Biodiversity in the city: key challenges for urban green space management

Cities play important roles in the conservation of global biodiversity, particularly through the planning and management of urban green spaces (UGS). However, UGS management is subject to a complex assortment of interacting social, cultural, and economic factors, including governance, economics, social networks, multiple stakeholders, individual preferences, and social constraints. To help deliver more effective conservation outcomes in cities, we identify major challenges to managing biodiversity in UGS and important topics warranting further investigation. Biodiversity within UGS must be managed at multiple scales while accounting for various socioeconomic and cultural influences. Although the environmental consequences of management activities to enhance urban biodiversity are now beginning to be addressed, additional research and practical management strategies must be developed to balance human needs and perceptions while maintaining ecological processes

Microbial Risk Assessment Framework for Exposure to Amended Sludge Projects

BackgroundAlthough the U.S. Environmental Protection Agency has a long history of using risk-based approaches for regulatory purposes, pollutant limits for pathogens in biosolids are not currently based on quantitative risk assessments.ObjectivesWe developed and demonstrated a risk-based methodology for assessing the risk to human health from exposure to pathogens via biosolids.MaterialsFour models were developed, incorporating direct ingestion, groundwater, and aerosol exposure pathways. Three sources of environmental data were used to estimate risk: pathogen monitoring of sludge, efficacy of sludge treatment, and pathogen monitoring of biosolids.ResultsRisk estimates were obtainable even for Class A biosolids, where posttreatment monitoring data are below detectable levels, demonstrating that risk assessments for biosolids exposure are practical. Model analyses suggest that: a) a two-digester design decreases the probability of risks >10(-4) compared with one-digester designs, b) risks associated with exposures to groundwater and aerosol pathways were, in general, lower than exposures to the direct ingestion pathway, and c) secondary transmission can be an important factor in risk estimation.ConclusionsThe risk-based approach presented here provides a tool to a) help biosolids producers interpret the results of biosolids monitoring data in terms of its health implications, b) help treatment plant engineers evaluate the risk-based benefits of operational changes to existing or projected treatment processes, and c) help environmental managers evaluate potential capital improvements and/or land application site placement issues. Regulation of pathogens can now be based on human health risk in a manner parallel to other water-related risks

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

<p>Abstract</p> <p>Background</p> <p>Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks.</p> <p>Methods</p> <p>Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008.</p> <p>Results</p> <p>NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley.</p> <p>Conclusions</p> <p>We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.</p

A spectral study of gamma-ray emitting AGN

In this paper we present a statistical analysis of the gamma-ray spectra of flat-spectrum radio quasars (FSRQ) compared to those of BL Lacs. The average spectra and possible systematic deviations from power-law behaviour are investigated by summing up the intensity and the power-law fit statistic for both classes of objects. We also compare the time-averaged spectrum to that at the time of gamma-ray outbursts. The spectrum of the average AGN is softer than that of the extragalactic gamma-ray background. It may be that BL Lacs, which on average have a harder spectrum than FSRQs, make up the bulk of the extragalactic background. We also find apparent cut-offs at both low and high energies in the spectra of FSRQs at the time of gamma-ray outbursts. While the cut-off at high energies may have something to do with opacity, the cut-off at low energies may be taken as indication that the gamma-ray emission of FSRQs is not a one component spectrum.Comment: 8 pages, accepted for publication in A&

Central Coherence in Eating Disorders: A Synthesis of Studies Using the Rey Osterrieth Complex Figure Test

Background: Large variability in tests and differences in scoring systems used to study central coherence in eating disorders may lead to different interpretations, inconsistent findings and between study discrepancies. This study aimed to address inconsistencies by collating data from several studies from the same research group that used the Rey Osterrieth Complex Figure Test (Rey Figure) in order to produce norms to provide benchmark data for future studies. Method: Data was collated from 984 participants in total. Anorexia Nervosa, Bulimia Nervosa, recovered Anorexia Nervosa, unaffected family members and healthy controls were compared using the Rey Figure. Results: Poor global processing was observed across all current eating disorder sub-groups and in unaffected relatives. There was no difference in performance between recovered AN and HC groups. Conclusions: This is the largest dataset reported in the literature and supports previous studies implicating poor global processing across eating disorders using the Rey Figure. It provides robust normative data useful for future studies

African tropical rainforest net carbon dioxide fluxes in the twentieth century

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO2 fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (−0.02 kg C m−2 yr−1 or −0.04 Pg C yr−1, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO2 flux at the beginning of the century (σ1901 = 0.02 kg C m−2 yr−1), but diverged exponentially throughout the century (σ2010 = 0.03 kg C m−2 yr−1). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO2, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO2 fluxes with increasing atmospheric CO2 concentrations and extreme climatic events, as the uncertainties will only amplify in the next century

Knowledge and perceptions of the risks of non-steroidal anti-inflammatory drugs among orthopaedic patients in Thailand

Background There is a high incidence of adverse effects from non-steroidal antiinflammatory drugs (NSAIDs) in Thailand, but patients’ perceptions and knowledge of NSAID risks is unknown. Objective This study aims to assess patients’ perceptions and knowledge of NSAID risks and factors affecting them. Setting University hospital in North-East of Thailand. Method A Cross-sectional study conducted over 4 months, using a self-administered questionnaire. Patients prescribed NSAIDs for at least one month duration from orthopaedic clinic were recruited using systematic random sampling. Main outcome measure Patients’ perceptions on NSAID risks, knowledge on risk factors, and their associated factors. Results A total of 474 questionnaires were assessed. Overall perceptions of risks was low (scoring below five on a 0–10 visual analogue scale), with risks associated with the renal system scoring highest. Perceived risk of gastrointestinal problems differed between patients using non-selective and selective NSAIDs (3.47 ± 2.75 vs 2.06 ± 2.98; P < 0.001). Receiving side effect information from a health professional was associated with higher risk perception. Most patients (80 %) identified high doses, renal disease and gastrointestinal ulcer increased risks of NSAIDs, but fewer than half recognized that use in the elderly, multiple NSAID use, drinking, hypertension and cardiovascular disease also increased risk of adverse events. Having underlying diseases and receiving side effect information were associated with 1.6–2.0 fold increased knowledge of NSAID risks. Conclusion Perceptions and knowledge concerning NSAID risks was generally low in Thai patients, but higher in those who had received side effect information. Risk-related information should be widely provided, especially in high-risk patients

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like

Quantifying the relative roles of selective and neutral processes in defining eukaryotic microbial communities

We have a limited understanding of the relative contributions of different processes that regulate microbial communities, which are crucial components of both natural and agricultural ecosystems. The contributions of selective and neutral processes in defining community composition are often confounded in field studies because as one moves through space, environments also change. Managed ecosystems provide an excellent opportunity to control for this and evaluate the relative strength of these processes by minimising differences between comparable niches separated at different geographic scales. We use next-generation sequencing to characterize the variance in fungal communities inhabiting adjacent fruit, soil and bark in comparable vineyards across 1000 kms in New Zealand. By compartmentalizing community variation, we reveal that niche explains at least four times more community variance than geographic location. We go beyond merely demonstrating that different communities are found in both different niches and locations by quantifying the forces that define these patterns. Overall, selection unsurprisingly predominantly shapes these microbial communities, but we show the balance of neutral processes also have a significant role in defining community assemblage in eukaryotic microbes