Saxifrage bouc et veaux: une histoire d'amour

Version vulgarisée avec compléments de l'article en anglais (Vittoz et al., 2006). Situation et répartition de l'espèce au niveau européen, sociologie de l'espèce dans les différents marais jurassiens, hydrologie et microtopographie, enracinement, sol, rôle du bétail dans la conservation de l'espèce, génétique et quelques pistes pour sa protection

Snowbeds are more affected than other subalpine-alpine plant communities by climate change in the Swiss Alps

While the upward shift of plant species has been observed on many alpine and nival summits, the reaction of the subalpine and lower alpine plant communities to the current warming and lower snow precipitation has been little investigated so far. To this aim, 63 old, exhaustive plant inventories, distributed along a subalpine-alpine elevation gradient of the Swiss Alps and covering different plant community types (acidic and calcareous grasslands; windy ridges; snowbeds), were revisited after 25 to 50-years. Old and recent inventories were compared in terms of species diversity with Simpson diversity and Bray-Curtis dissimilarity indices, and in terms of community composition with Principal Component Analysis. Changes in ecological conditions were inferred from the ecological indicator values. The alpha-diversity increased in every plant community, likely because of the arrival of new species. As observed on mountain summits, the new species led to a homogenisation of community compositions. The grasslands were quite stable in terms of species composition, whatever the bedrock type. Indeed, the newly arrived species were part of the typical species pool of the colonised community. In contrast, snowbed communities showed pronounced vegetation changes and a clear shift towards dryer conditions and shorter snow cover, evidenced by their colonisation by species from surrounding grasslands. Longer growing seasons allow alpine grassland species, which are taller and hence more competitive, to colonise the snowbeds. This study showed that subalpine-alpine plant communities reacted differently to the on-going climate changes. Lower snow/rain ratio and longer growing seasons seem to have a higher impact than warming, at least on plant communities dependent on long snow cover. Consequently, they are the most vulnerable to climate change and their persistence in the near future is seriously threatened. Subalpine and alpine grasslands are more stable and, until now, they do not seem to be affected by a warmer climate

A better understanding of ecological conditions for Leontopodium alpinum Cassini in the Swiss Alps

Although Leontopodium alpinum is considered to be threatened in many countries, only limited scientific information about its autecology is available. In this study, we aim to define the most important ecological factors which influence the distribution of L. alpinum in the Swiss Alps. These were assessed at the national scale using species distribution models based on topoclimatic predictors and at the community scale using exhaustive plant inventories. The latter were analysed using hierarchical clustering and principal component analysis, and the results were interpreted using ecological indicator values. L. alpinum was found almost exclusively on base-rich bedrocks (limestone and ultramaphic rocks). The species distribution models showed that the available moisture (dry regions, mostly in the Inner Alps), elevation (mostly above 2000 m.a.s.l.) and slope (mostly >30°) were the most important predictors. The relevés showed that L. alpinum is present in a wide range of plant communities, all subalpine-alpine open grasslands, with a low grass cover. As a light-demanding and short species, L. alpinum requires light at ground level; hence, it can only grow in open, nutrient-poor grasslands. These conditions are met in dry conditions (dry, summer-warm climate, rocky and draining soil, south-facing aspect and/or steep slope), at high elevations, on oligotrophic soils and/or on windy ridges. Base-rich soils appear to also be essential, although it is still unclear if this corresponds to physiological or ecological (lower competition) requirements

Learning from model errors: Can land use, edaphic and very high-resolution topo-climatic factors improve macroecological models of mountain grasslands?

Aim: Assess the potential of new predictors (land use, edaphic factors and high-resolution topographic and climatic variables, i.e., topo-climatic) to improve the prediction of plant community functional traits (specific leaf area, vegetative height and seed mass) and species richness in models of mountain grasslands. Location: The western Swiss Alps Methods: Using 912 grassland plots, we constructed predictive models for community-weighted means of plant traits and species richness using high resolution (25 m) topo-climatic predictors traditionally used in previous modelling studies in this area. In addition, 78 new plots were sampled for evaluation and error assessment in four narrower sets of homogenous conditions based on predictions by the topo-climatic models within two elevation belts (montane and alpine). New, finer-scale predictors were generated from direct field measurements or very high-resolution (5 m) numerical data. We then used multimodel inference to test the capacity of these finer predictors to explain part of the residual variance in the initial topo-climatic models. Results: We showed that the finer-scale predictors explained up to 44% of the residual variance in the classical topo-climatic models. The very high-resolution topographic position, soil C/N ratio and pH performed notably well in our analysis. Land use (farming intensity) was highlighted as potentially important in montane grasslands, but improvements were only significant for species richness predictions. Main conclusions: Compared with classical topo-climatic models, the new, finer-scale predictors significantly improved the prediction of all traits and species richness in alpine plant communities and that of specific leaf area and richness in montane grasslands. The differences in the importance of the predictors, dependent on both trait and position along the elevation gradient, highlight the different factors that shape the distribution of species and communities along elevation gradients

Disentangling the processes driving plant assemblages in mountain grasslands across spatial scales and environmental gradients

