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Mountain ecosystems are commonly regarded as being highly sensitive to global change. Due to the system complexity and multifaceted interacting drivers, however, understanding current responses and predicting future changes in these ecosystems is extremely difficult. We aim to discuss potential effects of global change on mountain ecosystems and give examples of the underlying response mechanisms as they are understood at present. Based on the development of scientific global change research in mountains and its recent structures, we identify future research needs, highlighting the major lack and the importance of integrated studies that implement multi-factor, multi-method, multi-scale, and interdisciplinary research. Zusammenfassung: Gebirgsökosysteme gelten generell als sehr empfindlich gegenüber dem Globalen Wandel. Allerdings sind aufgrund der Komplexität der Systeme und wegen vielfältiger Interaktionen der Einflussfaktoren sowohl das Verständnis gegenwärtiger Reaktionen als auch Vorhersagen zukünftiger Änderungen sehr schwierig. Unser Ziel ist es, potenzielle Effekte des Globalen Wandels auf Gebirgsökosysteme zu diskutieren und Beispiele für die zugrunde liegenden Reaktionsmechanismen zu geben, soweit sie derzeit verstanden sind. Basierend auf der Entwicklung und den heutigen Strukturen der "Global Change"-Forschung in Gebirgen zeigen wir den Forschungsbedarf auf und betonen insbesondere das weitgehende Fehlen und die Bedeutung integrativer Studien über verschiedene Faktoren, Methoden, Maßstäbe und Disziplinen hinweg.

Humus forms are the morphological results of organic matter decay and distribution in the topsoil, and thus important indicators for decomposer activities in forest ecosystems. The first aim was to examine if humus forms are suitable indicators of microbiological properties of the topsoil in a high mountain forest (Val di Rabbi, Trentino, Italian Alps). The second aim was to predict microbiological parameters based on the topsoil pH value on two slopes of the study area (ca. 1200-2200 m a.s.l.). We investigated humus forms and determined pH values and microbiological parameters (enzymatic activities, carbon/nitrogen (C/N) ratio and the ratio of bacterial/archaeal abundance) of the uppermost mineral horizon. The results reveal significant correlations between pH value and microbiological parameters (except for bacterial/archaeal abundance), which enable upscaling to the landscape scale using linear models. Based on a random forest with kriging of model residuals, predictive maps of humus form, pH value and microbiological parameters show that decomposition processes in our study area correspond with the topography. As compared to locations on south-facing slopes or close to the valley bottom, locations on north-facing slopes or close to the upper treeline exhibit Moder (scarcely Mull or Amphimull), more acidic topsoil (around pH 4), a lower activity of leucine-aminopeptidase, a lower ratio of alkaline/acid phosphomonoesterase activity and a higher soil C/N ratio (above 20). Our results suggest a high potential of humus forms to indicate soil microbiological properties in a high mountain forest. Together with the pH values of the topsoil, humus forms proved to be a useful tool as a basis for predictive maps of leucine-aminopeptidase activity, ratio of alkaline/acid phosphomonoesterase activity and C/N ratio of the mineral topsoil.

The aim of this study was to map the spatial distribution of enchytraeids and humus forms in a study area in the Italian Alps by means of a knowledge-based modeling approach. The modeled area is located around Val di Sole and Val di Rabbi (Trentino, Italy) and includes the forested parts in the range between 1100 m and 1800 m a.s.l. Elevation and slope exposure are considered as environmental covariates. Models were implemented regarding the spatial distribution of three variables at the landscape scale: 1) enchytraeids indicating mull humus forms, 2) enchytraeids indicating moder/mor humus forms, 3) humus forms showing an OH horizon. All three models reveal a consistent trend of an increasing accumulation of plant residues and humus in organic layers from low to high elevations and from south-facing to north-facing slopes. Validation and uncertainty analysis of input data confirm these trends, although some deviations are to be expected (RMSE values from validation sites range from 26.3 to 36.2 percentage points). Effects of additional potentially influencing variables may lead to uncertainties of the model predictions especially at positions with particular landforms (e.g. gullies and ridges). In the high mountains environmental conditions are often quite heterogeneous due to a highly variable topography, which also affects the species composition of the decomposer community and the occurrence of different humus forms.

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