Spatiotemporal variability of metal accumulation in mosses. Analysis of measurement data and metadata by statistics and GIS
Pesch, Roland; Schröder, Winfried
Measurement data and metadata from the German Heavy Metals in Mosses Surveys 1990, 1995 and 2000 are statistically analysed with regard to the following hypotheses on the variability of metal accumulation across several spatial scales: (1) The metal accumulation in mosses is correlated with the distance of the sampling sites to industrial plants, human settlements, roads and highways. (2) The metal accumulation in mosses is correlated with the distance between the sampling points and trees because of canopy drip effects. (3) Topographical features like inclination, exposition and altitude cause spatial variability of the metal accumulation. (4) Moss species accumulate metals specifically. (5) The accumulation of metals in mosses varies with ecoregions. The metadata were collected by the moss samplers during each monitoring campaign. They describe the measurement sites with respect to some of those surrounding environmental conditions like vegetation, land use and topography that could be relevant for the spatial variances of the metal accumulation in mosses. The statistical design to investigate these hypotheses includes GIS-techniques, conventional statistical methods like contingency tables and correlation analysis as well as geostatistical methods like variogram analysis, ordinary kriging and cross-validation. Although no directional dependencies can be detected by means of correlation analysis, ecoregions, altitude, moss species and the distance of the sampling site to the nearest trees influence the metal accumulation significantly. No correlation was found between the metal accumulation and the distance of the sampling sites to emission sources. This is probably caused by the low degree of differentiation of the metadata. Further statistical investigations should corroborate the findings on the spatial variability of metal accumulation and specify the multiple interrelations with site specific, local and regional influencing factors.