Effect of spatial processes on the evolution of ecological niches and dispersal in metacommunity systems

RésuméLa coexistence de nombreuses espèces différentes a de tout temps intrigué les biologistes. La diversité et la composition des communautés sont influencées par les perturbations et l'hétérogénéité des conditions environnementales. Bien que dans la nature la distribution spatiale des conditions environnementales soit généralement autocorrélée, cet aspect est rarement pris en compte dans les modèles étudiant la coexistence des espèces. Dans ce travail, nous avons donc abordé, à l'aide de simulations numériques, la coexistence des espèces ainsi que leurs caractéristiques au sein d'un environnement autocorrélé.Afin de prendre en compte cet élément spatial, nous avons développé un modèle de métacommunauté (un ensemble de communautés reliées par la dispersion des espèces) spatialement explicite. Dans ce modèle, les espèces sont en compétition les unes avec les autres pour s'établir dans un nombre de places limité, dans un environnement hétérogène. Les espèces sont caractérisées par six traits: optimum de niche, largeur de niche, capacité de dispersion, compétitivité, investissement dans la reproduction et taux de survie. Nous nous sommes particulièrement intéressés à l'influence de l'autocorrélation spatiale et des perturbations sur la diversité des espèces et sur les traits favorisés dans la métacommunauté. Nous avons montré que l'autocorrélation spatiale peut avoir des effets antagonistes sur la diversité, en fonction du taux de perturbations considéré. L'influence de l'autocorrélation spatiale sur la capacité de dispersion moyenne dans la métacommunauté dépend également des taux de perturbations et survie. Nos résultats ont aussi révélé que de nombreuses espèces avec différents degrés de spécialisation (i.e. différentes largeurs de niche) peuvent coexister. Toutefois, les espèces spécialistes sont favorisées en absence de perturbations et quand la dispersion est illimitée. A l'opposé, un taux élevé de perturbations sélectionne des espèces plus généralistes, associées avec une faible compétitivité.L'autocorrélation spatiale de l'environnement, en interaction avec l'intensité des perturbations, influence donc de manière considérable la coexistence ainsi que les caractéristiques des espèces. Ces caractéristiques sont à leur tour souvent impliquées dans d'importants processus, comme le fonctionnement des écosystèmes, la capacité des espèces à réagir aux invasions, à la fragmentation de l'habitat ou aux changements climatiques. Ce travail a permis une meilleure compréhension des mécanismes responsables de la coexistence et des caractéristiques des espèces, ce qui est crucial afin de prédire le devenir des communautés naturelles dans un environnement changeant.AbstractUnderstanding how so many different species can coexist in nature is a fundamental and long-standing question in ecology. Community diversity and composition are known to be influenced by heterogeneity in environmental conditions and disturbance. Though in nature the spatial distribution of environmental conditions is frequently autocorrelated, this aspect is seldom considered in models investigating species coexistence. In this work, we thus addressed several questions pertaining to species coexistence and composition in spatially autocorrelated environments, with a numerical simulations approach.To take into account this spatial aspect, we developed a spatially explicit model of metacommunity (a set of communities linked by dispersal of species). In this model, species are trophically equivalent, and compete for space in a heterogeneous environment. Species are characterized by six life-history traits: niche optimum, niche breadth, dispersal, competitiveness, reproductive investment and survival rate. We were particularly interested in the influence of environmental spatial autocorrelation and disturbance on species diversity and on the traits of the species favoured in the metacommunity. We showed that spatial autocorrelation can have antagonistic effects on diversity depending on disturbance rate. Similarly, spatial autocorrelation interacted with disturbance rate and survival rate to shape the mean dispersal ability observed in the metacommunity. Our results also revealed that many species with various degrees of specialization (i.e. different niche breadths) can coexist together. However specialist species were favoured in the absence of disturbance, and when dispersal was unlimited. In contrast, high disturbance rate selected for more generalist species, associated with low competitive ability.The spatial structure of the environment, together with disturbance and species traits, thus strongly impacts species diversity and, more importantly, species composition. Species composition is known to affect several important metacommunity properties such as ecosystem functioning, resistance and reaction to invasion, to habitat fragmentation and to climate changes. This work allowed a better understanding of the mechanisms responsible for species composition, which is of crucial importance to predict the fate of natural metacommunities in changing environments

Facilitatory and interfering effects of neighbourhood density on speech production: Evidence from aphasic errors.

