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International audience; Mc Corskey and al, 1977 have shown there is a link between a high aversion to oral communication and a lower self-esteem. We investigate if the Leviathan model which considers agents gossiping and having an opinion of each other (Deffuant et al 2013) is able to reproduce such a correlation. Our virtual agents form their opinions in face-to-face meetings. During these meetings, they act in self-defence applying vanity, and influence each other. They also gossip about their peers. In direct meeting and gossiping, a highly valued speaker compared to listener's self-opinion is more influential. The vanity impact depends on the distance between one's opinion of one self and the opinion conveyed by the speaker. Listeners felt held in low esteem sanction their speakers by decreasing their opinion of them. Those felt held in high esteem reward them by increasing their opinion of them. We modified the probability to talk of agents to consider a heterogeneous one: static depending on the agent itself, or dynamic depending on her self-esteem. The simplest law to obtain a heterogeneous probability to talk is sufficient to reproduce our search correlation. However, we also discover that the model argue it is possible to have a higher self-esteem for someone talking less than the others in some circumstances.

Altres ajuts: these projects are co-funded by European regional development fund (ERDF / FEDER, 2007-2013). Recent studies suggest that carbon (C) is stored in the topsoil of pastures established after deforestation. However, little is known about the long-term capacity of tropical pastures to sequester C in different soil layers after deforestation. Deep soil layers are generally not taken into consideration or are underestimated when C storage is calculated. Here we show that in French Guiana, the C stored in the deep soil layers contributes significantly to C stocks down to a depth of 100 cm and that C is sequestered in recalcitrant soil organic matter in the soil below a depth of 20 cm. The contribution of the 50-100 cm soil layer increased from 22 to 31 % with the age of the pasture. We show that long-term C sequestration in C4 tropical pastures is linked to the development of C3 species (legumes and shrubs), which increase both inputs of N into the ecosystem and the C:N ratio of soil organic matter. The deep soil under old pastures contained more C3 carbon than the native forest. If C sequestration in the deep soil is taken into account, our results suggest that the soil C stock in pastures in Amazonia would be higher with sustainable pasture management, in particular by promoting the development of legumes already in place and by introducing new species.

International audience; Extreme climatic events (ECEs) such as droughts and heat waves are predicted to increase in intensity and frequency and impact the terrestrial carbon balance. However, we lack direct experimental evidence of how the net carbon uptake of ecosystems is affected by ECEs under future elevated atmospheric CO2 concentrations (eCO2). Taking advantage of an advanced controlled environment facility for ecosystem research (Ecotron), we simulated eCO2 and extreme cooccurring heat and drought events as projected for the 2050s and analyzed their effects on the ecosystem-level carbon and water fluxes in a C3 grassland. Our results indicate that eCO2 not only slows down the decline of ecosystem carbon uptake during the ECE but also enhances its recovery after the ECE, as mediated by increases of root growth and plant nitrogen uptake induced by the ECE. These findings indicate that, in the predicted near future climate, eCO2 could mitigate the effects of extreme droughts and heat waves on ecosystem net carbon uptake.

This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland–atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal–vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m−2 yr−1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

International audience; Numerous climate futures are now available fromglobal climate models. Translation of climate data such as precipitation and temperatures into ecologicallymeaningful outputs formanagers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platformincludes a simulationmodeling engine and is suited towork with NetCDF format of input and output files. In a case study covering a region (Auvergne) in theMassif Central of France, the platformis configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks.

The Karoo biomes of South Africa are major feed resources for livestock farming, yet soil nutrient depletion and degradation is a major problem. The objective of this study was to assess impacts of long-term (> 75 years) grazing during spring (SPG), summer (SUG), winter (WG) and exclosure (non-grazed control) treatments on soil nutrients, penetration resistance and infiltration tests. A soil sampling campaign was carried out to collect soil to a depth of 60 cm to analyse bulk density, soil physical and chemical parameters as well as soil compaction and infiltration. Generally, grazing treatments reduced soil organic C (SOC) stocks and C:N ratios, and modified soil properties. There was higher SOC stock (0.128 Mg ha(-1) yr(-1)) in the exclosure than in the SPG (0.096 Mg ha(-1) yr(-1)), SUG (0.099 Mg ha(-1) yr(-1)) and WG (0.105 Mg ha(-1) yr(-1)). The C:N ratios exhibited similar pattern to that of C. From the grazing treatments, the WG demonstrated 7 to 10 % additional SOC stock over the SPG and SUG, respectively. Short period animal exclusion could be an option to be considered to improve plant nutrients in sandy soils of South Africa. However, this may require a policy environment which supports stock exclusion from such areas vulnerable to land degradation, nutrient and C losses by grazing-induced vegetation and landscape changes.

International audience; Plant species can exert a strong influence on soil processes. The aim of this field study was to examine the interactive effects of plant species identity and dung amendment on key soil properties related to carbon (C) and nitrogen (N) cycling. Monocultures of three co-occurring grass species (Dactylis glomerata, Lolium perenne, Festuca rubra) with contrasting nutrient acquisition strategies were examined. Soil CO2 fluxes, leaf litter decomposition, C and N storage in soil and soil microbes were measured in plots with and without dung addition. Four months after dung addition, soil sampled from plots was used in a greenhouse bioassay experiment to assess soil fertility. Dung addition increased CO2 fluxes from soil irrespective of plant species; increased leaf litter mass loss and C and N stocks in soil and microbial biomass were also observed. Bioassay results confirmed dung-induced increases in soil fertility. Significant plant species' effects were found for soil CO2 fluxes, soil inorganic N content, leaf litter mass loss and bioassay seedling root: shoot ratio. Nevertheless, dung effects showed no significant interactions with plant species identity on any of the soil variables examined. Soil responses to dung show additive effects with grass species identity, but are not clearly linked to plant nutrient acquisition strategy in this temperate study system. High nutrient inputs may buffer plant-soil interactions against variation in plant nutrient acquisition strategies.

