Impact of geographical region on urinary metabolomic and plasma fatty acid profiles in subjects with the metabolic syndrome across Europe: the LIPGENE study

The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R 2 X: 0•33, Q 2: 0•39) and plasma fatty acid (R 2 X: 0•32, Q 2: 0•60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0•001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0•001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.

Grassland leafhoppers (Hemiptera: Auchenorrhyncha) as indicators of habitat condition - a comparison of between-site and between-year differences in assemblage composition

The Auchenorrhyncha (leafhoppers) show great potential as indicators of grassland habitat quality, which would make them useful as a conservation tool. However, they are known to have labile populations. The relative importance of site identity and the year of sampling in the composition of leafhopper assemblages on chalk grassland are assessed for two sets of sites sampled twice. The study included a total of 95 sites (one set of 54, the other of 41), and demonstrated that for both sets the vegetation community and geographical location had high explanatory value, while the influence of year was small. The conclusion is that, notwithstanding population fluctuations, the leafhopper assemblages are a good indicator of habitat quality, and represent a potentially valuable tool in grassland conservation and restoration.

Linking bees and flowers: How do floral communities structure pollinator communities?

Pollinators provide essential ecosystem services, and declines in some pollinator communities around the world have been reported. Understanding the fundamental components defining these communities is essential if conservation and restoration are to be successful. We examined the structure of plant-pollinator communities in a dynamic Mediterranean landscape, comprising a mosaic of post-fire regenerating habitats, and which is a recognized global hotspot for bee diversity. Each community was characterized by a highly skewed species abundance distribution, with a few dominant and many rare bee species, and was consistent with a log series model indicating that a few environmental factors govern the community. Floral community composition, the quantity and quality of forage resources present, and the geographic locality organized bee communities at various levels: (1) The overall structure of the bee community (116 species), as revealed through ordination, was dependent upon nectar resource diversity (defined as the variety of nectar volume-concentration combinations available), the ratio of pollen to nectar energy, floral diversity, floral abundance, and post-fire age. (2) Bee diversity, measured as species richness, was closely linked to floral diversity (especially of annuals), nectar resource diversity, and post-fire age of the habitat. (3) The abundance of the most common species was primarily related to post-fire age, grazing intensity, and nesting substrate availability. Ordination models based on age-characteristic post-fire floral community structure explained 39-50% of overall variation observed in bee community structure. Cluster analysis showed that all the communities shared a high degree of similarity in their species composition (27-59%); however, the geographical location of sites also contributed a smaller but significant component to bee community structure. We conclude that floral resources act in specific and previously unexplored ways to modulate the diversity of the local geographic species pool, with specific disturbance factors, superimposed upon these patterns, mainly affecting the dominant species.

Rapeseed cytoplasm gives advantage in wild relatives and complicates genetically modified crop biocontainment

Biocontainment methods for genetically modified crops closest to commercial reality (chloroplast transformation, male sterility) would be compromised (in absolute terms) by seed-mediated gene flow leading to chloroplast capture. Even in these circumstances, however, it can be argued that biocontainment still represses transgene movement, with the efficacy depending on the relative frequency of seed-and pollen-mediated gene flow. In this study, we screened for crop-specific chloroplast markers from rapeseed (Brassica napus) amongst sympatric and allopatric populations of wild B. oleracea in natural cliff-top populations and B. rapa in riverside and weedy populations. We found only modest crop chloroplast presence in wild B. oleracea and in weedy B. rapa, but a surprisingly high incidence in sympatric (but not in allopatric) riverside B. rapa populations. Chloroplast inheritance models indicate that elevated crop chloroplast acquisition is best explained if crop cytoplasm confers selective advantage in riverside B. rapa populations. Our results therefore imply that chloroplast transformation may slow transgene recruitment in two settings, but actually accelerate transgene spread in a third. This finding suggests that the appropriateness of chloroplast transformation for biocontainment policy depends on both context and geographical location.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

