Modelling of Vegetation Dynamics from Satellite Time Series to Determine Proglacial Primary Succession in the Course of Global Warming—A Case Study in the Upper Martell Valley (Eastern Italian Alps)

Michael H Wimmer,Bettina Knoflach,Florentin Hofmeister,Camillo Ressl,Matthew Talluto,Katharina Ramskogler,Florian Haas,Clemens Geitner,Tobias Heckmann,Brigitta Erschbamer,Madlene Pfeiffer,Johann Stötter,Livia Piermattei

doi:10.3390/rs13214450

Abstract

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.

Highlights

Recent climate change has caused pronounced effects in the high mountain areas of the European Alps with significant implications in the glacial and periglacial zone [1].Alpine glaciers have lost roughly 50% of their area and two-thirds of their volume since the mid-19th century [2,3]—known as the end of the Little Ice Age (LIA) [4]
The gradual change in species composition between plots along the chronosequence allowed a discrimination of successional stages (Figure 2), which clearly differed in their mean vegetation cover
The high correlation between total vegetation cover values and Normalized Difference Vegetation Index (NDVI) has been found in other proglacial areas of the European Alps [42], in the arctic tundra [49], as well as in areas with sub-Antarctic climate influence [34]

Summary

Introduction

Recent climate change has caused pronounced effects in the high mountain areas of the European Alps with significant implications in the glacial and periglacial zone [1].Alpine glaciers have lost roughly 50% of their area and two-thirds of their volume since the mid-19th century [2,3]—known as the end of the Little Ice Age (LIA) [4]. Thereby, the space-for-time substitution (chronosequence approach) is a widely used method Due to their temporal development, glacier forelands can serve as a spatial representation of a chronological sequence to detect temporal changes in vegetation development (i.e., vegetation diversity and total vegetation cover). They provide an unique opportunity to study the primary succession of vegetation along transects from the very beginning (e.g., [7,13,14])

Methods

Results

Discussion

Conclusion