884 resultados para Data Streams Distribution
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In order to contribute to the debate about southern glacial refugia used by temperate species and more northern refugia used by boreal or cold-temperate species, we examined the phylogeography of a widespread snake species (Vipera berus) inhabiting Europe up to the Arctic Circle. The analysis of the mitochondrial DNA (mtDNA) sequence variation in 1043 bp of the cytochrome b gene and in 918 bp of the noncoding control region was performed with phylogenetic approaches. Our results suggest that both the duplicated control region and cytochrome b evolve at a similar rate in this species. Phylogenetic analysis showed that V. berus is divided into three major mitochondrial lineages, probably resulting from an Italian, a Balkan and a Northern (from France to Russia) refugial area in Eastern Europe, near the Carpathian Mountains. In addition, the Northern clade presents an important substructure, suggesting two sequential colonization events in Europe. First, the continent was colonized from the three main refugial areas mentioned above during the Lower-Mid Pleistocene. Second, recolonization of most of Europe most likely originated from several refugia located outside of the Mediterranean peninsulas (Carpathian region, east of the Carpathians, France and possibly Hungary) during the Mid-Late Pleistocene, while populations within the Italian and Balkan Peninsulas fluctuated only slightly in distribution range, with larger lowland populations during glacial times and with refugial mountain populations during interglacials, as in the present time. The phylogeographical structure revealed in our study suggests complex recolonization dynamics of the European continent by V. berus, characterized by latitudinal as well as altitudinal range shifts, driven by both climatic changes and competition with related species.
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This project examines similarities and differences between the automated condition data collected on and off county paved roads and the manual condition data collected by Iowa Department of Transportation (DOT) staff in 2000 and 2001. Also, the researchers will provide staff support to the advisory committee in exploring other options to the highway need process. The results show that the automated condition data can be used in a converted highway needs process with no major differences between the two methods. Even though the foundation rating difference was significant, the foundation rating weighting factor in HWYNEEDS is minimal and should not have a major impact. In terms of RUTF formula based distribution, the results clearly show the superiority of the condition-based analysis compared to the non-condition based. That correlation can be further enhanced by adding more distress variables to the analysis.
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The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).
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U-Pb dating of zircons by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) is a widely used analytical technique in Earth Sciences. For U-Pb ages below 1 billion years (1 Ga), Pb-206/U-238 dates are usually used, showing the least bias by external parameters such as the presence of initial lead and its isotopic composition in the analysed mineral. Precision and accuracy of the Pb/U ratio are thus of highest importance in LA-ICPMS geochronology. We consider the evaluation of the statistical distribution of the sweep intensities based on goodness-of-fit tests in order to find a model probability distribution fitting the data to apply an appropriate formulation for the standard deviation. We then discuss three main methods to calculate the Pb/U intensity ratio and its uncertainty in the LA-ICPMS: (1) ratio-of-the-mean intensities method, (2) mean-of-the-intensity-ratios method and (3) intercept method. These methods apply different functions to the same raw intensity vs. time data to calculate the mean Pb/U intensity ratio. Thus, the calculated intensity ratio and its uncertainty depend on the method applied. We demonstrate that the accuracy and, conditionally, the precision of the ratio-of-the-mean intensities method are invariant to the intensity fluctuations and averaging related to the dwell time selection and off-line data transformation (averaging of several sweeps); we present a statistical approach how to calculate the uncertainty of this method for transient signals. We also show that the accuracy of methods (2) and (3) is influenced by the intensity fluctuations and averaging, and the extent of this influence can amount to tens of percentage points; we show that the uncertainty of these methods also depends on how the signal is averaged. Each of the above methods imposes requirements to the instrumentation. The ratio-of-the-mean intensities method is sufficiently accurate provided the laser induced fractionation between the beginning and the end of the signal is kept low and linear. We show, based on a comprehensive series of analyses with different ablation pit sizes, energy densities and repetition rates for a 193 nm ns-ablation system that such a fractionation behaviour requires using a low ablation speed (low energy density and low repetition rate). Overall, we conclude that the ratio-of-the-mean intensities method combined with low sampling rates is the most mathematically accurate among the existing data treatment methods for U-Pb zircon dating by sensitive sector field ICPMS.
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This study aimed to use the plantar pressure insole for estimating the three-dimensional ground reaction force (GRF) as well as the frictional torque (T(F)) during walking. Eleven subjects, six healthy and five patients with ankle disease participated in the study while wearing pressure insoles during several walking trials on a force-plate. The plantar pressure distribution was analyzed and 10 principal components of 24 regional pressure values with the stance time percentage (STP) were considered for GRF and T(F) estimation. Both linear and non-linear approximators were used for estimating the GRF and T(F) based on two learning strategies using intra-subject and inter-subjects data. The RMS error and the correlation coefficient between the approximators and the actual patterns obtained from force-plate were calculated. Our results showed better performance for non-linear approximation especially when the STP was considered as input. The least errors were observed for vertical force (4%) and anterior-posterior force (7.3%), while the medial-lateral force (11.3%) and frictional torque (14.7%) had higher errors. The result obtained for the patients showed higher error; nevertheless, when the data of the same patient were used for learning, the results were improved and in general slight differences with healthy subjects were observed. In conclusion, this study showed that ambulatory pressure insole with data normalization, an optimal choice of inputs and a well-trained nonlinear mapping function can estimate efficiently the three-dimensional ground reaction force and frictional torque in consecutive gait cycle without requiring a force-plate.
Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.
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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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When health status is an ordered response variable, Allison and Foster (2004)postulate that a distribution Q exhibits more inequality than a distribution P if Q is obtained from P via a sequence of median preserving spreads. This paper introduces a parametric family of inequality indices which are founded on the Allison and Foster ordering. [Authors]
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BACKGROUND: Metals are known endocrine disruptors and have been linked to cardiometabolic diseases via multiple potential mechanisms, yet few human studies have both the exposure variability and biologically-relevant phenotype data available. We sought to examine the distribution of metals exposure and potential associations with cardiometabolic risk factors in the "Modeling the Epidemiologic Transition Study" (METS), a prospective cohort study designed to assess energy balance and change in body weight, diabetes and cardiovascular disease risk in five countries at different stages of social and economic development. METHODS: Young adults (25-45 years) of African descent were enrolled (N = 500 from each site) in: Ghana, South Africa, Seychelles, Jamaica and the U.S.A. We randomly selected 150 blood samples (N = 30 from each site) to determine concentrations of selected metals (arsenic, cadmium, lead, mercury) in a subset of participants at baseline and to examine associations with cardiometabolic risk factors. RESULTS: Median (interquartile range) metal concentrations (μg/L) were: arsenic 8.5 (7.7); cadmium 0.01 (0.8); lead 16.6 (16.1); and mercury 1.5 (5.0). There were significant differences in metals concentrations by: site location, paid employment status, education, marital status, smoking, alcohol use, and fish intake. After adjusting for these covariates plus age and sex, arsenic (OR 4.1, 95% C.I. 1.2, 14.6) and lead (OR 4.0, 95% C.I. 1.6, 9.6) above the median values were significantly associated with elevated fasting glucose. These associations increased when models were further adjusted for percent body fat: arsenic (OR 5.6, 95% C.I. 1.5, 21.2) and lead (OR 5.0, 95% C.I. 2.0, 12.7). Cadmium and mercury were also related with increased odds of elevated fasting glucose, but the associations were not statistically significant. Arsenic was significantly associated with increased odds of low HDL cholesterol both with (OR 8.0, 95% C.I. 1.8, 35.0) and without (OR 5.9, 95% C.I. 1.5, 23.1) adjustment for percent body fat. CONCLUSIONS: While not consistent for all cardiometabolic disease markers, these results are suggestive of potentially important associations between metals exposure and cardiometabolic risk. Future studies will examine these associations in the larger cohort over time.
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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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In French the adjective petit 'small, little' has a special status: it fulfills various pragmatic functions in addition to semantic meanings and it is thus highly frequent in discourse. Résumé: This study, based on the data of two children, aged 1;6 to 2;11, argues that petit and its pragmatic meanings play a specific role in the acquisition of French adjectives. In contrast to what is expected in child language, petit favours the early development of a pattern of noun phrase with prenominal attributive adjective. The emergence and distribution of petit in the children's production is examined and related to its distribution in the input, and the detailed pragmatic meanings and functions of petit are analysed. Prenominal petit emerges early as the preferred and most productive adjective. Pragmatic meanings of petit appear to be predominant in this early age and are of two main types: expressions of endearment (in noun phrases) and mitigating devices whose scope is the entire utterance. These results, as well as instances of children's pragmatic overgeneralizations, provide new evidence that at least some pragmatic meanings are prior to semantic meanings in early acquisition.
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A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.
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Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolution and geographic extent. Here, we assess whether climate-change induced habitat losses predicted at the European scale (10x10' grid cells) are also predicted from local scale data and modeling (25x25m grid cells) in two regions of the Swiss Alps. We show that local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10x10' cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.
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The Iowa Department of Natural Resources uses benthic macroinvertebrate and fish sampling data to assess stream biological condition and the support status of designated aquatic life uses (Wilton 2004; IDNR 2013). Stream physical habitat data assist with the interpretation of biological sampling results by quantifying important physical characteristics that influence a stream’s ability to support a healthy aquatic community (Heitke et al., 2006; Rowe et al. 2009; Sindt et al., 2012). This document describes aquatic community sampling and physical habitat assessment procedures currently followed in the Iowa stream biological assessment program. Standardized biological sampling and physical habitat assessment procedures were first established following a pilot sampling study in 1994 (IDNR 1994a, 1994b). The procedure documents were last updated in 2001 (IDNR 2001a; 2001b). The biological sampling and physical habitat assessment procedures described below are evaluated on a continual basis. Revision of this working document will occur periodically to reflect additional changes.
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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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The distribution and status of Iowa's fishes were last extensively described in Iowa Fish and Fishing (Harlan et al. 1987). Since then, numerous fish collections have been made in Iowa's interior and bordering rivers and streams. Excluding non-native species, there have been three documented accounts of new fish species distributional records in Iowa since 1987. In this paper, I describe new collections of Crystal Darter (Crystallaria asprella) and Bluntnose Darter (Etheostoma chlorosomum) from the Mississippi River. The first documented specimen of C. asprella in Iowa was collected in Pool 11 of the Upper Mississippi River (UMR) in 1995. One specimen of E. chlorosomum was collected in Pool 13 of the UMR in 1998, and another was collected in 1999. The bluntnose darter had not been collected since 1975 and was generally thought to be extirpated in Iowa.