949 resultados para multidimensional niche
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Despite the increase of animal and plant introductions worldwide and the strong augmentation of the reptile trade, few invasive snake populations have been studied. Dice snakes (Natrix tessellata) were introduced to the shores of Lake Geneva (Switzerland) in the early 1920s, and are now well established. This region of introduction was previously inhabited by Viperine snakes (N. maura). Ever since these two species have been under monitoring (which began in 1996) the Viperine snake population has shown drastic decline. We examine here the possibility of trophic competition by analysing diet composition, prey size and trophic niche overlap. Spatial distribution is also assessed in order to address the question of spatial competitive exclusion. We found very similar diets, and thus a high trophic niche overlap, indicating no partitioning of the trophic resource. No arguments in favour of spatial competitive exclusion were found. Our study suggests that trophic competition may occur between the two natricines and that it may give an explanation for the drastic decline of the Viperine snake in this area. Other pathways potentially playing a role in the exclusion of the Viperine snake are discussed.
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Oil-collecting bees are found worldwide and always in association with particular oil-producing flowers. In the Western Palearctic, three oil-collecting bee species within the genus Macropis (Hymenoptera, Melittidae) interact in a tight pollination mutualism with species of the only European oil-producing plant genus Lysimachia L. (Myrsinaceae). Two of these oil-collecting bees (Macropis europaea and Macropis fulvipes) show overlapping geographic distributions, comparable morphologies, and similar ecological characteristics (e.g., habitat type, floral preferences). In view of these similarities, we presume that hybridization should occur between the two species unless potential variation among the species' ecological niches prevents it, simultaneously decreasing competition for resources. Using modern genetic analyses and ecological niche modeling on a large bee sampling throughout Europe, we discuss new perspectives on the ecology and evolutionary history of this mutualism.
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Aim Species distribution models (SDMs) based on current species ranges underestimate the potential distribution when projected in time and/or space. A multi-temporal model calibration approach has been suggested as an alternative, and we evaluate this using 13,000 years of data. Location Europe. Methods We used fossil-based records of presence for Picea abies, Abies alba and Fagus sylvatica and six climatic variables for the period 13,000 to 1000yr bp. To measure the contribution of each 1000-year time step to the total niche of each species (the niche measured by pooling all the data), we employed a principal components analysis (PCA) calibrated with data over the entire range of possible climates. Then we projected both the total niche and the partial niches from single time frames into the PCA space, and tested if the partial niches were more similar to the total niche than random. Using an ensemble forecasting approach, we calibrated SDMs for each time frame and for the pooled database. We projected each model to current climate and evaluated the results against current pollen data. We also projected all models into the future. Results Niche similarity between the partial and the total-SDMs was almost always statistically significant and increased through time. SDMs calibrated from single time frames gave different results when projected to current climate, providing evidence of a change in the species realized niches through time. Moreover, they predicted limited climate suitability when compared with the total-SDMs. The same results were obtained when projected to future climates. Main conclusions The realized climatic niche of species differed for current and future climates when SDMs were calibrated considering different past climates. Building the niche as an ensemble through time represents a way forward to a better understanding of a species' range and its ecology in a changing climate.
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Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.
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Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.
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Background: Stem cells and their niches are studied in many systems, but mammalian germ stem cells (GSC) and their niches are still poorly understood. In rat testis, spermatogonia and undifferentiated Sertoli cells proliferate before puberty, but at puberty most spermatogonia enter spermatogenesis, and Sertoli cells differentiate to support this program. Thus, pre-pubertal spermatogonia might possess GSC potential and pre-pubertal Sertoli cells niche functions. We hypothesized that the different stem cell pools at pre-puberty and maturity provide a model for the identification of stem cell and niche-specific genes. We compared the transcript profiles of spermatogonia and Sertoli cells from pre-pubertal and pubertal rats and examined how these related to genes expressed in testicular cancers, which might originate from inappropriate communication between GSCs and Sertoli cells. Results: The pre-pubertal spermatogonia-specific gene set comprised known stem cell and spermatogonial stem cell (SSC) markers. Similarly, the pre-pubertal Sertoli cell-specific gene set comprised known niche gene transcripts. A large fraction of these specifically enriched transcripts encoded trans-membrane, extra-cellular, and secreted proteins highlighting stem cell to niche communication. Comparing selective gene sets established in this study with published gene expression data of testicular cancers and their stroma, we identified sets expressed genes shared between testicular tumors and pre-pubertal spermatogonia, and tumor stroma and pre-pubertal Sertoli cells with statistic significance. Conclusions: Our data suggest that SSC and their niche specifically express complementary factors for cell communication and that the same factors might be implicated in the communication between tumor cells and their micro-enviroment in testicular cancer.
