Metal accumulation in mosses across national boundaries: uncovering and ranking causes of spatial variation.

This study aimed at cross-border mapping metal loads in mosses in eight European countries in 1990, 1995, and 2000 and at investigating confounding factors. Geostatistics was used for mapping, indicating high local variances but clear spatial autocorrelations. Inference statistics identified differences of metal concentrations in mosses on both sides of the national borders. However, geostatistical analyses did not ascertain discontinuities of metal concentrations in mosses at national borders due to sample analysis in different laboratories applying a range of analytical techniques. Applying Classification and Regression Trees (CART) to the German moss data as an example, the local variation in metal concentrations in mosses were proved to depend mostly on different moss species, potential local emission sources, canopy drip and precipitation.

Analysis of climate change affecting German forests by combination of meteorological and phenological data within a GIS environment.

The regional assessment of global change effects on plant phenology usually relies on local observations that need to be up-scaled. Therefore, methodological difficulties mostly related to data spatial resolution and congruency arise while performing broader-scale evaluations. Geostatiscs could be a useful tool to solve this type of problem, provided that a database with adequate spatial and temporal resolution is available. An assessment of variations in air temperature and plant phenology was carried out at the country level by using two German datasets regarding spring phenological phases of 15 plant species and air temperature. The data were collected from 1961-2002 at 1,279 and 675 sites, respectively. The annual mean air temperature in Germany was found to rise from 8.3 degrees C in the 1961-1990 period to 9.1 degrees C in the 1991-2002 term. The overall 15-species mean for the start of spring was found to be 6 days earlier in the latter period. The geostatistical analysis of the data revealed the suitability of Syringa vulgaris to be used as an indicator species to detect phenological changes in German forests. Moreover, their spatial patterns were found to be related to altitude and latitude. Therefore, geostatistics proved to be a useful tool to overcome some of the methodological problems related to the regional assessments of global change impacts on terrestrial ecosystems.