Since the end of the Little Ice Age (LIA), formerly glaciated areas have undergone considerable changes in their morphodynamics due to external forces and system-internal dynamics. Using multi-temporal high-resolution digital elevation models (DEMs) from different remote sensing techniques such as historical digital aerial images and light detection and ranging (LiDAR), and the resulting DEMs of difference (DoD), spatial erosion and accumulation patterns can be analyzed in proglacial areas over several decades. In this study, several morphological sediment budgets of different test sites on lateral moraines and different long-term periods were determined, covering a total period of 49 years. The test sites show high ongoing morphodynamics, and therefore low vegetation development. A decrease as well as an increase of the mean annual erosion volume could be demonstrated at the different test sites. All test sites show a slope–channel coupling and a decrease in the efficiency of sediment transport from slopes to channels. These developments are generally subject to conditions of increasing temperature, decreasing short-term precipitation patterns and increasing runoff from adjacent mountain streams. Finally, the study shows that sediment is still available on the investigated test sites and the paraglacial adjustment process is still in progress even after several decades of deglaciation (~133 years).

Satellite-based long-term observations of vegetation cover development in combination with recent in-situ observations provide a basis to better understand the spatio-temporal changes of vegetation patterns, their sensitivity to climate drivers and thus climatic impact on proglacial landscape development. In this study we combined field investigations in the glacier forelands of Fürkele-, Zufall- and Langenferner (Ortles-Cevedale group/Eastern Italian Alps) with four different Vegetation Indices (VI) from Landsat scenes in order to test the suitability for modelling an area-wide vegetation cover map by using a Bayesian beta regression model (RStan). Since the model with the Normalized Difference Vegetation Index (NDVI) as predictor showed the best results, it was used to calculate a vegetation cover time series (1986–2019). The alteration of the proglacial areas since the end of the Little Ice Age (LIA) was analyzed from digital elevation models based on Airborne Laser Scanning (ALS) data and areal images, orthophotos, historical maps and field mapping campaigns. Our results show that a massive glacier retreat with an area loss of 8.1 km² (56.9%; LIA–2019) resulted in a constant enlargement of the glacier forelands, which has a statistically significant impact on the degree of vegetation cover. The area covered by vegetation increased from 0.25 km² (5.6%) in 1986 to 0.90 km² (11.2%) in 2019 with a significant acceleration of the mean annual changing rate. As patterns of both densification processes and plant colonization at higher elevations can be reflected by the model results, we consider in-situ observations combined with NDVI time series to be powerful tools for monitoring vegetation cover changes in alpine proglacial areas.

Climate change and the associated glacier retreat lead to considerable enlargement and alterations of the proglacial systems. The colonisation of plants in this ecosystem was found to be highly dependent on terrain age, initial site conditions and geomorphic disturbances. Although the explanatory variables are generally well understood, there is little knowledge on their collinearities and resulting influence on proglacial primary succession. To develop a sphere-spanning understanding of vegetation development, a more interdisciplinary approach was adopted. In the proglacial areas of Fürkeleferner, Zufallferner and Langenferner (Martell Valley, Eastern Italian Alps), in total 65 plots of 5×2 m were installed to perform the vegetation analysis on vegetation cover, species number and species composition. For each of those, 39 potential explanatory variables were collected, selected through an extensive literature review. To analyse and further avoid multicollinearities, 33 of the explanatory variables were clustered via principal component analysis (PCA) to five components. Subsequently, generalised additive models (GAMs) were used to analyse the potential explanatory factors of primary succession. The results showed that primary succession patterns were highly related to the first component (elevation and time), the second component (solar radiation), the third component (soil chemistry), the fifth component (soil physics) and landforms. In summary, the analysis of all explanatory variables together provides an overview of the most important influencing variables and their interactions; thus it provides a basis for the debate on future vegetation development in a changing climate.

Aerial photographs of the European Alps usually only reach back to the middle of the 20th century, which limits the time span of corresponding studies that quantitatively analyse long-term surface changes of proglacial areas using georeferenced orthophotos. To the end of the Little Ice Age, this leads to a gap of about 100 years. Using digital monoplotting and several historical terrestrial photographs, we show the quantification of surface changes of a Little Ice Age lateral moraine section until the late second half of the 19th century, reaching a total study period of 130 years (1890–2020). The (initial) gully system expands (almost) continuously over the entire study period from 1890 to 2020. Until 1953, the vegetation-covered areas also expanded (mainly scree communities, alpine grasslands and dwarf shrub communities), before decreasing again, especially between 1990 and 2003, due to large-scale erosion within the gully system. Furthermore, our results show that the land-cover development was impacted by temperature and precipitation changes. With the 130-year study period, we contribute to a substantial improvement in the understanding of the processes in the proglacial by analysing the early phase and thus the immediate response of the lateral moraine to the ice exposure.

Alpine ecosystems, highly sensitive to climate change, are experiencing shifts in species ranges and community structure. These changes are driven by a complex interplay of climatic and environmental factors, land use changes, geomorphological dynamics, and species interactions, which can often lead to contrasted and sometimes unexpected dynamics. Historical records provide a valuable opportunity to capture these complexities by revealing long‐term changes, opening a gateway to hypothesise about the key underlying processes. We investigated changes in the floristic composition of subalpine to nival vegetation communities by resurveying a period of 70 years. To understand vegetation patterns, we (i) resampled vegetation at plot level and remapped the area, (ii) analysed the role of driving climate, environmental, and land use factors on vegetation distribution and vascular plant species richness, and (iii) modelled plant‐plant interactions from community data. The results reveal that vegetation cover patterns were strongly influenced by local climate and soil properties. The species richness is also influenced by the livestock density and the flat morphology. It should be noted that climate change caused wetland habitats to become drier and accelerated secondary succession through upward migration and range‐infilling processes. Furthermore, a trend towards eutrophication was observed. The results suggested that certain plant communities, particularly those found in snowbeds, were more vulnerable to environmental changes that have occurred over the past 70 years. Synthesis: This study highlighted the complexity of vegetation dynamics. In addition to thermophilisation and aridification, changes in land use affect species composition, species richness, and vegetation cover. Substrate conditions also play an important role.

Climate change and the associated glacier retreat lead to considerable enlargement and alterations of the proglacial systems. The colonisation of plants in this ecosystem was found to be highly depending on terrain age, initial site conditions and geomorphic disturbances. Although the explanatory variables are generally well understood, there is little knowledge on their collinearities and resulting influence on proglacial primary succession. To develop a holistic understanding of vegetation development, a more interdisciplinary approach was adopted. In the proglacial area of Fürkele-, Zufall-, and Langenferner (Martell Valley/Eastern Italian Alps), totally 65 plots of 5 × 2 m were installed to perform the vegetation analysis on vegetation cover, species number, and species composition. For each of those, 30 potential explanatory variables were collected, selected through an extensive literature review. To analyse and further avoid multicollinearities, 26 of the explanatory variables were clustered via Principal Component Analysis (PCA) to five components. Subsequently, generalised additive models (GAM) were used to analyse the potential explanatory factors of primary succession. The results showed that primary succession patterns were highly related to the first component (‘elevation and time’), the second component (‘solar radiation’), and the third component (‘south-eastness’) as well as snow free freeze-thaw days, and landforms. In summary, the analysis of all explanatory variables together provides an overview of the most important influencing variables and their interactions, and thus a basis for the debate on future vegetation development in a changing climate.