A general model to predict individual exposure to solar UV by using ambient irradiance data

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

Effective exposure to solar UV in building workers: influence of local and individual factors.

Excessive exposure to solar UV light is the main cause of skin cancers in humans. UV exposure depends on environmental as well as individual factors related to activity. Although outdoor occupational activities contribute significantly to the individual dose received, data on effective exposure are scarce and limited to a few occupations. A study was undertaken in order to assess effective short-term exposure among building workers and characterize the influence of individual and local factors on exposure. The effective exposure of construction workers in a mountainous area in the southern part of Switzerland was investigated through short-term dosimetry (97 dosimeters). Three altitudes, of about 500, 1500 and 2500 m were considered. Individual measurements over 20 working periods were performed using Spore film dosimeters on five body locations. The postural activity of workers was concomitantly recorded and static UV measurements were also performed. Effective exposure among building workers was high and exceeded occupational recommendations, for all individuals for at least one body location. The mean daily UV dose in plain was 11.9 SED (0.0-31.3 SED), in middle mountain 21.4 SED (6.6-46.8 SED) and in high mountain 28.6 SED (0.0-91.1 SED). Measured doses between workers and anatomical locations exhibited a high variability, stressing the role of local exposure conditions and individual factors. Short-term effective exposure ranged between 0 and 200% of ambient irradiation, indicating the occurrence of intense, subacute exposures. A predictive irradiation model was developed to investigate the role of individual factors. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure, and were also found to account more than altitude on the total variance of effective daily exposures. Targeted sensitization actions through professional information channels and specific prevention messages are recommended. Altitude outdoor workers should also benefit from preventive medical examination.

Risk-based modelling of diffuse land use impacts from rural landscapes upon salmonid fry abundance

Research has demonstrated that landscape or watershed scale processes can influence instream aquatic ecosystems, in terms of the impacts of delivery of fine sediment, solutes and organic matter. Testing such impacts upon populations of organisms (i.e. at the catchment scale) has not proven straightforward and differences have emerged in the conclusions reached. This is: (1) partly because different studies have focused upon different scales of enquiry; but also (2) because the emphasis upon upstream land cover has rarely addressed the extent to which such land covers are hydrologically connected, and hence able to deliver diffuse pollution, to the drainage network However, there is a third issue. In order to develop suitable hydrological models, we need to conceptualise the process cascade. To do this, we need to know what matters to the organism being impacted by the hydrological system, such that we can identify which processes need to be modelled. Acquiring such knowledge is not easy, especially for organisms like fish that might occupy very different locations in the river over relatively short periods of time. However, and inevitably, hydrological modellers have started by building up piecemeal the aspects of the problem that we think matter to fish. Herein, we report two developments: (a) for the case of sediment associated diffuse pollution from agriculture, a risk-based modelling framework, SCIMAP, has been developed, which is distinct because it has an explicit focus upon hydrological connectivity; and (b) we use spatially distributed ecological data to infer the processes and the associated process parameters that matter to salmonid fry. We apply the model to spatially distributed salmon and fry data from the River Eden, Cumbria, England. The analysis shows, quite surprisingly, that arable land covers are relatively unimportant as drivers of fry abundance. What matters most is intensive pasture, a land cover that could be associated with a number of stressors on salmonid fry (e.g. pesticides, fine sediment) and which allows us to identify a series of risky field locations, where this land cover is readily connected to the river system by overland flow. (C) 2010 Elsevier B.V. All rights reserved.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

Regional abundance of on-premise outlets and drinking patterns among Swiss young men: District level analyses and geographic adjustments.

INTRODUCTION AND AIMS: This study investigated the associations of alcohol outlet density with specific alcohol outcomes (consumption and consequences) among young men in Switzerland and assessed the possible geographically related variations. DESIGN AND METHODS: Alcohol consumption and drinking consequences were measured in a 2010-2011 study assessing substance use risk factors (Cohort Study on Substance Use Risk Factors) among 5519 young Swiss men. Outlet density was based on the number of on- and off-premise outlets in the district of residence. Linear regression models were run separately for drinking level, heavy episodic drinking (HED) and drinking consequences. Geographically weighted regression models were estimated when variations were recorded at the district level. RESULTS: No consistent association was found between outlet density and drinking consequences. A positive association between drinking level and HED with on-premise outlet density was found. Geographically weighted regressions were run for drinking level and HED. The predicted values for HED were higher in the southwest part of Switzerland (French-speaking part). DISCUSSION AND CONCLUSIONS: Among Swiss young men, the density of outlets and, in particular, the abundance of bars, clubs and other on-premise outlets was associated with drinking level and HED, even when drinking consequences were not significantly affected. These findings support the idea that outlet density needs to be considered when developing and implementing regional-based prevention initiatives. [Astudillo M, Kuendig H, Centeno-Gil A, Wicki M, Gmel G. Regional abundance of on-premise outlets and drinking patterns among Swiss young men: District level analyses and geographic adjustments. Drug Alcohol Rev 2014;33:526-33].

