Testing a new multigroup inference approach to reconstructing past environmental conditions

A new, quantitative, inference model for environmental reconstruction (transfer function), based for the first time on the simultaneous analysis of multigroup species, has been developed. Quantitative reconstructions based on palaeoecological transfer functions provide a powerful tool for addressing questions of environmental change in a wide range of environments, from oceans to mountain lakes, and over a range of timescales, from decades to millions of years. Much progress has been made in the development of inferences based on multiple proxies but usually these have been considered separately, and the different numeric reconstructions compared and reconciled post-hoc. This paper presents a new method to combine information from multiple biological groups at the reconstruction stage. The aim of the multigroup work was to test the potential of the new approach to making improved inferences of past environmental change by improving upon current reconstruction methodologies. The taxonomic groups analysed include diatoms, chironomids and chrysophyte cysts. We test the new methodology using two cold-environment training-sets, namely mountain lakes from the Pyrenees and the Alps. The use of multiple groups, as opposed to single groupings, was only found to increase the reconstruction skill slightly, as measured by the root mean square error of prediction (leave-one-out cross-validation), in the case of alkalinity, dissolved inorganic carbon and altitude (a surrogate for air-temperature), but not for pH or dissolved CO2. Reasons why the improvement was less than might have been anticipated are discussed. These can include the different life-forms, environmental responses and reaction times of the groups under study.

Bryozoans of Banyoles lake

Data for bryozoan species from Banyoles lake (NE Spain) are presented. Three species have been recorded: Fredericella sultana, Lophopus crystallinus and Plurnatella repens, the first two for the first time in the Iberian peninsula. An examination of the F. sultana colony and the statoblast observations of L. crystallinus and P. repens with the scanning electron rnicroswpe made possible the identification. Details of the floatoblast structure are given.

Impact of Study Design on Reported Incidences of Acute Mountain Sickness: A Systematic Review.

AIMS: Published incidences of acute mountain sickness (AMS) vary widely. Reasons for this variation, and predictive factors of AMS, are not well understood. We aimed to identify predictive factors that are associated with the occurrence of AMS, and to test the hypothesis that study design is an independent predictive factor of AMS incidence. We did a systematic search (Medline, bibliographies) for relevant articles in English or French, up to April 28, 2013. Studies of any design reporting on AMS incidence in humans without prophylaxis were selected. Data on incidence and potential predictive factors were extracted by two reviewers and crosschecked by four reviewers. Associations between predictive factors and AMS incidence were sought through bivariate and multivariate analyses for different study designs separately. Association between AMS incidence and study design was assessed using multiple linear regression. RESULTS: We extracted data from 53,603 subjects from 34 randomized controlled trials, 44 cohort studies, and 33 cross-sectional studies. In randomized trials, the median of AMS incidences without prophylaxis was 60% (range, 16%-100%); mode of ascent and population were significantly associated with AMS incidence. In cohort studies, the median of AMS incidences was 51% (0%-100%); geographical location was significantly associated with AMS incidence. In cross-sectional studies, the median of AMS incidences was 32% (0%-68%); mode of ascent and maximum altitude were significantly associated with AMS incidence. In a multivariate analysis, study design (p=0.012), mode of ascent (p=0.003), maximum altitude (p<0.001), population (p=0.002), and geographical location (p<0.001) were significantly associated with AMS incidence. Age, sex, speed of ascent, duration of exposure, or history of AMS were inconsistently reported and therefore not further analyzed. CONCLUSIONS: Reported incidences and identifiable predictive factors of AMS depend on study design.

Schistosoma mansoni and HIV acquisition in fishing communities of Lake Victoria, Uganda: a nested case-control study.

OBJECTIVE: It has been suggested that Schistosoma mansoni, which is endemic in African fishing communities, might increase susceptibility to human immunodeficiency virus (HIV) acquisition. If confirmed, this would be of great public health importance in these high HIV-risk communities. This study was undertaken to determine whether S. mansoni infection is a risk factor for HIV infection among the fishing communities of Lake Victoria, Uganda. We conducted a matched case-control study, nested within a prospective HIV incidence cohort, including 50 HIV seroconverters (cases) and 150 controls during 2009-2011. METHODS: S. mansoni infection prior to HIV seroconversion was determined by measuring serum circulating anodic antigen (CAA) in stored serum. HIV testing was carried out using the Determine rapid test and infection confirmed by enzyme-linked immunosorbent assays. RESULTS: About 49% of cases and 52% of controls had S. mansoni infection prior to HIV seroconversion (or at the time of a similar study visit, for controls): odds ratio, adjusting for ethnicity, religion, marital status, education, occupation, frequency of alcohol consumption in previous 3 months, number of sexual partners while drunk, duration of stay in the community, and history of schistosomiasis treatment in the past 2 years was 1.23 (95% CI 0.3-5.7) P = 0.79. S. mansoni infections were chronic (with little change in status between enrolment and HIV seroconversion), and there was no difference in median CAA concentration between cases and controls. CONCLUSIONS: These results do not support the hypothesis that S. mansoni infection promotes HIV acquisition.

Sedimentology and Stratigraphy of the Pleistocene sediments in Lake Llauset (Southern Pyrenees, Spain)-a first approach

The high alpine valleys in the Southem Pyrenees are characterised by a many small lakes and ponds. They occur above 2000 m and are said to have been formed by glacial erosion. The sediments in these basins should, therefore, contain s t p tigraphic information since deglaciation, at least. An interesting and may be one of the most important of these basins is Lake Llauset in the Alta Ribagorca. The Llauset basin has recently been developped for hydsopower production. In conection with the construction of the retaining wall at the 'Riegel' the sedimentary filling of the lake basin could be investigated, and the first sedimentological and stratigraphicalresults are presented.

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

Macrofossils in Raraku Lake (Easter Island) integrated with sedimentary and geochemical records towards a palaeoecological synthesis for the last 34,000 years

Macrofossil analysis of a composite 19 m long sediment core from Rano Raraku Lake (Easter Island)was related to litho-sedimentary and geochemical features of the sediment. Strong stratigraphical patterns are shown by indirect gradient analyses of the data. The good correspondence between the stratigraphical patterns derived from macrofossil (Correspondence Analysis) and sedimentary and geochemical data (Principal Component Analysis) shows that macrofossil associations provide sound palaeolimnological information in conjunction with sedimentary data. The main taphonomic factors in fluencing the macrofossil assemblages are run-off from the catchment, the littoral plant belt, and the depositional environment within the basin. Five main stages during the last 34,000 calibrated years BP (cal yr BP) are characterised from the lithological, geochemical, and macrofossil data. From 34 to 14.6 cal kyr BP (last glacial period) the sediments were largely derived from the catchment, indicating a high energy lake environment with much erosion and run-off bringing abundant plant trichomes, lichens, and mosses into the centre of Raraku Lake.

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