1. Large topsoil organic carbon variability is controlled by Andisol properties and effectively assessed by VNIR spectroscopy in a coffee agroforestry system of Costa Rica
- Author
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Tiphaine Chevallier, Simon Taugourdeau, Rintaro Kinoshita, Harold M. van Es, Zia U. Ahmed, Alain Albrecht, Olivier Roupsard, Sch Integrat Plant Sci, Soil & Crop Sci Sect, Cornell University, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Institut National de la Recherche Agronomique (INRA)-Institut de Recherche pour le Développement (IRD)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Tropical Agricultural Centre for Research and Higher Education, Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET), Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), International Maize and Wheat Improvement Center (CIMMYT), Cornell University [New York], Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
- Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences ,Concentration ,010504 meteorology & atmospheric sciences ,F08 - Systèmes et modes de culture ,Arbre d'ombrage ,Coffea ,Agroforesterie ,andisols ,01 natural sciences ,Erythrina poeppigiana ,Multivariate interpolation ,Productivité ,agroforestry ,Partial least squares regression ,2. Zero hunger ,Agroforestry ,Elettaria cardamomum ,Sol volcanique ,04 agricultural and veterinary sciences ,Co-kriging ,co-kriging ,P33 - Chimie et physique du sol ,Carbone ,Watershed ,food.ingredient ,Spectroscopie infrarouge ,Soil Science ,Soil science ,allophane ,Allophane ,food ,Andisols ,Bassin versant ,Composé organique ,Mesure ,Propriété physicochimique du sol ,vnir spectroscopy ,0105 earth and related environmental sciences ,Topsoil ,Random Forest ,Structure du sol ,Soil organic carbon ,Soil carbon ,15. Life on land ,Andisol ,soil organic carbon ,P32 - Classification des sols et pédogenèse ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Environmental science ,Spatial variability ,Cycle du carbone ,VNIR spectroscopy ,random forest - Abstract
Assessing the spatial variability of soil organic carbon (SOC) is crucial for SOC monitoring and comparing management options. Topsoil (0–5 cm) SOC concentrations were surveyed in a coffee agroforestry watershed (0.9 km2) on Andisols in Costa Rica with uniform farm management. We encountered high values and large spatial variations of SOC, from 48.1 to 172 g kg− 1 in the dry combustion set (SOCref; n = 72) used for calibrating the visible-near-infrared reflectance spectroscopy (VNIRS) samples (SOCVNIRS; 350–2500 nm; n = 520). VNIRS using partial least squares regression was effective in predicting SOC (R2 = 0.85; a root mean square error (RMSE) = 12.3 g kg− 1) and proved an effective proxy measurement. We assessed several topographic, vegetation and andic soil property variables, of which only the latter (metal–humus complexes and allophanes) displayed strong correlations with SOCref concentrations. We compared Random Forest and three geostatistical approaches for the interpolation of SOC in unsampled locations. Ordinary kriging with SOCref yielded an RMSE of 28.0 g kg− 1. Random Forest was successful in incorporating many weakly and non-linearly correlated covariates with SOC (RMSE = 14.7 g kg− 1), provided Alp (the sodium pyrophosphate extractable aluminum), the best predictor of SOC (r = 0.85) but also the most costly variable to acquire. Co-kriging with Alp also showed high reduction in RMSE (16.0 g kg− 1). Co-kriging with SOCVNIRS only showed marginal reduction in RMSE to 24.2 g kg− 1 due to the presence of a high nugget effect. Local variability of SOC in this volcanic agroforestry watershed was dominated by andic properties whereas topographic or vegetation variables had very little impact. Estimation of SOC variability is recommended using inexpensive proxy measurements like VNIRS (RMSE = 12.3 g kg− 1) rather than spatial interpolation techniques. (Resume d'auteur)
- Published
- 2016
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