Combining niche modelling and landscape genetics to study local adaptation: A novel approach illustrated using alpine plants

Understanding the factors that shape adaptive genetic variation across species niches has become of paramount importance in evolutionary ecology, especially to understand how adaptation to changing climate affects the geographic range of species. The distribution of adaptive alleles in the ecological niche is determined by the emergence of novel mutations, their fitness consequences and gene flow that connects populations across species niches. Striking demographical differences and source sink dynamics of populations between the centre and the margin of the niche can play a major role in the emergence and spread of adaptive alleles. Although some theoretical predictions have long been proposed, the origin and distribution of adaptive alleles within species niches remain untested. In this paper, we propose and discuss a novel empirical approach that combines landscape genetics with species niche modelling, to test whether alleles that confer local adaptation are more likely to occur in either marginal or central populations of species niches. We illustrate this new approach by using a published data set of 21 alpine plant species genotyped with a total of 2483 amplified fragment length polymorphisms (AFLP), distributed over more than 1733 sampling sites across the Alps. Based on the assumption that alleles that were statistically associated with environmental variables were adaptive, we found that adaptive alleles in the margin of a species niche were also present in the niche centre, which suggests that adaptation originates in the niche centre. These findings corroborate models of species range evolution, in which the centre of the niche contributes to the emergence of novel adaptive alleles, which diffuse towards niche margins and facilitate niche and range expansion through subsequent local adaptation. Although these results need to be confirmed via fitness measurements in natural populations and functionally characterised genetic sequences, this study provides a first step towards understanding how adaptive genetic variation emerges and shapes species niches and geographic ranges along environmental gradients.

Study and modelling of the effect of herbicides pulse exposure on freshwater microalgae

De plus en plus de substances chimiques sont émises et détectées dans l'environnement.Parmi ces substances, on trouve les herbicides qui sont utilisés en agriculture pour luttercontre la présence des mauvaises herbes. Après leur application sur les sols, les herbicidespeuvent être entrainés par les eaux de pluie jusque dans les ruisseaux et les rivières. Lesconcentrations de ces substances varient donc de manière importante dans les systèmesaquatiques en période de pluie ou en période de temps sec. Des pics élevés de concentrationssont suivis de période de concentrations très faibles ou nulles. Les herbicides présents dans lescours d'eau peuvent engendrer des effets toxiques sur les algues et les plantes aquatiques. Orles tests classiques d'écotoxicologie effectués en laboratoire sont réalisés en exposant lesespèces vivantes à des polluants de manière continue. Ils ne permettent donc pas d'évaluer leseffets des concentrations fluctuantes comme celles des herbicides. Le but de cette thèse estd'étudier et de modéliser les effets des concentrations fluctuantes d'herbicide sur les espècesde microalgues vertes Scenedesmus vacuolatus et Pseudokirchneriella subcapitata. Desexpériences en laboratoire ont également été effectuées dans le but de valider le modèle.Quatre herbicides ont été testés. Il s'agit de l'atrazine (utilisé jusqu'à récemment pour lemaïs), du diuron (utilisé dans la vigne), de l'isoproturon (utilisé pour les céréales) et du Smétolachlore(utilisé pour le maïs). Les résultats de ce travail de thèse indiquent que les effetsdes concentrations fluctuantes d'herbicide peuvent être modélisés sur des algues d'eau douce.Le modèle est relativement simple pour les inhibiteurs de la photosynthèse tels que l'atrazine,le diuron ou l'isoproturon. Il nécessite la connaissance de deux paramètres, le taux decroissance de l'algue sans polluant et la courbe dose-réponse pour chaque substance.Cependant, des expériences supplémentaires doivent être réalisées si la substance étudiéeinduit un délai de l'effet et du rétablissement ou si une algue est cultivée avec une autre alguedans le même milieu de croissance. Le modèle pourrait également être adapté pour tenircompte des mélanges de substances. Appliqué pour prédire les effets sur les algues descénarios réels, le modèle montre que les longs pics de concentrations jouent le rôle le plusimportant. Il est donc crucial de les mesurer lors du monitoring des cours d'eau. D'autre part,une évaluation du risque effectuée avec ce modèle montre que l'impact des pics deconcentrations sur les espèces les plus sensibles est total. Cela met en évidence, une fois deplus, l'importance de tenir compte de ces concentrations fluctuantes dans l'évaluation durisque environnemental des herbicides, mais également des autres polluants.

Animal modelling for inherited central vision loss.

Disease-causing variants of a large number of genes trigger inherited retinal degeneration leading to photoreceptor loss. Because cones are essential for daylight and central vision such as reading, mobility, and face recognition, this review focuses on a variety of animal models for cone diseases. The pertinence of using these models to reveal genotype/phenotype correlations and to evaluate new therapeutic strategies is discussed. Interestingly, several large animal models recapitulate human diseases and can serve as a strong base from which to study the biology of disease and to assess the scale-up of new therapies. Examples of innovative approaches will be presented such as lentiviral-based transgenesis in pigs and adeno-associated virus (AAV)-gene transfer into the monkey eye to investigate the neural circuitry plasticity of the visual system. The models reported herein permit the exploration of common mechanisms that exist between different species and the identification and highlighting of pathways that may be specific to primates, including humans.