Vulnerability assessment to climate change is an issue of concern.We develop Java-based software for vulnerability assessment to climate change.We illustrate the software in vulnerability assessments of European grasslands. Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts.

International audience; Modification in grazing intensity causes functional changes in permanent grasslands, e.g. in carbon (C) cycling. However, we still know little about how the soil organic C of permanent grasslands responds to grazing intensity. In a grassland experiment with three levels of grazing intensity, we monitored root and rhizome C stocks, particulate organic C stocks, total soil C stocks, above-ground net primary production and plant species groups abundance over 7 years. A simple model was used to estimate the mortality of roots and rhizomes, decomposition rates of particulate organic C, and C fluxes under different grazing intensities. After 7 years, low grazing intensity and no grazing led to a modification in above-ground vegetation (production, plant species composition, nitrogen content) and a reduction in C transferred between roots and particulate organic matter fractions, while the C stocks of root and rhizomes, particulate organic matter and total soil were not significantly affected by grazing intensity. However, particulate organic C showed a strong interannual variability. Particulate organic C could have reacted more slowly than expected to changes in grazing intensity, or a marked interannual variability of particulate organic C stocks, through an increase in decomposition rates in all the grazing treatments, could have slowed down the accumulation of particulate organic C and masked the effect of the grazing intensity treatments.

International audience; In this study, we compare two community modelling approaches to determine their ability to predict the taxonomic, functional and phylogenetic properties of plant assemblages along a broad elevation gradient and at a fine resolution. The first method is the standard stacking individual species distribution modelling (SSDM) approach, which applies a simple environmental filter to predict species assemblages. The second method couples the SSDM and macroecological modelling (MEMSSDM-MEM) approaches to impose a limit on the number of species co-occurring at each site. Because the detection of diversity patterns can be influenced by different levels of phylogenetic or functional trees, we also examine whether performing our analyses from broad to more exact structures in the trees influences the performance of the two modelling approaches when calculating diversity indices. We found that coupling the SSDM with the MEM improves the overall predictions for the three diversity facets compared with those of the SSDM alone. The accuracy of the SSDM predictions for the diversity indices varied greatly along the elevation gradient, and when considering broad to more exact structure in the functional and phylogenetic trees, the SSDM-MEM predictions were more stable. SSDM-MEM moderately but significantly improved the prediction of taxonomic diversity, which was mainly driven by the corrected number of predicted species. The performance of both modelling frameworks increased when predicting the functional and phylogenetic diversity indices. In particular, fair predictions of the taxonomic composition by SSDM-MEM led to increasingly accurate predictions of the functional and phylogenetic indices, suggesting that the compositional errors were associated with species that were functionally or phylogenetically close to the correct ones; however, this did not always hold for the SSDM predictions.Synthesis. In this study, we tested the use of a recently published approach that couples species distribution and macroecological models to provide the first predictions of the distribution of multiple facets of plant diversity: taxonomic, functional and phylogenetic. Moderate but significant improvements were obtained; thus, our results open promising avenues for improving our ability to predict the different facets of biodiversity in space and time across broad environmental gradients when functional and phylogenetic information is available.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SEDYVIN [ADD1_IRSTEA]Dynamique et fonctionnement des écosystèmes; International audience; How the patterns of niche occupancy vary from species-poor to species-rich communities is a fundamental question in ecology that has a central bearing on the processes that drive patterns of biodiversity. As species richness increases, habitat filtering should constrain the expansion of total niche volume, while limiting similarity should restrict the degree of niche overlap between species. Here, by explicitly incorporating intraspecific trait variability, we investigate the relationship between functional niche occupancy and species richness at the global scale. 2.We assembled 21 datasets worldwide, spanning tropical to temperate biomes and consisting of 313 plant communities representing different growth forms. We quantified three key niche occupancy components (the total functional volume, the functional overlap between species and the average functional volume per species) for each community, related each component to species richness, and compared each component to the null expectations. 3.As species richness increased, communities were more functionally diverse (an increase in total functional volume), and species overlapped more within the community (an increase in functional overlap) but did not more finely divide the functional space (no decline in average functional volume). Null model analyses provided evidence for habitat filtering (smaller total functional volume than expectation), but not for limiting similarity (larger functional overlap and larger average functional volume than expectation) as a process driving the pattern of functional niche occupancy. 4.Synthesis. Habitat filtering is a widespread process driving the pattern of functional niche occupancy across plant communities and coexisting species tend to be more functionally similar rather than more functionally specialized. Our results indicate that including intraspecific trait variability will contribute to a better understanding of the processes driving patterns of functional niche occupancy

Agricultural management practices including soil tillage exert strong control on soil organic matter (SOM) turnover and its interactions with global C cycle through different mechanisms. One control mechanism is the priming effect (PE) which consists in stimulating SOM mineralization with the addition of fresh, energetic plant material. In this study, we quantified C mineralization and PE in soils sampled in two contrasted long-term (40 years) tillage treatments which deeply modified soil properties (e.g. organic C concentration, microbial biomass, pH). We hypothesized that soil tillage might affect these processes through changes in C addition rates, nutrient availability, and long-term variations in SOM content and microbial communities. We investigated the relationship between PE intensity, tillage and nutrients availability in soil samples taken in no till (NT) and full inversion tillage (FIT) in two layers (0–5 and 15–20 cm). Soils were incubated with or without addition of 13 C labeled cellulose and mineral nutrients. Potential C mineralization and primed C were measured during 262 days. Unlabeled soil microbial biomass C was determined at the end of the experiment to separate apparent and real priming effect. Basal cumulative C mineralization in the control soil ranged from 363 to 1490 mg kg −1 soil at day 262. It was strongly correlated with soil organic carbon (SOC) concentration. Specific mineralization rates were 44.8 and 68.8 g kg −1 SOC in the 0–5 cm layer for the FIT and NT treatments, respectively and were strongly linked with the particulate organic matter content ( r = 0.99***). These results suggest that SOC was more active in the upper layer of the NT treatment due to the high concentration of readily-decomposable, particulate organic matter. The cellulose was entirely metabolized after 60 days and its kinetics of mineralization was affected neither by tillage, depth nor nutrients. The percentage of cellulose C released as CO 2 represented 55–61% of the added cellulose-C at day 262. A positive PE was found in all treatments and its kinetics was parallel to that of cellulose mineralization. The cumulative PE significantly varied with nutrients level but not tillage, ranging from 73 to 78 mg kg −1 under high nutrients level and from 116 to 136 mg kg −1 in low nutrients level. No significant differences were found in unlabeled microbial biomass C between control and amended soil, suggesting no apparent priming effect. We conclude that the priming was mainly controlled by nutrient availability but not tillage, in spite of strong tillage-induced changes in SOC concentration and microbial biomass. Since PE is known to depend on C addition rate, tillage is expected to affect in situ PE through variations in the ratio of fresh carbon to nutrient concentration along the soil profile.

