The persistence of solar activity indicators and the descent of the sun into Maunder Minimum conditions

The recent low and prolonged minimum of the solar cycle, along with the slow growth in activity of the new cycle, has led to suggestions that the Sun is entering a Grand Solar Minimum (GSMi), potentially as deep as the Maunder Minimum (MM). This raises questions about the persistence and predictability of solar activity. We study the autocorrelation functions and predictability R^2_L(t) of solar indices, particularly group sunspot number R_G and heliospheric modulation potential phi for which we have data during the descent into the MM. For R_G and phi, R^2_L (t) > 0.5 for times into the future of t = 4 and 3 solar cycles, respectively: sufficient to allow prediction of a GSMi onset. The lower predictability of sunspot number R_Z is discussed. The current declines in peak and mean R_G are the largest since the onset of the MM and exceed those around 1800 which failed to initiate a GSMi.

The representation of highly pathogenic avian influenza in the Chinese media

In the early 2000s the threat of Highly Pathogenic Avian Influenza captured the attention of the world's media. While China is often considered the epicentre of the panzootic, few studies have explored coverage of this variant of avian flu in China. To address this issue, the authors examined the portrayal of Highly Pathogenic Avian Influenza across four Chinese newspapers at the local and national level. A textual analysis was performed on 160 articles across an eight-year period from 2001–2008. The study approach drew from Critical Discourse Analysis and Social Representation Theory. The headline analysis showed the extent that risk of the disease was subverted by the depiction of a strong and efficient ‘China’ that was a global leader in the fight against the disease. Ideological referents were called upon to stress teamwork in confronting the crisis. The diachronic analysis illustrated how the relationship between commercial interests, science and public health risks played out within the Chinese media.

Designing and implementing livestock value chain studies: a practical aid for Highly Pathogenic and Emerging Disease (HPED) control

Value chain studies, including production system and market chain studies, are essential to value chain analysis, which when coupled with disease risk analysis is a powerful tool to identify key constraints and opportunities for disease control based on risk management in a livestock production and marketing system. Several production system and market chain studies have been conducted to support disease control interventions in South East Asia. This practical aid summarizes experiences and lessons learned from the implementation of such value chain studies in South East Asia. Based on these experiences it prioritizes the required data for the respective purpose of a value chain study and recommends data collection as well as data analysis tools. This practical aid is intended as an adjunct to the FAO value chain approach and animal diseases risk management guidelines document. Further practical advice is provided for more effective use of value chain studies in South and South East Asia as part of animal health decision support.

Measuring societal awareness of the rural agrarian landscape: indicators and scale issues

The work presented in this report is part of the effort to define the landscape state and diversity indicator in the frame of COM (2006) 508 “Development of agri-environmental indicators for monitoring the integration of environmental concerns into the common agricultural policy”. The Communication classifies the indicators according to their level of development, which, for the landscape indicator is “in need of substantial improvements in order to become fully operational”. For this reason a full re-definition of the indicator has been carried out, following the initial proposal presented in the frame of the IRENA operation (“Indicator Reporting on the Integration of Environmental Concerns into Agricultural Policy”). The new proposal for the landscape state and diversity indicator is structured in three components: the first concerns the degree of naturalness, the second landscape structure, the third the societal appreciation of the rural landscape. While the first two components rely on a strong bulk of existing literature, the development of the methodology has made evident the need for further analysis of the third component, which is based on a newly proposed top-down approach. This report presents an in-depth analysis of such component of the indicator, and the effort to include a social dimension in large scale landscape assessment.

Analysis of 16S rDNA sequences from pathogenic Leptospira serovars and use of single nucleotide polymorphisms for rapid speciation by D-HPLC

Leptospira have a worldwide distribution and include important zoonotic pathogens yet diagnosis and differentiation still tend to rely on traditional bacteriological and serological approaches. In this study a 1.3 kb fragment of the rrs gene (16S rDNA) was sequenced from a panel of 22 control strains, representing serovars within the pathogenic species Leptospira interrogans, Leptospira borgpetersenii, and Leptospira kirschneri, to identify single nucleotide polymorphisms (SNPs). These were identified in the 5' variable region of the 16S sequence and a 181 bp PCR fragment encompassing this region was used for speciation by Denaturing High Performance Liquid Chromatography (D-HPLC). This method was applied to eleven additional species, representing pathogenic, non-pathogenic and intermediate species and was demonstrated to rapidly differentiate all but 2 of the non-pathogenic Leptospira species. The method was applied successfully to infected tissues from field samples proving its value for diagnosing leptospiral infections found in animals in the UK. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.

