272 resultados para Connectivity Patterns


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The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.

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Summary Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In my study, I developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, I assessed the effect of scale on predictor variables and geographic projections of SDM. I also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, I used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, I showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe 61 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the warmer conditions as far as competition is low However, in subalpine grasslands, competition of already present species is probably important and limit establishment of newly arrived species. Results from future simulations also showed that heavy extinctions of alpine plants may start already in 2040, but the latest in 2080. My study also highlighted the importance of fine scale and regional. assessments of climate change impact on mountain vegetation, using more direct predictor variables. Indeed, predictions at the continental scale may fail to predict local refugees or local extinctions, as well as loss of connectivity between local populations. On the other hand, migrations of low-elevation species to higher altitude may be difficult to predict at the local scale. Résumé La forme conique des montagnes ainsi que la diminution de surface dans les hautes altitudes sont reconnues pour exposer plus sensiblement les écosystèmes de montagne au réchauffement global. En outre, les systèmes de montagne seront sans doute soumis durant le 21ème siècle à un réchauffement deux à trois fois plus rapide que celui mesuré durant le 20ème siècle. Dans ce contexte, les modèles prédictifs de distribution géographique de la végétation se sont imposés comme des outils puissants pour de rapides évaluations de l'impact des changements climatiques et de la transformation du paysage par l'homme sur la végétation. Dans mon étude, j'ai développé de nouvelles variables prédictives pour les modèles de distribution, spécifiques à la projection géographique présente et future des plantes dans un système de montagne, en utilisant les Préalpes vaudoises comme zone d'échantillonnage. La méso- et la microtopographie étant particulièrement adaptées pour expliquer les patrons de distribution géographique des plantes dans un environnement montagneux, j'ai testé les effets d'échelle sur les variables prédictives et sur les projections des modèles de distribution. J'ai aussi développé un cadre méthodologique pour tester la robustesse potentielle des modèles lors de projections pour le futur. Finalement, j'ai utilisé un automate cellulaire pour simuler de manière dynamique la migration future des plantes dans le paysage et dans quatre scénarios de changement climatique pour le 21ème siècle. J'ai intégré dans ces simulations des mécanismes et des distances plus réalistes de dispersion de graines. J'ai pu montrer, avec les simulations les plus réalistes, que près du tiers des 284 espèces considérées (28.5%) pourraient être menacées d'extinction en 2100 dans le cas du plus sévère scénario de changement climatique A1. Pour le moins sévère des scénarios B1, seulement 4.6% des espèces sont menacées d'extinctions, mais 54% (153 espèces) risquent de perdre plus 80% de leur habitat initial. Les résultats de monitoring des changements de végétation dans le passé montrent que les plantes peuvent réagir rapidement au réchauffement climatique si la compétition est faible. Dans les prairies subalpines, les espèces déjà présentes limitent certainement l'arrivée de nouvelles espèces par effet de compétition. Les résultats de simulation pour le futur prédisent le début d'extinctions massives dans les Préalpes à partir de 2040, au plus tard en 2080. Mon travail démontre aussi l'importance d'études régionales à échelle fine pour évaluer l'impact des changements climatiques sur la végétation, en intégrant des variables plus directes. En effet, les études à échelle continentale ne tiennent pas compte des micro-refuges, des extinctions locales ni des pertes de connectivité entre populations locales. Malgré cela, la migration des plantes de basses altitudes reste difficile à prédire à l'échelle locale sans modélisation plus globale.

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The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.

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This study investigates the potential stages of drug use. Data from the longitudinal Cohort Study on Substance Use Risk Factors were used (N = 5,116). Drug use (alcohol, tobacco, and 16 illicit drugs) over the previous 12 months was assessed at two time points. Patterns and trajectories of drug use were studied using latent transition analysis (LTA). This study's substantive contributions are twofold. First, the pattern of drug use displayed the well-known sequence of drug involvement (licit drugs to cannabis to other illicit drugs), but with an added distinction between two kinds of illicit drugs ("middle-stage" drugs: uppers, hallucinogens, inhaled drugs; and "final-stage" drugs: heroin, ketamine, GHB/GBL, research chemicals, crystal meth, and spice). Second, subgroup membership was stable over time, as the most likely transition was remaining in the same latent class.

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BACKGROUND: The Advisa MRI system is designed to safely undergo magnetic resonance imaging (MRI). Its influence on image quality is not well known. OBJECTIVE: To evaluate cardiac magnetic resonance (CMR) image quality and to characterize myocardial contraction patterns by using the Advisa MRI system. METHODS: In this international trial with 35 participating centers, an Advisa MRI system was implanted in 263 patients. Of those, 177 were randomized to the MRI group and 150 underwent MRI scans at the 9-12-week visit. Left ventricular (LV) and right ventricular (RV) cine long-axis steady-state free precession MR images were graded for quality. Signal loss along the implantable pulse generator and leads was measured. The tagging CMR data quality was assessed as the percentage of trackable tagging points on complementary spatial modulation of magnetization acquisitions (n=16) and segmental circumferential fiber shortening was quantified. RESULTS: Of all cine long-axis steady-state free precession acquisitions, 95% of LV and 98% of RV acquisitions were of diagnostic quality, with 84% and 93%, respectively, being of good or excellent quality. Tagging points were trackable from systole into early diastole (360-648 ms after the R-wave) in all segments. During RV pacing, tagging demonstrated a dyssynchronous contraction pattern, which was not observed in nonpaced (n = 4) and right atrial-paced (n = 8) patients. CONCLUSIONS: In the Advisa MRI study, high-quality CMR images for the assessment of cardiac anatomy and function were obtained in most patients with an implantable pacing system. In addition, this study demonstrated the feasibility of acquiring tagging data to study the LV function during pacing.

