RT Journal Article
T1 Comparison of soil quality indexes calculated by network and principal component analysis for carbonated soils under different uses
A1 Martín Sanz, Juan Pedro
A1 Santiago Martín, Ana De
A1 Valverde Asenjo, María Inmaculada
A1 Quintana Nieto, José Ramón
A1 González Huecas, Concepción
A1 López Lafuente, Antonio Leovigildo
AB 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.
PB Elsevier
SN 1470-160X
YR 2022
FD 2022-08-30
LK https://hdl.handle.net/20.500.14352/71990
UL https://hdl.handle.net/20.500.14352/71990
LA eng
NO Martín Sanz, J. P., Santiago Martín, A., Valverde Asenjo, M. I. et al. «Comparison of Soil Quality Indexes Calculated by Network and Principal Component Analysis for Carbonated Soils under Different Uses». Ecological Indicators, vol. 143, octubre de 2022, p. 109374. DOI.org (Crossref), https://doi.org/10.1016/j.ecolind.2022.109374.
NO CRUE-CSIC (Acuerdos Transformativos 2022)
NO Comunidad de Madrid
NO Universidad Complutense de Madrid/Banco de Santander
NO Ministerio de Universidades/Universidad Complutense
DS Docta Complutense
RD 22 abr 2025