In a system where tens of thousands of words are made up of a limited number of phonemes, many words are bound to sound alike. This similarity of the words in the lexicon as characterized by phonological neighbourhood density (PhND) has been shown to affect speed and accuracy of word comprehension and production. Whereas there is a consensus about the interfering nature of neighbourhood effects in comprehension, the language production literature offers a more contradictory picture with mainly facilitatory but also interfering effects reported on word production. Here we report both of these two types of effects in the same study. Multiple regression mixed models analyses were conducted on PhND effects on errors produced in a naming task by a group of 21 participants with aphasia. These participants produced more formal errors (interfering effect) for words in dense phonological neighbourhoods, but produced fewer nonwords and semantic errors (a facilitatory effect) with increasing density. In order to investigate the nature of these opposite effects of PhND, we further analysed a subset of formal errors and nonword errors by distinguishing errors differing on a single phoneme from the target (corresponding to the definition of phonological neighbours) from those differing on two or more phonemes. This analysis confirmed that only formal errors that were phonological neighbours of the target increased in dense neighbourhoods, while all other errors decreased. Based on additional observations favouring a lexical origin of these formal errors (they exceeded the probability of producing a real-word error by chance, were of a higher frequency, and preserved the grammatical category of the targets), we suggest that the interfering effect of PhND is due to competition between lexical neighbours and target words in dense neighbourhoods.

Occupational exposure to diisononyl phthalate (DiNP) in polyvinyl chloride processing operations

PURPOSE: Diisononyl phthalate (DiNP) is primarily used as a plasticizer in polyvinyl chloride (PVC) materials. While information is available on general population exposure to DiNP, occupational exposure data are lacking. We present DiNP metabolite urinary concentrations in PVC processing workers, estimate DiNP daily intake for these workers, and compare worker estimates to other populations. METHODS: We assessed DiNP exposure in participants from two companies that manufactured PVC materials, a PVC film manufacturer (n = 25) and a PVC custom compounder (n = 12). A mid-shift and end-shift urine sample was collected from each participant and analyzed for the DiNP metabolite mono(carboxy-isooctyl) phthalate (MCiOP). Mixed models were used to assess the effect on MCiOP concentrations of a worker being assigned to (1) a task using DiNP and (2) a shift where DiNP was used. A simple pharmacokinetic model was used to estimate DiNP daily intake from the MCiOP concentrations. RESULTS: Creatinine-adjusted MCiOP urinary concentrations ranged from 0.42-80 μg/g in PVC film and from 1.11-13.4 μg/g in PVC compounding. PVC film participants who worked on a task using DiNP (n = 7) had the highest MCiOP geometric mean (GM) end-shift concentration (25.2 μg/g), followed by participants who worked on a shift where DiNP was used (n = 11) (17.7 μg/g) as compared to participants with no task (2.92 μg/g) or shift (2.08 μg/g) exposure to DiNP. The GM end-shift MCiOP concentration in PVC compounding participants (4.80 μg/g) was comparable to PVC film participants with no task or shift exposure to DiNP. Because no PVC compounding participants were assigned to tasks using DINP on the day sampled, DiNP exposure in this company may be underestimated. The highest DiNP intake estimate was 26 μg/kg/day. CONCLUSION: Occupational exposure to DiNP associated with PVC film manufacturing tasks were substantially higher (sixfold to tenfold) than adult general population exposures; however, all daily intake estimates were less than 25% of current United States or European acceptable or tolerable daily intake estimates. Further characterization of DiNP occupational exposures in other industries is recommended.

Analysis of Industrial Granular Flow Applications by Using Advanced Collision Models

Granular flow phenomena are frequently encountered in the design of process and industrial plants in the traditional fields of the chemical, nuclear and oil industries as well as in other activities such as food and materials handling. Multi-phase flow is one important branch of the granular flow. Granular materials have unusual kinds of behavior compared to normal materials, either solids or fluids. Although some of the characteristics are still not well-known yet, one thing is confirmed: the particle-particle interaction plays a key role in the dynamics of granular materials, especially for dense granular materials. At the beginning of this thesis, detailed illustration of developing two models for describing the interaction based on the results of finite-element simulation, dimension analysis and numerical simulation is presented. The first model is used to describing the normal collision of viscoelastic particles. Based on some existent models, more parameters are added to this model, which make the model predict the experimental results more accurately. The second model is used for oblique collision, which include the effects from tangential velocity, angular velocity and surface friction based on Coulomb's law. The theoretical predictions of this model are in agreement with those by finite-element simulation. I n the latter chapters of this thesis, the models are used to predict industrial granular flow and the agreement between the simulations and experiments also shows the validation of the new model. The first case presents the simulation of granular flow passing over a circular obstacle. The simulations successfully predict the existence of a parabolic steady layer and show how the characteristics of the particles, such as coefficients of restitution and surface friction affect the separation results. The second case is a spinning container filled with granular material. Employing the previous models, the simulation could also reproduce experimentally observed phenomena, such as a depression in the center of a high frequency rotation. The third application is about gas-solid mixed flow in a vertically vibrated device. Gas phase motion is added to coherence with the particle motion. The governing equations of the gas phase are solved by using the Large eddy simulation (LES) and particle motion is predicted by using the Lagrangian method. The simulation predicted some pattern formation reported by experiment.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Early selection in open-pollinated Eucalyptus families based on competition covariates