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BACKGROUND: Secondary prevention programs for patients experiencing an acute coronary syndrome have been shown to be effective in the outpatient setting. The efficacy of in-hospital prevention interventions administered soon after acute cardiac events is unclear. We performed a systematic review and meta-analysis to determine whether in-hospital, patient-level interventions targeting multiple cardiovascular risk factors reduce all-cause mortality after an acute coronary syndrome. METHODS AND RESULTS: Using a prespecified search strategy, we included controlled clinical trials and before-after studies of secondary prevention interventions with at least a patient-level component (ie, education, counseling, or patient-specific order sets) initiated in hospital with outcomes of mortality, readmission, or reinfarction rates in acute coronary syndrome patients. We classified the interventions as patient-level interventions with or without associated healthcare provider-level interventions and/or system-level interventions. Twenty-six studies met our inclusion criteria. The summary estimate of 14 studies revealed a relative risk of all-cause mortality of 0.79 (95% CI, 0.69 to 0.92; n=37,585) at 1 year. However, the apparent benefit depended on study design and level of intervention. The before-after studies suggested reduced mortality (relative risk [RR], 0.77; 95% CI, 0.66 to 0.90; n=3680 deaths), whereas the RR was 0.96 (95% CI, 0.64 to 1.44; n=99 deaths) among the controlled clinical trials. Only interventions including a provider- or system-level intervention suggested reduced mortality compared with patient-level-only interventions. CONCLUSIONS: The evidence for in-hospital, patient-level interventions for secondary prevention is promising but not definitive because only before-after studies suggest a significant reduction in mortality. Future research should formally test which components of interventions provide the greatest benefit.
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Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process
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When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.
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1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.
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OBJECTIVE: To test the effect of a multidimensional lifestyle intervention on aerobic fitness and adiposity in predominantly migrant preschool children. DESIGN: Cluster randomised controlled single blinded trial (Ballabeina study) over one school year; randomisation was performed after stratification for linguistic region. SETTING: 40 preschool classes in areas with a high migrant population in the German and French speaking regions of Switzerland. PARTICIPANTS: 652 of the 727 preschool children had informed consent and were present for baseline measures (mean age 5.1 years (SD 0.7), 72% migrants of multicultural origins). No children withdrew, but 26 moved away. INTERVENTION: The multidimensional culturally tailored lifestyle intervention included a physical activity programme, lessons on nutrition, media use (use of television and computers), and sleep and adaptation of the built environment of the preschool class. It lasted from August 2008 to June 2009. MAIN OUTCOME MEASURES: Primary outcomes were aerobic fitness (20 m shuttle run test) and body mass index (BMI). Secondary outcomes included motor agility, balance, percentage body fat, waist circumference, physical activity, eating habits, media use, sleep, psychological health, and cognitive abilities. RESULTS: Compared with controls, children in the intervention group had an increase in aerobic fitness at the end of the intervention (adjusted mean difference: 0.32 stages (95% confidence interval 0.07 to 0.57; P=0.01) but no difference in BMI (-0.07 kg/m(2), -0.19 to 0.06; P=0.31). Relative to controls, children in the intervention group had beneficial effects in motor agility (-0.54 s, -0.90 to -0.17; P=0.004), percentage body fat (-1.1%, -2.0 to -0.2; P=0.02), and waist circumference (-1.0 cm, -1.6 to -0.4; P=0.001). There were also significant benefits in the intervention group in reported physical activity, media use, and eating habits, but not in the remaining secondary outcomes. CONCLUSIONS: A multidimensional intervention increased aerobic fitness and reduced body fat but not BMI in predominantly migrant preschool children.
