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Among the multiple forms of freshwater pelagic cyanobacteria, the phycoerythrin-rich species Planktothrix rubescens is well adapted to temperate, deep and large lakes. In Lake Geneva, this filamentous and microcystin-producing species has been the dominant cyanobacterial species observed since the early years of this century. In addition to the trophic state (e.g., the phosphorus level), the influences of air and water temperature on the occurrence and development of cyanobacteria are particularly relevant in the context of global climate change. The latter may indeed be particularly marked for lakes in the Alpine region, with a rate of warming that may be twice as large as the global average. The impact of climate change on P. rubescens is thus an important challenge and it has been analysed in this study through two different approaches: (1) the extreme air temperature events as a proxy for future climate and (2) the multi adaptive regression splines (MARS) model to predict future P. rubescens biomass. These methods allowed us to determine whether Lake Geneva will still sustain an important biomass of P. rubescens in forthcoming years, provided there is no severe over-enrichment with nutrients in the future. The outcomes strongly suggest that the fraction of cyanobacterium could increase with respect to the total phytoplankton community by as much as 34 % by the end of this century and induce a significant change in the microalgal composition. Additionally, the results point to the fact that spring is a key period during which air temperature and nutrients become the determinant factors for outbreaks of this species in the subsequent seasons.

Hydrogeomorphic processes are a major threat in many parts of the Alps, where they periodically damage infrastructure, disrupt transportation corridors or even cause loss of life. Nonetheless, past torrential activity and the analysis of areas affected during particular events remain often imprecise. It was therefore the purpose of this study to reconstruct spatio-temporal patterns of past debris-flow activity in abandoned channels on the forested cone of the Manival torrent (Massif de la Chartreuse, French Prealps). A Light Detecting and Ranging (LiDAR) generated Digital Elevation Model (DEM) was used to identify five abandoned channels and related depositional forms (lobes, lateral levees) in the proximal alluvial fan of the torrent. A total of 156 Scots pine trees (Pinus sylvestris L.) with clear signs of debris flow events was analyzed and growth disturbances (GD) assessed, such as callus tissue, the onset of compression wood or abrupt growth suppression. In total, 375 GD were identified in the tree-ring samples, pointing to 13 debris-flow events for the period 1931-2008. While debris flows appear to be very common at Manival, they have only rarely propagated outside the main channel over the past 80 years. Furthermore, analysis of the spatial distribution of disturbed trees contributed to the identification of four patterns of debris-flow routing and led to the determination of three preferential breakout locations. Finally, the results of this study demonstrate that the temporal distribution of debris flows did not exhibit significant variations since the beginning of the 20th century.