The objetive of this work was to evaluate the influence of intergenotypic competition in open-pollinated families of Eucalyptus and its effects on early selection efficiency. Two experiments were carried out, in which the timber volume was evaluated at three ages, in a randomized complete block design. Data from the three years of evaluation (experiment 1, at 2, 4, and 7 years; and experiment 2, at 2, 5, and 7 years) were analyzed using mixed models. The following were estimated: variance components, genetic parameters, selection gains, effective number, early selection efficiency, selection gain per unit time, and coincidence of selection with and without the use of competition covariates. Competition effect was nonsignificant for ages under three years, and adjustment using competition covariates was unnecessary. Early selection for families is effective; families that have a late growth spurt are more vulnerable to competition, which markedly impairs ranking at the end of the cycle. Early selection is efficient according to all adopted criteria, and the age of around three years is the most recommended, given the high efficiency and accuracy rate in the indication of trees and families. The addition of competition covariates at the end of the cycle improves early selection efficiency for almost all studied criteria.

Semivariogram models for estimating fig fly population density throughout the year

The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months) has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.

Effect of water contamination on the shear bond strength of five orthodontic adhesives

Objectives: To evaluate the shear bond strength and site of failure of brackets bonded to dry and wet enamel. Study design: 50 teeth were divided into ten groups of 5 teeth each (10 surfaces). In half the groups enamel was kept dry before bonding, and in the other half distilled water was applied to wet the surface after etching. The following groups were established: 1)Acid/Transbond-XT (dry/wet) XT; 2) Transbond Plus Self Etching Primer (TSEP)/Transbond-XT paste (dry/wet); 3) Concise (dry), Transbond MIP/Concise (wet), 4) FujiOrtho-LC (dry/wet); 5) SmartBond (dry/wet). Brackets were bonded to both buccal and lingual surfaces. Specimens were stored in distilled water (24 hours at 37ºC) and thermocycled. Brackets were debonded using a Universal testing machine (cross-head speed 1 mm/min). Failure sites were classified using a stereomicroscope. Results: No significant differences in bond strength were detected between the adhesives under wet and dry conditions except for Smart- Bond, whose bond strength was significantly lower under dry conditions. For all the adhesives most bond failures were of mixed site location except for Smartbond, which failed at the adhesive-bracket interface. Conclusions: Under wet conditions the bonding capacity of the adhesives tested was similar than under dry conditions, with the exception of SmartBond which improved under wet conditions

Thermogenesis in obese women: effect of fructose vs. glucose added to a meal.

To assess the effect of a fructose meal on resting energy expenditure (EE), indirect calorimetry was used in 23 women (10 lean and 13 obese) for 30 min before and 6 h after the ingestion of a mixed meal containing 20% protein, 33% fat, and either 75 g glucose or 75 g fructose as carbohydrate source (47%). Expressed as a percentage of the energy content of the meal, the thermogenic response to the fructose meal was significantly greater (10.2 +/- 0.5%) than that of the glucose meal (8.4 +/- 0.4%, P less than 0.01). This difference was still apparent when the lean and obese women were considered separately. The mean respiratory quotient during the 6-h postprandial period was significantly greater (P less than 0.01) for the fructose (0.85 +/- 0.01) than for the glucose meal (0.83 +/- 0.01) in the combined subjects. In addition, cumulative carbohydrate oxidation was significantly greater after the fructose than after the glucose meal (51.1 +/- 2.3 vs. 40.9 +/- 2.0 g/6 h, respectively, P less than 0.01). Only small changes were observed in postprandial plasma levels of glucose and insulin after the fructose meal, but the plasma levels of lactate increased more with fructose than with the glucose meal. These results suggest that there might be some advantages (higher thermogenesis and carbohydrate oxidations) in using fructose as part of the carbohydrate source in diet of people with obesity and/or insulin resistance.

