175 research outputs found
Equilibrium of Global Amphibian Species Distributions with Climate
A common assumption in bioclimatic envelope modeling is that species distributions are in equilibrium with contemporary climate. A number of studies have measured departures from equilibrium in species distributions in particular regions, but such investigations were never carried out for a complete lineage across its entire distribution. We measure departures of equilibrium with contemporary climate for the distributions of the world amphibian species. Specifically, we fitted bioclimatic envelopes for 5544 species using three presence-only models. We then measured the proportion of the modeled envelope that is currently occupied by the species, as a metric of equilibrium of species distributions with climate. The assumption was that the greater the difference between modeled bioclimatic envelope and the occupied distribution, the greater the likelihood that species distribution would not be at equilibrium with contemporary climate. On average, amphibians occupied 30% to 57% of their potential distributions. Although patterns differed across regions, there were no significant differences among lineages. Species in the Neotropic, Afrotropics, Indo-Malay, and Palaearctic occupied a smaller proportion of their potential distributions than species in the Nearctic, Madagascar, and Australasia. We acknowledge that our models underestimate non equilibrium, and discuss potential reasons for the observed patterns. From a modeling perspective our results support the view that at global scale bioclimatic envelope models might perform similarly across lineages but differently across regions
The magnitude of syphilis: from prevalence to vertical transmission
ABSTRACT Introduction: In 2013, the World Health Organization (WHO) reported that 1.9 million pregnant women were infected with syphilis worldwide, of which 66.5% had adverse fetal effects in cases of untreated syphilis. Congenital syphilis contributes significantly to infant mortality, accounting for 305,000 perinatal deaths worldwide annually. Aim: To estimate the prevalence of syphilis in parturients, the incidence of congenital syphilis and the vertical transmission rate. Material and methods: a cross-sectional study with data collected from 2041 parturients who had undergone treatment between 2012 and 2014 in the maternity section of the Pedro Ernesto Hospital of the State University of Rio de Janeiro, in the metropolitan area of Rio de Janeiro. The inclusion criterion was positive VDRL and treponemal test in a hospital environment. Results: the prevalence of syphilis in pregnant women was 4.1% in 2012, 3.1% in 2013 and 5% in 2014, with official reporting of 15.6%, 25.0% and 48.1%, respectively. The incidence of congenital syphilis (CS) was 22/1,000 in live births (LB) in 2012; 17/1,000 LB in 2013 and 44.8/1,000 LB in 2014. CS underreporting during the period was 6.7%. Vertical transmission occurred in 65.8% of infants from infected mothers. It was concluded that, in 34.6% of the CS cases, maternal VDRL titers were = 1/4. Conclusion: Results demonstrate the magnitude of the disease, fragility of the reporting system in the assessment of the actual prevalence, impact on perinatal outcomes, and they are a warning about the real situation of syphilis, which is still underestimated in the State
Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change
Forecasts of species range shifts under climate change are fraught with uncertainties and ensemble forecasting may provide a framework to deal with such uncertainties. Here, a novel approach to partition the variance among modeled attributes, such as richness or turnover, and map sources of uncertainty in ensembles of forecasts is presented. We model the distributions of 3837 New World birds and project them into 2080. We then quantify and map the relative contribution of different sources of uncertainty from alternative methods for niche modeling, general circulation models (AOGCM), and emission scenarios. The greatest source of uncertainty in forecasts of species range shifts arises from using alternative methods for niche modeling, followed by AOGCM, and their interaction. Our results concur with previous studies that discovered that projections from alternative models can be extremely varied, but we provide a new analytical framework to examine uncertainties in models by quantifying their importance and mapping their patterns
Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression
Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation
Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer
Abstract Gastric cancer (GC) is the fifth most common type of cancer worldwide with high incidences in Asia, Central, and South American countries. This patchy distribution means that GC studies are neglected by large research centers from developed countries. The need for further understanding of this complex disease, including the local importance of epidemiological factors and the rich ancestral admixture found in Brazil, stimulated the implementation of the GE4GAC project. GE4GAC aims to embrace epidemiological, clinical, molecular and microbiological data from Brazilian controls and patients with malignant and pre-malignant gastric disease. In this letter, we summarize the main goals of the project, including subject and sample accrual and current findings
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