1. Habitat filtering and limiting similarity are well-documented ecological assembly processes that hierarchically filter species across spatial scales, from a regional pool to local assemblages. However, information on the effects of fine-scale spatial partitioning of species, working as an additional mechanism of coexistence, on community patterns, is much scarcer. 2. In this study, we quantified the importance of fine-scale spatial partitioning, relative to habitat filtering and limiting similarity, in structuring grassland communities in the western Swiss Alps. To do so, 298 vegetation plots (2 m × 2 m ) each with five nested subplots (20 cm × 20 cm) were used for trait based assembly tests (i.e. comparisons with several alternative null expectations), examining the observed plot and subplot level α-diversity (indicating habitat filtering and limiting similarity) and the between-subplot β-diversity of traits (indicating fine-scale spatial partitioning). We further assessed variations in the detected signatures of these assembly processes along a set of environmental gradients. 3. We found habitat filtering to be the dominating assembly process at the plot level with diminished effect at the subplot level, while limiting similarity prevailed at the subplot level with weaker average effect at the plot level. Plot-level limiting similarity was positively correlated with fine-scale partitioning suggesting that the trait divergence may result from a combination of competitive exclusion between functionally similar species and environmental micro-heterogeneities. Overall, signatures of assembly processes only marginally changed along environmental gradients but the observed trends were more prominent at the plot than at the subplot scale. Synthesis: Our study emphasises the importance of considering multiple assembly processes and traits simultaneously across spatial scales and environmental gradients to understand the complex drivers of plant community composition

Orexinergic Input to Dopaminergic Neurons of the Human Ventral Tegmental Area

The mesolimbic reward pathway arising from dopaminergic (DA) neurons of the ventral tegmental area (VTA) has been strongly implicated in reward processing and drug abuse. In rodents, behaviors associated with this projection are profoundly influenced by an orexinergic input from the lateral hypothalamus to the VTA. Because the existence and significance of an analogous orexigenic regulatory mechanism acting in the human VTA have been elusive, here we addressed the possibility that orexinergic neurons provide direct input to DA neurons of the human VTA. Dual-label immunohistochemistry was used and orexinergic projections to the VTA and to DA neurons of the neighboring substantia nigra (SN) were analyzed comparatively in adult male humans and rats. Orexin B-immunoreactive (IR) axons apposed to tyrosine hydroxylase (TH)-IR DA and to non-DA neurons were scarce in the VTA and SN of both species. In the VTA, 15.062.8% of TH-IR perikarya in humans and 3.260.3% in rats received orexin B-IR afferent contacts. On average, 0.2460.05 and 0.0560.005 orexinergic appositions per TH-IR perikaryon were detected in humans and rats, respectively. The majority(86–88%) of randomly encountered orexinergic contacts targeted the dendritic compartment of DA neurons. Finally, DA neurons of the SN also received orexinergic innervation in both species. Based on the observation of five times heavierorexinergic input to TH-IR neurons of the human, compared with the rat, VTA, we propose that orexinergic mechanism acting in the VTA may play just as important roles in reward processing and drug abuse in humans, as already established well in rodents

Decoupling of topsoil and subsoil controls on organic matter dynamics in the Swiss Alps

Our understanding of mechanisms governing soil organic matter (OM) stability is evolving. It is gradually becoming accepted that soil OM stability is not primarily regulated by the molecular structure of plant inputs, but instead by the biotic and abiotic properties of the edaphic environment. Moreover, several experimental studies conducted in artificial systems have suggested that mechanisms regulating OM stability may differ with depth in the soil profile. Up to now however, there is very limited field-scale evidence regarding the hierarchy of controls on soil OM dynamics and their changes with soil depth. In this study, we take advantage of the high heterogeneity of ecological conditions occurring in the alpine belt to identify the major determinants of OM dynamics and how their significance varies with depth in the soil profile. Aboveground litter, mineral topsoil, and subsoil samples originating from 46 soil profiles spanning a wide range of soil and vegetation types were analysed. We used Rock-Eval pyrolysis, a technique that investigates the thermal stability of OM, as an indicator of OM dynamics. Our results show a clear divergence in predictors of OM thermal stability in the litter, topsoil, and subsoil layers. The composition of OM correlated with its thermal stability in the litter layer but not in mineral soil horizons, where the supply rate of fresh organic material and the physical and chemical characteristics of the pedogenic environment appeared important instead. This study offers direct confirmation that soil OM dynamics are influenced by different ecosystem properties in each soil layer. This has important implications for our understanding of carbon cycling in soils under a changing climate

Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain

In this paper we present a low-cost approach to mapping vegetation cover by means of high-resolution close-range terrestrial photogrammetry. A total of 249 clusters of nine 1 m2 plots each, arranged in a 3 × 3 grid, were set up on 18 summits in Mediterranean mountain regions and in the Alps to capture images for photogrammetric processing and in-situ vegetation cover estimates. This was done with a hand-held pole-mounted digital single-lens reflex (DSLR) camera. Low-growing vegetation was automatically segmented using high-resolution point clouds. For classifying vegetation we used a two-step semi-supervised Random Forest approach. First, we applied an expert-based rule set using the Excess Green index (ExG) to predefine non-vegetation and vegetation points. Second, we applied a Random Forest classifier to further enhance the classification of vegetation points using selected topographic parameters (elevation, slope, aspect, roughness, potential solar irradiation) and additional vegetation indices (Excess Green Minus Excess Red (ExGR) and the vegetation index VEG). For ground cover estimation the photogrammetric point clouds were meshed using Screened Poisson Reconstruction. The relative influence of the topographic parameters on the vegetation cover was determined with linear mixed-effects models (LMMs). Analysis of the LMMs revealed a high impact of elevation, aspect, solar irradiation, and standard deviation of slope. The presented approach goes beyond vegetation cover values based on conventional orthoimages and in-situ vegetation cover estimates from field surveys in that it is able to differentiate complete 3D surface areas, including overhangs, and can distinguish between vegetation-covered and other surfaces in an automated manner. The results of the Random Forest classification confirmed it as suitable for vegetation classification, but the relative feature importance values indicate that the classifier did not leverage the potential of the included topographic parameters. In contrast, our application of LMMs utilized the topographic parameters and was able to reveal dependencies in the two biomes, such as elevation and aspect, which were able to explain between 87% and 92.5% of variance