Combined effect of tobacco and alcohol on laryngeal cancer risk : a case-control study

OBJECTIVE: To provide information on the effects of alcohol and tobacco on laryngeal cancer and its subsites. METHODS: This was a case-control study conducted between 1992 and 2000 in northern Italy and Switzerland. A total of 527 cases of incident squamous-cell carcinoma of the larynx and 1297 hospital controls frequency-matched with cases on age, sex, and area of residence were included. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were estimated using multiple logistic regression. RESULTS: In comparison with never smokers, ORs were 19.8 for current smokers and 7.0 for ex-smokers. The risk increased in relation to the number of cigarettes (OR = 42.9 for > or = 25 cigarettes/day) and for duration of smoking (OR = 37.2 for > or = 40 years). For alcohol, the risk increased in relation to number of drinks (OR = 5.9 for > or = 56 drinks per week). Combined alcohol and tobacco consumption showed a multiplicative (OR = 177) rather than an additive risk. For current smokers and current drinkers the risk was higher for supraglottis (ORs 54.9 and 2.6, respectively) than for glottis (ORs 7.4 and 1.8) and others subsites (ORs 10.9 and 1.9). CONCLUSIONS: Our study shows that both cigarette smoking and alcohol drinking are independent risk factors for laryngeal cancer. Heavy consumption of alcohol and cigarettes determined a multiplicative risk increase, possibly suggesting biological synergy.

Effect of meal ingestion on liver stiffness in patients with cirrhosis and portal hypertension.

BACKGROUND AND AIMS: Liver stiffness is increasingly used in the non-invasive evaluation of chronic liver diseases. Liver stiffness correlates with hepatic venous pressure gradient (HVPG) in patients with cirrhosis and holds prognostic value in this population. Hence, accuracy in its measurement is needed. Several factors independent of fibrosis influence liver stiffness, but there is insufficient information on whether meal ingestion modifies liver stiffness in cirrhosis. We investigated the changes in liver stiffness occurring after the ingestion of a liquid standard test meal in this population. METHODS: In 19 patients with cirrhosis and esophageal varices (9 alcoholic, 9 HCV-related, 1 NASH; Child score 6.9±1.8), liver stiffness (transient elastography), portal blood flow (PBF) and hepatic artery blood flow (HABF) (Doppler-Ultrasound) were measured before and 30 minutes after receiving a standard mixed liquid meal. In 10 the HVPG changes were also measured. RESULTS: Post-prandial hyperemia was accompanied by a marked increase in liver stiffness (+27±33%; p<0.0001). Changes in liver stiffness did not correlate with PBF changes, but directly correlated with HABF changes (r = 0.658; p = 0.002). After the meal, those patients showing a decrease in HABF (n = 13) had a less marked increase of liver stiffness as compared to patients in whom HABF increased (n = 6; +12±21% vs. +62±29%,p<0.0001). As expected, post-prandial hyperemia was associated with an increase in HVPG (n = 10; +26±13%, p = 0.003), but changes in liver stiffness did not correlate with HVPG changes. CONCLUSIONS: Liver stiffness increases markedly after a liquid test meal in patients with cirrhosis, suggesting that its measurement should be performed in standardized fasting conditions. The hepatic artery buffer response appears an important factor modulating postprandial changes of liver stiffness. The post-prandial increase in HVPG cannot be predicted by changes in liver stiffness.

Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

Automated formulation of optimisation models for steel beam structures

Over 70% of the total costs of an end product are consequences of decisions that are made during the design process. A search for optimal cross-sections will often have only a marginal effect on the amount of material used if the geometry of a structure is fixed and if the cross-sectional characteristics of its elements are property designed by conventional methods. In recent years, optimalgeometry has become a central area of research in the automated design of structures. It is generally accepted that no single optimisation algorithm is suitable for all engineering design problems. An appropriate algorithm, therefore, mustbe selected individually for each optimisation situation. Modelling is the mosttime consuming phase in the optimisation of steel and metal structures. In thisresearch, the goal was to develop a method and computer program, which reduces the modelling and optimisation time for structural design. The program needed anoptimisation algorithm that is suitable for various engineering design problems. Because Finite Element modelling is commonly used in the design of steel and metal structures, the interaction between a finite element tool and optimisation tool needed a practical solution. The developed method and computer programs were tested with standard optimisation tests and practical design optimisation cases. Three generations of computer programs are developed. The programs combine anoptimisation problem modelling tool and FE-modelling program using three alternate methdos. The modelling and optimisation was demonstrated in the design of a new boom construction and steel structures of flat and ridge roofs. This thesis demonstrates that the most time consuming modelling time is significantly reduced. Modelling errors are reduced and the results are more reliable. A new selection rule for the evolution algorithm, which eliminates the need for constraint weight factors is tested with optimisation cases of the steel structures that include hundreds of constraints. It is seen that the tested algorithm can be used nearly as a black box without parameter settings and penalty factors of the constraints.

A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

An expression of mixed animal model equations to account for different means and variances in the base population

This paper presents a general expression to predict breeding values using animal models when the base population is selected, i.e. the means and variances of breeding values in the base generation differ among individuals. Rules for forming the mixed model equations are also presented. A numerical example illustrates the procedure.