Publications by authors named "Dominique Arrouays"

21 Publications

  • Page 1 of 1

Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France.

Glob Chang Biol 2021 Jun 8;27(11):2458-2477. Epub 2021 Apr 8.

INRAE, UMR ISPA, Bordeaux Sciences Agro, Villenave D'Ornon, France.

Increasing soil organic carbon (SOC) stocks is a promising way to mitigate the increase in atmospheric CO concentration. Based on a simple ratio between CO anthropogenic emissions and SOC stocks worldwide, it has been suggested that a 0.4% (4 per 1000) yearly increase in SOC stocks could compensate for current anthropogenic CO emissions. Here, we used a reverse RothC modelling approach to estimate the amount of C inputs to soils required to sustain current SOC stocks and to increase them by 4‰ per year over a period of 30 years. We assessed the feasibility of this aspirational target first by comparing the required C input with net primary productivity (NPP) flowing to the soil, and second by considering the SOC saturation concept. Calculations were performed for mainland France, at a 1 km grid cell resolution. Results showed that a 30%-40% increase in C inputs to soil would be needed to obtain a 4‰ increase per year over a 30-year period. 88.4% of cropland areas were considered unsaturated in terms of mineral-associated SOC, but characterized by a below target C balance, that is, less NPP available than required to reach the 4‰ aspirational target. Conversely, 90.4% of unimproved grasslands were characterized by an above target C balance, that is, enough NPP to reach the 4‰ objective, but 59.1% were also saturated. The situation of improved grasslands and forests was more evenly distributed among the four categories (saturated vs. unsaturated and above vs below target C balance). Future data from soil monitoring networks should enable to validate these results. Overall, our results suggest that, for mainland France, priorities should be (1) to increase NPP returns in cropland soils that are unsaturated and have a below target carbon balance and (2) to preserve SOC stocks in other land uses.
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http://dx.doi.org/10.1111/gcb.15547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252610PMC
June 2021

Can N O emissions offset the benefits from soil organic carbon storage?

Glob Chang Biol 2021 Jan 11;27(2):237-256. Epub 2020 Oct 11.

Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, P. R. China.

To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5°C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large-scale deployment of other climate mitigation strategies is also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N O), a powerful greenhouse gas, and increasing SOC may influence N O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta-analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g. biochar or non-pyrogenic C amendment application) may even decrease N O emissions.
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http://dx.doi.org/10.1111/gcb.15342DOI Listing
January 2021

Biogeography of Soil Bacterial Networks along a Gradient of Cropping Intensity.

Sci Rep 2019 03 7;9(1):3812. Epub 2019 Mar 7.

Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, F- 21000, Dijon, France.

Although land use drives soil bacterial diversity and community structure, little information about the bacterial interaction networks is available. Here, we investigated bacterial co-occurrence networks in soils under different types of land use (forests, grasslands, crops and vineyards) by sampling 1798 sites in the French Soil Quality Monitoring Network covering all of France. An increase in bacterial richness was observed from forests to vineyards, whereas network complexity respectively decreased from 16,430 links to 2,046. However, the ratio of positive to negative links within the bacterial networks ranged from 2.9 in forests to 5.5 in vineyards. Networks structure was centered on the most connected genera (called hub), which belonged to Bacteroidetes in forest and grassland soils, but to Actinobacteria in vineyard soils. Overall, our study revealed that soil perturbation due to intensive cropping reduces strongly the complexity of bacterial network although the richness is increased. Moreover, the hub genera within the bacterial community shifted from copiotrophic taxa in forest soils to more oligotrophic taxa in agricultural soils.
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http://dx.doi.org/10.1038/s41598-019-40422-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405751PMC
March 2019

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

Sci Total Environ 2019 May 21;666:355-367. Epub 2019 Feb 21.

UMR SAS, INRA, Agrocampus Ouest, 35042 Rennes, France. Electronic address:

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 CO 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.
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http://dx.doi.org/10.1016/j.scitotenv.2019.02.249DOI Listing
May 2019

A high-resolution map of soil pH in China made by hybrid modelling of sparse soil data and environmental covariates and its implications for pollution.

Sci Total Environ 2019 Mar 18;655:273-283. Epub 2018 Nov 18.

Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China. Electronic address:

The soil's pH is the single most important indicator of the soil's quality, whether for agriculture, pollution control or environmental health and ecosystem functioning. Well documented data on soil pH are sparse for the whole of China - data for only 4700 soil profiles were available from China's Second National Soil Inventory. By combining those data, standardized for the topsoil (0-20 cm), with 17 environmental covariates at a fine resolution (3 arc-second or 90 m) we have predicted the soil's pH at that resolution, that is at more than 10 points. We did so by parallel computing over tiles, each 100 km × 100 km, with two machine learning techniques, namely Random Forest and XGBoost. The predictions for the tiles were then merged into a single map of soil pH for the whole of China. The quality of the predictions were assessed by cross-validation. The root mean squared error (RMSE) was an acceptable 0.71 pH units per point, and Lin's Concordance Correlation Coefficient was 0.84. The hybrid model revealed that climate (mean annual precipitation and mean annual temperature) and soil type were the main factors determining the soil's pH. The pH map showed acid soil mainly in southern and north-eastern China, and alkaline soil dominant in northern and western China. This map can provide a benchmark against which to evaluate the impacts of changes in land use and climate on the soil's pH, and it can guide advisors and agencies who make decisions on remediation and prevention of soil acidification, salinization and pollution by heavy metals, for which we provide examples for cadmium and mercury.
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http://dx.doi.org/10.1016/j.scitotenv.2018.11.230DOI Listing
March 2019

Biogeography of soil bacteria and archaea across France.

Sci Adv 2018 07 4;4(7):eaat1808. Epub 2018 Jul 4.

Agroécologie, AgroSup Dijon, Institut National de la Recherche Agronomique (INRA), Université Bourgogne Franche-Comté, F-21000 Dijon, 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 16 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 16 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.
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http://dx.doi.org/10.1126/sciadv.aat1808DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031370PMC
July 2018

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

Sci Total Environ 2018 Jul 24;630:389-400. Epub 2018 Feb 24.

INRA, Unité InfoSol, 45075 Orléans, France. Electronic address:

Although soils have a high potential to offset CO 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 (SOC) 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 SOC over the French territory using a regression Kriging approach with environmental covariates. Results show that the controlling factors of SOC 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 SOC 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 SOC 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.
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http://dx.doi.org/10.1016/j.scitotenv.2018.02.209DOI Listing
July 2018

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives.

GeoResJ 2017 Dec;14(9):1-19

The James Hutton Institute, Craigiebuckler, Aberde and, UK.

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1km in 2014, followed by an update at a resolution of 250m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications.
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http://dx.doi.org/10.1016/j.grj.2017.06.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450209PMC
December 2017

Mapping and predictive variations of soil bacterial richness across France.

PLoS One 2017 23;12(10):e0186766. Epub 2017 Oct 23.

Agroécologie, AgroSup Dijon, INRA, Univ. Bourgogne Franche-Comté, Dijon, 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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186766PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5653302PMC
November 2017

Future C loss in mid-latitude mineral soils: climate change exceeds land use mitigation potential in France.

Sci Rep 2016 11 3;6:35798. Epub 2016 Nov 3.

Geography Department, College of Life and Environmental Sciences, University of Exeter, Exeter, UK.

Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO emissions will be crucial to prevent further loss of carbon from our soils.
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http://dx.doi.org/10.1038/srep35798DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5093904PMC
November 2016

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

PLoS One 2014 3;9(11):e111667. Epub 2014 Nov 3.

Unité Mixte de Recherche 1347 Agroécologie, Institut National de la Recherche Agronomique-AgroSup Dijon-Université de Bourgogne, Dijon, France; Unité Mixte de Recherche 1347 Agroécologie-Plateforme GenoSol, Institut National de la Recherche Agronomique-AgroSup Dijon-Université de Bourgogne, Dijon, France.

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
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0111667PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4218796PMC
August 2015

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

J Environ Qual 2012 Nov-Dec;41(6):1893-905

INRA, US 1106 InfoSol, Orleans, France.

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.
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http://dx.doi.org/10.2134/jeq2011.0478DOI Listing
May 2013

Validation and application of a PCR primer set to quantify fungal communities in the soil environment by real-time quantitative PCR.

PLoS One 2011 8;6(9):e24166. Epub 2011 Sep 8.

INRA-Université de Bourgogne, UMR Microbiologie du Sol et de l'Environnement, CMSE, Dijon, France.

