A conceptual framework for predicting the effects of urban environments on floras.

1 With the majority of people now living in urban environments, urbanization is arguably the most intensive and irreversible ecosystem change on the planet. 2 Urbanization transforms floras through a series of filters that change: (i) habitat availability; (ii) the spatial arrangement of habitats; (iii) the pool of plant species; and (iv) evolutionary selection pressures on populations persisting in the urban environment. 3 Using a framework based on mechanisms of change leads to specific predictions of floristic change in urban environments. Explicitly linking drivers of floristic change to predicted outcomes in urban areas can facilitate sustainable management of urban vegetation as well as the conservation of biodiversity. 4 Synthesis. We outline how the use of our proposed framework, based on environmental filtering, can be used to predict responses of floras to urbanization. These floristic responses can be assessed using metrics of taxonomic composition, phylogenetic relatedness among species, plant trait distributions or plant community structure. We outline how this framework can be applied to studies that compare floras within cities or among cities to better understand the various floristic responses to urbanization.The working group was funded by the ARC‐NZ Research Network for Vegetation Function. Financial support was also provided by The Baker Foundation

Traffic-Related Atmospheric Pollutants Levels during Pregnancy and Offspring’s Term Birth Weight: A Study Relying on a Land-Use Regression Exposure Model

International audienceBACKGROUND: Some studies have suggested that particulate matter (PM) levels during pregnancy may be associated with birth weight. Road traffic is a major source of fine PM (PM with aero-dynamic diameter 2,500 g in Munich metropolitan area were included. We assessed PM(2.5), PM(2.5) absorbance (which depends on the blackness of PM(2.5), a marker of traffic-related air pollution), and nitrogen dioxide levels using a land-use regression model, taking into account the type and length of roads, population density, land coverage around the home address, and temporal variations in pollution during pregnancy. Using Poisson regression, we estimated prevalence ratios (PR) of birth weight < 3,000 g, adjusted for gestational duration, sex, maternal smoking, height, weight, and education. RESULTS: Exposure was defined for 1,016 births. Taking the lowest quartile of exposure during pregnancy as a reference, the PR of birth weight < 3,000 g associated with the highest quartile was 1.7 for PM(2.5) [95% confidence interval (CI), 1.2-2.7], 1.8 for PM(2.5) absorbance (95% CI, 1.1-2.7), and 1.2 for NO(2) (95% CI, 0.7-1.7). The PR associated with an increase of 1 microg/m(3) in PM(2.5) levels was 1.13 (95% CI, 1.00-1.29). CONCLUSION: Increases in PM(2.5) levels and PM(2.5) absorbance were associated with decreases in term birth weight. Traffic-related air pollutants may have adverse effects on birth weight

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Patients with femoral or distal forearm fracture in Germany: a prospective observational study on health care situation and outcome

BACKGROUND: Distal radius and proximal femoral fractures are typical injuries in later life, predominantly due to simple falls, but modulated by other relevant factors such as osteoporosis. Fracture incidence rates rise with age. Because of the growing proportion of elderly people in Western industrialized societies, the number of these fractures can be expected to increase further in the coming years, and with it the burden on healthcare resources. Our study therefore assessed the effects of these injuries on the health status of older people over time. The purpose of this paper is to describe the study method, clinical parameters of fracture patients during hospitalization, mortality up to one and a half years after discharge in relation to various factors such as type of fracture, and to describe changes in mobility and living situation. METHODS: Data were collected from all consecutive patients (no age limit) admitted to 423 hospitals throughout Germany with distal radius or femoral fractures (57% acute-care, femoral and forearm fractures; 43% rehabilitation, femoral fractures only) between January 2002 and September 2003. Polytrauma and coma patients were excluded. Demographic characteristics, exact fracture location, mobility and living situation, clinical and laboratory parameters were examined. Current health status was assessed in telephone interviews conducted on average 6–7 months after discharge. Where telephone contact could not be established, at least survival status (living/deceased/date of death) was determined. RESULTS: The study population consisted of 12,520 femoral fracture patients (86.8% hip fractures), average age 77.5 years, 76.5% female, and 2,031 forearm fracture patients, average age 67.6 years, 81.6% female. Women's average age was 6.6 (femoral fracture) to 10 years (forearm fracture) older than men's (p < 0.0001). Only 4.6% of femoral fracture patients experienced changes in their living situation post-discharge (53% because of the fracture event), although less than half of subjects who were able to walk without assistive devices prior to the fracture event (76.7%) could still do so at time of interview (34.9%). At time of interview, 1.5% of subjects were bed-ridden (0.2% before fracture). Forearm fracture patients reported no change in living situation at all. Of the femoral fracture patients 119 (0.95%), and of the forearm fracture patients 3 (0.15%) died during hospital stay. Post-discharge (follow-up one and a half years) 1,463 femoral fracture patients died (19.2% acute-care patients, 8.5% rehabilitation patients), but only 60 forearm fracture patients (3.0%). Ninety percent of femoral fracture deaths happened within the first year, approximately 66% within the first 6 months. More acute-care patients with a pertrochanteric fracture died within one year post-discharge (20.6%) than patients with a cervical fracture (16.1%). CONCLUSION: Mortality after proximal femoral fracture is still alarmingly high and highest after pertrochanteric fracture. Although at time of interview more than half of femoral fracture patients reported reduced mobility, most patients (96%) attempt to live at home. Since forearm fracture patients were on average 10 years younger than femoral fracture patients, forearm fractures may be a means of diagnosing an increased risk of later hip fractures

