Mapping soil Pb stocks and availability in mainland France combining regression trees with robust geostatistics

Availability; Diffuse contamination mapping; Regression tree; Robust geostatistics; Soil Pb; Ethylenediaminetetraacetic acid; Explanatory variables; Fixed effects; Geo-statistics; Geostatistical; Key factors; Linear mixed models; Parent materials; Peak concentrations; Population densities; Regression tree models; Regression trees; Soil monitoring; Spatial correlations; Winsorizing; Lithology; Population statistics; Regression analysis; Soils; Textures; Forestry; EDTA; Biological Populations; Soil; Statistics; Texture; France

Abstract :

[en] Maps of lead (Pb) stocks in soils and estimates of its availability are needed to assess risks of contamination. Stocks in soils of total and ethylenediamine tetraacetic acid (EDTA) extractable Pb, as well as Pb availability, assessed by EDTA/total Pb ratio, were measured and calculated to a depth of 30. cm with the French soil monitoring network at sites defined by a regular 16 × 16. km grid. Setting aside punctual anomalies by winsorizing, these properties were mapped using linear mixed models (LMM). LMMs combined conditional partitioning trees upon 5 predictors (pH, texture, parent material, land use, population density) with robust geostatistics to avoid distortion due to outlying values. Rather than selecting the fixed effects according to expert-knowledge, regression trees were used to account for explanatory variables in a single classification. This original method stressed both the necessity for a geostatistical component to complement regression tree models when spatial correlation is evident, and the usefulness of these trees to interpret maps. Pb stocks varied widely with peak concentrations and availability in densely populated areas. Lithology, texture and forestation also affected total Pb stocks. With regards to availability, forestation and pH appeared as key factors. © 2011 Elsevier B.V.

Disciplines :

Environmental sciences & ecology

Author, co-author :

Lacarce, E.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Saby, N. P. A.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Martin, M. P.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Marchant, B. P.; Rothamstead Research, Harpenden, Hertfordshire AL5 2JQ, United Kingdom

Boulonne, L.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Meersmans, Jeroen ; Université de Liège - ULiège > Département GxABT > Analyse des risques environnementaux

Jolivet, C.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Bispo, A.; ADEME, Centre d'Angers, Direction Déchets et Sols, 20 avenue du Grésillé, BP 90406, F49004 Angers Cedex 01, France

Arrouays, D.; INRA, US 1106 Infosol, INRA Orléans, CS 40001 Ardon, F45075 Orleans Cedex 2, France

Language :

English

Title :

Mapping soil Pb stocks and availability in mainland France combining regression trees with robust geostatistics

Publication date :

2012

Journal title :

Geoderma

ISSN :

0016-7061

eISSN :

1872-6259

Publisher :

Elsevier, Netherlands

Volume :

170

Pages :

359-368

Peer reviewed :

Peer Reviewed verified by ORBi

Funders :

BBSRC - Biotechnology and Biological Sciences Research Council [GB]

Funding number :

BBS/E/C/00004943

Available on ORBi :

since 08 November 2021

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