Predicting soil quality indices with near infrared analysis in a wildfire chronosequence

Lauric Cécillon (1, 2) , Nathalie Cassagne (3) , Sonia Czarnes (4) , Raphaël Gros (5) , Michel Vennetier (6) , Jean-Jacques Brun (1)

1 UR EMGR - Ecosystèmes montagnards
2 ADEME - Agence de l'Environnement et de la Maîtrise de l'Energie
3 URFM - Unité de Recherches Forestières Méditerranéennes
4 LEM - Laboratoire d'Ecologie Microbienne - UMR 5557
5 IMEP - Institut Méditerranéen d'Ecologie et de Paléoécologie
6 UR EMAX - Ecosystèmes méditerranéens et risques

We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066–3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.

Mots clés: Soil health; Soil monitoring; NIRS; GISQ; Soil biogenic structures; Soil quality

Domaines: Science des sols

Lauric Cécillon, Nathalie Cassagne, Sonia Czarnes, Raphaël Gros, Michel Vennetier, et al.. Predicting soil quality indices with near infrared analysis in a wildfire chronosequence. Science of the Total Environment, 2009, 407 (3), pp.1200-1205. ⟨10.1016/j.scitotenv.2008.07.029⟩. ⟨hal-00396383⟩