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The molecular mechanisms that control how progenitors generate distinct subtypes of neurons, and how undifferentiated neurons acquire their specific identity during corticogenesis, are increasingly understood. However, whether postmitotic neurons can change their identity at late stages of differentiation remains unknown. To study this question, we developed an electrochemical in vivo gene delivery method to rapidly manipulate gene expression specifically in postmitotic neurons. Using this approach, we found that the molecular identity, morphology, physiology and functional input-output connectivity of layer 4 mouse spiny neurons could be specifically reprogrammed during the first postnatal week by ectopic expression of the layer 5B output neuron-specific transcription factor Fezf2. These findings reveal a high degree of plasticity in the identity of postmitotic neocortical neurons and provide a proof of principle for postnatal re-engineering of specific neural microcircuits in vivo.

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Amnestic mild cognitive impairment (aMCI) is characterized by memory deficits alone (single-domain, sd-aMCI) or associated with other cognitive disabilities (multi-domain, md-aMCI). The present study assessed the patterns of electroencephalographic (EEG) activity during the encoding and retrieval phases of short-term memory in these two aMCI subtypes, to identify potential functional differences according to the neuropsychological profile. Continuous EEG was recorded in 43 aMCI patients, whose 16 sd-aMCI and 27 md-aMCI, and 36 age-matched controls (EC) during delayed match-to-sample tasks for face and letter stimuli. At encoding, attended stimuli elicited parietal alpha (8-12 Hz) power decrease (desynchronization), whereas distracting stimuli were associated with alpha power increase (synchronization) over right central sites. No difference was observed in parietal alpha desynchronization among the three groups. For attended faces, the alpha synchronization underlying suppression of distracting letters was reduced in both aMCI subgroups, but more severely in md-aMCI cases that differed significantly from EC. At retrieval, the early N250r recognition effect was significantly reduced for faces in md-aMCI as compared to both sd-aMCI and EC. The results suggest a differential alteration of working memory cerebral processes for faces in the two aMCI subtypes, face covert recognition processes being specifically altered in md-aMCI.

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Until the mid-1990s, gastric cancer has been the first cause of cancer death worldwide, although rates had been declining for several decades and gastric cancer has become a relatively rare cancer in North America and in most Northern and Western Europe, but not in Eastern Europe, Russia and selected areas of Central and South America or East Asia. We analyzed gastric cancer mortality in Europe and other areas of the world from 1980 to 2005 using joinpoint regression analysis, and provided updated site-specific incidence rates from 51 selected registries. Over the last decade, the annual percent change (APC) in mortality rate was around -3, -4% for the major European countries. The APC were similar for the Republic of Korea (APC = -4.3%), Australia (-3.7%), the USA (-3.6%), Japan (-3.5%), Ukraine (-3%) and the Russian Federation (-2.8%). In Latin America, the decline was less marked, but constant with APC around -1.6% in Chile and Brazil, -2.3% in Argentina and Mexico and -2.6% in Colombia. Cancers in the fundus and pylorus are more common in high incidence and mortality areas and have been declining more than cardia gastric cancer. Steady downward trends persist in gastric cancer mortality worldwide even in middle aged population, and hence further appreciable declines are likely in the near future.

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Background: There may be a considerable gap between LDL cholesterol (LDL-C) and blood pressure (BP) goal values recommended by the guidelines and results achieved in daily practice. Design Prospective cross-sectional survey of cardiovascular disease risk profiles and management with focus on lipid lowering and BP lowering in clinical practice. Methods: In phase 1, the cardiovascular risk of patients with known lipid profile visiting their general practitioner was anonymously assessed in accordance to the PROCAM-score. In phase 2, high-risk patients who did not achieve LDL-C goal less than 2.6 mmol/l in phase 1 could be further documented. Results: Six hundred thirty-five general practitioners collected the data of 23 892 patients with known lipid profile. Forty percent were high-risk patients (diabetes mellitus or coronary heart disease or PROCAM-score >20%), compared with 27% estimated by the physicians. Goal attainment rate was almost double for BP than for LDL-C in high-risk patients (62 vs. 37%). Both goals were attained by 25%. LDL-C values in phase 1 and 2 were available for 3097 high-risk patients not at LDL-C goal in phase 1; 32% of patients achieved LDL-C goal of less than 2.6 mmol/l after a mean of 17 weeks. The most successful strategies for LDL-C reduction were implemented in only 22% of the high-risk patients. Conclusion: Although patients at high cardiovascular risk were treated more intensively than low or medium risk patients, the majority remained insufficiently controlled, which is an incentive for intensified medical education. Adequate implementation of Swiss and International guidelines would expectedly contribute to improved achievement of LDL-C and BP goal values in daily practice.