Estimating the confidence level of white matter connections obtained with MRI tractography.

BACKGROUND: Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.

Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

Case studies and mathematical models of ecological speciation. 1. Cichlids in a crater lake.

A recent study of a pair of sympatric species of cichlids in Lake Apoyo in Nicaragua is viewed as providing probably one of the most convincing examples of sympatric speciation to date. Here, we describe and study a stochastic, individual-based, explicit genetic model tailored for this cichlid system. Our results show that relatively rapid (<20,000 generations) colonization of a new ecological niche and (sympatric or parapatric) speciation via local adaptation and divergence in habitat and mating preferences are theoretically plausible if: (i) the number of loci underlying the traits controlling local adaptation, and habitat and mating preferences is small; (ii) the strength of selection for local adaptation is intermediate; (iii) the carrying capacity of the population is intermediate; and (iv) the effects of the loci influencing nonrandom mating are strong. We discuss patterns and timescales of ecological speciation identified by our model, and we highlight important parameters and features that need to be studied empirically to provide information that can be used to improve the biological realism and power of mathematical models of ecological speciation.

Parallel evolution of facial stripe patterns in the Neolamprologus brichardi/pulcher species complex endemic to Lake Tanganyika.

Colour pattern diversity can be due to random processes or to natural or sexual selection. Consequently, similarities in colour patterns are not always correlated with common ancestry, but may result from convergent evolution under shared selection pressures or drift. Neolamprologus brichardi and Neolamprologus pulcher have been described as two distinct species based on differences in the arrangement of two dark bars on the operculum. Our study uses DNA sequences of the mitochondrial control region to show that relatedness of haplotypes disagrees with species assignment based on head colour pattern. This suggests repeated parallel evolution of particular stripe patterns. The complete lack of shared haplotypes between populations of the same or different phenotypes reflects strong philopatric behaviour, possibly induced by the cooperative breeding mode in which offspring remain in their natal territory and serve as helpers until they disperse to nearby territories or take over a breeding position. Concordant phylogeographic patterns between N. brichardi/N. pulcher populations and other rock-dwelling cichlids suggest that the same colonization routes have been taken by sympatric species and that these routes were affected by lake level fluctuations in the past.

Estimating slope and level change in N=1 designs

The current study proposes a new procedure for separately estimating slope change and level change between two adjacent phases in single-case designs. The procedure eliminates baseline trend from the whole data series prior to assessing treatment effectiveness. The steps necessary to obtain the estimates are presented in detail, explained, and illustrated. A simulation study is carried out to explore the bias and precision of the estimators and compare them to an analytical procedure matching the data simulation model. The experimental conditions include two data generation models, several degrees of serial dependence, trend, level and/or slope change. The results suggest that the level and slope change estimates provided by the procedure are unbiased for all levels of serial dependence tested and trend is effectively controlled for. The efficiency of the slope change estimator is acceptable, whereas the variance of the level change estimator may be problematic for highly negatively autocorrelated data series.

Migration Determinants at a Local Level

This paper is about determinants of migration at a local level. We use data from Catalan municipalities in order to understand what explains migration patterns trying to identify whether they are main explained by amenities or economic characteristics. We distinguish three typologies of migration in terms of distance travelled: short-distance, short-medium-distance and medium-distance and we hypothesize whether migration determinants vary across these groups. Our results show that, effectively, there are some noticeable differences, suggest that spatial issues must be taken into account and provide some insights for future research. Keywords: population dynamics, spatial econometrics. JEL codes: C21, R0, R23

Predicting current and future spatial community patterns of plant functional traits

Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.

Phenotypic and molecular characterization of the onset of neuropathy in rodent models of diabetes mellitus

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.

Global habitat suitability models of terrestrial mammals.

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.

Using niche-based models to improve the sampling of rare species

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.

Do stacked species distribution models reflect altitudinal diversity patterns?

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.

Density, climate and varying return points: an analysis of long-term population fluctuations in the threatened European tree frog.

Experimental research has identified many putative agents of amphibian decline, yet the population-level consequences of these agents remain unknown, owing to lack of information on compensatory density dependence in natural populations. Here, we investigate the relative importance of intrinsic (density-dependent) and extrinsic (climatic) factors impacting the dynamics of a tree frog (Hyla arborea) population over 22 years. A combination of log-linear density dependence and rainfall (with a 2-year time lag corresponding to development time) explain 75% of the variance in the rate of increase. Such fluctuations around a variable return point might be responsible for the seemingly erratic demography and disequilibrium dynamics of many amphibian populations.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

Potential Impacts of Climate Change on Ecosystem Services in Europe: the Case of Pest Control by Vertebrates. BioScience.

Global environmental changes threaten ecosystems and cause significant alterations to the supply of ecosystem services that are vital for human well-being. We provide an assessment of the potential impacts of climate change on European diversity of vertebrates and their associated pest control services. We modeled the distributions of the species that provide this service using ensembles of forecasts from bioclimatic envelope models and then used their results to generate maps of potential species richness among vertebrate providers of pest control services. We assessed how potential richness of pest control providers would change according to different climate and greenhouse emissions scenarios. We found that potential richness of pest control providers was likely to face substantial reductions, especially in southern European countries that had economies highly dependent on agricultural yields. In much of central and northern Europe, where countries had their economies less dependent on agriculture, climate change was likely to benefit pest control providers

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.