Modelling the consequences of a reduction in alcohol consumption among patients with alcohol dependence based on real-life observational data.

BACKGROUND: Most available pharmacotherapies for alcohol-dependent patients target abstinence; however, reduced alcohol consumption may be a more realistic goal. Using randomized clinical trial (RCT) data, a previous microsimulation model evaluated the clinical relevance of reduced consumption in terms of avoided alcohol-attributable events. Using real-life observational data, the current analysis aimed to adapt the model and confirm previous findings about the clinical relevance of reduced alcohol consumption. METHODS: Based on the prospective observational CONTROL study, evaluating daily alcohol consumption among alcohol-dependent patients, the model predicted the probability of drinking any alcohol during a given day. Predicted daily alcohol consumption was simulated in a hypothetical sample of 200,000 patients observed over a year. Individual total alcohol consumption (TAC) and number of heavy drinking days (HDD) were derived. Using published risk equations, probabilities of alcohol-attributable adverse health events (e.g., hospitalizations or death) corresponding to simulated consumptions were computed, and aggregated for categories of patients defined by HDDs and TAC (expressed per 100,000 patient-years). Sensitivity analyses tested model robustness. RESULTS: Shifting from >220 HDDs per year to 120-140 HDDs and shifting from 36,000-39,000 g TAC per year (120-130 g/day) to 15,000-18,000 g TAC per year (50-60 g/day) impacted substantially on the incidence of events (14,588 and 6148 events avoided per 100,000 patient-years, respectively). Results were robust to sensitivity analyses. CONCLUSIONS: This study corroborates the previous microsimulation modeling approach and, using real-life data, confirms RCT-based findings that reduced alcohol consumption is a relevant objective for consideration in alcohol dependence management to improve public health.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Modelling the disability severity score in motor insurance claims: an application to the Spanish case

Bodily injury claims have the greatest impact on the claim costs of motor insurance companies. The disability severity of motor claims is assessed in numerous European countries by means of score systems. In this paper a zero inflated generalized Poisson regression model is implemented to estimate the disability severity score of victims in-volved in motor accidents on Spanish roads. We show that the injury severity estimates may be automatically converted into financial terms by insurers at any point of the claim handling process. As such, the methodology described may be used by motor insurers operating in the Spanish market to monitor the size of bodily injury claims. By using insurance data, various applications are presented in which the score estimate of disability severity is of value to insurers, either for computing the claim compensation or for claim reserve purposes.

Modelling of North-West Russian market behavior considering technical restrictions of transmission grid

Nowadays the Finnish-Russian electric energy interaction is carried out through the back-to-back DC Vyborg substation and several power plants working synchronously with Finnish power system. Constant amount of energy flows in one direction — from Russia to Finland. But the process of electricity market development in Russian energy system makes the new possibilities of electrical cooperation available. The goal of master's thesis is to analyze the current state and possible evolution trends of North-West Russian system in relation with future possible change in power flow between Russia and Finland. The research is done by modelling the market of North-West Russia and examination of technical grid restrictions. The operational market models of North-West region of Russia for the years 2008 and 2015 were created during the research process. The description of prepared market models together with modelling results and their analysis are shown in the work. The description of power flow study process and results are also presented.

Reaction Kinetics and Viscosity Modelling in the Fusion Syntheses of Ca- and Ca/Mg-resinates

Rosin is a natural product from pine forests and it is used as a raw material in resinate syntheses. Resinates are polyvalent metal salts of rosin acids and especially Ca- and Ca/Mg- resinates find wide application in the printing ink industry. In this thesis, analytical methods were applied to increase general knowledge of resinate chemistry and the reaction kinetics was studied in order to model the non linear solution viscosity increase during resinate syntheses by the fusion method. Solution viscosity in toluene is an important quality factor for resinates to be used in printing inks. The concept of critical resinate concentration, c crit, was introduced to define an abrupt change in viscosity dependence on resinate concentration in the solution. The concept was then used to explain the non-inear solution viscosity increase during resinate syntheses. A semi empirical model with two estimated parameters was derived for the viscosity increase on the basis of apparent reaction kinetics. The model was used to control the viscosity and to predict the total reaction time of the resinate process. The kinetic data from the complex reaction media was obtained by acid value titration and by FTIR spectroscopic analyses using a conventional calibration method to measure the resinate concentration and the concentration of free rosin acids. A multivariate calibration method was successfully applied to make partial least square (PLS) models for monitoring acid value and solution viscosity in both mid-infrared (MIR) and near infrared (NIR) regions during the syntheses. The calibration models can be used for on line resinate process monitoring. In kinetic studies, two main reaction steps were observed during the syntheses. First a fast irreversible resination reaction occurs at 235 °C and then a slow thermal decarboxylation of rosin acids starts to take place at 265 °C. Rosin oil is formed during the decarboxylation reaction step causing significant mass loss as the rosin oil evaporates from the system while the viscosity increases to the target level. The mass balance of the syntheses was determined based on the resinate concentration increase during the decarboxylation reaction step. A mechanistic study of the decarboxylation reaction was based on the observation that resinate molecules are partly solvated by rosin acids during the syntheses. Different decarboxylation mechanisms were proposed for the free and solvating rosin acids. The deduced kinetic model supported the analytical data of the syntheses in a wide resinate concentration region, over a wide range of viscosity values and at different reaction temperatures. In addition, the application of the kinetic model to the modified resinate syntheses gave a good fit. A novel synthesis method with the addition of decarboxylated rosin (i.e. rosin oil) to the reaction mixture was introduced. The conversion of rosin acid to resinate was increased to the level necessary to obtain the target viscosity for the product at 235 °C. Due to a lower reaction temperature than in traditional fusion synthesis at 265 °C, thermal decarboxylation is avoided. As a consequence, the mass yield of the resinate syntheses can be increased from ca. 70% to almost 100% by recycling the added rosin oil.

