997 resultados para Hydrologic models.
Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.
Resumo:
The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.
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Abstract : The principal focus of this work was to study the molecular changes leading to the development of diabetic peripheral neuropathy (DPN). DPN is the most common complication associated with both type I and II diabetes mellitus (DM). This pathology is the leading cause of non-traumatic amputations. Even though the pathological and morphological changes underlying DPN are relatively well described, the implicated molecular mechanisms remain poorly understood. The following two approaches were developed to study the development of DPN in a rodent model of DM type I. As a first approach, we studied the implication of lipid metabolism in DPN phenotype, concentrating on Sterol Response Element Binding Protein (SREBP)-lc which is the key regulator of storage lipid metabolism. We showed that SREBP-1c was expressed in peripheral nerves and that its expression profile followed the expression of genes involved in storage lipid metabolism. In addition, the expression of SREBP-1c in the endoneurium of peripheral nerves was dependant upon nutritional status and this expression was also perturbed in type I diabetes. In line with this, we showed that insulin elevated the expression of SREBP-1c in primary cultured Schwann cells by activating the SREBP-1c promoter. Taken together, these findings reveal that SREBP-1c expression in Schwann cells responds to metabolic stimuli including insulin and that this response is affected in type I diabetes mellitus. This suggests that disturbed SREBP-1c regulated lipid metabolism may contribute to the pathophysiology of DPN. As a second approach, we performed a comprehensive analysis of the molecular changes associated with DPN in the Akital~1~+ mouse which is a model of spontaneous early-onset type I diabetes mellitus. This mouse expresses a mutated non-functional isoform of insulin, leading to hypoinsulinemia and hyperglycaemia. To determine the onset of DPN, weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Akital+/+ mice during the first three months of life. A decrease in MNCV was evident akeady one week after the onset of hyperglycemia. To explore the molecular changes associated with the development of DPN in these mice, we performed gene expression profiling using sciatic nerve endoneurium and dorsal root ganglia (DRG) isolated from early diabetic male Akita+/+ mice and sex-matched littermate controls. No major transcriptional changes were detected either in the DRG or in the sciatic nerve endoneurium. This experiment indicates that the phenotypic changes observed during the development of DPN are not correlated with major transcriptional alterations, but mainly with alterations at the protein level. Résumé Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1 c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita+/+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique. Résumé : Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita~~Z~+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique.
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Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.
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The mode of action of nuclear receptors in living cells is an actively investigated field but much remains hypothetical due to the lack, until recently, of methods allowing the assessment of molecular mechanisms in vivo. However, these last years, the development of fluorescence microscopy methods has allowed initiating the dissection of the molecular mechanisms underlying gene regulation by nuclear receptors directly in living cells or organisms. Following our analyses on peroxisome proliferator activated receptors (PPARs) in living cells, we discuss here the different models arising from the use of these tools, that attempt to link mobility, DNA binding or chromatin interaction, and transcriptional activity.
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Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium.
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Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.
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Hydrologic analysis is a critical part of transportation design because it helps ensure that hydraulic structures are able to accommodate the flow regimes they are likely to see. This analysis is currently conducted using computer simulations of water flow patterns, and continuing developments in elevation survey techniques result in higher and higher resolution surveys. Current survey techniques now resolve many natural and anthropogenic features that were not practical to map and, thus, require new methods for dealing with depressions and flow discontinuities. A method for depressional analysis is proposed that uses the fact that most anthropogenically constructed embankments are roughly more symmetrical with greater slopes than natural depressions. An enforcement method for draining depressions is then analyzed on those depressions that should be drained. This procedure has been evaluated on a small watershed in central Iowa, Walnut Creek of the South Skunk River, HUC12 # 070801050901, and was found to accurately identify 88 of 92 drained depressions and place enforcements within two pixels, although the method often tries to drain prairie pothole depressions that are bisected by anthropogenic features.
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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: Thymic stromal lymphopoietin (TSLP) is a cytokine primarily produced by epithelial cells, which has been shown to be a potent inducer of T-helper 2 (Th2)-type responses. However, TSLP has pleiotropic effects upon immune cells, and although extensively studied in the context of atopic asthma, its relevance as a therapeutic target and its role in the pathogenesis of nonatopic asthma remains unknown. We sought to investigate the role of TSLP in atopic, nonatopic and viral-induced exacerbations of pulmonary inflammation. METHODS: Using stringently defined murine models of atopic, nonatopic and virally exacerbated forms of pulmonary inflammation, we compared inflammatory responses of C57BL/6 wild-type (WT) and TSLP receptor-deficient (TSLPR KO) mice. RESULTS: Thymic stromal lymphopoietin receptor (TSLPR) signaling was crucial for the development of atopic asthma. Specifically, TSLPR signaling to lung recruited CD4+ T cells enhanced eosinophilia, goblet cell hyperplasia, and overall inflammation within the airways. In contrast, the absence of TSLPR signaling was associated with strikingly exaggerated pulmonary neutrophilic inflammation in a nonatopic model of airway inflammation. The inflammation was associated with excessive levels of interleukin (IL)-17A in the lungs, indicating that TSLP negatively regulates IL-17A. In addition, in a model of influenza-induced exacerbation of atopic airway inflammation, the absence of TSLPR signaling also led to exaggerated neutrophilic inflammation. CONCLUSION: Thymic stromal lymphopoietin plays divergent roles in the pathogenesis of atopic and nonatopic asthma phenotypes by either enhancing Th2 responses or curtailing T-helper 17 responses. These findings raise important caveats for the design of therapeutic interventions targeting TSLP in asthma.
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The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.
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En tot cas, jo voldria que aquesta conferència fos això que he dit: una breu lliçó sobre la importància de les equacions diferencials. Parlaré d'elles des de el punt de vista del models, és a dir, dels fenòmens que modelitzeu. I intentaré explicar que malgrat el seu origen antic, totes elles segueixen presentant avui en dia problemes nous i interessants, tant des de el punt de vista teòric com pràctic.