Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.

Urban areas are hot spots that drive environmental change at multiple scales. Material demands of production and human consumption alter land use and cover, biodiversity, and hydrosystems locally to regionally, and urban waste discharge affects local to global biogeochemical cycles and climate. For urbanites, however, global environmental changes are swamped by dramatic changes in the local environment. Urban ecology integrates natural and social sciences to study these radically altered local environments and their regional and global effects. Cities themselves present both the problems and solutions to sustainability challenges of an increasingly urbanized world.

 Wetlands are ecologically and economically important ecosystems but are threatened globally by many forms of human disturbance. Understanding the responses of wetland species to human disturbance is essential for effective wetland management and conservation.  We undertook a study to determine (i) whether anurans can be used effectively to assess the ecological integrity of wetlands affected by groundwater withdrawal and, if so, (ii) what effect increasing urbanization might have on the utility of anurans as wetland indicators. We monitored the intensity of anuran calls at 42 wetlands in south-western Florida throughout 2001-2002 and 2005-2009.  We first validated the use of anurans to assess wetland integrity using a small group of wetlands by comparing anuran calling and subsequent tadpole development with an established index employing vegetation composition and structure. We then verified that the results could be expanded to a variety of sites throughout the region. Finally, we focused on urbanized wetlands to determine whether urbanization could interfere with the use of anurans to assess wetland integrity.  We used PRESENCE to estimate occupancy and detection probabilities and to examine the relationship between occupancy and five covariates expected to influence individual species occurrence. We used FRAGSTATS to calculate the mean proximity index for urbanized wetlands, which assesses the size and distribution of land use types within a specified area.  Our results showed that the group of species including oak toad, southern cricket frog, pinewoods treefrog, barking treefrog, and little grass frog is a reliable indicator of wetland integrity. However, this same group of species, which is sensitive to wetland health, is selectively excluded from urbanized wetlands.. Although anurans are effective indicators of wetland health and complement vegetation surveys, the usefulness of this group for monitoring the ecological integrity of wetlands can be substantially reduced, or eliminated, as a consequence of urbanization. We urge for careful consideration of confounding factors in any studies examining the utility of indicator species.© 2012 The Authors. Journal of Applied Ecology © 2012 British Ecological Society.

The scale and extent of global urbanization are unprecedented and increasing. As urbanization generally encroaches on natural habitats and the urban ecological footprint reaches far beyond the city limits, how urbanization affects biodiversity has received increasing attention from the scientific community. Nonetheless, the comprehensive syntheses of urbanization consequences for biodiversity, including diverse taxonomic groups, across multiple spatial scales and spanning a wide gradient range of urbanization intensity are still insufficient. Here, based on the urban-rural gradient approach, we assessed the effects of urbanization on Chinese mammal and amphibian richness across the entire urbanization gradient (i.e., urbanization level from 0 to 1) at the national, regional and urban agglomeration scales. We used the global mammal and amphibian distribution data along with corresponding background climate, habitat conditions and socioeconomic activities data for analysis. Our results revealed a detailed and diverse pattern of Chinese mammal and amphibian richness along the entire spectrum of urbanization gradient across three spatial scales. And an approximately monotonic decrease only existed in certain urban agglomerations. The imprint of urbanization on mammal and amphibian richness were largely masked by the overall primacy of background climate at the national and regional scales. As the scale of analysis shifting from the country to urban agglomerations, urbanization-associated variables and locally specific limiting factors started to play important roles in driving the richness patterns. Moreover, the environmental Kuznets curve hypothesis can explain the relationship between biodiversity pressure and urbanization activities in certain Chinese urban agglomerations. However, the findings of urbanization effects on biodiversity using the urban-rural gradient analysis should be interpreted with caution because many possible driving forces simultaneously present along the urban-rural gradient and are very challenging to attribute.

