A new approach to estimate soil organic carbon content targets in European croplands topsoils.

Adopting land management practices that increase the stock of soil organic carbon (SOC) in croplands is widely promoted as a win-win strategy to enhance soil health and mitigate climate change. In this context, the definition of reference SOC content and stock values is needed to provide reliable targets to farmers, policymakers, and stakeholders. In this study, we used the LUCAS dataset to compare different methods for evaluating reference SOC content and stock values in European croplands topsoils (0-20 cm depth). Methods gave generally similar estimates although being built on very different assumptions. In the absence of an objective criterion to establish which approach is the most suitable to determine SOC reference values, we propose an ensemble modelling approach that consists in extracting the estimates using different relevant methods and retaining the median value among them. Interestingly, this approach led us to select values from the three different approaches with similar frequencies. Using estimated bulk density values, we obtained a first rough estimate of 3.5 Gt C of SOC storage potential in the cropland topsoils that we interpret as a long-term aspirational target that would be reachable only under extreme changes in agricultural practices. The use of additional methods in the ensemble modelling approach and more valid statistical spatial estimates may further refine our approach designed for the estimation of SOC reference values for croplands.

Pesticide Residues in French Soils: Occurrence, Risks, and Persistence.

Contamination of the environment by pesticide residues is a growing concern given their widespread presence in the environment and their effects on ecosystems. Only a few studies have addressed the occurrence of pesticides in soils, and their results highlighted the need for further research on the persistence and risks induced by those substances. We monitored 111 pesticide residues (48 fungicides, 36 herbicides, 25 insecticides and/or acaricides, and two safeners) in 47 soils sampled across France under various land uses (arable lands, vineyards, orchards, forests, grasslands, and brownfields). Pesticides were found in 98% of the sites (46 of the 47 sampled), including untreated areas such as organic fields, forests, grasslands, and brownfields, with up to 33 different substances detected in one sample, mostly fungicides and herbicides. The concentrations of herbicides were the highest in soils with glyphosate, and its transformation product, AMPA, contributed 70% of the cumulative herbicides. Risk assessment underlined a moderate to high risk for earthworms in arable soils mostly attributed to insecticides and/or acaricides. Finally, the comparison with pesticide application by farmers underlines the presence of some residues long after their supposed 90% degradation and at concentrations higher than predicted environmental concentrations, leading to questions their real persistence in soils.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

Management of soil pH promotes nitrous oxide reduction and thus mitigates soil emissions of this greenhouse gas.

While concerns about human-induced effects on the Earth's climate have mainly concentrated on carbon dioxide (CO2) and methane (CH4), reducing anthropogenic nitrous oxide (N2O) flux, mainly of agricultural origin, also represents an opportunity for substantial mitigation. To develop a solution that induces neither the transfer of nitrogen pollution nor decreases agricultural production, we specifically investigated the last step of the denitrification pathway, the N2O reduction path, in soils. We first observed that this path is mainly driven by soil pH and is progressively inhibited when pH is lower than 6.8. During field experiments, we observed that liming acidic soils to neutrality made N2O reduction more efficient and decreased soil N2O emissions. As we estimated acidic fertilized soils to represent 37% [27-50%] of French soils, we calculated that liming could potentially decrease France's total N2O emissions by 15.7% [8.3-21.2%]. Nevertheless, due to the different possible other impacts of liming, we currently recommend that the deployment of this solution to mitigate N2O emission should be based on local studies that take into account agronomic, environmental and economic aspects.

National estimation of soil organic carbon storage potential for arable soils: A data-driven approach coupled with carbon-landscape zones.

Soil organic carbon (SOC) is important for its contributions to agricultural production, food security, and ecosystem services. Increasing SOC stocks can contribute to mitigate climate change by transferring atmospheric CO2 into long-lived soil carbon pools. The launch of the 4 per 1000 initiative has resulted in an increased interest in developing methods to quantity the additional SOC that can be stored in soil under different management options. In this work, we have made a first attempt to estimate SOC storage potential of arable soils using a data-driven approach based on the French National Soil Monitoring Network. The data-driven approach was used to determine the maximum SOC stocks of arable soils for France. We first defined different carbon-landscape zones (CLZs) using clustering analysis. We then computed estimates of the highest possible values using percentile of 0.8, 0.85, 0.9 and 0.95 of the measured SOC stocks within these CLZs. The SOC storage potential was calculated as the difference between the maximum SOC stocks and current SOC stocks for topsoil and subsoil. The percentile used to determine highest possible SOC had a large influence on the estimates of French national SOC storage potential. When the percentile increased from 0.8 to 0.95, the national SOC storage potential increased by two to three-fold, from 336 to 1020 Mt for topsoil and from 165 to 433 Mt for subsoil, suggesting a high sensitivity of this approach to the selected percentile. Nevertheless, we argue that this approach can offer advantages from an operational point of view, as it enables to set targets of SOC storage taking into account both policy makers' and farmers' considerations about their feasibility. Robustness of the estimates should be further assessed using complementary approaches such as mechanistic modelling.

Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in France.

Reducing environmental health inequalities has become a major focus of public health efforts in France, as evidenced by the French action plans for health and the environment. To evaluate environmental inequalities, routine monitoring networks provide a valuable source of data on environmental contamination, which can be used in integrated assessments, to identify overexposed populations and prioritize actions. However, available databases generally do not meet sufficient spatial representativeness to characterize population exposure, as they are usually not assembled for this specific purpose. The aim of this study was to develop geoprocessing procedures and statistical methods to build spatial environmental variables (water, air, soil, and food pollutant concentrations) at a fine resolution, and provide appropriate input for the exposure modelling. Those methods were designed to combine in situ monitoring data with correlated auxiliary information (for example, atmospheric emissions, population, and altitude), in order to better represent the variability of the environmental compartment quality. The MODUL'ERS multimedia exposure model developed by INERIS (French Institute for industrial Environment and Risks) was then used to assess the transfer of substances from the environment to humans, through inhalation and ingestion pathway characterization. We applied the methodology to a carcinogenic Polycyclic Aromatic Hydrocarbon substance, benzo[a]pyrene(B[a]P), to map spatialized exposure indicators, at the national scale. The largest environmental contribution corresponded to the ingestion pathway. Data processing algorithms and calculation of exposure will be integrated into the French coordinated integrated environment and health platform PLAINE (PLteforme intégrée d'Analyse des INégalités Environnementales) which has been developed to map and analyze environmental health inequalities.

Biogeography of soil bacteria and archaea across France.

Over the last two decades, a considerable effort has been made to decipher the biogeography of soil microbial communities as a whole, from small to broad scales. In contrast, few studies have focused on the taxonomic groups constituting these communities; thus, our knowledge of their ecological attributes and the drivers determining their composition and distribution is limited. We applied a pyrosequencing approach targeting 16S ribosomal RNA (rRNA) genes in soil DNA to a set of 2173 soil samples from France to reach a comprehensive understanding of the spatial distribution of bacteria and archaea and to identify the ecological processes and environmental drivers involved. Taxonomic assignment of the soil 16S rRNA sequences indicated the presence of 32 bacterial phyla or subphyla and 3 archaeal phyla. Twenty of these 35 phyla were cosmopolitan and abundant, with heterogeneous spatial distributions structured in patches ranging from a 43- to 260-km radius. The hierarchy of the main environmental drivers of phyla distribution was soil pH > land management > soil texture > soil nutrients > climate. At a lower taxonomic level, 47 dominant genera belonging to 12 phyla aggregated 62.1% of the sequences. We also showed that the phylum-level distribution can be determined largely by the distribution of the dominant genus or, alternatively, reflect the combined distribution of all of the phylum members. Together, our study demonstrated that soil bacteria and archaea present highly diverse biogeographical patterns on a nationwide scale and that studies based on intensive and systematic sampling on a wide spatial scale provide a promising contribution for elucidating soil biodiversity determinism.

Fine resolution map of top- and subsoil carbon sequestration potential in France.

Although soils have a high potential to offset CO2 emissions through its conversion into soil organic carbon (SOC) with long turnover time, it is widely accepted that there is an upper limit of soil stable C storage, which is referred to SOC saturation. In this study we estimate SOC saturation in French topsoil (0-30cm) and subsoil (30-50cm), using the Hassink equation and calculate the additional SOC sequestration potential (SOCsp) by the difference between SOC saturation and fine fraction C on an unbiased sampling set of sites covering whole mainland France. We then map with fine resolution the geographical distribution of SOCsp over the French territory using a regression Kriging approach with environmental covariates. Results show that the controlling factors of SOCsp differ from topsoil and subsoil. The main controlling factor of SOCsp in topsoils is land use. Nearly half of forest topsoils are over-saturated with a SOCsp close to 0 (mean and standard error at 0.19±0.12) whereas cropland, vineyard and orchard soils are largely unsaturated with degrees of C saturation deficit at 36.45±0.68% and 57.10±1.64%, respectively. The determinant of C sequestration potential in subsoils is related to parent material. There is a large additional SOCsp in subsoil for all land uses with degrees of C saturation deficit between 48.52±4.83% and 68.68±0.42%. Overall the SOCsp for French soils appears to be very large (1008Mt C for topsoil and 1360Mt C for subsoil) when compared to previous total SOC stocks estimates of about 3.5Gt in French topsoil. Our results also show that overall, 176Mt C exceed C saturation in French topsoil and might thus be very sensitive to land use change.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

Mapping and predictive variations of soil bacterial richness across France.

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters.

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses.

