Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Training Diaries during Altitude Training Camp in Two Olympic Champions: An Observational Case Study.

Traditionally, Live High-Train High (LHTH) interventions were adopted when athletes trained and lived at altitude to try maximising the benefits offered by hypoxic exposure and improving sea level performance. Nevertheless, scientific research has proposed that the possible benefits of hypoxia would be offset by the inability to maintain high training intensity at altitude. However, elite athletes have been rarely recruited as an experimental sample, and training intensity has almost never been monitored during altitude research. This case study is an attempt to provide a practical example of successful LHTH interventions in two Olympic gold medal athletes. Training diaries were collected and total training volumes, volumes at different intensities, and sea level performance recorded before, during and after a 3-week LHTH camp. Both athletes successfully completed the LHTH camp (2090 m) maintaining similar absolute training intensity and training volume at high-intensity (> 91% of race pace) compared to sea level. After the LHTH intervention both athletes obtained enhancements in performance and they won an Olympic gold medal. In our opinion, LHTH interventions can be used as a simple, yet effective, method to maintain absolute, and improve relative training intensity in elite endurance athletes. Key PointsElite endurance athletes, with extensive altitude training experience, can maintain similar absolute intensity during LHTH compared to sea level.LHTH may be considered as an effective method to increase relative training intensity while maintaining the same running/walking pace, with possible beneficial effects on sea level performance.Training intensity could be the key factor for successful high-level LHTH camp.

Comparison of "Live High-Train Low" in Normobaric versus Hypobaric Hypoxia.

We investigated the changes in both performance and selected physiological parameters following a Live High-Train Low (LHTL) altitude camp in either normobaric hypoxia (NH) or hypobaric hypoxia (HH) replicating current "real" practices of endurance athletes. Well-trained triathletes were split into two groups (NH, n = 14 and HH, n = 13) and completed an 18-d LHTL camp during which they trained at 1100-1200 m and resided at an altitude of 2250 m (PiO2  = 121.7±1.2 vs. 121.4±0.9 mmHg) under either NH (hypoxic chamber; FiO2 15.8±0.8%) or HH (real altitude; barometric pressure 580±23 mmHg) conditions. Oxygen saturations (SpO2) were recorded continuously daily overnight. PiO2 and training loads were matched daily. Before (Pre-) and 1 day after (Post-) LHTL, blood samples, VO2max, and total haemoglobin mass (Hbmass) were measured. A 3-km running test was performed near sea level twice before, and 1, 7, and 21 days following LHTL. During LHTL, hypoxic exposure was lower for the NH group than for the HH group (220 vs. 300 h; P<0.001). Night SpO2 was higher (92.1±0.3 vs. 90.9±0.3%, P<0.001), and breathing frequency was lower in the NH group compared with the HH group (13.9±2.1 vs. 15.5±1.5 breath.min-1, P<0.05). Immediately following LHTL, similar increases in VO2max (6.1±6.8 vs. 5.2±4.8%) and Hbmass (2.6±1.9 vs. 3.4±2.1%) were observed in NH and HH groups, respectively, while 3-km performance was not improved. However, 21 days following the LHTL intervention, 3-km run time was significantly faster in the HH (3.3±3.6%; P<0.05) versus the NH (1.2±2.9%; ns) group. In conclusion, the greater degree of race performance enhancement by day 21 after an 18-d LHTL camp in the HH group was likely induced by a larger hypoxic dose. However, one cannot rule out other factors including differences in sleeping desaturations and breathing patterns, thus suggesting higher hypoxic stimuli in the HH group.

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.

Prooxidant/Antioxidant Balance in Hypoxia: A Cross-Over Study on Normobaric vs. Hypobaric "Live High-Train Low".

"Live High-Train Low" (LHTL) training can alter oxidative status of athletes. This study compared prooxidant/antioxidant balance responses following two LHTL protocols of the same duration and at the same living altitude of 2250 m in either normobaric (NH) or hypobaric (HH) hypoxia. Twenty-four well-trained triathletes underwent the following two 18-day LHTL protocols in a cross-over and randomized manner: Living altitude (PIO2 = 111.9 ± 0.6 vs. 111.6 ± 0.6 mmHg in NH and HH, respectively); training "natural" altitude (~1000-1100 m) and training loads were precisely matched between both LHTL protocols. Plasma levels of oxidative stress [advanced oxidation protein products (AOPP) and nitrotyrosine] and antioxidant markers [ferric-reducing antioxidant power (FRAP), superoxide dismutase (SOD) and catalase], NO metabolism end-products (NOx) and uric acid (UA) were determined before (Pre) and after (Post) the LHTL. Cumulative hypoxic exposure was lower during the NH (229 ± 6 hrs.) compared to the HH (310 ± 4 hrs.; P<0.01) protocol. Following the LHTL, the concentration of AOPP decreased (-27%; P<0.01) and nitrotyrosine increased (+67%; P<0.05) in HH only. FRAP was decreased (-27%; P<0.05) after the NH while was SOD and UA were only increased following the HH (SOD: +54%; P<0.01 and UA: +15%; P<0.01). Catalase activity was increased in the NH only (+20%; P<0.05). These data suggest that 18-days of LHTL performed in either NH or HH differentially affect oxidative status of athletes. Higher oxidative stress levels following the HH LHTL might be explained by the higher overall hypoxic dose and different physiological responses between the NH and HH.

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.

Same Performance Changes after Live High-Train Low in Normobaric vs. Hypobaric Hypoxia.

PURPOSE: We investigated the changes in physiological and performance parameters after a Live High-Train Low (LHTL) altitude camp in normobaric (NH) or hypobaric hypoxia (HH) to reproduce the actual training practices of endurance athletes using a crossover-designed study. METHODS: Well-trained triathletes (n = 16) were split into two groups and completed two 18-day LTHL camps during which they trained at 1100-1200 m and lived at 2250 m (P i O2 = 111.9 ± 0.6 vs. 111.6 ± 0.6 mmHg) under NH (hypoxic chamber; FiO2 18.05 ± 0.03%) or HH (real altitude; barometric pressure 580.2 ± 2.9 mmHg) conditions. The subjects completed the NH and HH camps with a 1-year washout period. Measurements and protocol were identical for both phases of the crossover study. Oxygen saturation (S p O2) was constantly recorded nightly. P i O2 and training loads were matched daily. Blood samples and VO2max were measured before (Pre-) and 1 day after (Post-1) LHTL. A 3-km running-test was performed near sea level before and 1, 7, and 21 days after training camps. RESULTS: Total hypoxic exposure was lower for NH than for HH during LHTL (230 vs. 310 h; P < 0.001). Nocturnal S p O2 was higher in NH than in HH (92.4 ± 1.2 vs. 91.3 ± 1.0%, P < 0.001). VO2max increased to the same extent for NH and HH (4.9 ± 5.6 vs. 3.2 ± 5.1%). No difference was found in hematological parameters. The 3-km run time was significantly faster in both conditions 21 days after LHTL (4.5 ± 5.0 vs. 6.2 ± 6.4% for NH and HH), and no difference between conditions was found at any time. CONCLUSION: Increases in VO2max and performance enhancement were similar between NH and HH conditions.