Description:    Persistently high activity concentrations of radioactive Cs-137 ( T 1/2  = 30.17 a) in various animals and fruits originating from Bavarian forest ecosystems suggest that the contamination of soils in these ecosystems is still critical even decades after the severe inputs following the Chernobyl nuclear accident. Aware of the fact, that such inputs are a global threat that can re-emerge at any time, a new monitoring network was established in cooperation with the Bavarian State Ministry of the Environment and Public Health, to enhance the value of long-term radioprotection strategies in forests. Based on the investigation of 48 forest sites throughout the entire state territory, the project delivers a total of 889 gamma spectrometric records and demonstrates the current Cs-137 contamination situation of Bavarian forest soils, providing a valuable update on the residual contamination levels and thus a comprehensive inventory for any future radioprotection management. First results of this project are presented hereby. The total Cs-137 areal activity densities in Bavarian forest soils currently vary between 640 and 61,166 Bq m − ², with the peak areal activity density of each profile being located in the uppermost, humus rich mineral A-horizon in 68 % of all cases. Moreover, the results detect a positive correlation of humus thickness and relative areal Cs-137 activity density in humus horizons ( R ² = 0.50), validating previous findings on that topic by means of a very comprehensive data set across 2.56 Mio ha forest stands by showing that humus bodies 〉7.5 cm still contain at least 50 % of the total areal topsoil activity density. Content Type Journal Article Category Original Paper Pages 1-15 DOI 10.1007/s10342-012-0626-5 Authors Jennifer Winkelbauer, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Jörg Völkel, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Matthias Leopold, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Kerstin Hürkamp, Institute of Radiation Protection, Helmholtz-Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany Rudolf Dehos, Department of Radioprotection and Radioecology, Bavarian State Ministry of the Environment and Public Health, Munich, Germany Journal European Journal of Forest Research Online ISSN 1612-4677 Print ISSN 1612-4669

Description: Agriculture significantly contributes to global greenhouse gas (GHG) emissions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO 3 − ) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L 16 design, comprising 16 experimental units. Within this L 16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N 2 O), methane (CH 4 ) and carbon dioxide (CO 2 ) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO 3 − addition were the main factors affecting N 2 O fluxes, whilst glucose, NO 3 − and soil temperature were the main factors affecting CO 2 and CH 4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.