Open AccessApplying fingerprint Fourier transformed infrared spectroscopy and chemometrics to assess soil ecosystem disturbance and recovery
Author(s) -
Jonathan J. Maynard,
Mark G. Johnson
Publication year - 2018
Publication title -
journal of soil and water conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 75
eISSN - 1941-3300
pISSN - 0022-4561
DOI - 10.2489/jswc.73.4.443
Subject(s) - soil water , chemometrics , environmental science , ecosystem , fourier transform infrared spectroscopy , fingerprint (computing) , soil test , soil quality , soil science , chemistry , environmental chemistry , ecology , computer science , biology , artificial intelligence , physics , chromatography , quantum mechanics
The assessment and monitoring of soil disturbance and its effect on soil quality (i.e., ability to support a range of ecosystem services) has been hindered due to the shortcomings of many traditional analytical techniques (e.g., soil enzyme activities, microbial incubations), including: high cost, long-term time investment and difficulties with data interpretation. Consequently, there is a critical need to develop a rapid and repeatable approach for quantifying changes in soil quality that will provide an assessment of the current status, condition and trend of natural and managed ecosystems. Here we report on a rapid, high-throughput approach to develop an ecological 'fingerprint' of a soil using Fourier transformed infrared (FTIR) spectroscopy and chemometric modeling, and its application to assess soil ecosystem status and trend. This methodology was applied in a highly disturbed forest ecosystem over a 19-year sampling period to detect changes in soil quality (detected via changes in spectral properties), resulting from changes in dynamic soil properties (e.g., soil organic matter, reactive mineralogy). Two chemometric statistical techniques (i.e., hierarchical clustering analysis and discriminate analysis of principal components) were evaluated for interpreting and quantifying similarities/dissimilarities between samples utilizing the entire FTIR spectra (i.e., fingerprint) from each sample. We found that this approach provided a means for clearly discriminating between degraded soils, soils in recovery and reference soils. Results from fingerprint FTIR analysis illustrate its power and potential for the monitoring and assessment of soil quality and soil landscape change.