Humoral immunity following chickenpox is influenced by geography and ethnicity

Objectives To investigate the contribution of ethnicity and geographical location to varicella-zoster virus (VZV) serostatus and antibody concentrations. Methods The presence and concentrations of antibodies to VZV were measured in 639 Bangladeshi women born in Bangladesh (BBB), 94 Bangladeshi women born in the UK (BUK) and 262 White women born in the UK (WUK). The results were anaylsed in relation to demographic and social data. Results BBB women were significantly less likely to be VZV seropositive at all ages than both BUK and WUK women. However, the odds of a Bangladeshi-born woman being seropositive increased by 1.04 for each year under the age of 15 spent in the UK. In contrast, antibody concentrations were significantly lower in ethnic Bangladeshi women, irrespective of country of birth. White, but not Bangladeshi women, showed evidence of antibody boosting over time despite the latter having more exposure to children. Conclusion Geographical location during childhood is the major influence on age of primary infection with VZV while the level of antibody is related to ethnicity. Since the risk of re-infection with VZV following both natural infection and vaccination is increased as antibody concentrations fall, these results have implications for VZV vaccination programmes particularly in non-White populations.

Community mix, affordable housing and metropolitan planning strategy in Melbourne

Income segregation across Melbourne’s residential communities is widening, and at a pace faster than in some other Australian cities. The widening gap between Melbourne’s rich and poor communities raises fears about concentrations of poverty and social exclusion, particularly if the geography of these communities is such that they and their residents are increasingly isolated from urban services and employment centres. Social exclusion in our metropolitan areas and the government responses to it are commonly thought to be the proper domain of social and economic policy. The role of urban planning is typically neglected, yet it helps shape the economic opportunities available to communities in its attempts to influence the geographical location of urban services, infrastructure and jobs. Under the current metropolitan strategy ‘Melbourne 2030’ urban services and transport infrastructure are to be concentrated within Principal Activity Centres spread throughout the metropolitan area and it is the intention that lower-income households should have ready access to these activity centres. However, the Victorian state government has few housing policy instruments to achieve this goal and there are fears that community mix may suffer as house prices and rents are bid up in the vicinity of Principal Activity Centres, and lower-income households are displaced. But are these fears justified by the changing geography of house prices in the metropolitan region? This is the key research question addressed in this paper which examines whether the Victorian practice of placing reliance on the market to deliver affordable housing, while intervening to promote a more compact pattern of urban settlement, is effective.

The relative importance sector and regional factors in Italy

The benefits of sector and regional diversification have been well documented in the literature but have not previously been investigated in Italy. In addition, previous studies have used geographically defined regions, rather than economically functional areas, when performing the analysis even though most would argue that it is the economic structure of the area that will lead to differences in demand and hence property performance. This study therefore uses economically defined regions of Italy to test the relative benefits of regional diversification versus sector diversification within the Italian real estate portfolio. To examine this issue we use constrained cross-section regressions the on the sector and regional affiliation of 14 cities in Italy to extract the “pure” return effects of the different factors using annual data over the period 1989 to 2003. In contrast, to previous studies we find that regional factors effects in Italy have a much greater influence on property returns than sector-specific effects, which is probably a direct result of using the extremely diverse economic regions of Italy rather than arbitrary geographically locations. Be that as it may, the results strongly suggest that that diversification across the regions of Italy used here is likely to offer larger risk reduction benefits than a sector diversification strategy within a region. In other words, fund managers in Italy must monitor the regional composition of their portfolios more closely than its sector allocation. Additionally, the results supports that contemporary position that ‘regional areas’ based on economic function, provide greater diversification benefits rather than areas defined by geographical location.

Virulotyping and antimicrobial resistance typing of salmonella enterica serovars relevant to human health in Europe

The combination of virulence gene and antimicrobial resistance gene typing using DNA arrays is a recently developed genomics-based approach to bacterial molecular epidemiology. We have now applied this technology to 523 Salmonella enterica subsp. enterica strains collected from various host sources and public health and veterinary institutes across nine European countries. The strain set included the five predominant Salmonella serovars isolated in Europe (Enteritidis, Typhimurium, Infantis, Virchow, and Hadar). Initially, these strains were screened for 10 potential virulence factors (avrA, ssaQ, mgtC, siiD, sopB, gipA, sodC1, sopE1, spvC, and bcfC) by polymerase chain reaction. The results indicated that only 14 profiles comprising these genes (virulotypes) were observed throughout Europe. Moreover, most of these virulotypes were restricted to only one (n = 9) or two (n = 4) serovars. The data also indicated that the virulotype did not vary significantly with host source or geographical location. Subsequently, a representative subset of 77 strains was investigated using a microarray designed to detect 102 virulence and 49 resistance determinants. The results confirmed and extended the previous observations using the virulo-polymerase chain reaction screen. Strains belonging to the same serovar grouped together, indicating that the broader virulence-associated gene complement corresponded with the serovar. There were, however, some differences in the virulence gene profiles between strains belonging to an individual serovar. This variation occurred primarily within those virulence genes that were prophage encoded, in fimbrial clusters or in the virulence plasmid. It seems likely that such changes enable Salmonella to adapt to different environmental conditions, which might be reflected in serovar-specific ecology. In this strain subset a number of resistance genes were detected and were serovar restricted to a varying degree. Once again the profiles of those genes encoding resistance were similar or the same for each serovar in all hosts and countries investigated.

