25 years of movement monitoring on the south peak of Turtle mountain: Understanding the hazard

En 1981, le gouvernement de l'Alberta a amélioré la surveillance de la pointe sud « South Peak » de la montagne Turtle, sur la frontière sud du glissement Frank de 1903. Le programme de surveillance vise à comprendre les taux de déformation des fissures larges et profondes sur « South Peak », et à prédire une seconde avalanche rocheuse sur la montagne. Le programme de surveillance consiste à installer un complément de points statiques et de stations suivies à distance, qui sont mesurés périodiquement. Des données climatiques, microsismiques et de déformation sont recueillies automatiquement à intervalles journaliers, et sont archivées. À la fin des années 1980, le financement pour le développement du programme de surveillance a cessé et quelques installations se sont détériorées. Entre mai 2004 et septembre 2006, des lectures sur les points de surveillance encore fonctionnels ont été compilées et interprétées. De plus, les lectures prélevées auparavant ont été réinterprétées à partir des connaissances récentes sur les modèles de mouvement à court terme et les influences climatiques. Ces observations ont été comparées à des récentes observations aériennes d'un modèle digital d'élévation, provenant de « light detection and ranging (LiDAR) », et des photos de terrain, afin d'estimer plus précisément les taux, l'étendue et la distribution des mouvements pour les derniers 25 ans.

Influence of the world's most challenging mountain ultra-marathon on energy cost and running mechanics

PURPOSE: To examine the effects of the world's most challenging mountain ultra-marathon (Tor des Géants(®) 2012) on the energy cost of three types of locomotion (cycling, level and uphill running) and running kinematics. METHODS: Before (pre-) and immediately after (post-) the competition, a group of ten male experienced ultra-marathon runners performed in random order three submaximal 4-min exercise trials: cycling at a power of 1.5 W kg(-1) body mass; level running at 9 km h(-1) and uphill running at 6 km h(-1) at an inclination of +15 % on a motorized treadmill. Two video cameras recorded running mechanics at different sampling rates. RESULTS: Between pre- and post-, the uphill-running energy cost decreased by 13.8 % (P = 0.004); no change was noted in the energy cost of level running or cycling (NS). There was an increase in contact time (+10.3 %, P = 0.019) and duty factor (+8.1 %, P = 0.001) and a decrease in swing time (-6.4 %, P = 0.008) in the uphill-running condition. CONCLUSION: After this extreme mountain ultra-marathon, the subjects modified only their uphill-running patterns for a more economical step mechanics.

Spatial predictions of land-use transitions and associated threats to biodiversity: the case of forest regrowth in mountain grasslands

Question Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location Western Swiss Alps (4003210m a.s.l.). Methods We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for the management and conservation of biodiversity at intermediate elevations. Conclusions Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

The increase in hydric volume is associated to contractile impairment in the calf after the world's most extreme mountain ultra-marathon

BACKGROUND: Studies have recently focused on the effect of running a mountain ultra-marathon (MUM) and their results show muscular inflammation, damage and force loss. However, the link between peripheral oedema and muscle force loss is not really established. We tested the hypothesis that, after a MUM, lower leg muscles' swelling could be associated with muscle force loss. The knee extensor (KE) and the plantar flexor (PF) muscles' contractile function was measured by supramaximal electrical stimulations, potentiated low- and high-frequency doublets (PS10 and PS100) of the KE and the PF were measured by transcutaneous electrical nerve stimulation and bioimpedance was used to assess body composition in the runners (n = 11) before (Pre) and after (Post) the MUM and compared with the controls (n = 8). RESULTS: The maximal voluntary contraction of the KE and the PF significantly decreased by 20 % Post-MUM in the runners. Hydration of the non-fat mass (NF-Hyd) and extracellular water volume (Ve) were increased by 12 % Post-MUM (p < 0.001) in the runners. Calf circumference (+2 %, p < 0.05) was also increased. Significant relationships were found for percentage increases in Ve and NF-Hyd with percentage decrease in PS10 of the PF (r = -0.68 and r = -0.70, p < 0.05) and with percentage increase of calf circumference (r = 0.72 and r = 0.73, p < 0.05) in the runners. CONCLUSIONS: The present study suggests that increases in circumference and in hydric volume are associated to contractile impairment in the calf in ultra-marathon runners.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition