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1. Within-plant genetic drift to control virus adaptation to host resistance genes.

Author: Lucie Tamisier, Frédéric Fabre, Marion Szadkowski, Lola Chateau, Ghislaine Nemouchi, Grégory Girardot, Pauline Millot, Alain Palloix, and Benoît Moury
Subjects: Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract: Manipulating evolutionary forces imposed by hosts on pathogens like genetic drift and selection could avoid the emergence of virulent pathogens. For instance, increasing genetic drift could decrease the risk of pathogen adaptation through the random fixation of deleterious mutations or the elimination of favorable ones in the pathogen population. However, no experimental proof of this approach is available for a plant-pathogen system. We studied the impact of pepper (Capsicum annuum) lines carrying the same major resistance gene but contrasted genetic backgrounds on the evolution of Potato virus Y (PVY). The pepper lines were chosen for the contrasted levels of genetic drift (inversely related to Ne, the effective population size) they exert on PVY populations, as well as for their contrasted resistance efficiency (inversely related to the initial replicative fitness, Wi, of PVY in these lines). Experimental evolution was performed by serially passaging 64 PVY populations every month on six contrasted pepper lines during seven months. These PVY populations exhibited highly divergent evolutionary trajectories, ranging from viral extinctions to replicative fitness gains. The sequencing of the PVY VPg cistron, where adaptive mutations are likely to occur, allowed linking these replicative fitness gains to parallel adaptive nonsynonymous mutations. Evolutionary trajectories were well explained by the genetic drift imposed by the host. More specifically, Ne, Wi and their synergistic interaction played a major role in the fate of PVY populations. When Ne was low (i.e. strong genetic drift), the final PVY replicative fitness remained close to the initial replicative fitness, whereas when Ne was high (i.e. low genetic drift), the final PVY replicative fitness was high independently of the replicative fitness of the initially inoculated virus. We show that combining a high resistance efficiency (low Wi) and a strong genetic drift (low Ne) is the best solution to increase resistance durability, that is, to avoid virus adaptation on the long term.
Published: 2024
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2. Effects of pathogen reproduction system on the evolutionary and epidemiological control provided by deployment strategies for two major resistance genes in agricultural landscapes

Author: Marta Zaffaroni, Loup Rimbaud, Jean‐François Rey, Julien Papaïx, and Frédéric Fabre
Subjects: deployment strategy, disease control, durable resistance, evolutionary epidemiology, sexual reproduction, simulation modelling, Evolution, QH359-425
Abstract: Abstract Resistant cultivars are of value for protecting crops from disease, but can be rapidly overcome by pathogens. Several strategies have been proposed to delay pathogen adaptation (evolutionary control), while maintaining effective protection (epidemiological control). Resistance genes can be (i) combined in the same cultivar (pyramiding), (ii) deployed in different cultivars sown in the same field (mixtures) or in different fields (mosaics), or (iii) alternated over time (rotations). The outcomes of these strategies have been investigated principally in pathogens displaying pure clonal reproduction, but many pathogens have at least one sexual event in their annual life cycles. Sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed. Here, we improved the spatially explicit stochastic model landsepi to include pathogen sexual reproduction, and we used the improved model to investigate the effect of sexual reproduction on evolutionary and epidemiological outcomes across deployment strategies for two major resistance genes. Sexual reproduction favours the establishment of a superpathogen when single mutant pathogens are present together at a sufficiently high frequency, as in mosaic and mixture strategies. However, sexual reproduction did not affect the strategy recommendations for a wide range of mutation probabilities, associated fitness costs, and landscape organisations.
Published: 2024
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3. An epi‐evolutionary model for predicting the adaptation of spore‐producing pathogens to quantitative resistance in heterogeneous environments

