Document généré le 07/08/2026 depuis l'adresse: https://www.documentation.eauetbiodiversite.fr/fr/notice/spatial-analysis-of-trace-elements-in-a-moss-bio-monitoring-data-over-france-by-accounting-for-source-protocol-and-environmental-parameters-
Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters
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Identifiant documentaire
25-4284837
Identifiant OAI
4284837
Notice source
https://mnhn.hal.science/mnhn-04284837v1
Auteur(s):
Lequy Emeline,Saby Nicolas P. A.,Ilyin Ilia,Bourin Aude,Sauvage Stéphane,Leblond Sébastien
Mots clés
Sciences du sol
Autocorrélation
Autocorrélation spatiale
Modèle spatial
Cadmium
France
Date de publication
01/07/2017
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Description
Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses.
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