Background, aim and scope: The European Heavy Metals in Mosses Surveys (UNECE-ICP Vegetation) is a programme performed every 5 years since 1990 in at least 21 European countries. The moss surveys aim at uncovering the spatiotemporal patterns of metal and nitrogen bioaccumulation in mosses. In France, the moss survey was conducted for the third time in 2006. Five hundred thirty-six monitoring sites were sampled across the whole French territory. The aim of the presented study is to give an integrative picture of the metal bioaccumulation for the entire French territory without geographical gaps. Furthermore, confounding factors of the metal bioaccumulation in mosses should be investigated.
Materials and methods: Element loads of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), nickel (Ni), lead (Pb), antimony (Sb), vanadium (V) and zinc (Zn) measured in the French campaign 2006 were aggregated to a multi-metal index (MMI). This index was first introduced in the German moss surveys and represents the mean rank of each monitoring site or estimated raster cell regarding all elements referred to. Hence, the spatial variability of the metal bioaccumulation in France could be assessed as a whole. A comparison of the MMI map with the spatial patterns of the Cu loads in mosses was then drawn, as Cu originates to a large extent from urban sources. Applying CHAID, the MMI and the Cu loads in the mosses were further investigated with regard to confounding factors. The said results were discussed on the basis of recent scientific publications.
Results: The MMI surface map shows high values in strongly industrialized and urbanized regions as well as at sites of high altitude, lying, for example in the Massif Central and the French Alps. Accordingly, the CHAID decision tree consequently shows the altitude to be the statistically most significant influencing factor of the MMI followed by the sampled moss species. As for the MMI map, the surface map for Cu mirrors urban agglomerations, as high values can be found in the areas of Greater Paris, Lyon and Marseille. The CHAID tree for Cu revealed the sampled moss species and the ratio of urban land uses within 5 km of the sampling sites to be the main influencing factors.
Discussion: The aggregation of metal bioaccumulation data was adopted for the French monitoring campaign. The influence of altitude, moss species-specific accumulation rates and urban emissions on the bioaccumulation is confirmed by international scientific publications. Nevertheless, the confounding factors in France differ from those derived from the German data, where the MMI was mainly associated to canopy drip effects and the growth patterns of the sampled mosses.
Conclusions: The Cu and the MMI maps give a comprehensive overview of the metal bioaccumulation in France without geographical gaps. Hence, this approach allows summarising the spatial patterns of eleven element loads in mosses by use of geostatistics and percentile statistics.
Recommendations and perspectives: The presented metal integrating approach should be applied on data from past French moss surveys and on those to come. Additionally, the decision tree analyses should be carried out to examine possibly changing boundary conditions of the metal accumulation in mosses over time.