Author: Frédéric Fabre, Jean‐Baptiste Burie, Arnaud Ducrot, Sébastien Lion, Quentin Richard, and Ramsès Djidjou‐Demasse
Subjects: adaptive dynamics, basic reproduction number, integro‐differential equations, quantitative resistance, resistance durability, spore‐producing pathogens, Evolution, QH359-425
Abstract: Abstract We have modeled the evolutionary epidemiology of spore‐producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection‐age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits determining its infection efficiency and a time‐varying sporulation curve taking into account lesion aging. We first derived a general expression of the basic reproduction number R0 for fungal pathogens in heterogeneous environments. We show that the evolutionary attractors of the model coincide with local maxima of R0 only if the infection efficiency is the same on all host types. We then studied the contribution of three basic resistance characteristics (the pathogenicity trait targeted, resistance effectiveness, and adaptation cost), in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar), to (i) pathogen diversification at equilibrium and (ii) the shaping of transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance affecting only the sporulation curve will always lead to a monomorphic population, whereas dimorphism (i.e., pathogen diversification) can occur if resistance alters infection efficiency, notably with high adaptation costs and proportions of the resistant cultivar. Accordingly, the choice of the quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the time to emergence of the evolutionary attractor best adapted to the resistant cultivar tends to be shorter when resistance affects infection efficiency than when it affects sporulation. Conversely, from an epidemiological perspective, epidemiological control is always greater when the resistance affects infection efficiency. This highlights the difficulty of defining deployment strategies for quantitative resistance simultaneously maximizing epidemiological and evolutionary outcomes.
Published: 2022
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4. Estimating virus effective population size and selection without neutral markers.

Author: Elsa Rousseau, Benoît Moury, Ludovic Mailleret, Rachid Senoussi, Alain Palloix, Vincent Simon, Sophie Valière, Frédéric Grognard, and Frédéric Fabre
Subjects: Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract: By combining high-throughput sequencing (HTS) with experimental evolution, we can observe the within-host dynamics of pathogen variants of biomedical or ecological interest. We studied the evolutionary dynamics of five variants of Potato virus Y (PVY) in 15 doubled-haploid lines of pepper. All plants were inoculated with the same mixture of virus variants and variant frequencies were determined by HTS in eight plants of each pepper line at each of six sampling dates. We developed a method for estimating the intensities of selection and genetic drift in a multi-allelic Wright-Fisher model, applicable whether these forces are strong or weak, and in the absence of neutral markers. This method requires variant frequency determination at several time points, in independent hosts. The parameters are the selection coefficients for each PVY variant and four effective population sizes Ne at different time-points of the experiment. Numerical simulations of asexual haploid Wright-Fisher populations subjected to contrasting genetic drift (Ne ∈ [10, 2000]) and selection (|s| ∈ [0, 0.15]) regimes were used to validate the method proposed. The experiment in closely related pepper host genotypes revealed that viruses experienced a considerable diversity of selection and genetic drift regimes. The resulting variant dynamics were accurately described by Wright-Fisher models. The fitness ranks of the variants were almost identical between host genotypes. By contrast, the dynamics of Ne were highly variable, although a bottleneck was often identified during the systemic movement of the virus. We demonstrated that, for a fixed initial PVY population, virus effective population size is a heritable trait in plants. These findings pave the way for the breeding of plant varieties exposing viruses to stronger genetic drift, thereby slowing virus adaptation.
Published: 2017
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5. Canopy Height Estimation in French Guiana with LiDAR ICESat/GLAS Data Using Principal Component Analysis and Random Forest Regressions

