Comparison of soil quality indexes calculated by network and principal component analysis for carbonated soils under different uses

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Martín Sanz, Juan Pedro and Santiago Martín, Ana de and Valverde Asenjo, Inmaculada and Quintana Nieto, José Ramón and González Huecas, Concepción and López Lafuente, Antonio L. (2022) Comparison of soil quality indexes calculated by network and principal component analysis for carbonated soils under different uses. Ecological Indicators, 143 . p. 109374. ISSN 1470-160X

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Official URL: https://doi.org/10.1016/j.ecolind.2022.109374



Abstract

There is an urgent need to conserve and improve the quality of agricultural soils in the coming decades. Decision tools capable of providing reliable information about soil quality are needed, and soil quality index (SQI) is one of the most used. Principal component analysis (PCA) is the common methodology to calculate it, however in some cases fails to differentiate soil quality properly. Therefore, the aim of this work is to assess a SQI through a different methodology as network analysis (NTA) and compare it with PCA, assuming that soil uses affect soil qualities differently. From soils with different uses (rainfed, olive grove and forest) network analysis and principal component analysis have been used to select a minimum dataset (MDS) to generate SQI from 36 physical, chemical and biological soil variables. Using NTA, geometric mean of the enzyme activities (GMEAN), bulk density (BD) and phosphatase activity (phos) where selected as indicators, while PCA selected total organic carbon (TOC), free Fe oxides (FeF), crystalline Mn oxides (MnX), pH, electrical conductivity (EC) and percentage of coarse sand (CS). Four SQI were calculated from each MDS through linear and non-linear scoring equations and by additive integration and weights. The SQI generated by NTA were more useful than those generated by PCA, as in addition to having fewer indicators they were able to better differentiate the uses in the study. This greater resolution capacity of the NTA would be the consequence of a better selection of indicators using this method than using PCA.


Item Type:Article
Additional Information:

CRUE-CSIC (Acuerdos Transformativos 2022)

Uncontrolled Keywords:Soil quality, Land use, Network analysis, Principal component analysis, Mediterranean calcareous soil
Subjects:Medical sciences > Pharmacy > Soil science
ID Code:74591
Deposited On:19 Sep 2022 11:19
Last Modified:19 Sep 2022 14:08

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