Sea surface temperature from a geostationary satellite by optimal estimation

Optimal estimation (OE) is applied as a technique for retrieving sea surface temperature (SST) from thermal imagery obtained by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on Meteosat 9. OE requires simulation of observations as part of the retrieval process, and this is done here using numerical weather prediction fields and a fast radiative transfer model. Bias correction of the simulated brightness temperatures (BTs) is found to be a necessary step before retrieval, and is achieved by filtered averaging of simulations minus observations over a time period of 20 days and spatial scale of 2.5° in latitude and longitude. Throughout this study, BT observations are clear-sky averages over cells of size 0.5° in latitude and longitude. Results for the OE SST are compared to results using a traditional non-linear retrieval algorithm (“NLSST”), both validated against a set of 30108 night-time matches with drifting buoy observations. For the OE SST the mean difference with respect to drifter SSTs is − 0.01 K and the standard deviation is 0.47 K, compared to − 0.38 K and 0.70 K respectively for the NLSST algorithm. Perhaps more importantly, systematic biases in NLSST with respect to geographical location, atmospheric water vapour and satellite zenith angle are greatly reduced for the OE SST. However, the OE SST is calculated to have a lower sensitivity of retrieved SST to true SST variations than the NLSST. This feature would be a disadvantage for observing SST fronts and diurnal variability, and raises questions as to how best to exploit OE techniques at SEVIRI's full spatial resolution.

“Pussy cat, pussy cat where have you been..?” Evaluating the use of stable isotopes, radiogenic isotopes and trace elements for investigating the ecology of Panthera leo

1. Understanding the behaviour and ecology of large carnivores is becoming increasingly important as the list of endangered species grows, with felids such as Panthera leo in some locations heading dangerously close to extinction in the wild. In order to have more reliable and effective tools to understand animal behaviour, movement and diet, we need to develop novel, integrated approaches and effective techniques to capture a detailed profile of animal foraging and movement patterns. 2. Ecological studies have shown considerable interest in using stable isotope methods, both to investigate the nature of animal feeding habits, and to map their geographical location. However, recent work has suggested that stable isotope analyses of felid fur and bone is very complex and does not correlate directly with the isotopic composition of precipitation (and hence geographical location). 3. We present new data that suggest these previous findings may be atypical, and demonstrate that isotope analyses of Felidae are suitable for both evaluating dietary inputs and establishing geo-location as they have strong environmental referents to both food and water. These data provide new evidence of an important methodology that can be applied to the family Felidae for future research in ecology, conservation, wildlife forensics and archaeological science.

The location of executive suites and business centers in the United States: an exploratory analysis

Increasingly, corporate occupiers seek more flexible ways of meeting their accommodation needs. One consequence of this process has been the growth of the executive suite, serviced office or business centre market. This paper, the final report of a research project funded by the Real Estate Research Institute, focuses upon the geographical distribution of business centers offering executive suites within the US. After a brief review of the development of the market, the paper examines the availability of data, provides basic descriptive statistics of the distribution of executive suites by state and by metropolitan statistical area and then attempts to model the distribution using demographic and socio-economic data at MSA level. The distribution reflects employment in key growth sectors and the position of the MSA in the urban hierarchy. An appendix presents a preliminary view of the global distribution of suites.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Estimating surface CO2 fluxes from space-borne dry air mole fraction observations using an Ensemble Kalman filter

We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Cue combination for 3D location judgements

Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only 'physical' (stereo and motion parallax) or 'texture-based' cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the tarte relative to other objects was varied, the ration of 'physical' to 'texture-based' thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying geometric reconstruction.