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1/FF390. This in silico analysis of the specificity of FR1/FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1/FF390 for Fungi was validated in vitro by cloning--sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0024166PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3169588PMC
March 2012

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

Sci Total Environ 2011 Sep 3;409(19):3719-31. Epub 2011 Jul 3.

INRA, US1106 Unité Infosol, Centre de recherches d'Orléans, CS 40001, Ardon, 45075 Orléans Cedex 2, 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.
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http://dx.doi.org/10.1016/j.scitotenv.2011.05.048DOI Listing
September 2011

Spatial distribution of lindane in top soil of Northern France.

Chemosphere 2009 Nov 30;77(9):1249-55. Epub 2009 Sep 30.

INRA, US 1106, InfoSol Unit, CS 40001 Ardon, F-45075 Orléans Cedex 2, 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.
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http://dx.doi.org/10.1016/j.chemosphere.2009.08.060DOI Listing
November 2009

Biogeographical patterns of soil bacterial communities.

Environ Microbiol Rep 2009 Aug 22;1(4):251-5. Epub 2009 Jun 22.

INRA-Université de Bourgogne, UMR Microbiologie du Sol et de l'Environnement, CMSE, 17, rue Sully, B.V. 86510, 21065 Dijon, Cedex, France. Université de Bourgogne, UMR 1229, CMSE, 17, rue Sully, B.V. 86510, 21065 Dijon, Cedex, France. Platform GenoSol, INRA-Université de Bourgogne, CMSE, 17, rue Sully, B.V. 86510, 21065 Dijon, Cedex, France. Université de Lyon, F-69000, Lyon; Université Lyon 1; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne Cedex, France. INRA Orléans - US 1106, Unité INFOSOL, Avenue de la Pomme de Pin - BP 20619 Ardon 45166 Olivet, Cedex, France.

This study provides the first maps of variations in bacterial community structure on a broad scale based on genotyping of DNA extracts from 593 soils from four different regions of France (North, Brittany, South-East and Landes). Soils were obtained from the soil library of RMQS ('Réseau de Mesures de la Qualité des Sols' = French soil quality monitoring network). The relevance of a biogeographic approach for studying bacterial communities was demonstrated by the great variability in community structure and specific geographical patterns within and between the four regions. The data indicated that the distribution of bacterial community composition might be more related to local factors such as soil type and land cover than to more global factors such as climatic and geomorphologic characteristics. Furthermore, the regional pools of biodiversity could be ordered: South-East ≥ North > Brittany > Landes, according to the observed regional variability of the bacterial communities, which could be helpful for improving land use in accordance with soil biodiversity management.
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http://dx.doi.org/10.1111/j.1758-2229.2009.00040.xDOI Listing
August 2009

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

Environ Microbiol 2009 Dec 23;11(12):3096-104. Epub 2009 Jul 23.

INRA, UMR 1229, F-21000 Dijon, France.

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.
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http://dx.doi.org/10.1111/j.1462-2920.2009.02014.xDOI Listing
December 2009

Mapping field-scale spatial patterns of size and activity of the denitrifier community.

Environ Microbiol 2009 Jun 2;11(6):1518-26. Epub 2009 Mar 2.

INRA, UMR 1229, F-21000 Dijon, France.

There is ample evidence that microbial processes can exhibit large variations in activity on a field scale. However, very little is known about the spatial distribution of the microbial communities mediating these processes. Here we used geostatistical modelling to explore spatial patterns of size and activity of the denitrifying community, a functional guild involved in N-cycling, in a grassland field subjected to different cattle grazing regimes. We observed a non-random distribution pattern of the size of the denitrifier community estimated by quantification of the denitrification genes copy numbers with a macro-scale spatial dependence (6-16 m) and mapped the distribution of this functional guild in the field. The spatial patterns of soil properties, which were strongly affected by presence of cattle, imposed significant control on potential denitrification activity, potential N(2)O production and relative abundance of some denitrification genes but not on the size of the denitrifier community. Absolute abundance of most denitrification genes was not correlated with the distribution patterns of potential denitrification activity or potential N(2)O production. However, the relative abundance of bacteria possessing the nosZ gene encoding the N(2)O reductase in the total bacterial community was a strong predictor of the N(2)O/(N(2) + N(2)O) ratio, which provides evidence for a relationship between bacterial community composition based on the relative abundance of denitrifiers in the total bacterial community and ecosystem processes. More generally, the presented geostatistical approach allows integrated mapping of microbial communities, and hence can facilitate our understanding of relationships between the ecology of microbial communities and microbial processes along environmental gradients.
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http://dx.doi.org/10.1111/j.1462-2920.2009.01879.xDOI Listing
June 2009

The carbon balance of forest soils: detectability of changes in soil carbon stocks in temperate and Boreal forests.