The development of a real-time PCR to detect pathogenic Leptospira species in kidney tissue

A LightCycler(R) real-time PCR hybridization probe-based assay that detects a conserved region of the 16S rRNA gene of pathogenic but not saprophytic Leptospira species was developed for the rapid detection of pathogenic leptospires directly from processed tissue samples. In addition, a differential PCR specific for saprophytic leptospires and a control PCR targeting the porcine beta-actin gene were developed. To assess the suitability of these PCR methods for diagnosis, a trial was performed on kidneys taken from adult pigs with evidence of leptospiral infection, primarily a history of reproductive disease and serological evidence of exposure to pathogenic leptospires (n = 180) and aborted pig foetuses (n = 24). Leptospire DNA was detected by the 'pathogenic' specific PCR in 25 tissues (14%) and the control beta-actin PCR was positive in all 204 samples confirming DNA was extracted from all samples. No leptospires were isolated from these samples by culture and no positives were detected with the 'saprophytic' PCR. In a subsidiary experiment, the 'pathogenic' PCR was used to analyse kidney samples from rodents (n = 7) collected as part of vermin control in a zoo, with show animals with high microagglutination titres to Leptospira species, and five were positive. Fifteen PCR amplicons from 1 mouse, 2 rat and 14 pig kidney samples, were selected at random from positive PCRs (n = 30) and sequenced. Sequence data indicated L. interrogans DNA in the pig and rat samples and L. inadai DNA, which is considered of intermediate pathogenicity, in the mouse sample. The only successful culture was from this mouse kidney and the isolate was confirmed to be L. inadai by classical serology. These data suggest this suite of PCRs is suitable for testing for the presence of pathogenic leptospires in pig herds where abortions and infertility occur and potentially in other animals such as rodents. Crown Copyright (C) 2007 Published by Elsevier Ltd. All rights reserved.

Pathogenic LRRK2 mutations do not alter gene expression in cell model systems or human brain tissue

Point mutations in LRRK2 cause autosomal dominant Parkinson's disease. Despite extensive efforts to determine the mechanism of cell death in patients with LRRK2 mutations, the aetiology of LRRK2 PD is not well understood. To examine possible alterations in gene expression linked to the presence of LRRK2 mutations, we carried out a case versus control analysis of global gene expression in three systems: fibroblasts isolated from LRRK2 mutation carriers and healthy, non-mutation carrying controls; brain tissue from G2019S mutation carriers and controls; and HEK293 inducible LRRK2 wild type and mutant cell lines. No significant alteration in gene expression was found in these systems following correction for multiple testing. These data suggest that any alterations in basal gene expression in fibroblasts or cell lines containing mutations in LRRK2 are likely to be quantitatively small. This work suggests that LRRK2 is unlikely to play a direct role in modulation of gene expression, although it remains possible that this protein can influence mRNA expression under pathogenic cicumstances.

An investigation into the pathogenic properties of Escherichia coli strains BLR, BL21, DH5 alpha and EQ1

Aims: To examine Escherichia coli strains EQ1, DH5 alpha, BLR and BL21 for known pathogenic mechanisms. Methods and Results: Using specific DNA probes, the strains were shown not to carry the genes encoding invasion, various adhesion phenotypes or expression of a range of enterotoxins. The strains were unable to express long-chain lipopolysaccharide and were susceptible to the effects of serum complement. Using a BALB/c mouse model, the strains were shown to be unable to survive in selected tissues or to persist in the mouse gut. Using a chick model, strains EQ1, BLR and BL21 invaded livers but not spleens; only strain EQ1 persisted in the chick gut. In Merino sheep, only strain EQ1 was detected 6 d postinfection. Conclusions: Escherichia coli strains EQ1, DH5 alpha, BLR and BL21 did not carry the well-recognized pathogenic mechanisms required by strains of E. coli causing the majority of enteric infections. Significance and Impact of the Study: Escherichia coli strains EQ1, DH5 alpha, BLR and BL21 were considered to be non-pathogenic and unlikely to survive in host tissues and cause disease.

Developing consensus on hospital prescribing indicators of potential harms amenable to decision support

Aim: To develop a list of prescribing indicators specific for the hospital setting that would facilitate the prospective collection of high severity and/or high frequency prescribing errors, which are also amenable to electronic clinical decision support (CDS). Method: A three-stage consensus technique (electronic Delphi) was carried out with 20 expert pharmacists and physicians across England. Participants were asked to score prescribing errors using a 5-point Likert scale for their likelihood of occurrence and the severity of the most likely outcome. These were combined to produce risk scores, from which median scores were calculated for each indicator across the participants in the study. The degree of consensus between the participants was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or more was achieved. Results: A total of 80 prescribing errors were identified by consensus as being high or extreme risk. The most common drug classes named within the indicators were antibiotics (n=13), antidepressants (n=8), nonsteroidal anti-inflammatory drugs (n=6), and opioid analgesics (n=6).The most frequent error type identified as high or extreme risk were those classified as clinical contraindications (n=29/80). Conclusion: 80 high risk prescribing errors in the hospital setting have been identified by an expert panel. These indicators can serve as the basis for a standardised, validated tool for the collection of data in both paperbased and electronic prescribing processes, as well as to assess the impact of electronic decision support implementation or development.