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Este trabalho teve como objetivo avaliar o desempenho biológico de sistemas consorciados de cenoura e alface, sob diferentes combinações de densidades populacionais, com uso das análises bivariada de variância e envoltória de dados (DEA). O delineamento experimental usado foi o de blocos ao acaso completos, com cinco repetições, com os tratamentos arranjados em esquema fatorial 4x4. Os tratamentos resultaram da combinação de quatro populações de plantas de cenoura (40, 60, 80 e 100% da população recomendada no cultivo solteiro - PRCS) com quatro populações de plantas de alface (40, 60, 80 e 100% da PRCS). As populações recomendadas para os cultivos solteiros da cenoura e alface foram 500 mil e 250 mil plantas por hectare, respectivamente. Tanto o método bivariado como o método de análise de envoltória de dados são bastante eficazes na discriminação dos melhores sistemas de cultivo consorciados, por meio dos rendimentos das culturas. Os resultados da eficiência produtiva, medidos por modelos DEA, permitem uma análise estatística simples do ensaio consorciado. A robustez do método de análise bivariada de variância assegura a validade dos resultados.
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RAPPORT DE SYNTHÈSE : Contexte Les programmes de prévention cardiovasculaire secondaire après un événement coronarien aigu ont pu démontrer leur efficacité dans le contexte des soins ambulatoires. L'hospitalisation pour une maladie aiguë peut être considérée comme un «instant charnière», particulièrement adapté à un changement de comportement de santé et où des interventions de prévention secondaire, telle l'éducation du patient, pourraient être particulièrement efficaces. De plus, la prescription de médicaments de prévention cardiovasculaire durant l'hospitalisation semble augmenter la proportion des patients traités selon les recommandations sur le long terme. Récemment, plusieurs études ont évalué l'efficacité de programmes de prévention ayant pour but l'éducation des patients et/ou une augmentation du taux de prescription de médicaments prouvés efficaces par les médecins en charge. L'article faisant l'objet du travail de thèse synthétise la littérature existante concernant l'efficacité en termes de mortalité des interventions multidimensionnelles de prévention cardiovasculaire après un syndrome coronarien aigu, débutées à l'hôpital, centrées sur le patient et ciblant plusieurs facteurs de risque cardiovasculaire. MÉTHODE ET RÉSULTATS : En utilisant une stratégie de recherche définie à l'avance, nous avons inclus des essais cliniques avec groupe contrôle et des études avant-après, débutées à l'hôpital et qui incluaient des résultats cliniques de suivi en terme de mortalité, de taux de réadmission et/ou de récidive de syndrome coronarien aigu. Nous avons catégorisé les études selon qu'elles ciblaient les patients (par exemple une intervention d'éducation aux patients par des infirmières), les soignants (par exemple des cours destinés aux médecins-assistants pour leur enseigner comment prodiguer des interventions éducatives) ou le système de soins (par exemple la mise en place d'itinéraires cliniques au niveau de l'institution). Globalement, les interventions rapportées dans les 14 études répondant aux critères montraient une réduction du risque relatif (RR) de mortalité après un an (RR= 0.79; 95% intervalle de confiance (IC), 0.69-0.92; n=37'585). Cependant, le bénéfice semblait dépendre du type d'étude et du niveau d'intervention. Les études avant-après suggéraient une réduction du risque de mortalité (RR, 0.77; 95% IC, 0.66-0.90; n=3680 décès), tandis que le RR était de 0.96 (95% IC, 0.64-1.44; n=99 décès) pour les études cliniques contrôlées. Seules les études avant-après et les études ciblant les soignants et le système, en plus de cibler les patients, semblaient montrer un bénéfice en termes de mortalité à une année. CONCLUSIONS ET PERSPECTIVES : Les preuves d'efficacité des interventions de prévention secondaires débutées à l'hôpital, ciblant le patient, sont prometteuses, mais pas définitives. En effet, seules les études avant-après montrent un bénéfice en termes de mortalité. Les recherches futures dans ce domaine devraient tester formellement quels éléments des interventions amènent le plus de bénéfices pour les patients.
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Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species' invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.