Forecasting changes in population genetic structure of alpine plants in response to global warming.

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.

Species distributions and interactions in a changing world : from understanding to forecasting

Les écosystèmes fournissent de nombreuses ressources et services écologiques qui sont utiles à la population humaine. La biodiversité est une composante essentielle des écosystèmes et maintient de nombreux services. Afin d'assurer la permanence des services écosystémiques, des mesures doivent être prises pour conserver la biodiversité. Dans ce but, l'acquisition d'informations détaillées sur la distribution de la biodiversité dans l'espace est essentielle. Les modèles de distribution d'espèces (SDMs) sont des modèles empiriques qui mettent en lien des observations de terrain (présences ou absences d'une espèce) avec des descripteurs de l'environnement, selon des courbes de réponses statistiques qui décrive la niche réalisée des espèces. Ces modèles fournissent des projections spatiales indiquant les lieux les plus favorables pour les espèces considérées. Le principal objectif de cette thèse est de fournir des projections plus réalistes de la distribution des espèces et des communautés en montagne pour le climat présent et futur en considérant non-seulement des variables abiotiques mais aussi biotiques. Les régions de montagne et l'écosystème alpin sont très sensibles aux changements globaux et en même temps assurent de nombreux services écosystémiques. Cette thèse est séparée en trois parties : (i) fournir une meilleure compréhension du rôle des interactions biotiques dans la distribution des espèces et l'assemblage des communautés en montagne (ouest des Alpes Suisses), (ii) permettre le développement d'une nouvelle approche pour modéliser la distribution spatiale de la biodiversité, (iii) fournir des projections plus réalistes de la distribution future des espèces ainsi que de la composition des communautés. En me focalisant sur les papillons, bourdons et plantes vasculaires, j'ai détecté des interactions biotiques importantes qui lient les espèces entre elles. J'ai également identifié la signature du filtre de l'environnement sur les communautés en haute altitude confirmant l'utilité des SDMs pour reproduire ce type de processus. A partir de ces études, j'ai contribué à l'amélioration méthodologique des SDMs dans le but de prédire les communautés en incluant les interactions biotiques et également les processus non-déterministes par une approche probabiliste. Cette approche permet de prédire non-seulement la distribution d'espèces individuelles, mais également celle de communautés dans leur entier en empilant les projections (S-SDMs). Finalement, j'ai utilisé cet outil pour prédire la distribution d'espèces et de communautés dans le passé et le futur. En particulier, j'ai modélisé la migration post-glaciaire de Trollius europaeus qui est à l'origine de la structure génétique intra-spécifique chez cette espèce et évalué les risques de perte face au changement climatique. Finalement, j'ai simulé la distribution des communautés de bourdons pour le 21e siècle afin d'évaluer les changements probables dans ce groupe important de pollinisateurs. La diversité fonctionnelle des bourdons va être altérée par la perte d'espèces spécialistes de haute altitude et ceci va influencer la pollinisation des plantes en haute altitude. - Ecosystems provide a multitude of resources and ecological services, which are useful to human. Biodiversity is an essential component of those ecosystems and guarantee many services. To assure the permanence of ecosystem services for future generation, measure should be applied to conserve biodiversity. For this purpose, the acquisition of detailed information on how biodiversity implicated in ecosystem function is distributed in space is essential. Species distribution models (SDMs) are empirical models relating field observations to environmental predictors based on statistically-derived response surfaces that fit the realized niche. These models result in spatial predictions indicating locations of the most suitable environment for the species and may potentially be applied to predict composition of communities and their functional properties. The main objective of this thesis was to provide more accurate projections of species and communities distribution under current and future climate in mountains by considering not solely abiotic but also biotic drivers of species distribution. Mountain areas and alpine ecosystems are considered as particularly sensitive to global changes and are also sources of essential ecosystem services. This thesis had three main goals: (i) a better ecological understanding of biotic interactions and how they shape the distribution of species and communities, (ii) the development of a novel approach to the spatial modeling of biodiversity, that can account for biotic interactions, and (iii) ecologically more realistic projections of future species distributions, of future composition and structure of communities. Focusing on butterfly and bumblebees in interaction with the vegetation, I detected important biotic interactions for species distribution and community composition of both plant and insects along environmental gradients. I identified the signature of environmental filtering processes at high elevation confirming the suitability of SDMs for reproducing patterns of filtering. Using those case-studies, I improved SDMs by incorporating biotic interaction and accounting for non-deterministic processes and uncertainty using a probabilistic based approach. I used improved modeling to forecast the distribution of species through the past and future climate changes. SDMs hindcasting allowed a better understanding of the spatial range dynamic of Trollius europaeus in Europe at the origin of the species intra-specific genetic diversity and identified the risk of loss of this genetic diversity caused by climate change. By simulating the future distribution of all bumblebee species in the western Swiss Alps under nine climate change scenarios for the 21st century, I found that the functional diversity of this pollinator guild will be largely affected by climate change through the loss of high elevation specialists. In turn, this will have important consequences on alpine plant pollination.