International audience; Viral proteins have enabled the design of selective and efficacious treatments for viral diseases. While focus in this area has been on viral enzymes, it appears that multifunctional viral proteins may be even more susceptible to small molecule interference. As exemplified by HIV capsid, small molecule inhibitors can bind to multiple binding sites on the capsid protein and induce or prevent protein interactions and conformational changes. Resistance selection is complicated by the fact that the capsid proteins have to engage in different protein interactions at different times of the life cycle. Viral capsid assembly and disassembly have therefore emerged as highly sensitive processes that could deliver a new generation of antiviral agents across viral diseases.

Much of the uncertainty in crop and grassland model predictions of how arable and grassland systems respond to changes in management and environmental drivers can be attributed to differences in the structure of these models. This has created an urgent need for international bench- marking of models, in which uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty in model predictions (Asseng et al. , 2013). Simulations of C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions (Sandor et al. , 2016) and complicated by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C and N Models Inter-comparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide (C-N MIP) and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models that estimate C – N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model- intercomparison-on-agricultural-ghg-emissions). This study presents some preliminary results on the uncertainty of outputs from 12 grassland models, whereas exploring differences in model response when increasing data resources are used for model calibration.

European grassland-based livestock production systems face the challenge of producing more meat and milk to meet increasing world demands and to achieve this using fewer resources. Legumes offer great potential for achieving these objectives. They have numerous features that can act together at different stages in the soil–plant–animal–atmosphere system, and these are most effective in mixed swards with a legume proportion of 30–50%. The resulting benefits include reduced dependence on fossil energy and industrial N-fertilizer, lower quantities of harmful emissions to the environment (greenhouse gases and nitrate), lower production costs, higher productivity and increased protein self-sufficiency. Some legume species offer opportunities for improving animal health with less medication, due to the presence of bioactive secondary metabolites. In addition, legumes may offer an adaptation option to rising atmospheric CO2 concentrations and climate change. Legumes generate these benefits at the level of the managed land-area unit and also at the level of the final product unit. However, legumes suffer from some limitations, and suggestions are made for future research to exploit more fully the opportunities that legumes can offer. In conclusion, the development of legume-based grassland–livestock systems undoubtedly constitutes one of the pillars for more sustainable and competitive ruminant production systems, and it can be expected that forage legumes will become more important in the future.

This study proposes a forecast skill scheme for winter temperatures in the central Mediterranean Sub-regional Area. An original series of mean winter (December to February) temperatures spanning the period 1698–2010 is the basis for developing long-term climate prediction. A procedure was identified where a predictable structure was first provided by reducing noise via the Empirical Mode Decomposition method and then an Ensemble Climate Prediction (ECP) was applied. The predictability limit of the decomposed series was assessed by applying a collection of methods from linear and nonlinear time series analysis (Hurst coefficients, Lyapunov exponents and wavelet patterns). The analysis was based on a set of tools that are suitable to discover the manifestation of a possible trajectory of projected temperature change. The progress of the winter temperature forecast was inferred by an Exponential Smoothing with a Damped (ESD) multiplicative trend model. ECP-ESD hindcast experiments were tested and ensemble forecasts run until the year 2040. ECP-ESD yields an ensemble mean path that consists: (1) of a sharp decline in winter temperature in the current decade; (2) more widespread predictions for 2020–2030, with fluctuations near the present multi-decadal average; and (3) a sharp warming for the 2030–2040 decade. Our results are compatible with projections for European winters and major climatic indices such as the Pacific Decadal Oscillation and the Atlantic Multi-decadal Oscillation.

International audience; Radioactive C-14 is formed as a by-product of nuclear power generation and from the operation of nuclear fuel reprocessing plants like AREVA-NC La Hague (North France), which releases about 15 TBq per year of C-14 into the atmosphere. This article evaluates a recently improved radioecology model (TOCATTA-chi) to assess C-14 transfers to grassland ecosystems under normal operating conditions. The new version of the TOCATTA model (TOCATTA-chi) includes developments that were derived from PaSiM, a pasture model for simulating grassland carbon and radiocarbon cycling. The TOCATTA-chi model has been tested against observations of C-14 activity concentrations in grass samples collected monthly from six plots which are located around the periphery of the reprocessing plant. Simulated C-14 activities are consistent with observations on both intensively managed and poorly managed grasslands, but an adaptation of the mean turn-over time for C-14 within the plant is necessary in the model to account for different management practices. When atmospheric C-14 activity concentrations are directly inferred from observations, TOCATTA-chi performs better than TOCATTA (the root mean square error is decreased by 45%), but when atmospheric C-14 activity concentrations are not known and must be calculated, the uncertainty associated with the TOCATTA-chi model outcomes is estimated to be larger than the standard deviation of the observations. (C) 2013 Elsevier Ltd. All rights reserved.

