Spatiotemporal Gradients of Environmental Forcing across the Eastern Alps: Quantifying Drivers of Landscape and Ecosystem Dynamics

Climatic variables as well as geological and biotic factors in the Alps have been recorded for decades by various sensors with increasing spatial, spectral and temporal resolution. A changing climate has clearly triggered morphological (hillslope and river dynamics) and biotic (vegetation cover and production) responses. However, understanding these dynamics well enough to predict future changes in coupled bio-geo-systems such as pore fluid pressure, landsliding, and vegetation, remains challenging. Changes in the system dynamics itself cannot be directly observed in remote sensing time series but have to be inferred from climate variables in combination with local factors (e.g. topographic metrics, lithology, vegetation cover).

We employ Google Earth Engine (GEE) and its wealth of freely available topographic, climate, and satellite datasets to compute spatiotemporal gradients of biotic and abiotic factors across the Eastern Alps. Using GEE's Python interface and the novel high-performance computing facility at University of Salzburg, we implemented a swath profile modelling framework that applies a curvilinear approach with signed distance metrics to capture variability across complex mountainous terrain. While previously only applied at local or regional scales, this study provides the first orogen-scale, swath-profile based assessment of spatial and temporal gradients across the Eastern Alps.

Our analysis quantifies past, present, and the projected changes in precipitation, temperature, and vegetation patterns, identifying regions of high landscape sensitivity. These results improve our understanding of climate-driven variability in the European Alps and establish a solid basis for future orogen-scale analyses of spatiotemporal gradients.