Production of renewable polymers from crop plants

Plants produce a range of biopolymers for purposes such as maintenance of structural integrity, carbon storage, and defense against pathogens and desiccation. Several of these natural polymers are used by humans as food and materials, and increasingly as an energy carrier. In this review, we focus on plant biopolymers that are used as materials in bulk applications, such as plastics and elastomers, in the context of depleting resources and climate change, and consider technical and scientific bottlenecks in the production of novel or improved materials in transgenic or alternative crop plants. The biopolymers discussed are natural rubber and several polymers that are not naturally produced in plants, such as polyhydroxyalkanoates, fibrous proteins and poly-amino acids. In addition, monomers or precursors for the chemical synthesis of biopolymers, such as 4-hydroxybenzoate, itaconic acid, fructose and sorbitol, are discussed briefly

The role of mycorrhizas in more sustainable oil palm cultivation

Oil palm is a significant and developing crop in many developing countries. The introduction of oil palm puts pressure on natural resources because it is often planted in cleared-cut land that previously supported other crops or was forested. This has led to environmental concerns which require attention. Hence it is important that new plantations are managed in a sustainable way to reduce the impact of oil palm cultivation on ecosystems whilst maximising yield and productivity to farmers. The application of arbuscular mycorrhizal fungi (AMF) technology is one option that can benefit both agronomic plant health and ecosystems. AMF have the potential to increase conventional agricultural productivity and are crucial for the sustainable functioning of agricultural ecosystems. This paper provides an insight into how AMF application might benefit oil palm cultivation through more sustainable management and the practical use of AMF for oil palm plantations.

BIOMOD - a platform for ensemble forecasting of species distributions

BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

Impact of colonic cleansing on quality and diagnostic yield of colonoscopy: the European Panel of Appropriateness of Gastrointestinal Endoscopy European multicenter study.

BACKGROUND: The quality of colon cleansing is a major determinant of quality of colonoscopy. To our knowledge, the impact of bowel preparation on the quality of colonoscopy has not been assessed prospectively in a large multicenter study. Therefore, this study assessed the factors that determine colon-cleansing quality and the impact of cleansing quality on the technical performance and diagnostic yield of colonoscopy. METHODS: Twenty-one centers from 11 countries participated in this prospective observational study. Colon-cleansing quality was assessed on a 5-point scale and was categorized on 3 levels. The clinical indication for colonoscopy, diagnoses, and technical parameters related to colonoscopy were recorded. RESULTS: A total of 5832 patients were included in the study (48.7% men, mean age 57.6 [15.9] years). Cleansing quality was lower in elderly patients and in patients in the hospital. Procedures in poorly prepared patients were longer, more difficult, and more often incomplete. The detection of polyps of any size depended on cleansing quality: odds ratio (OR) 1.73: 95% confidence interval (CI)[1.28, 2.36] for intermediate-quality compared with low-quality preparation; and OR 1.46: 95% CI[1.11, 1.93] for high-quality compared with low-quality preparation. For polyps >10 mm in size, corresponding ORs were 1.0 for low-quality cleansing, OR 1.83: 95% CI[1.11, 3.05] for intermediate-quality cleansing, and OR 1.72: 95% CI[1.11, 2.67] for high-quality cleansing. Cancers were not detected less frequently in the case of poor preparation. CONCLUSIONS: Cleansing quality critically determines quality, difficulty, speed, and completeness of colonoscopy, and is lower in hospitalized patients and patients with higher levels of comorbid conditions. The proportion of patients who undergo polypectomy increases with higher cleansing quality, whereas colon cancer detection does not seem to critically depend on the quality of bowel preparation.

