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The objective of the thesis is the model-based analysis of spatial patterns of decomposition properties on the forested slopes of the montane level (ca. 1200-2200 m a.s.l.) in a study area in the Italian Alps (Val di Sole / Val di Rabbi, Autonomous Province of Trento). The analysis includes humus forms and enchytraeid assemblages as well as pH values, activities of extracellular enzymes and C/N ratios of the topsoil. The first aim is to develop, test and apply data-based techniques for spatial modelling of soil ecological parameters. This methodological approach is based on the concept of digital soil mapping. The second aim is to reveal the relationships between humus forms, soil organisms and soil microbiological parameters in the study area. The third aim is to analyze if the spatial patterns of indicators of decomposition differ between the landscape scale and the slope scale. At the landscape scale, sample data from six sites are used, covering three elevation levels at both north- and south-facing slopes. A knowledge-based approach that combines a decision tree analysis with the construction of fuzzy membership functions is introduced for spatial modelling. According to the sampling design, elevation and slope exposure are the explanatory variables. The investigations at the slope scale refer to one north-facing and one south-facing slope, with 30 sites occurring on each slope. These sites have been derived using conditioned Latin Hypercube Sampling, and thus reasonably represent the environmental conditions within the study area. Predictive maps have been produced in a purely data-based approach with random forests. At both scales, the models indicate a high variability of spatial decomposition patterns depending on the elevation and the slope exposure. In general, sites at high elevation on north-facing slopes almost exclusively exhibit the humus forms Moder and Mor. Sites on south-facing slopes and at low elevation exhibit also Mull and Amphimull. The predictions of those enchytraeid species characterized as Mull and Moder indicators match the occurrence of the corresponding humus forms well. Furthermore, referencing the mineral topsoil, the predictive models show increasing pH values, an increasing leucine-aminopeptidase activity, an increasing ratio alkaline/acid phosphomonoesterase activity and a decreasing C/N ratio from north-facing to south-facing slopes and from high to low elevation. The predicted spatial patterns of indicators of decomposition are basically similar at both scales. However, the patterns are predicted in more detail at the slope scale because of a larger data basis and a higher spatial precision of the environmental covariates. These factors enable the observation of additional correlations between the spatial patterns of indicators of decomposition and environmental influences, for example slope angle and curvature. Both the corresponding results and broad model evaluations have shown that the applied methods are generally suitable for modelling spatial patterns of indicators of decomposition in a heterogeneous high mountain environment. The overall results suggest that the humus form can be used as indicator of organic matter decomposition processes in the investigated high mountain area.

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