Experimental plant communities develop phylogenetically overdispersed abundance distributions during assembly

The importance of competition between similar species in driving community assembly is much debated. Recently, phylogenetic patterns in species composition have been investigated to help resolve this question: phylogenetic clustering is taken to imply environmental filtering, and phylogenetic overdispersion to indicate limiting similarity between species. We used experimental plant communities with random species compositions and initially even abundance distributions to examine the development of phylogenetic pattern in species abundance distributions. Where composition was held constant by weeding, abundance distributions became overdispersed through time, but only in communities that contained distantly related clades, some with several species (i.e., a mix of closely and distantly related species). Phylogenetic pattern in composition therefore constrained the development of overdispersed abundance distributions, and this might indicate limiting similarity between close relatives and facilitation/complementarity between distant relatives. Comparing the phylogenetic patterns in these communities with those expected from the monoculture abundances of the constituent species revealed that interspecific competition caused the phylogenetic patterns. Opening experimental communities to colonization by all species in the species pool led to convergence in phylogenetic diversity. At convergence, communities were composed of several distantly related but species-rich clades and had overdispersed abundance distributions. This suggests that limiting similarity processes determine which species dominate a community but not which species occur in a community. Crucially, as our study was carried out in experimental communities, we could rule out local evolutionary or dispersal explanations for the patterns and identify ecological processes as the driving force, underlining the advantages of studying these processes in experimental communities. Our results show that phylogenetic relations between species provide a good guide to understanding community structure and add a new perspective to the evidence that niche complementarity is critical in driving community assembly.

A stratified approach for modeling the distribution of a threatened ant species in the Swiss National Park

We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.

Use of the frc gene as a molecular marker to characterize oxalate-oxidizing bacterial abundance and diversity structure in soil.

Oxalate catabolism, which can have both medical and environmental implications, is performed by phylogenetically diverse bacteria. The formyl-CoA-transferase gene was chosen as a molecular marker of the oxalotrophic function. Degenerated primers were deduced from an alignment of frc gene sequences available in databases. The specificity of primers was tested on a variety of frc-containing and frc-lacking bacteria. The frc-primers were then used to develop PCR-DGGE and real-time SybrGreen PCR assays in soils containing various amounts of oxalate. Some PCR products from pure cultures and from soil samples were cloned and sequenced. Data were used to generate a phylogenetic tree showing that environmental PCR products belonged to the target physiological group. The extent of diversity visualised on DGGE pattern was higher for soil samples containing carbonate resulting from oxalate catabolism. Moreover, the amount of frc gene copies in the investigated soils was detected in the range of 1.64x10(7) to 1.75x10(8)/g of dry soil under oxalogenic tree (representing 0.5 to 1.2% of total 16S rRNA gene copies), whereas the number of frc gene copies in the reference soil was 6.4x10(6) (or 0.2% of 16S rRNA gene copies). This indicates that oxalotrophic bacteria are numerous and widespread in soils and that a relationship exists between the presence of the oxalogenic trees Milicia excelsa and Afzelia africana and the relative abundance of oxalotrophic guilds in the total bacterial communities. This is obviously related to the accomplishment of the oxalate-carbonate pathway, which explains the alkalinization and calcium carbonate accumulation occurring below these trees in an otherwise acidic soil. The molecular tools developed in this study will allow in-depth understanding of the functional implication of these bacteria on carbonate accumulation as a way of atmospheric CO(2) sequestration.

Improved statistical analysis of low abundance phenomena in bimodal bacterial populations.

Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods' resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.