International audience; Fractionation of soil is undertaken to isolate organic carbon with distinct functional properties, such as stability and turnover times. Soil organic carbon (SOC) fractionation helps us to understand better the response of SOC to changes in land use, management or climate. However, fractionation procedures are often poorly defined and there is little information available on their reproducibility in different laboratories. In a ring trial, we assessed the reproducibility of a SOC fractionation method introduced by Zimmermann et al. (2007). The isolated fractions were linked to the model pool sizes of the Rothamsted carbon model (RothC). We found significant differences between six laboratories for all five defined fractions in three different soils with coefficients of variation ranging from 14 to 138%. During ultrasonic dispersion, the output power (energy per unit time) was identified as an important factor controlling the distribution of SOC within these five fractions, while commonly only the output energy is standardized. The amount of water used to wet-sieve dispersed soil slurry significantly influenced the amount of extracted dissolved organic carbon (DOC). We therefore suggest using a fixed amount of power for ultrasonic dispersion (20W) and a minimum amount of water for wet sieving (2000ml). RothC pool sizes were predicted from the measured fractions and compared with RothC equilibrium pool size distributions. This model initialization using measured SOC fractions, however, led to an over-estimation of stable RothC SOC pools when compared with pool size distributions derived from RothC equilibrium runs under a bare fallow soil model simulation. To improve the isolation of particulate organic matter from stable mineral-bound organic matter, we suggest that the density should be increased from 1.8 to 2.0gcm(-3) in the density fractionation step. We formulated a modified fractionation procedure, which aims specifically to enhance reproducibility across laboratories and to improve the match of the isolated SOC fractions with RothC's SOC pools.

Branched broomrape (Phelipanche ramosa (L.) Pomel) is a holoparasite weed causing significant yield losses on several crops, especially in France on winter oilseed rape fields. The ability to induce germination of seeds of branched broomrape, variable between host species, represent an important information to identify the status of weed species present in the crop (host or non-host). In this study, conducted in in vitro conditions, we focused on two botanical families and two dominant pathovars of branched broomrape in France. We show that the host species is the only important explanatory factor of seed germination rate, the latter being not affected by the pathovar. Among the species studied, the birdsfoot trefoil (Lotus corniculatus L.) induce a mean germination rate of almost 90% and could be an interesting candidate as intercrop species in infested plots., L'orobanche rameuse (Phelipanche ramosa (L.) Pomel) est une adventice holoparasite obligatoire causant d'importantes pertes de rendement dans différentes cultures, et notamment en France dans les parcelles de colza d’hiver. Le taux de germination des graines d'orobanche rameuse, variable entre espèces hôtes, constitue une information importante afin d'identifier le statut des espèces adventices présentes dans la culture (hôte ou non-hôte). Dans cette étude, réalisée en conditions in vitro, nous nous sommes focalisés sur deux familles botaniques et deux pathovars d'orobanche rameuse dominants en France. Nous montrons que l’espèce hôte constitue le principal facteur explicatif du taux de germination des graines et que ce taux n’est pas affecté par le pathovar. Parmi les espèces étudiées, le lotier corniculé (Lotus corniculatus L.) induit un taux de germination moyen de près de 90% et pourrait représenter un candidat intéressant comme espèce d'interculture dans les parcelles infestées.

Permanent grasslands are one of the main forms of land use in Europe. In France, permanent grasslands represent around 40% of Utilised Agricultural Land and support many animal-based farming systems. Current climate change scenarios predict increased climate variability that could result in an increase in extreme events such as drought episodes. These extreme events can significantly alter the structure and functioning of grasslands, with implications for their capacity to provide agricultural, ecological and environmental services. Improved understanding of the resistance and resilience mechanisms of grassland plant communities exposed to extreme drought is therefore critical in order to assess the stability of grassland functions, in particular that of biomass production.This thesis aims at assessing the capacity of permanent grasslands to sustain their production when exposed to an extreme drought event. The study uses an experimental approach and semi-controlled conditions to investigate the role of community composition and functional diversity for drought resistance and resilience in grassland mixtures. Monocultures and mixtures combining grasses and legumes were selected to test the importance of composition and functional diversity for plant community responses during drought and up to a year after the end of water stress. The originality of this work is the use of a functional ecological approach to assess the impacts of species’ interactions via measurements of plant morphological and physiological traits both above- and below-ground.This study demonstrates the importance of white clover (Trifolium repens) in modulating the impact of extreme droughts on biomass production of grassland mixtures. Community composition did not have a buffering effect on biomass production during the drought event but the presence and abundance of white clover in mixtures was linked to higher recovery of biomass production in the long-term. After the extreme drought event, overyielding in mixtures combining grass and white clover could be attributed to mechanisms of nitrogen facilitation and vertical root complementarity for water uptake. Results also show the importance of deep root growth for the establishment of functional complementarity between species and the maintenance of biomass production under extreme drought. Drought had lasting effects on the root system patterns and thus on the underlying mechanisms of the positive effect of white clover on aboveground production. Moreover, this work highlights the key role of heterospecific interactions in the expression of intraspecific traits related to resource acquisition strategies. Heterospecific interactions are thus an important driver of the species performance under extreme drought.We show that the structure and functional composition of the plant community in simplified mixtures are critical for modulating grassland responses to an extreme drought event. In our study, the recovery of aboveground biomass production is mainly related to the presence of white clover and the establishment of positive interactions between species. Changes of species behaviour in response to heterospecific interactions should be taken into account to better predict grassland biomass production under future climatic conditions. From an applied perspective, accounting for the key role of white clover and the inherent variability or neighbour-induced plasticity of intraspecific traits appears important to adapt mixtures of species or varieties to more intense and frequent drought events.; Les prairies permanentes représentent l’une des principales formes d’utilisation des terres en Europe. En France, elles représentent près de 40% de la Surface Agricole Utile (SAU) et restent le support de nombreux systèmes d’élevage. Les scénarios actuels de changement climatique prévoient tous un accroissement de la variabilité climatique qui pourrait se traduire par un accroissement des évènements extrêmes, notamment en ce qui concerne les épisodes de sécheresses. Ces événements extrêmes sont de nature à altérer la structure et le fonctionnement des prairies et en conséquence la capacité de ces écosystèmes à rendre des services agricoles, écologiques et environnementaux. Une meilleure compréhension des mécanismes de résistance et de résilience des communautés végétales prairiales face à l’occurrence de sécheresses extrêmes s’avère donc cruciale pour évaluer la stabilité du fonctionnement de l’écosystème prairial et notamment du service de production qu'il supporte. Cette thèse a pour objectif principal d’évaluer la capacité des prairies permanentes à maintenir leur fonction de production face à un événement de sécheresse extrême. Elle s’appuie sur une démarche expérimentale en mésocosmes sous conditions semi-contrôlées permettant de caractériser le rôle de la composition et de la structure des communautés végétales prairiales dans la résistance et la résilience à la sécheresse des prairies. Pour évaluer l’importance de la composition et de la diversité fonctionnelle dans la réponse des communautés végétales, des monocultures et des mélanges associant graminées et une légumineuse ont été sélectionnés. L’originalité de ce travail réside dans une approche d’écologie fonctionnelle permettant d’appréhender l’importance des interactions entre espèces dans la réponse de la communauté via l’analyse de traits morphologiques et physiologiques mesurés conjointement dans les compartiments aérien et souterrain de la végétation. Cette étude a mis en évidence le rôle prépondérant du Trèfle blanc (Trifolium repens) dans la modulation de l’impact d’un événement de sécheresse extrême sur la production de biomasse de mélanges prairiaux. Si aucun effet tampon de la composition et de la structure de la communauté n’a été mis en évidence durant la sécheresse, la présence et l’abondance de Trèfle blanc a été reliée à une meilleure récupération à long terme de la production de biomasse des mélanges. Après l’extrême, une surproduction des mélanges associant graminée et Trèfle blanc a ainsi été attribuée à des mécanismes de facilitation azotée et de complémentarité verticale de niches au niveau racinaire pour l’acquisition de l’eau. Nous avons ainsi souligné l’importance de la croissance des racines profondes pour la mise en place de complémentarités fonctionnelles entre espèces et donc pour le maintien de la production sous sécheresse extrême. L’événement de sécheresse affecte durablement le comportement des racines et de ce fait les mécanismes sous-jacents de l’effet bénéfique du Trèfle blanc sur la production aérienne. Par ailleurs, notre étude a mis en évidence le rôle majeur des interactions hétérospécifiques dans l’expression de traits intraspécifiques liés aux stratégies d’acquisition des ressources et par conséquent dans la régulation de la performance des espèces sous sécheresse extrême. Nous montrons que la structure et la composition fonctionnelle de la communauté végétale apparaît essentielle dans la régulation de la réponse à un événement de sécheresse extrême. Dans notre étude, la récupération de la production de biomasse aérienne après sécheresse extrême repose essentiellement sur la présence de Trèfle blanc et la mise en place d’interactions positives entre espèces. La prise en compte de la modulation par les interactions interspécifiques du comportement des espèces en mélanges s’avère nécessaire dans la prévision de la production des prairies sous climat futur. (...)