Author: Ibrahim Fayad, Nicolas Baghdadi, Jean-Stéphane Bailly, Nicolas Barbier, Valéry Gond, Mahmoud El Hajj, Frédéric Fabre, and Bernard Bourgine
Subjects: LiDAR, ICESat/GLAS, canopy height, tropical forest, French Guiana, Science
Abstract: Estimating forest canopy height from large-footprint satellite LiDAR waveforms is challenging given the complex interaction between LiDAR waveforms, terrain, and vegetation, especially in dense tropical and equatorial forests. In this study, canopy height in French Guiana was estimated using multiple linear regression models and the Random Forest technique (RF). This analysis was either based on LiDAR waveform metrics extracted from the GLAS (Geoscience Laser Altimeter System) spaceborne LiDAR data and terrain information derived from the SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model) or on Principal Component Analysis (PCA) of GLAS waveforms. Results show that the best statistical model for estimating forest height based on waveform metrics and digital elevation data is a linear regression of waveform extent, trailing edge extent, and terrain index (RMSE of 3.7 m). For the PCA based models, better canopy height estimation results were observed using a regression model that incorporated both the first 13 principal components (PCs) and the waveform extent (RMSE = 3.8 m). Random Forest regressions revealed that the best configuration for canopy height estimation used all the following metrics: waveform extent, leading edge, trailing edge, and terrain index (RMSE = 3.4 m). Waveform extent was the variable that best explained canopy height, with an importance factor almost three times higher than those for the other three metrics (leading edge, trailing edge, and terrain index). Furthermore, the Random Forest regression incorporating the first 13 PCs and the waveform extent had a slightly-improved canopy height estimation in comparison to the linear model, with an RMSE of 3.6 m. In conclusion, multiple linear regressions and RF regressions provided canopy height estimations with similar precision using either LiDAR metrics or PCs. However, a regression model (linear regression or RF) based on the PCA of waveform samples with waveform extent information is an interesting alternative for canopy height estimation as it does not require several metrics that are difficult to derive from GLAS waveforms in dense forests, such as those in French Guiana.
Published: 2014
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6. Temporal niche differentiation of parasites sharing the same plant host: oak powdery mildew as a case study

Author: Frédéric M. Hamelin, Anne Bisson, Marie‐Laure Desprez‐Loustau, Frédéric Fabre, and Ludovic Mailleret
Subjects: coexistence, epidemiology, pathogen, seasonality, semidiscrete model, trade‐off, Ecology, QH540-549.5
Abstract: Abstract Plant diseases are often caused by complexes of closely related parasite species. The coexistence of species sharing the same niche challenges the competitive exclusion principle. Here, we performed the mathematical analysis of a generic model of sibling parasite species coexistence based on seasonality. We showed that coexistence through temporal niche partitioning is biologically plausible as it occurred in a significant part of the parameter space of the model. Moreover, the reversal of species relative frequencies (i.e., the most frequent species at the beginning of the season becoming the last frequent at the end) can occur without compromising the long‐term coexistence of the two species. We provided data showing that this reversal pattern does repeat over years in the case of two sibling species responsible for oak powdery mildew (Erysiphe alphitoides and Erysiphe quercicola) in Europe. Last, the model was fitted to the data and satisfactorily described the population dynamics of oak powdery mildew species. The seasonal succession of these two plant pathogen species provides one of the few examples of coexistence by temporal niche partitioning at the scale of the season caused by exploitative competition. We discuss whether evolutionary branching may have led to temporal niche differentiation in this system.
Published: 2016
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7. Narrow bottlenecks affect Pea seedborne mosaic virus populations during vertical seed transmission but not during leaf colonization.

Author: Frédéric Fabre, Benoît Moury, Elisabeth Ida Johansen, Vincent Simon, Mireille Jacquemond, and Rachid Senoussi
Subjects: Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract: The effective size of populations (Ne) determines whether selection or genetic drift is the predominant force shaping their genetic structure and evolution. Populations having high Ne adapt faster, as selection acts more intensely, than populations having low Ne, where random effects of genetic drift dominate. Estimating Ne for various steps of plant virus life cycle has been the focus of several studies in the last decade, but no estimates are available for the vertical transmission of plant viruses, although virus seed transmission is economically significant in at least 18% of plant viruses in at least one plant species. Here we study the co-dynamics of two variants of Pea seedborne mosaic virus (PSbMV) colonizing leaves of pea plants (Pisum sativum L.) during the whole flowering period, and their subsequent transmission to plant progeny through seeds. Whereas classical estimators of Ne could be used for leaf infection at the systemic level, as virus variants were equally competitive, dedicated stochastic models were needed to estimate Ne during vertical transmission. Very little genetic drift was observed during the infection of apical leaves, with Ne values ranging from 59 to 216. In contrast, a very drastic genetic drift was observed during vertical transmission, with an average number of infectious virus particles contributing to the infection of a seedling from an infected mother plant close to one. A simple model of vertical transmission, assuming a cumulative action of virus infectious particles and a virus density threshold required for vertical transmission to occur fitted the experimental data very satisfactorily. This study reveals that vertically-transmitted viruses endure bottlenecks as narrow as those imposed by horizontal transmission. These bottlenecks are likely to slow down virus adaptation and could decrease virus fitness and virulence.
Published: 2014
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8. Regional Scale Rain-Forest Height Mapping Using Regression-Kriging of Spaceborne and Airborne LiDAR Data: Application on French Guiana

