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Is forest a robust indicator of rockfall dynamics within the context of environmental changes?

Abstract : Rockfalls are one of the most common geomorphological processes in the steeply sloping environments. Despite their limited volumes, rockfalls pose a significant hazard, due to their rapid evolution, high velocity and impact energy, but their unpredictable occurrence hinders detailed investigation of their dynamics and drivers under natural conditions. As the relative influence of rainfall, snowmelt, temperature, or freeze–thaw cycles have long been identified, based on medium-term monitoring methods, as the main drivers of rockfall activity, increasing rockfall hazards triggered by climate change are a major concern expressed both in scientific and non-scientific media.At high altitude sites, unequivocal relationships have been established between heightened rockfall activity, permafrost thawing and global warming. By contrast, below the permafrost limit, in the absence of longer-term assessments of rockfall triggers and possible changes thereof, our knowledge of rockfall dynamics remains still lacunary as a result of the persisting scarcity of exhaustive and precise rockfall databases.Over the last two decades, dendrogeomorphology – based on the analysis of damage inflicted to trees after rockfall impacts – has been used to overcome certain limitations inherent to historical archives and reconstructions of rockfall activity have been developed. Paradoxically, tree-ring reconstructions have only rarely been compared with climatic data to precisely constrain the potential meteorological triggers of process activity or to detect potential influences of global warming mostly due to the absence of clear recommendations to derive reconstructions that optimally capture the climatic signal in rockfall-prone environments.In this context, this PhD thesis first aims at proposing clear methodological guidelines to optimize sampling strategies of trees so as to precisely quantify uncertainties in dendrogeomorphic reconstructions back in time. Our results clearly evidence that the high-resolution mapping of stems on the studied combined with a careful selection of tree-species located at the vicinity of the cliffs improve the robustness of our reconstructions at the Saint-Guillaume (mixed forest stand, Vercors massif, French Alps) and Valdrôme (monospecific planted forest stands, Diois massif, French Alps) studied plots.In the second part, we capitalize on rockfall activity derived from optimized reconstructions and on the high-spatio-temporal resolution of the SAFRAN reanalyses, to precisely identify the meteorological triggers of rockfall events. At the interannual scale, our results evidence that summer precipitations and intense rainfall-events are the main drivers at both sites while no clear impact of temperature or freeze-thaw cycles could be detected.Finally, we compare decadal fluctuations existing in both tree-ring records with climatic series available for the period 1959-2017 with the purpose to detect the potential impacts of global warming on rockfall activity. In the Vercors massif, we explain increasing rockfall activity observed in the reconstruction since 1959 by a rapid forest recolonization and the overrepresentation of young sensitive trees rather than by climate change. In the Diois massif, the absence of significant trend suggests that a premature warning of increasing rockfall hazard, is not supported by the existing data. Yet, the weak robustness of the multiple regression models used here, the limited increase of temperature at the study sites and the incompleteness of our tree-ring reconstructions suggest that these results have to be treated with cautiously. All in all, this PhD thesis clearly demonstrates the added-value of the dendrogeomorphic approach to reconstruct rockfall activity, assess the meteorological driver of past events as well as to detect the potential impacts of environmental changes on the process dynamics.
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Submitted on : Tuesday, August 25, 2020 - 10:04:41 AM
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Robin Mainieri. Is forest a robust indicator of rockfall dynamics within the context of environmental changes?. Environmental studies. Université Grenoble Alpes [2020-..], 2020. English. ⟨NNT : 2020GRALU009⟩. ⟨tel-02894983v2⟩

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