SEB Exp Biol Ser 2005 :235-49

Institute of Environmental Geosciences, University of Basel, Switzerland.

Estimating soil carbon content as the product of mean carbon concentration and bulk density can result in considerable overestimation. Carbon concentration and soil mass need to be measured on the same sample and carbon contents calculated for each individual sample before averaging. The effect of this bias is likely to be smaller (but still greater than zero) when the primary objective is to determine stock changes over time. Variance and mean carbon content are significantly and positively related to each other, although some sites showed much higher variability than predicted by this relationship, as a likely consequence of their particular site history, forest management, and micro-topography. Because of the proportionality between mean and variance, the number of samples required to detect a fixed change in soil carbon stocks varied directly with the site mean carbon content from less than 10 to several thousands across the range of carbon stocks normally encountered in temperate and Boreal forests. This raises important questions about how to derive an optimal sampling strategy across such a varied range of conditions so as to achieve the aims of the Kyoto Protocol. Overall, on carbon-poor forest sites with little or no disturbance to the soil profile, it is possible to detect changes in total soil organic carbon over time of the order of 0.5 kg (C) m(-2) with manageable sample sizes even using simple random sampling (i.e., about 50 samples per sampling point). More efficient strategies will reveal even smaller differences. On disturbed forest sites (ploughed, windthrow) this is no longer possible (required sample sizes are much larger than 100). Soils developed on coarse aeolian sediments (sand dunes), or where buried logs or harvest residues of the previous rotation are present, can also exhibit large spatial variability in soil carbon. Generally, carbon-rich soils will always require larger numbers of samples. On these sites, simple random sampling is unlikely to be the preferred method, because of its inherent inefficiency. More sophisticated approaches, such as paired re-sampling inside relatively small plots (see, for example, Ellert et al., 2001) are likely to reduce sample size significantly and lead to detection of smaller differences in carbon stocks over time. However, it remains to be shown that at these sites the application of efficient sampling designs will result in the detection of differences relevant for the objectives of the Kyoto Protocol (cf., Conant et al., 2003). Finally, it should also be noted that, compared to the accuracy with which changes in atmospheric carbon content can be detected (less than 1 p.p.m. CO2), changes in soil carbon stocks are very uncertain. A release of 0.5 kg (C) from 1 m2 of soil surface is equivalent to an increase in CO, concentration of about 125 p.p.m. in the air column above the same area.
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September 2007

Modeling climate change effects on the potential production of French plains forests at the sub-regional level.

Tree Physiol 2005 Jul;25(7):813-23

INRA-EPHYSE 69 route d'Arcachon, 33612 Gazinet Cédex, France.

We modeled the effects of climate change and two forest management scenarios on wood production and forest carbon balance in French forests using process-based models of forest growth. We combined data from the national forest inventory and soil network survey, which were aggregated over a 50 x 50-km grid, i.e., the spatial resolution of the climate scenario data. We predicted and analyzed the climate impact on potential forest production over the period 1960-2100. All models predicted a slight increase in potential forest yield until 2030-2050, followed by a plateau or a decline around 2070-2100, with overall, a greater increase in yield in northern France than in the south. Gross and net primary productivities were more negatively affected by soil water and atmospheric water vapor saturation deficits in western France because of a more pronounced shift in seasonal rainfall from summer to winter. The rotation-averaged values of carbon flux and production for different forest management options were estimated during four years (1980, 2015, 2045 and 2080). Predictions were made using a two-dimensional matrix covering the range of local soil and climate conditions. The changes in ecosystem fluxes and forest production were explained by the counterbalancing effect of rising CO2 concentration and increasing water deficit. The effect of climate change decreased with rotation length from short rotations with high production rates and low standing biomasses to long rotations with low productivities and greater standing biomasses. Climate effects on productivity, both negative and positive, were greatest on high fertility sites. Forest productivity in northern France was enhanced by climate change, increasingly from west to east, whereas in the southwestern Atlantic region, productivity was reduced by climate change to an increasing degree from west to east.
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http://dx.doi.org/10.1093/treephys/25.7.813DOI Listing
July 2005
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