.; Perring, Michael P.; Herrmann, Tim; Lewis, Tom; Cavagnaro, Timothy R.; England, Jacqueline R.; Paul, Keryn I.; Weston, Christopher J.; Baker, Thomas G.
• Is Part Of: Journal of environmental management. Volume 193(2017)
• Page Start: 290
• Page End: 299
• Publication Date: 2017-05-15
• Subjects: C sequestration -- Biodiverse environmental plantings -- Mid-infrared spectroscopy -- Near-infrared spectroscopy -- NMR spectroscopy -- Partial least squares regression; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.02.013
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Reforestation of agricultural lands with mixed-species environmental plantings can effectively sequester C. While accurate and efficient methods for predicting soil organic C content and composition have recently been developed for soils under agricultural land uses, such methods under forested land uses are currently lacking. This study aimed to develop a method using infrared spectroscopy for accurately predicting total organic C (TOC) and its fractions (particulate, POC; humus, HOC; and resistant, ROC organic C) in soils under environmental plantings. Soils were collected from 117 paired agricultural-reforestation sites across Australia. TOC fractions were determined in a subset of 38 reforested soils using physical fractionation by automated wet-sieving and 13 C nuclear magnetic resonance (NMR) spectroscopy. Mid- and near-infrared spectra (MNIRS, 6000–450 cm −1 ) were acquired from finely-ground soils from environmental plantings and agricultural land. Satisfactory prediction models based on MNIRS and partial least squares regression (PLSR) were developed for TOC and its fractions. Leave-one-out cross-validations of MNIRS-PLSR models indicated accurate predictions ( R 2 > 0.90, negligible bias, ratio of performance to deviation > 3) and fraction-specific functional group contributions to beta coefficients in the models. TOC and its fractions were predicted using the cross-validated models and soil spectra for 3109 reforested and agricultural soils. The reliability of predictions determined using k -nearest neighbour score distance indicated that >80% of predictions were within the satisfactory inlier limit. The study demonstrated the utility of infrared spectroscopy (MNIRS-PLSR) to rapidly and economically determine TOC and its fractions and thereby accurately describe the effects of land use change such as reforestation on agricultural soils. Graphical abstract: Highlights: We developed rapid methods to predict TOC, POC, HOC and ROC in reforested soils. TOC fractions were measured using automated wet-sieving and 13 C NMR in soil subsets. Robust MNIRS-PLSR models were built for TOC and its fractions and cross-validated. TOC and its fractions were accurately predicted in reforested and agriculture soils. MNIRS suits rapid and accurate assessment of C sequestration in different land uses.