Making robust policy decision using global biodiversity indicators

In order to influence global policy effectively, conservation scientists need to be able to provide robust predictions of the impact of alternative policies on biodiversity and measure progress towards goals using reliable indicators. We present a framework for using biodiversity indicators predictively to inform policy choices at a global level. The approach is illustrated with two case studies in which we project forwards the impacts of feasible policies on trends in biodiversity and in relevant indicators. The policies are based on targets agreed at the Convention on Biological Diversity (CBD) meeting in Nagoya in October 2010. The first case study compares protected area policies for African mammals, assessed using the Red List Index; the second example uses the Living Planet Index to assess the impact of a complete halt, versus a reduction, in bottom trawling. In the protected areas example, we find that the indicator can aid in decision-making because it is able to differentiate between the impacts of the different policies. In the bottom trawling example, the indicator exhibits some counter-intuitive behaviour, due to over-representation of some taxonomic and functional groups in the indicator, and contrasting impacts of the policies on different groups caused by trophic interactions. Our results support the need for further research on how to use predictive models and indicators to credibly track trends and inform policy. To be useful and relevant, scientists must make testable predictions about the impact of global policy on biodiversity to ensure that targets such as those set at Nagoya catalyse effective and measurable change.

Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit

Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.

Variation in genome organization of the plant pathogenic fungus Colletotrichum lindemuthianum

The genome structure of Colletotrichum lindemuthianum in a set of diverse isolates was investigated using a combination of physical and molecular approaches. Flow cytometric measurement of genome size revealed significant variation between strains, with the smallest genome representing 59% of the largest. Southern-blot profiles of a cloned fungal telomere revealed a total chromosome number varying from 9 to 12. Chromosome separations using pulsed-field gel electrophoresis (PFGE) showed that these chromosomes belong to two distinct size classes: a variable number of small (< 2.5 Mb) polymorphic chromosomes and a set of unresolved chromosomes larger than 7 Mb. Two dispersed repeat elements were shown to cluster on distinct polymorphic minichromosomes. Single-copy flanking sequences from these repeat-containing clones specifically marked distinct small chromosomes. These markers were absent in some strains, indicating that part of the observed variability in genome organization may be explained by the presence or absence, in a given strain, of dispensable genomic regions and/or chromosomes.

Pediastrum species as potential indicators of lake-level change in tropical South America

We explored the potential for using Pediastrum (Meyen), a genus of green alga commonly found in palaeoecological studies, as a proxy for lake-level change in tropical South America. The study site, Laguna La Gaiba (LLG) (17°45′S, 57°40′W), is a broad, shallow lake located along the course of the Paraguay River in the Pantanal, a 135,000-km2 tropical wetland located mostly in western Brazil, but extending into eastern Bolivia. Fourteen surface sediment samples were taken from LLG across a range of lake depths (2-5.2 m) and analyzed for Pediastrum. We found seven species, of which P. musteri (Tell et Mataloni), P. argentiniense (Bourr. et Tell), and P. cf. angulosum (Ehrenb.) ex Menegh. were identified as potential indicators of lake level. Results of the modern dataset were applied to 31 fossil Pediastrum assemblages spanning the early Holocene (12.0 kyr BP) to present to infer past lake level changes qualitatively. Early Holocene (12.0-9.8 kyr BP) assemblages do not show a clear signal, though abundance of P. simplex (Meyen) suggests relatively high lake levels. Absence of P. musteri, characteristic of deep, open water, and abundance of macrophyte-associated taxa indicate lake levels were lowest from 9.8 to 3.0 kyr BP. A shift to wetter conditions began at 4.4 kyr BP, indicated by the appearance of P. musteri, though inferred lake levels did not reach modern values until 1.4 kyr BP. The Pediastrum-inferred mid-Holocene lowstand is consistent with lower precipitation, previously inferred using pollen from this site, and is also in agreement with evidence for widespread drought in the South American tropics during the middle Holocene. An inference for steadily increasing lake level from 4.4 kyr BP to present is consistent with diatom-inferred water level rise at Lake Titicaca, and demonstrates coherence with the broad pattern of increasing monsoon strength from the late Holocene until present in tropical South America.

The phenology of phytoplankton blooms: ecosystems indicators from remote sensing

Remote sensing offers many advantages in the development of ecosystem indicators for the pelagic zone of the ocean. Particularly suitable in this context are the indicators arising from time series that can be constructed from remotely sensed data. For example, using ocean-colour radiometry, the phenology of phytoplankton blooms can be assessed. Metrics defined in this way show promise as informative indicators for the entire pelagic ecosystem. A simple phytoplankton–substrate model, with forcing dependent on latitude and day number is used to explore the qualitative features of bloom phenology for comparison with the results observed in a suite of 10-year time series of chlorophyll concentration, as assessed by remote sensing, from the Northwest Atlantic Ocean. The model reveals features of the dynamics that might otherwise have been overlooked in evaluation of the observational data.

Forecasting US output growth using leading indicators: an appraisal using MIDAS models

We evaluate the predictive power of leading indicators for output growth at horizons up to 1 year. We use the MIDAS regression approach as this allows us to combine multiple individual leading indicators in a parsimonious way and to directly exploit the information content of the monthly series to predict quarterly output growth. When we use real-time vintage data, the indicators are found to have significant predictive ability, and this is further enhanced by the use of monthly data on the quarter at the time the forecast is made