Les sols représentent une réserve de carbone plus importante que celles de l’atmosphère et de la végétation terrestre combinées. Ce réservoir de carbone impacte directement les concentrations en CO2 atmosphérique via le processus de minéralisation de la matière organique. Comprendre et prédire les flux de carbone dans le sol et entre le sol et l’atmosphère nécessite donc d’appréhender l’ensemble des processus soutenant la minéralisation de la matière organique dans le sol. Jusqu’en 2013, il était communément admis que la respiration par les microorganismes hétérotrophes du sol était la principale voie régulant la minéralisation de la matière organique dans ce compartiment. Cependant, suite à l’observation d’émissions de CO2 par des sols stérilisés, l’hypothèse d’une voie de minéralisation de matière organique soutenue par des métabolismes oxydatifs extracellulaires (EXOMET) a été proposée. Les travaux conduits au cours de cette thèse ont visé (i) à établir que les émissions de CO2 dans des sols stérilisés étaient le fait de métabolismes extracellulaires, (ii) à vérifier le caractère cosmopolite de ce processus quelles que soient les conditions édaphiques (iii) à identifier des facteurs impliqués dans la régulation de l’EXOMET et (iv) à proposer une approche permettant de déterminer sa contribution aux émissions de CO2 dans des sols vivants. Les résultats obtenus soutiennent l’hypothèse de l’EXOMET et mettent en exergue que les métabolismes extracellulaires sont régulés par des facteurs et des lois physico-chimiques différentes de celles supportées par les organismes vivants. Les données acquises suggèrent également que l’expression de l’EXOMET pourrait avoir des conséquences importantes pour certains écosystèmes (e.g., rhizosphère) et serait accentuée par les modifications de variables liées au changement climatique (e.g., température, humidité). Compte tenu des estimations de la contribution de l’EXOMET aux émissions de CO2 par les sols, de son activité au sein de sols aux conditions physico-chimiques variables et de la potentielle universalité de ce processus dans les sols, il est maintenant nécessaire d’intégrer l’EXOMET dans les modèles biogéochimiques globaux visant à appréhender les flux de carbone dans les sols et à prédire les émissions de CO2 et l’évolution du climat. Les données présentées dans ce manuscrit, contribuent significativement à la connaissance et à la compréhension de l’EXOMET mais soulignent également qu’un travail conséquent reste à mener pour appréhender les mécanismes sous tendant l’EXOMET et pour caractériser et quantifier ces métabolismes extracellulaires à l’échelle écosystémique.

The contribution of bacteriochlorophyll a (BChl a) to photosynthetically driven electron transport is generally low in aquatic and terrestrial systems. Here, we provide evidence that anoxygenic bacterial phototrophy is widespread and substantial in water retained by tank bromeliads of a primary rainforest in French Guiana. An analysis of the water extracted from 104 randomly selected tank bromeliads using infrared fluorimetry suggested the overall presence of abundant anoxygenic phototrophic bacterial populations. We found that purple bacteria dominated these populations responsible for unusually high BChl a/chlorophyll a ratios (>50%). Our data suggest that BChl a-based phototrophy in tank bromeliads can have significant effects on the ecology of tank-bromeliad ecosystems and on the carbon and energy fluxes in Neotropical forests.