Temporal changes in mosquito abundance (Culex pipiens), avian malaria prevalence and lineage composition

Background: Knowledge on the temporal dynamics of host/vector/parasite interactions is a pre-requisite to further address relevant questions in the fields of epidemiology and evolutionary ecology of infectious diseases. In studies of avian malaria, the natural history of Plasmodium parasites with their natural mosquito vectors, however, is mostly unknown. Methods: Using artificial water containers placed in the field, we monitored the relative abundance of parous females of Culex pipiens mosquitoes during two years (2010-2011), in a population in western Switzerland. Additionally, we used molecular tools to examine changes in avian malaria prevalence and Plasmodium lineage composition in female C. pipiens caught throughout one field season (April-August) in 2011. Results: C. pipiens relative abundance varied both between years and months, and was associated with temperature fluctuations. Total Plasmodium prevalence was high and increased from spring to summer months (13.1-20.3%). The Plasmodium community was composed of seven different lineages including P. relictum (SGS1, GRW11 and PADOM02 lineages), P. vaughani (lineage SYAT05) and other Plasmodium spp. (AFTRU5, PADOM1, COLL1). The most prevalent lineages, P. vaughani (lineage SYAT05) and P. relictum (lineage SGS1), were consistently found between years, although they had antagonistic dominance patterns during the season survey. Conclusions: Our results suggest that the time window of analysis is critical in evaluating changes in the community of avian malaria lineages infecting mosquitoes. The potential determinants of the observed changes as well as their implications for future prospects on avian malaria are discussed.

Novel targets of the CbrAB/Crc carbon catabolite control system revealed by transcript abundance in Pseudomonas aeruginosa.

The opportunistic human pathogen Pseudomonas aeruginosa is able to utilize a wide range of carbon and nitrogen compounds, allowing it to grow in vastly different environments. The uptake and catabolism of growth substrates are organized hierarchically by a mechanism termed catabolite repression control (Crc) whereby the Crc protein establishes translational repression of target mRNAs at CA (catabolite activity) motifs present in target mRNAs near ribosome binding sites. Poor carbon sources lead to activation of the CbrAB two-component system, which induces transcription of the small RNA (sRNA) CrcZ. This sRNA relieves Crc-mediated repression of target mRNAs. In this study, we have identified novel targets of the CbrAB/Crc system in P. aeruginosa using transcriptome analysis in combination with a search for CA motifs. We characterized four target genes involved in the uptake and utilization of less preferred carbon sources: estA (secreted esterase), acsA (acetyl-CoA synthetase), bkdR (regulator of branched-chain amino acid catabolism) and aroP2 (aromatic amino acid uptake protein). Evidence for regulation by CbrAB, CrcZ and Crc was obtained in vivo using appropriate reporter fusions, in which mutation of the CA motif resulted in loss of catabolite repression. CbrB and CrcZ were important for growth of P. aeruginosa in cystic fibrosis (CF) sputum medium, suggesting that the CbrAB/Crc system may act as an important regulator during chronic infection of the CF lung.

Occupational exposure to solar ultraviolet radiation of outdoor workers in France

Question: Outdoor occupational exposure could be associated with important cumulative and intense exposure to ultraviolet (UV) solar radiation. Such exposure would increase risk of skin cancer. However, little information exists on jobs associated with intense UV exposure. The objective of this study was to characterise occupational UV exposure in a representative sample in France. Methods: A population-based survey was conducted in May-June 2012 through computer-assisted telephonic interviews in population 25 to 69 years of age. Individual UV irradiation was computed with declared time and place of residence matched to UV records from satellite measurement (Eurosun project). We analysed factors influencing exposure to UV (annual average and seasonal peak). Results: A total of 1442 individuals declared having an occupational exposure to UV which represents 18% of population aged 25 to 69 years. Outdoor workers were more frequently men (58%), aged 40-54 (43%), with a phototype III or IV (69%). Occupations associated with highest UV exposure were: construction workers (annual daily average 62.8 Joules/m2), gardeners (62.6), farmers (52.8), culture/art/social sciences workers (52.0) and transport workers/mail carriers (49.5). The maximum of UVA exposure was found for occupation with a strong seasonality of exposure: culture, art or social sciences works (98.1 Joules/m2), construction works (97.2), gardening (96.7) and farming (95.0). Significant factors associated with high occupational UV exposure were gender (men vs. women: 53.6 vs. 42.6), phototype (IV vs. I: 51.9 vs. 45.5) and taking lunch outdoors (always vs. never: 59.8 vs. 48.6). Conclusion: Our study showed that some occupations were associated with particularly intense UV exposure such as farmers, gardeners, construction workers. Other unexpected occupations were also associated with high UV exposure such as transport workers, mail carriers and culture/art/social sciences workers.