Multivariate spatial analyses of the distribution and origin of trace and major elements in soils surrounding a secondary lead smelter.

Major and trace elements in soils originate from natural processes and different anthropogenic activities which are difficult to discriminate. On a 17-ha impacted site in northern France, two industrial sources of soil contamination were xidentified: a former iron foundry and a current secondary lead smelter. To discriminate and map natural and anthropogenic sources of major and trace elements on this site, the rarely applied MULTISPATI-principal component analysis (PCA) method was used. Using a 20-m × 20-m grid, 247 topsoil horizons were sampled and analysed with a field-portable X-ray fluorescence analyser for screening soil contamination. The study site was heavily contaminated with Pb and, to a lesser degree, with Sn. Summary statistics and enrichment factors allowed the differentiation of the main lithogenic or anthropogenic origin of the elements. The MULTISPATI-PCA method, which explained 73.9 % of the variability with the three first factors, evidenced strong spatial structures. Those spatial structures were attributed to different natural and artificial processes in the study area. The first axis can be interpreted as a lithogenic effect. Axes 2 and 3 reflect the two different contamination sources. Pb, Sn and S originated from the secondary lead smelter while Fe and Ca were mainly derived from the old iron foundry activity and the old railway built with foundry sand. This study demonstrated that the MULTISPATI-PCA method can be successfully used to investigate multicontaminated sites to discriminate the various sources of contamination.

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape.

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km(2) , by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., ß-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management.

Mapping and determinism of soil microbial community distribution across an agricultural landscape.

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity.

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Low occurrence of Pseudomonas aeruginosa in agricultural soils with and without organic amendment.

The occurrence of Pseudomonas aeruginosa was monitored at a broad spatial scale in French agricultural soils, from various soil types and under various land uses to evaluate the ability of soil to be a natural habitat for that species. To appreciate the impact of agricultural practices on the potential dispersion of P. aeruginosa, we further investigated the impact of organic amendment at experimental sites in France and Burkina Faso. A real-time quantitative PCR (qPCR) approach was used to analyze a set of 380 samples selected within the French RMQS ("Réseau de Mesures de la Qualité des Sols") soil library. In parallel, a culture-dependent approach was tested on a subset of samples. The results showed that P. aeruginosa was very rarely detected suggesting a sporadic presence of this bacterium in soils from France and Burkina Faso, whatever the structural and physico-chemical characteristics or climate. When we analyzed the impact of organic amendment on the prevalence of P. aeruginosa, we found that even if it was detectable in various manures (at levels from 10(3) to 10(5) CFU or DNA targets (g drywt)(-1) of sample), it was hardly ever detected in the corresponding soils, which raises questions about its survival. The only case reports were from a vineyard soil amended with a compost of mushroom manure in Burgundy, and a few samples from two fields amended with raw urban wastes in the sub-urban area of Ouagadougou, Burkina Faso. In these soils the levels of culturable cells were below 10 CFU (g drywt)(-1).

Analyzing the spatial distribution of PCB concentrations in soils using below-quantification limit data.

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). The AIC provides a trade-off between 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. The 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.

Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France.

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.

Spatial distribution of lindane in top soil of Northern France.

Lindane is a persistent organochlorine insecticide and the use of this insecticide in agriculture was banned in France in 1998. In this study we investigated the concentrations of lindane in top soil in Northern France and used robust geostatistics to map the geographical distribution of lindane. The study was based on a 16 km x 16 km grid covering an area of ca 25,000 km(2). Lindane was found in all soils, even those from non-agricultural-application areas. Very low ratios of alpha-/gamma-HCH and delta-/gamma-HCH suggested that a long time had passed since technical HCH was used in the studied area, or that emission sources of lindane were still present. A strong gradient in lindane concentration was observed, with the highest lindane concentrations in an area located in the northern region. Results suggested that some of the lindane observed in the high concentration area may have come from volatilization of old lindane applied to intensively cultivated areas, which was then transported by prevailing winds coming from the south-west and deposited in a densely inhabited depression.

Spatial patterns of bacterial taxa in nature reflect ecological traits of deep branches of the 16S rRNA bacterial tree.

Whether bacteria display spatial patterns of distribution and at which level of taxonomic organization such patterns can be observed are central questions in microbial ecology. Here we investigated how the total and relative abundances of eight bacterial taxa at the phylum or class level were spatially distributed in a pasture by using quantitative PCR and geostatistical modelling. The distributions of the relative abundance of most taxa varied by a factor of 2.5-6.5 and displayed strong spatial patterns at the field scale. These spatial patterns were taxon-specific and correlated to soil properties, which indicates that members of a bacterial clade defined at high taxonomical levels shared specific ecological traits in the pasture. Ecologically meaningful assemblages of bacteria at the phylum or class level in the environment provides evidence that deep branching patterns of the 16S rRNA bacterial tree are actually mirrored in nature.