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Spatial analysis and indicator building for metal accumulation in mosses
Winfried Schröder1, Roland Pesch
1Institut für Umweltwissenschaften und Forschungszentrum für Geoinformatik für und Fernerkundung der Hochschule Vechta, Vechta, Germany. wschroeder@iuw.uni-vechta.de
Environmental Monitoring and Assessment
|October 12, 2004
Summary
This study focuses on statistical methods for analyzing European moss monitoring data on metal accumulation. It details geostatistical and multivariate techniques to assess environmental metal levels and improve monitoring indicators.
Area of Science:
- Environmental Science
- Ecology
- Biomonitoring
Background:
- Mosses serve as passive monitors for metal accumulation in terrestrial ecosystems.
- Germany participated in European-wide moss monitoring campaigns in 1990, 1995, and 2000.
- This article concentrates on the statistical data analysis methods used in these campaigns.
Purpose of the Study:
- To summarize the design of data collection for moss monitoring.
- To present geostatistical analysis and transformation of point data into areal information.
- To describe the aggregation of element-specific metal concentrations into a spatially and temporally differentiated indicator of metal accumulation.
Main Methods:
- Geostatistical analysis for spatial data transformation.
- Descriptive and multivariate statistical methods for data aggregation.
- Focus on statistical data analysis rather than complete investigation results.
Main Results:
- Methodical aspects of statistical data analysis are presented.
- Geostatistical methods transform point data to areal information.
- Descriptive and multivariate statistics aggregate metal concentrations into an indicator.
Conclusions:
- The presented work is a part of geostatistics and multivariate statistics applicable to moss monitoring data.
- Further steps include cluster-analytic evaluation and optimizing indicator building.
- Future research should detail cluster results and test multivariate regression models for improved metal accumulation indicators.
