Selection of sampling sites in Germany for the International Moss Survey 2020 using statistics and decision modelling
Abstract Background After 1990, 1995, 2000, 2005 and 2015, Germany participated in the International Moss Monitoring 2020 (MM2020). The German contribution to MM2020 aimed at pilot studies on the suitability of bioindication with mosses for recording the atmospheric deposition of persistent organic...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-01-01
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| Series: | Environmental Sciences Europe |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12302-025-01055-3 |
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| Summary: | Abstract Background After 1990, 1995, 2000, 2005 and 2015, Germany participated in the International Moss Monitoring 2020 (MM2020). The German contribution to MM2020 aimed at pilot studies on the suitability of bioindication with mosses for recording the atmospheric deposition of persistent organic pollutants and microplastics. Results This investigation was based on moss samples collected at 25 sites in Germany: Eight sites at which concentrations of persistent organic pollutants were determined in the Moss Survey 2015 were included. In addition, twelve sites were selected from the pool of the total of 400 moss collection sites in 2015. Further five sites of the German moss monitoring network 2015 were added, at which moss samples were collected in 2020 for developing the sample preparation and for preliminary investigations. The selection of the five test sites was based on the same criteria as for the 20 target sites of the 2020 monitoring to make the analysis data of the test phase usable for later evaluations. To ensure methodological transparency and objectivity, a procedure based on statistical methods and decision modelling was developed for this purpose. The decision algorithm enabled taking into account a large number of technical criteria. Selected features of the three subsamples comprising 8, 20 and 25 sites were compared with those of the full sample (n = 400 sites of Moss Survey 2015) and inferentially tested whether the thinning of the 2015 sampling network (n = 400) to 8, 20 and 25 sites, respectively, leads to significant changes in its information quality or not. Conclusions Methods of decision modelling and inferential statistics have proven their worth for transparently restructuring the moss monitoring network. |
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| ISSN: | 2190-4715 |