Despite growing interest in the effects of landscape heterogeneity on genetic structuring, few tools are available to incorporate data on landscape composition into population genetic studies. Analyses of isolation by distance have typically either assumed spatial homogeneity for convenience or applied theoretically unjustified distance metrics to compensate for heterogeneity. Here I propose the isolation-by-resistance (IBR) model as an alternative for predicting equilibrium genetic structuring in complex landscapes. The model predicts a positive relationship between genetic differentiation and the resistance distance, a distance metric that exploits precise relationships between random walk times and effective resistances in electronic networks. As a predictor of genetic differentiation, the resistance distance is both more theoretically justified and more robust to spatial heterogeneity than Euclidean or least cost path-based distance measures. Moreover, the metric can be applied with a wide range of data inputs, including coarse-scale range maps, simple maps of habitat and nonhabitat within a species' range, or complex spatial datasets with habitats and barriers of differing qualities. The IBR model thus provides a flexible and efficient tool to account for habitat heterogeneity in studies of isolation by distance, improve understanding of how landscape characteristics affect genetic structuring, and predict genetic and evolutionary consequences of landscape change.

Urbanization results in pervasive habitat fragmentation and reduces standing genetic variation through bottlenecks and drift. Loss of genomewide variation may ultimately reduce the evolutionary potential of animal populations experiencing rapidly changing conditions. In this study, we examined genomewide variation among 23 white-footed mouse (Peromyscus leucopus) populations sampled along an urbanization gradient in the New York City metropolitan area. Genomewide variation was estimated as a proxy for evolutionary potential using more than 10 000 single nucleotide polymorphism (SNP) markers generated by ddRAD-Seq. We found that genomewide variation is inversely related to urbanization as measured by percent impervious surface cover, and to a lesser extent, human population density. We also report that urbanization results in enhanced genomewide differentiation between populations in cities. There was no pattern of isolation by distance among these populations, but an isolation by resistance model based on impervious surface significantly explained patterns of genetic differentiation. Isolation by environment modeling also indicated that urban populations deviate much more strongly from global allele frequencies than suburban or rural populations. This study is the first to examine loss of genomewide SNP variation along an urban-to-rural gradient and quantify urbanization as a driver of population genomic patterns.

I reexamine the use of isolation by distance models as a basis for the estimation of demographic parameters from measures of population subdivision. To that aim, I first provide results for values of F-statistics in one-dimensional models and coalescence times in two-dimensional models, and make more precise earlier results for F-statistics in two-dimensional models and coalescence times in one-dimensional models. Based on these results, I propose a method of data analysis involving the regression of FST/(1-FST) estimates for pairs of subpopulations on geographic distance for populations along linear habitats or logarithm of distance for populations in two-dimensional habitats. This regression provides in principle an estimate of the product of population density and second moment of parental axial distance. In two cases where comparison to direct estimates is possible, the method proposed here is more satisfactory than previous indirect methods.

Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.

Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Investigating the properties of ecological landscapes that influence gene flow among populations can provide key insights into the earliest stages of biological divergence. Both ecological and geographical factors can reduce gene flow, which can lead to population divergence, but we know little of the relative strengths of these phenomena in nature. Here, we use a novel application of structural equation modelling to quantify the contributions of ecological and geographical isolation to spatial genetic divergence in 17 species of Anolis lizards. Our comparative analysis shows that although both processes contributed significantly, geographical isolation explained substantially more genetic divergence than ecological isolation (36.3 vs. 17.9% of variance respectively), suggesting that despite the proposed ubiquity of ecological divergence, non-ecological factors play the dominant role in the evolution of spatial genetic divergence.© 2012 Blackwell Publishing Ltd/CNRS.

Urbanization is one of the major causes for plant diversity loss at the local and regional scale. However, how plant species distribute along the urban–rural gradient and what the relationship between urbanization degree and plant diversity is, is not very clear. In this paper, 134 sample sites along two 18 km width transects that run across the urban center of Shanghai were investigated. We quantified the spatial patterns of plant diversity along the urban–rural gradient and measured the relationship between plant diversity and urbanization degree, which was calculated using a land use land cover map derived from high spatial resolution aerial photos. We recorded 526 vascular plant species in 134 plots, 57.8% of which are exotic plant species. Six spatial distribution patterns of species richness were identified for different plant taxa along the rural to urban gradient. The native plant species richness showed no significant relationship to urbanization degree. The richness of the all plants, woody plants and perennial herbs presented significant positive relationship with urbanization degree, while the richness of annual herbs, Shannon-Wiener diversity and Heip evenness all exhibited a negative relationship to urbanization degree. Urbanization could significantly influence plant diversity in Shanghai. Our findings can provide insights to understand the mechanism of urbanization effects on plant diversity, as well as plant diversity conservation in urban areas.