Importance of food-demand management for climate mitigation

Recent studies show that current trends in yield improvement will not be sufficient to meet projected global food demand in 2050, and suggest that a further expansion of agricultural area will be required. However, agriculture is the main driver of losses of biodiversity and a major contributor to climate change and pollution, and so further expansion is undesirable. The usual proposed alternative - intensification with increased resource use - also has negative effects. It is therefore imperative to find ways to achieve global food security without expanding crop or pastureland and without increasing greenhouse gas emissions. Some authors have emphasised a role for sustainable intensification in closing global 'yield gaps' between the currently realised and potentially achievable yields. However, in this paper we use a transparent, data-driven model, to show that even if yield gaps are closed, the projected demand will drive further agricultural expansion. There are, however, options for reduction on the demand side that are rarely considered. In the second part of this paper we quantify the potential for demand-side mitigation options, and show that improved diets and decreases in food waste are essential to deliver emissions reductions, and to provide global food security in 2050.This work was funded by a grant to the University of Cambridge from BP as part of their Energy Sustainability Challenge.This is the accepted manuscript version. The final version is available from Nature Climate Change at http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2353.html

Eight grand challenges in socio-environmental systems modeling

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.</jats:p

The Calcitonin and Glucocorticoids Combination: Mechanistic Insights into Their Class-Effect Synergy in Experimental Arthritis

PMCID: PMC3564948This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.ML thanks the Institut Technique français de la Betterave industrielle (ITB) for funding this project. CAG and JANF were funded by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Three Aphid-Transmitted Viruses Encourage Vector Migration From Infected Common Bean (Phaseolus vulgaris) Plants Through a Combination of Volatile and Surface Cues

Bean common mosaic virus (BCMV), bean common mosaic necrosis virus (BCMNV), and cucumber mosaic virus (CMV) are important pathogens of common bean (Phaseolus vulgaris), a crop vital for food security in sub-Saharan Africa. These viruses are vectored by aphids non-persistently, with virions bound loosely to stylet receptors. These viruses also manipulate aphid-mediated transmission by altering host properties. Virus-induced effects on host-aphid interactions were investigated using choice test (migration) assays, olfactometry, and analysis of insect-perceivable volatile organic compounds (VOCs) using gas chromatography (GC)-coupled mass spectrometry, and GC-coupled electroantennography. When allowed to choose freely between infected and uninfected plants, aphids of the legume specialist species Aphis fabae, and of the generalist species Myzus persicae, were repelled by plants infected with BCMV, BCMNV, or CMV. However, in olfactometer experiments with A. fabae, only the VOCs emitted by BCMNV-infected plants repelled aphids. Although BCMV, BCMNV, and CMV each induced distinctive changes in emission of aphid-perceivable volatiles, all three suppressed emission of an attractant sesquiterpene, α-copaene, suggesting these three different viruses promote migration of virus-bearing aphids in a similar fashion

Bacterial infections in Lilongwe, Malawi: aetiology and antibiotic resistance

<p>Abstract</p> <p>Background</p> <p>Life-threatening infections present major challenges for health systems in Malawi and the developing world because routine microbiologic culture and sensitivity testing are not performed due to lack of capacity. Use of empirical antimicrobial therapy without regular microbiologic surveillance is unable to provide adequate treatment in the face of emerging antimicrobial resistance. This study was conducted to determine antimicrobial susceptibility patterns in order to inform treatment choices and generate hospital-wide baseline data.</p> <p>Methods</p> <p>Culture and susceptibility testing was performed on various specimens from patients presenting with possible infectious diseases at Kamuzu Central Hospital, Lilongwe, Malawi.</p> <p>Results</p> <p>Between July 2006 and December 2007 3104 specimens from 2458 patients were evaluated, with 60.1% from the adult medical service. Common presentations were sepsis, meningitis, pneumonia and abscess. An etiologic agent was detected in 13% of patients. The most common organisms detected from blood cultures were <it>Staphylococcus aureus</it>, <it>Escherichia </it><it>coli</it>, Salmonella species and <it>Streptococcus pneumoniae</it>, whereas <it>Streptococcus pneumoniae </it>and <it>Cryptococcus neoformans </it>were most frequently detected from cerebrospinal fluid. <it>Haemophilus influenzae </it>was rarely isolated. Resistance to commonly used antibiotics was observed in up to 80% of the isolates while antibiotics that were not commonly in use maintained susceptibility.</p> <p>Conclusions</p> <p>There is widespread resistance to almost all of the antibiotics that are empirically used in Malawi. Antibiotics that have not been widely introduced in Malawi show better laboratory performance. Choices for empirical therapy in Malawi should be revised accordingly. A microbiologic surveillance system should be established and prudent use of antimicrobials promoted to improve patient care.</p

Election proximity and representation focus in party-constrained environments

Do elected representatives have a time-constant representation focus or do they adapt their focus depending on election proximity? In this article, we examine these overlooked theoretical and empirical puzzles by looking at how reelection-seeking actors adapt their legislative behavior according to the electoral cycle. In parliamentary democracies, representatives need to serve two competing principals: their party and their district. Our analysis hinges on how representatives make a strategic use of parliamentary written questions in a highly party-constrained institutional context to heighten their reselection and reelection prospects. Using an original data set of over 32,000 parliamentary questions tabled by Portuguese representatives from 2005 to 2015, we examine how time interacts with two key explanatory elements: electoral vulnerability and party size. Results show that representation focus is not static over time and, in addition, that electoral vulnerability and party size shape strategic use of parliamentary questions

The professionalism disconnect: Do entering residents identify yet participate in unprofessional behaviors?

Background Professionalism has been an important tenet of medical education, yet defining it is a challenge. Perceptions of professional behavior may vary by individual, medical specialty, demographic group and institution. Understanding these differences should help institutions better clarify professionalism expectations and provide standards with which to evaluate resident behavior. Methods Duke University Hospital and Vidant Medical Center/East Carolina University surveyed entering PGY1 residents. Residents were queried on two issues: their perception of the professionalism of 46 specific behaviors related to training and patient care; and their own participation in those specified behaviors. The study reports data analyses for gender and institution based upon survey results in 2009 and 2010. The study received approval by the Institutional Review Boards of both institutions. Results 76% (375) of 495 PGY1 residents surveyed in 2009 and 2010 responded. A majority of responders rated all 46 specified behaviors as unprofessional, and a majority had either observed or participated in each behavior. For all 46 behaviors, a greater percentage of women rated the behaviors as unprofessional. Men were more likely than women to have participated in behaviors. There were several significant differences in both the perceptions of specified behaviors and in self-reported observation of and/or involvement in those behaviors between institutions. Respondents indicated the most important professionalism issues relevant to medical practice include: respect for colleagues/patients, relationships with pharmaceutical companies, balancing home/work life, and admitting mistakes. They reported that professionalism can best be assessed by peers, patients, observation of non-medical work and timeliness/detail of paperwork. Conclusion Defining professionalism in measurable terms is a challenge yet critical in order for it to be taught and assessed. Recognition of the differences by gender and institution should allow for tailored teaching and assessment of professionalism so that it is most meaningful. A shared understanding of what constitutes professional behavior is an important first step