The Vulnverability Cube: A Multi-Dimensional Framework for Assessing Relative Vulnerability

The diversity and abundance of information available for vulnerability assessments can present a challenge to decision-makers. Here we propose a framework to aggregate and present socioeconomic and environmental data in a visual vulnerability assessment that will help prioritize management options for communities vulnerable to environmental change. Socioeconomic and environmental data are aggregated into distinct categorical indices across three dimensions and arranged in a cube, so that individual communities can be plotted in a three-dimensional space to assess the type and relative magnitude of the communities’ vulnerabilities based on their position in the cube. We present an example assessment using a subset of the USEPA National Estuary Program (NEP) estuaries: coastal communities vulnerable to the effects of environmental change on ecosystem health and water quality. Using three categorical indices created from a pool of publicly available data (socioeconomic index, land use index, estuary condition index), the estuaries were ranked based on their normalized averaged scores and then plotted along the three axes to form a vulnerability cube. The position of each community within the three-dimensional space communicates both the types of vulnerability endemic to each estuary and allows for the clustering of estuaries with like-vulnerabilities to be classified into typologies. The typologies highlight specific vulnerability descriptions that may be helpful in creating specific management strategies. The data used to create the categorical indices are flexible depending on the goals of the decision makers, as different data should be chosen based on availability or importance to the system. Therefore, the analysis can be tailored to specific types of communities, allowing a data rich process to inform decision-making

Using citizen science data to identify the sensitivity of species to human land use

Conservation practitioners must contend with an increasing array of threats that affect biodiversity. Citizen scientists can provide timely and expansive information for addressing these threats across large scales, but their data may contain sampling biases. We used randomization procedures to account for possible sampling biases in opportunistically reported citizen science data to identify species' sensitivities to human land use. We analyzed 21,044 records of 143 native reptile and amphibian species reported to the Carolina Herp Atlas from North Carolina and South Carolina between 1 January 1990 and 12 July 2014. Sensitive species significantly associated with natural landscapes were 3.4 times more likely to be legally protected or treated as of conservation concern by state resource agencies than less sensitive species significantly associated with human-dominated landscapes. Many of the species significantly associated with natural landscapes occurred primarily in habitats that had been nearly eradicated or otherwise altered in the Carolinas, including isolated wetlands, longleaf pine savannas, and Appalachian forests. Rare species with few reports were more likely to be associated with natural landscapes and 3.2 times more likely to be legally protected or treated as of conservation concern than species with at least 20 reported occurrences. Our results suggest that opportunistically reported citizen science data can be used to identify sensitive species and that species currently restricted primarily to natural landscapes are likely at greatest risk of decline from future losses of natural habitat. Our approach demonstrates the usefulness of citizen science data in prioritizing conservation and in helping practitioners address species declines and extinctions at large extents

BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology

BackgroundMaking forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as “Web services”) and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust “in silico” science. However, use of this approach in biodiversity science and ecology has thus far been quite limited.ResultsBioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible ‘virtual laboratory’, free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity.ConclusionsOur work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.<br/

A review of modelling tools for implementation of the EU Water Framework Directive in handling diffuse water pollution

A numerical catchment-scale model capable of simulating diffuse water pollution is necessary in sustainable environmental management for better implementation of the EU Water Framework Directive. This paper provides critical reviews of most popular and free models for diffuse water modelling, with detailed sources and application potential. Based upon these reviews, further work of selecting and testing the HSPF model was carried out, with a case study in the Upper Bann Catchment, Northern Ireland. The calibrated and validated HSPF model can well represent the characteristics of surface water quantity and quality. Climate change scenario evaluation in 5 years showed that when the annual mean temperature increase 3◦C the mean yearly total runoff volume will decrease by 11.1% and the mean daily river flow 11.4%. If 20% crop and pasture land is converted into forest land in the study area, the mean river concentration of nitrate, nitrite, NH4 and PO4 in 5 years will decrease by 19.4%, 33.3%, 31.3% and 31.3% respectively. When applying filter strip method in 80% crop and pasture land in the area, the reduction of the mean concentration of nitrate, nitrite, NH4 and PO4 in 5 years will be 15.3%, 33.3%, 31.3%, and 5.6% respectively. This study shows that HSPF is a suitable model in handling diffuse source water pollution, which can be introduced into the Programme of Measures in the River Basin Management Plans for better implementation of the EUWFD