International audience

National audience

Priorities for modelling European grasslands under climate change. 26th General meeting of the European Grassland Federation

Climate challenges and opportunities in northern and southern Europe - role of management and exploitation of plant traits in the adaptation of grasslands. 26th General meeting of the European Grassland Federation

SPEGESTADAGROSUPINRA; L’Orobanche rameuse (Phelipanche ramosa (L.) Pomel.) est une plante holoparasite obligatoire se développant sur une gamme très large d’hôtes sauvages et cultivés. En France, elle présente différents types génétiques (pathovars) caractérisés par une divergence génétique associée préférentiellement à une espèce cultivée d’hôte (notamment le colza, le tabac et le chanvre). L’Orobanche rameuse peut aussi se développer sur plusieurs dizaines d’espèces caractéristiques de la flore adventice des grandes cultures, et ainsi se maintenir au sein d’une parcelle, même en l’absence de la culture hôte durant plusieurs années. Connaitre la sensibilité de la communauté adventice à cette plante parasite pourrait permettre d’anticiper les risques associés à la présence de l’Orobanche rameuse. Plusieurs études récentes ont mis en évidence l’existence d’un signal phylogénétique pour différents traits caractérisant les hôtes d’un parasite au sein d’un groupe d’espèces ; les espèces apparentées présentant des valeurs de traits plus similaires que le simple hasard. L’existence d’un signal de ce type, lié à la sensibilité à l’Orobanche, pourrait constituer un prédicteur potentiel du risque d’infestation d’une communauté[1]. Dans le but d’évaluer cette hypothèse, nous avons étudié 2 pathovars (associé au colza et au chanvre) en vue de caractériser la capacité de l’hôte à induire la germination des graines d’Orobanche rameuse, en nous intéressant à 12 espèces de la famille des Fabacées. Pour chaque pathovar, nous avons évalué le taux de germination des graines d’Orobanche rameuse induit par chaque espèce hôte. Ensuite, en nous appuyant sur un arbre phylogénétique construit sur la base des séquences d'ADN (gènes rbcL et matK), nous avons recherché l’existence d’un signal phylogénétique via l’indice K* de Blomberg[2], les espèces d’hôtes étant réparties dans différentes tribus relativement éloignées sur l’arbre phylogénétique.

National audience

CT3 ; EnjS2-4 ; Département EA; Measuring rhizosphere regulations of carbon and nitrogen cycles: an innovate design. EcoSummit 2016. Ecological Sustainability: Engineering Change

National audience

National audience

National audience; Permanent grassland provides ecosystem services such as protection of soil quality, preservation of ground and surface water quality and regulation of climate through soil carbon sequestration. Intensification of management practices through changes of mowing, fertilization and grazing intensity may threaten these services as well as climate variability through increasing drought intensity and frequency. In grassland, root activity (growth, mortality) contributes to the main inputs of C and N compounds into the soil. Understanding how root activity and soil C stock respond to management is of prime importance for the ecosystem C sequestration service. We studied during two years the dynamics of root mass production of an upland grassland subjected to different grazing intensity (abandonment, low and high stocking density with respectively 0, 6.9 and 13.8 LSU ha-1, livestock unit) and to ambient climate variability. We expected to have lower below-ground net primary production in intensive than in extensive grazing treatments due to stimulation of shoot mass at the expense of roots. The site is part of the long-term observatory network (ACBB-SOERE) located at St-Genès-Champanelle, France and included 12 plots, in which four ingrowth cores were inserted at 20 cm and collected 10 times each year during two following years. In addition root mass was measured three times during the first year to calculate root turnover. We showed strong seasonal root production in spring and autumn for all treatments either during a wet (first) or a dry (second) year. Root production started earlier in spring for both grazing treatments than in abandonment, which can be explained by higher soil temperature. However at the annual scale, root production and root stock were similar between treatments, leading to unchanged root turnover. Thus grazing intensity did not lead to change of root stock, although root dynamics, above-ground biomass and species composition were affected.

Extreme events such as frost, drought or excessive heat occurring during a critical plant stage can cause extensive and sometimes irreversible damages to agricultural production. Tools for gauging the occurrence of extreme events can thus play an important role in the context of agricultural decision problems. Agroclimatic indicators offer simple means to discriminate between favourable and unfavourable conditions. Their evaluation can be supported by dedicated software tools, even though this typically requires local installation of the proposed solution. Here we present webXTREME, a new web-based tool to characterize the occurrence and intensity of extreme events in agriculture (available through www.modextreme.org/webxtreme, accessed on 6 April, 2016). Objectives, which motivated its development, were: ease of access (available from any internet-connected device), simple setup, universal compatibility (no installation required), extensibility and the possibility to offer regular updating services. webXTREME was designed to help scientists and practitioners with various backgrounds to configure the solving algorithms by taking into account plant-specific thresholds and relevant time windows during the growing seasons of arable crops, grasslands and woody species. Graphical display of the results enables comparative assessments, either in space or in time. webXTREME was implemented using Shiny, an open-source web application framework for R. This allows combining the computational power of dedicated R functions with modern web technologies. webXTREME can easily be integrated into other modelling platforms (e.g. BioMA, http://bioma.jrc.ec.europa.e

We used a functional trait-based plant classification to improve the plant module of the biogeochemical grassland model PaSim. Based on four main classes (A, B, C, D) and two derived types (b, d) covering a gradient from high to low productive/fertile grassland vegetation types, we derived new classes of model plant parameters representing an evolution of a previous parameterization obtained by calibration without considering any plant diversity. Illustrative results are presented for the French grassland site of Laqueuille, by comparing two grazing management treatments: intensive (type B) and low animal stocking rate extensive (type b). [br/] Model performances (reflected by root mean square error and coefficient of determination metrics) showed that accounting for plant traits may help predicting carbon-water fluxes (actual evapotranspiration, gross primary productivity, ecosystem respiration and net ecosystem exchange) and soil variables (temperature and water content). Whether the pattern of results (yet complex) generally supported the validity of the plant trait-based approach to derive model parameters, a substantiation is required by assessing model performances on a range of sites (as listed in the paper) covering a wide variety of conditions