Forecasting the effects of global warming on biodiversity

The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.

Flowering date of taxonomic families predicts phenological sensitivity to temperature: Implications for forecasting the effects of climate change on unstudied taxa.

PREMISE OF THE STUDY: Numerous long-term studies in seasonal habitats have tracked interannual variation in first flowering date (FFD) in relation to climate, documenting the effect of warming on the FFD of many species. Despite these efforts, long-term phenological observations are still lacking for many species. If we could forecast responses based on taxonomic affinity, however, then we could leverage existing data to predict the climate-related phenological shifts of many taxa not yet studied. METHODS: We examined phenological time series of 1226 species occurrences (1031 unique species in 119 families) across seven sites in North America and England to determine whether family membership (or family mean FFD) predicts the sensitivity of FFD to standardized interannual changes in temperature and precipitation during seasonal periods before flowering and whether families differ significantly in the direction of their phenological shifts. KEY RESULTS: Patterns observed among species within and across sites are mirrored among family means across sites; early-flowering families advance their FFD in response to warming more than late-flowering families. By contrast, we found no consistent relationships among taxa between mean FFD and sensitivity to precipitation as measured here. CONCLUSIONS: Family membership can be used to identify taxa of high and low sensitivity to temperature within the seasonal, temperate zone plant communities analyzed here. The high sensitivity of early-flowering families (and the absence of early-flowering families not sensitive to temperature) may reflect plasticity in flowering time, which may be adaptive in environments where early-season conditions are highly variable among years.

Genetics of Parkinson's disease: the yield.

The discovery of genes implicated in familial forms of Parkinson's disease (PD) has provided new insights into the molecular events leading to neurodegeneration. Clinically, patients with genetically determined PD can be difficult to distinguish from those with sporadic PD. Monogenic causes include autosomal dominantly (SNCA, LRRK2, VPS35, EIF4G1) as well as recessively (PARK2, PINK1, DJ-1) inherited mutations. Additional recessive forms of parkinsonism present with atypical signs, including very early disease onset, dystonia, dementia and pyramidal signs. New techniques in the search for phenotype-associated genes (next-generation sequencing, genome-wide association studies) have expanded the spectrum of both monogenic PD and variants that alter risk to develop PD. Examples of risk genes include the two lysosomal enzyme coding genes GBA and SMPD1, which are associated with a 5-fold and 9-fold increased risk of PD, respectively. It is hoped that further knowledge of the genetic makeup of PD will allow designing treatments that alter the course of the disease.

The yield of high-density electric source imaging in focal epilepsy

Background: EEG is the cornerstone of epilepsy diagnostics and mandatory to determine the underlying epilepsy syndrome (e.g. focal vs idiopathic generalized). However, its potential as imaging tool is still underrecognized. In the present study, we aim to determine the prerequisites of maximal benefit of electric source imaging (ESI) to localize the irritative zone in patients with focal epilepsy. Methods: 150 patients suffering from focal epilepsy and with minimum 1 year post-operative follow-up were studied prospectively by reviewers blinded to the underlying diagnosis and outcome. We evaluated the influence of two important factors on sensitivity and specificity of ESI: the number of electrodes (low resolution, LR-ESI: \30 vs. high resolution, HR-ESI: 128-256 electrodes), and the use of individual MRI (i-MRI) vs. template MRI (t-MRI) as head model.Results: ESI had a sensitivity of 85% and a specificity of 87% when HR-ESI with i-MRI was used. Using LR-ESI, sensitivity decreased to 68%, or even 57% when only t-MRI was available. The sensitivity of HR-ESI/i-MRI compared favorably with those of MRI (76%), PET (69%) and ictal/interictal SPECT (64%).Interpretation: This study on a large patient group shows excellent sensitivity and specificity of ESI if 128 EEG channels or more are used for ESI and if the results are co-registered to the patient's individual MRI. Localization precision is as high as or even higher than established brain imaging techniques, providing excellent costeffectiveness in epilepsy evaluation. HR-ESI appears to be a valuable additional imaging tool, given that larger electrode arrays are easily and rapidly applied with modern EEG equipment and that structural MRI is nearly always available for these patients.