Ultrafine grinding of FGD and phosphogypsum with an attrition bead mill and a jet mill : optimisation and modelling of grinding and mill comparison

Fine powders of minerals are used commonly in the paper and paint industry, and for ceramics. Research for utilizing of different waste materials in these applications is environmentally important. In this work, the ultrafine grinding of two waste gypsum materials, namely FGD (Flue Gas Desulphurisation) gypsum and phosphogypsum from a phosphoric acid plant, with the attrition bead mill and with the jet mill has been studied. The ' objective of this research was to test the suitability of the attrition bead mill and of the jet mill to produce gypsum powders with a particle size of a few microns. The grinding conditions were optimised by studying the influences of different operational grinding parameters on the grinding rate and on the energy consumption of the process in order to achieve a product fineness such as that required in the paper industry with as low energy consumption as possible. Based on experimental results, the most influential parameters in the attrition grinding were found to be the bead size, the stirrer type, and the stirring speed. The best conditions, based on the product fineness and specific energy consumption of grinding, for the attrition grinding process is to grind the material with small grinding beads and a high rotational speed of the stirrer. Also, by using some suitable grinding additive, a finer product is achieved with a lower energy consumption. In jet mill grinding the most influential parameters were the feed rate, the volumetric flow rate of the grinding air, and the height of the internal classification tube. The optimised condition for the jet is to grind with a small feed rate and with a large rate of volumetric flow rate of grinding air when the inside tube is low. The finer product with a larger rate of production was achieved with the attrition bead mill than with the jet mill, thus the attrition grinding is better for the ultrafine grinding of gypsum than the jet grinding. Finally the suitability of the population balance model for simulation of grinding processes has been studied with different S , B , and C functions. A new S function for the modelling of an attrition mill and a new C function for the modelling of a jet mill were developed. The suitability of the selected models with the developed grinding functions was tested by curve fitting the particle size distributions of the grinding products and then comparing the fitted size distributions to the measured particle sizes. According to the simulation results, the models are suitable for the estimation and simulation of the studied grinding processes.

Modelling nitrogen and phosphorus loads in a Mediterranean river catchment (La Tordera, NE Spain)

Human activities have resulted in increased nutrient levels in many rivers all over Europe. Sustainable management of river basins demands an assessment of the causes and consequences of human alteration of nutrient flows, together with an evaluation of management options. In the context of an integrated and interdisciplinary environmental assessment (IEA) of nutrient flows, we present and discuss the application of the nutrient emission model MONERIS (MOdelling Nutrient Emissions into River Systems) to the Catalan river basin, La Tordera (north-east Spain), for the period 1996–2002. After a successful calibration and verification process (Nash-Sutcliffe efficiencies E=0.85 for phosphorus and E=0.86 for nitrogen), the application of the model MONERIS proved to be useful in estimating nutrient loads. Crucial for model calibration, in-stream retention was estimated to be about 50 % of nutrient emissions on an annual basis. Through this process, we identified the importance of point sources for phosphorus emissions (about 94% for 1996–2002), and diffuse sources, especially inputs via groundwater, for nitrogen emissions (about 31% for 1996–2002). Despite hurdles related to model structure, observed loads, and input data encountered during the modelling process, MONERIS provided a good representation of the major interannual and spatial patterns in nutrient emissions. An analysis of the model uncertainty and sensitivity to input data indicates that the model MONERIS, even in data-starved Mediterranean catchments, may be profitably used by water managers for evaluating quantitative nutrient emission scenarios for the purpose of managing river basins. As an example of scenario modelling, an analysis of the changes in nutrient emissions through two different future scenarios allowed the identification of a set of relevant measures to reduce nutrient loads.

Predicting overall service quality: a structural equation modelling approach

In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct

Modelling syntectonic sedimentation: combining a discrete element model of tectonic. Deformation and process-based sedimentary Model in 3D.

This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.