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Boulogne-sur-Mer, France

Orton T.G.,French National Institute for Agricultural Research | Saby N.P.A.,French National Institute for Agricultural Research | Arrouays D.,French National Institute for Agricultural Research | Jolivet C.C.,French National Institute for Agricultural Research | And 6 more authors.
Science of the Total Environment | Year: 2013

Lindane [γ-hexachlorocyclohexane (γ-HCH)] is an organochlorine pesticide with toxic effects on humans. It is bioaccumulative and can remain in soils for long periods, and although its use for crop spraying was banned in France in 1998, it is possible that residues from before this time remain in the soil. The RMQS soil monitoring network consists of soil samples from 2200 sites on a 16. km regular grid across France, collected between 2002 and 2009. We use 726 measurements of the Lindane concentration in these samples to (i) investigate the main explanatory factors for its spatial distribution across France, and (ii) map this distribution. Geostatistics provides an appropriate framework to analyze our spatial dataset, though two issues regarding the data are worth special consideration: first, the harmonization of two subsets of the data (which were analyzed using different measurement processes), and second, the large proportion of data from one of these subsets that fell below a limit of quantification. We deal with these issues using recent methodological developments in geostatistics. Results demonstrate the importance of land use and rainfall for explaining part of the variability of Lindane across France: land use due to the past direct input of Lindane on cropland and its subsequent persistence in the soil, and rainfall due to the re-deposition of volatilized Lindane. Maps show the concentrations to be generally largest in the north and northwest of France, areas of more intensive agricultural land. We also compare levels to some contamination thresholds taken from the literature, and present maps showing the probability of Lindane concentrations exceeding these thresholds across France. These maps could be used as guidelines for deciding which areas require further sampling before some possible remediation strategy could be applied. © 2012 Elsevier B.V.

Orton T.G.,French National Institute for Agricultural Research | Saby N.P.A.,French National Institute for Agricultural Research | Arrouays D.,French National Institute for Agricultural Research | Jolivet C.C.,French National Institute for Agricultural Research | And 7 more authors.
Journal of Environmental Quality | Year: 2012

Polychlorinated biphenyls (PCBs) are highly toxic environmental pollutants that can accumulate in soils. We consider the problem of explaining and mapping the spatial distribution of PCBs using a spatial data set of 105 PCB-187 measurements from a region in the north of France. A large proportion of our data (35%) fell below a quantification limit (QL), meaning that their concentrations could not be determined to a sufficient degree of precision. Where a measurement fell below this QL, the inequality information was all that we were presented with. In this work, we demonstrate a full geostatistical analysis-bringing together the various components, including model selection, cross-validation, and mapping-using censored data to represent the uncertainty that results from below-QL observations. We implement a Monte Carlo maximum likelihood approach to estimate the geostatistical model parameters. To select the best set of explanatory variables for explaining and mapping the spatial distribution of PCB-187 concentrations, we apply the Akaike Information Criterion (AIC). Th e AIC provides a trade-offbetween the goodness-of-fit of a model and its complexity (i.e., the number of covariates). We then use the best set of explanatory variables to help interpolate the measurements via a Bayesian approach, and produce maps of the predictions. We calculate predictions of the probability of exceeding a concentration threshold, above which the land could be considered as contaminated. Th e work demonstrates some differences between approaches based on censored data and on imputed data (in which the below-QL data are replaced by a value of half of the QL). Cross-validation results demonstrate better predictions based on the censored data approach, and we should therefore have confidence in the information provided by predictions from this method. © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Villanneau E.J.,French National Institute for Agricultural Research | Saby N.P.A.,French National Institute for Agricultural Research | Marchant B.P.,Rothamsted Research | Jolivet C.C.,French National Institute for Agricultural Research | And 6 more authors.
Science of the Total Environment | Year: 2011

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16. km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules. © 2011 Elsevier B.V.

Brauge T.,Laboratory for Food Safety | Sadovskaya I.,University of the Littoral Opal Coast | Faille C.,French National Institute for Agricultural Research | Benezech T.,French National Institute for Agricultural Research | And 3 more authors.
FEMS Microbiology Letters | Year: 2015

The aim of this study was to characterize the Listeria monocytogenes biofilm and particularly the nature of the carbohydrates in the biofilm extracellular matrix and culture supernatant versus to cell wall carbohydrates. Listeria monocytogenes serotype 1/2a and 4b strains were able to form complex biofilms embedded in an extracellular matrix. The soluble carbohydrates from biofilm extracellular matrix and culture supernatant were identified as teichoic acids, structurally identical to cell wall teichoic acids. In addition, the DSS 1130 BFA2 strain had a serotype 1/2a teichoic acid lacking N-acetyl glucosamine glycosylation due to a mutation in the lmo2550 gene. Consequently, we hypothesized that the extracellular teichoic acids in L. monocytogenes biofilms have the same origin as cell wall teichoic acid. © FEMS 2015.

Buffet J.-P.,French National Institute for Agricultural Research | Pisanu B.,CNRS Science Conservation Center | Brisse S.,Institute Pasteur Paris | Roussel S.,Laboratory for Food Safety | And 4 more authors.
PLoS ONE | Year: 2013

Host-specificity is an intrinsic feature of many bacterial pathogens, resulting from a long history of co-adaptation between bacteria and their hosts. Alpha-proteobacteria belonging to the genus Bartonella infect the erythrocytes of a wide range of mammal orders, including rodents. In this study, we performed genetic analysis of Bartonella colonizing a rodent community dominated by bank voles (Myodes glareolus) and wood mice (Apodemus sylvaticus) in a French suburban forest to evaluate their diversity, their capacity to recombine and their level of host specificity. Following the analysis of 550 rodents, we detected 63 distinct genotypes related to B. taylorii, B. grahamii, B. doshiae and a new B. rochalimae-like species. Investigating the most highly represented species, we showed that B. taylorii strain diversity was markedly higher than that of B. grahamii, suggesting a possible severe bottleneck for the latter species. The majority of recovered genotypes presented a strong association with either bank voles or wood mice, with the exception of three B. taylorii genotypes which had a broader host range. Despite the physical barriers created by host specificity, we observed lateral gene transfer between Bartonella genotypes associated with wood mice and Bartonella adapted to bank voles, suggesting that those genotypes might co-habit during their life cycle. © 2013 Buffet et al.

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