The Pasture Simulation model – evaluation of plant acclimatory effects on grassland systems in France. 8th International Congress on Environmental Modelling and Software (iEMSs)

L’hétérogénéité spatiale d’un écosystème a été étudiée au sein de prairies pâturées, afin de déterminer l’impact d’une intensification des pratiques d’élevage sur la distribution spatiale de différentes variables liées d’une part aux propriétés physico-chimiques du sol et à celle de la végétation. Pour mener à bien cette étude, des mesures spatialisées ont été conduites sur deux parcelles de prairie permanente auvergnate située en moyenne montagne. Ces sites d’études sont en place depuis 2002, l’une des parcelles subit un traitement dit intensif (fort chargement animal, fertilisation), la seconde subit un traitement dit extensif (faible chargement animal, pas de fertilisation). Les résultats montrent que la distribution spatiale de certaines variables (hauteur d’herbe, composition floristique ou encore stock de carbone) est dépendante de l’intensité du pâturage. L’intensification conduit généralement à la diminution de la taille des patchs, voire à une perte de la dépendance spatiale et donc à une homogénéisation de l’écosystème. Cette étude a donc permis de mettre en avant l’impact d’une intensification des pratiques d’élevage mais également de mettre au points une méthode d’analyse de l’hétérogénéité spatiale en vue de la déployé dans le cadre d’un projet européen., Ecosystem’s spatial heterogeneity was studied in grazed grassland. With the aim of identify the effects of a livestock intensification on the spatial distribution of varied variables describing the soil’s physicochemical and vegetation properties. To perform this study, spatialize measurements were lead on two permanent grassland localized in Auvergne, a low mountain region. Those experimental sites are used since 2002, one of the grassland receives an intensive treatment (high stock rate, fertilization), and the second one endures an extensive treatment (low stock rate, no fertilization). Results show for some variables (plant height, floristic composition, carbon stocks) a spatial distribution dependent of the grazing intensity. Usually, the intensification leads to à decrease of the patch sizes. But can also go further with a loose of the spatial dependence and so bring to an ecosystem homogenization. This study permit to show us the effects of an intensification of livestock management on spatial heterogeneity but as well to develop a method of heterogeneity analysis in grassland with the purpose of use it as part of an European project.

CT3 Biogéochimie, physique et écologie des solsEnjS4 Bouclage des cycles N et P et stockage de carboneTyp_Proj_Bourse de thèse/Post-DocTyp_Proj_Projet ANR; Uncertainties in the response of crop and grassland models to management and environmental drivers can be attributed to differences in the structure of different models. This has created an urgent need for international benchmarking of models, where uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty (e.g. Asseng et al., 2013). Simulations of the agricultural C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions (e.g. Sándor et al., 2016) and characterized by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C-N MIP and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models that estimate C-N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model-intercomparison-on-agricultural-ghg-emissions). This study presents some preliminary results on the uncertainty of outputs from 12 grassland models while exploring model differences when models were calibrated with increasing data resources.

Scenario analysis of alternative management options on the forage production and greenhouse gas emissions in Mediterranean grasslands. 19th Meeting of the FAO-CIHEAM Mountain Pastures Network

National audience

International audience; Legume species promote productivity and increase the digestibility of herbage in grasslands. Considerable experimental data also indicate that communities with legumes produce more above-ground biomass than is expected from monocultures. While it has been attributed to N facilitation, evidence to identify the mechanisms involved is still lacking and the role of complementarity in soil water acquisition by vertical root differentiation remains unclear. We used a 20-months mesocosm experiment to investigate the effects of species richness (single species, two- and five-species mixtures) and functional diversity (presence of the legume Trifolium repens) on a set of traits related to light, N and water use and measured at community level. We found a positive effect of Trifolium presence and abundance on biomass production and complementarity effects in the two-species mixtures from the second year. In addition the community traits related to water and N acquisition and use (leaf area, N, wateruse efficiency, and deep root growth) were higher in the presence of Trifolium. With a multiple regression approach, we showed that the traits related to water acquisition and use were with N the main determinants of biomass production and complementarity effects in diverse mixtures. At shallow soil layers, lower root mass of Trifolium and higher soil moisture should increase soil water availability for the associated grass species. Conversely at deep soil layer, higher root growth and lower soil moisture mirror soil resource use increase of mixtures. Altogether, these results highlight N facilitation but almost soil vertical differentiation and thus complementarity for water acquisition and use in mixtures with Trifolium. Contrary to grass-Trifolium mixtures, no significant overyielding was measured for grass mixtures even those having complementary traits (short and shallow vs. tall and deep). Thus, vertical complementarity for soil resources uptake in mixtures was not only dependant on the inherent root system architecture but also on root plasticity. We also observed a time-dependence for positive complementarity effects due to the slow development of Trifolium in mixtures, possibly induced by competition with grasses. Overall, our data underlined that soil water resource was an important driver of over-yielding and complementarity effects in Trifolium-grass mixtures.

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

International audience; Radioactive C-14 is formed as a by-product of nuclear power generation and from operation of nuclear fuel reprocessing plants like AREVA-NC La Hague (North France), which releases about 15 TBq per year of C-14 into the atmosphere. Since the autumn of 2006, C-14 activity concentrations in samples from the terrestrial environment (air, grass and soil) have been monitored monthly on grassland 2 km downwind of the reprocessing plant. The monitoring data provides an opportunity to validate radioecology models used to assess C-14 transfer to grassland ecosystems. This article compares and discusses the ability of two different models to reproduce the observed temporal variability in grass C-14 activity in the vicinity of AREVA-NC La Hague. These two models are the TOCATTA model which is specifically designed for modelling transfer of C-14 and tritium in the terrestrial environment, and PaSim, a pasture model for simulating grassland carbon and nitrogen cycling. Both TOCATTA and PaSim tend to under-estimate the magnitude of observed peaks in grass C-14 activity, although they reproduce the general trends. PaSim simulates C-14 activities in substrate and structural pools of the plant. We define a mean turn-over time for C-14 within the plant, which is based on both experimental data and the frequency of cuts. An adapted PaSim result is presented using the 15 and 20 day moving average results for the C-14 activity in the substrate pool, which shows a good match to the observations. This model reduces the Root Mean Square Error (RMSE) by nearly 40% in comparison to TOCATTA. (c) 2012 Elsevier Ltd. All rights reserved.

