A new simple topo-climatic model to predict surface displacement in paraglacial and periglacial mountains of the European Alps: The importance of ground heating index and floristic components as ecological indicators. (January 2021)

• Record Type: Journal Article
• Authors: Ponti, Stefano; Cannone, Nicoletta; Guglielmin, Mauro
• Is Part Of: Ecological indicators. Volume 120(2021)
• Publication Date: 2021-01
• Subjects: Surface displacement model -- Slope -- Ground heating index -- Permafrost degradation -- Vegetation rooting depth -- Ecological indication of movement; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2020.106889
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Climate warming is promoting surface instability in mountain areas. We propose a model of surface displacement based on topographic and climatic variables. slope and ground heating index play a key role in surface displacement. vegetation response depends on surface displacement depth respect to the rooting depth. Abstract: Landscape evolution is occurring at rapid rates in alpine areas in response to recent climate warming, also due to the susceptibility and the heterogeneity of these environments. Here we present a prediction model of surface displacements that takes into account both topographic and climatic variables. Observed points of surficial displacements have been associated to non-climatic (altitude, slope, solar radiation, till deposit type, deposit age, vegetation coverage) and climatic (days of snow permanence, ground surface temperature index, ground heating index, ground cooling index) variables through a general regression model in the European central Alps. The model output shows the importance of slope and ground heating index (GHI) – an estimation of the amount of energy transferred to the ground, to predict surface displacements independently from the type of considered processes. In particular, the general regression model shows that steep zones with high GHI are more susceptible to undergo periglacial and paraglacial processes producing surface displacements. As expected, slope is fundamental to trigger processes such as gravitation, nivation, solifluction and their interactions. The results of our model emphasize the key role of GHI, highlighting the importance of climate in controlling the surface displacement. Indeed, in areas in which GHI is higher, the ground can remain snow free for a longer time and snow melting can be faster, the former favoring more runoff and slopewash, and the latter promoting the saturation of the deposits consequent to a higher intensity of solifluction and/or mass movements processes. Within the study area, the sites with the largest displacements (>35 cm) were detected where permafrost degradation occurred since 1990. This permafrost degradation process could remain one of the main triggering factors of future surface displacements. Our results confirm that when movement involves material with coarse texture (pebbles and boulders) exceeding the rooting depth, only tolerant plant species can withstand the high movement rates. The areas where this can happen (like rock glaciers or screes) act as a physical barrier to grasslands species not adapted to surface displacements and trying to shift towards higher altitude in response to climate warming. However, plant species not considered as indicators of movement (such as graminoids), can develop also with large surface displacements in specific geomorphic conditions. Therefore, the combination of surface displacement type (deep vs surficial), material texture (fine vs coarse) and vegetation cover (high vs low) and floristic composition can be used as a valuable ecological indicator of movement. Our results suggest that both landscape degradation and vegetation displacement can be rapid especially where the air warming was strong as in the selected study area.