Factors promoting the exposure to bioaerosols among crop workers

Introduction. Agricultural workers are among the professional groups most at risk of developing acute or chronic respiratory problems. Despite this fact, the etiology of these occupational diseases is poorly known, even in important sectors of agriculture such as the crops sector. Cereals can be colonized by a large number of fungal species throughout the plants' growth, but also during grain storage. Some of these fungi deliver toxins that can have a serious impact on human health when they are ingested via wheat products. Although International and European legislation on contaminants in food, including mycotoxins, include measures to ensure protection of public health by setting down the maximum levels for certain contaminants, the risks associated with the inhalation of such molecules during grain handling remains poorly documented. Goal of study. This project's objective was to characterize worker exposure to pathogenic, irritative or allergenic microorganisms and to identify the abiotic or biotic factors that reduce the growth of these microorganisms in crops. Indeed, the proliferation of microorganisms on wheat is dependent on temperature, rainfall and human disturbance (e.g. usage of tillage, addition of fungicides). A change in the concentration of these microorganisms in the substrate will directly result in a change in the concentration of aerosolized particles of the same microorganisms. Therefore, the exposure of worker to bioaérosols will also change. The Vaud region of Switzerland is a perfect region for conduct such a project as weather conditions vary and agricultural land management programs are divers at a small geographic scale. Methods. Bioaerosols and wheat dust have been sampled during wheat harvesting of summer 2010 at 100 sites uniformly distributed in the Vaud region that are representative of the different agriculture practices. Personal exposure has been evaluated for different wheat related activities: harvesting, grain unload, baling straw, the cleaning of harvesters and silos. Aerosols have been sampled at a rate of 2L/min between 15 min to 4 hours (t) on a 5m PVC filter for estimating the total dust inhaled, on gelatine filter for the identification and quantification of molds, and on a 0.45um polycarbonate filter for endotoxin quantification. Altitude, temperature and annual average rainfall were considered for each site. The physical and chemical characteristics of soils were determined using the methods in effect at Sol Council (Nyon). Total dust has been quantified following NIOSH 0500 method. Reactive endotoxine activity has been determined with Limulus Amebocyte Lysate Assay. All molds have been identified by the pyrosequencing of ITS2 amplicons generated from bioaerosol or wheat dust genomic DNA. Results & Conclusions. Our results confirm the previous quantitative data on the worker exposure to wheat dust. In addition, they show that crop workers are systematically exposed to complex mixtures of allergens, irritants or cytotoxic components. The novelty of our study is the systematic detection of molds such as Fusarium - that is a mycotoxins producer - in the bioaerosols. The results are interpreted by taking in account the agriculture practice, the Phosphorus : Carbon : Nitrogen ratio of the soil, the altitude and the average of rainy days per year.

Yield of intermittent versus continuous EEG in comatose survivors of cardiac arrest treated with hypothermia.

INTRODUCTION: Electroencephalography (EEG) has a central role in the outcome prognostication in subjects with anoxic/hypoxic encephalopathy following a cardiac arrest (CA). Continuous EEG monitoring (cEEG) has been consistently developed and studied; however, its yield as compared to repeated standard EEG (sEEG) is unknown. METHODS: We studied a prospective cohort of comatose adults treated with therapeutic hypothermia (TH) after a CA. cEEG data regarding background activity and epileptiform components were compared to two 20 minute sEEG extracted from the cEEG recording (one during TH, and one in early normothermia). RESULTS: In this cohort, 34 recordings were studied. During TH, the agreement between cEEG and sEEG was 97.1% (95% CI: 84.6 - 99.9%) for background discontinuity and reactivity evaluation, while it was 94.1% (95% CI 80.3 - 99.2%) regarding epileptiform activity. In early normothermia, we did not find any discrepancies. Thus, concordance was very good during TH (kappa 0.83), and optimal during normothermia (kappa=1). The median delay between CA and the first EEG reactivity testing was 18 hours (range: 4.75 - 25) for patients with perfect agreement and 10 hours (range: 5.75 - 10.5) for the three patients in whom there were discordant findings (P=0.02, Wilcoxon). CONCLUSION: Standard intermittent EEG has comparable performance than continuous EEG both for variables important for outcome prognostication (EEG reactivity) and identification of epileptiform transients in this relatively small sample of comatose survivors of CA. This finding has an important practical implication, especially for centers where EEG resources are limited.