This study reveals the changes and evolution of rainstorm-driven intermediate floods occurring and driving multiple damaging hydrological events in the Rhone River Basin (RRB), since 1500 until 2010. A parsimonious approach was developed to simulate the major hydroclimatological flood-producing forcing, the Multiscale Rainstorm Climate Model (STORMCLIMM). We collected the frequency of intermediate floods—a type of particularly hazardous floods commonly taking place between June and beginning of November—from the RCB to be compared to STORMCLIMM estimates. The latter, smoothed by a moving window of 21 years, results in a high-pass filter in the time domain, which magnifies the signal of forcing variations causing intermediate floods. The RRB showed large temporal variations in both extreme rainstorms and associated multidecadal intermediate-floods (MUDIF) frequency at different climatic periods and land-use systems through historical times. An important peak was observed in the Maunder Minimum (1645–1715 AD). The model allowed detecting MUDIF occurred in the historical times. The situation becomes interesting with respect to recent times, because the Rhone landscape looks more vulnerable in the last decades as a consequence of land-use changes and climate shift towards more erratic and intensive storms. This evidence suggests that the interactions of land-use and climatic changes may turn into considerable vulnerability to fluvial flooding and agro-ecosystem connected to them for upcoming years. The Rhone, for example, provides basis for use of hydrological indicators (such as the one represented by STORMCLIMM) for one site or region and which, through minor modifications, can be made relevant to specific needs.

In order to feed the world we need innovative thinking on how to increase agricultural production whilst also mitigating climate change. Agriculture and land-use change are responsible for approximately one-third of total anthropogenic greenhouse gas (GHG) emissions but hold potential for climate change mitigation but are only tangentially included in UNFCCC mitigation policies. To get a full estimate of GHG emissions from agricultural crop production both energy-based emissions and land-based emissions need to be accounted for. Furthermore, the major mitigation potential is likely to be indirect reduction of emissions i.e. reducing emissions per unit of agricultural product rather than the absolute emissions per se. Hence the system productivity must be included in the same analysis. This paper presents the Kaya-Porter identity, derived from the Maya identity, as a new way to calculate GHG emissions from agricultural crop production by deconstructing emissions into five elements; the GHG intensity of the energy used for production (kg CO2-eq./MJ), energy intensity of the production (MJ/kg dry matter), areal productivity (kg dry matter/ha), areal land-based GHG emissions (CO2-eq./ha) and area (ha). These separate elements in the identity can be targeted in emissions reduction and mitigation policies and are useful to analyse past and current trends in emissions and to explore future scenarios. Using the Kaya-Porter identity we have performed a case study on Danish crop production and find emissions to have been reduced by 12% from 1992 to 2008, whilst yields per unit area have remained constant. Both land-based emissions and energy-based emissions have decreased, mainly due to a 41% reduction in nitrogen fertilizer use. The initial identity based analysis for crop production presented here needs to be extended to include livestock to reflect the entire agricultural production and food demand sectors, thereby permitting analysis of the trade-offs between animal and plant food production, human dietary preferences and population and resulting GHG emissions. (C) 2012 Elsevier B.V. All rights reserved.

Question Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location Western Swiss Alps (400–3210 m a.s.l.). Methods We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for the management and conservation of biodiversity at intermediate elevations. Conclusions Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

The number of real-time polymerase chain reaction (qPCR) instruments available has greatly increased over recent years. However, little information is available on the performance of validated quantitative methods when tested in different instruments. A study has been designed to evaluate the robustness of three validated methods for genetically modified organisms (GMO) quantification across six real-time platforms from four different suppliers. The performance of three validated methods for event-specific detection of Bt11 maize, DAS 59122 maize and MON 89788 soybean was evaluated on six qPCR platforms (ABI 7900 HT, ABI Prism® 7700 and ABI 7500 from Applied Biosystems; LightCycler® 480 from Roche; Mx3005P® from Stratagene; and iQ™5 from Bio-Rad). Method performance criteria were compared against European Network of GMO Laboratories method performance requirements for analytical methods of GMO testing. The latter comparison indicates that the criteria are fulfilled for most of the platforms and levels of GMO concentrations, though with minor exceptions. The analysis of variance (one-way) indicated that the quantification of GMOs was affected by the platforms, which did not respond consistently across GM levels. A two-way analysis of variance confirmed that there were significant interactions between platforms and GM levels. The pairwise comparison of the platforms' performance indicated that some deviate significantly from others, though differences between methods were observed.

Une discussion entre les reviewers a donné lieu à une publication (The requested discussion paper has a corresponding peer-reviewed final revised paper.) :Yiou, P. (Auteur de correspondance), Garcia De Cortazar Atauri, I., Chuine, I., Daux, V., Garnier, E., Viovy, N., Van Leeuwen, C., Parker, A., Boursiquot, J.-M. (2011). Continental atmospheric circulation over Europe during Little Ice Age inferred from grape harvest dates. Discussions. Climate of the past, 7 (5), 3023-3048. DOI : 10.5194/cpd-7-3023-2011; Estimates of climate conditions before the 19th century are based on proxy data reconstructions or sparse meteorological measurements. The reconstruction of the atmospheric circulation that prevailed during the European Little Ice Age (∼1500–1850) has fostered many efforts. This study illustrates a methodology, combining historical proxies and modern datasets to obtain detailed information on the atmospheric circulation that prevailed over the North Atlantic region during the Little Ice Age. We used reconstructions of temperature gradients over France based on grape harvest dates to infer the atmospheric circulation. We found that blocking situations were more likely in summer, inducing a continental atmospheric flow. This study advocates that the reconstructions of the past atmospheric circulation should take this regime into account.