Author: Ibrahim Fayad, Nicolas Baghdadi, Jean-Stéphane Bailly, Nicolas Barbier, Valéry Gond, Bruno Hérault, Mahmoud El Hajj, Frédéric Fabre, and José Perrin
Subjects: canopy height mapping, airborne LiDAR, ICESat GLAS, forests, French Guiana, Science
Abstract: LiDAR data has been successfully used to estimate forest parameters such as canopy heights and biomass. Major limitation of LiDAR systems (airborne and spaceborne) arises from their limited spatial coverage. In this study, we present a technique for canopy height mapping using airborne and spaceborne LiDAR data (from the Geoscience Laser Altimeter System (GLAS)). First, canopy heights extracted from both airborne and spaceborne LiDAR were extrapolated from available environmental data. The estimated canopy height maps using Random Forest (RF) regression from airborne or GLAS calibration datasets showed similar precisions (~6 m). To improve the precision of canopy height estimates, regression-kriging was used. Results indicated an improvement in terms of root mean square error (RMSE, from 6.5 to 4.2 m) using the GLAS dataset, and from 5.8 to 1.8 m using the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on canopy height estimates precision, six subsets were derived from the initial airborne LiDAR dataset. Results indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. This precision decreased to 4.8 m for flight line spacing of 50 km.
Published: 2016
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9. Modelling the evolutionary dynamics of viruses within their hosts: a case study using high-throughput sequencing.

Author: Frédéric Fabre, Josselin Montarry, Jérôme Coville, Rachid Senoussi, Vincent Simon, and Benoît Moury
Subjects: Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract: Uncovering how natural selection and genetic drift shape the evolutionary dynamics of virus populations within their hosts can pave the way to a better understanding of virus emergence. Mathematical models already play a leading role in these studies and are intended to predict future emergences. Here, using high-throughput sequencing, we analyzed the within-host population dynamics of four Potato virus Y (PVY) variants differing at most by two substitutions involved in pathogenicity properties. Model selection procedures were used to compare experimental results to six hypotheses regarding competitiveness and intensity of genetic drift experienced by viruses during host plant colonization. Results indicated that the frequencies of variants were well described using Lotka-Volterra models where the competition coefficients β(ij) exerted by variant j on variant i are equal to their fitness ratio, r(j)/r(i). Statistical inference allowed the estimation of the effect of each mutation on fitness, revealing slight (s = -0.45%) and high (s = -13.2%) fitness costs and a negative epistasis between them. Results also indicated that only 1 to 4 infectious units initiated the population of one apical leaf. The between-host variances of the variant frequencies were described using Dirichlet-multinomial distributions whose scale parameters, closely related to the fixation index F(ST), were shown to vary with time. The genetic differentiation of virus populations among plants increased from 0 to 10 days post-inoculation and then decreased until 35 days. Overall, this study showed that mathematical models can accurately describe both selection and genetic drift processes shaping the evolutionary dynamics of viruses within their hosts.
Published: 2012
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10. Towards a Multi-Model Approach to Support User-Driven Extensibility in Data Warehouses: Agro-ecology Case Study.

Author: Fagnine Alassane Coulibaly, Sandro Bimonte, Stefano Rizzi, Sylvie Malembic-Maher, and Frédéric Fabre
Published: 2023

11. Bayesian inference for spatio-temporal stochastic transmission of plant disease in the presence of roguing: A case study to characterise the dispersal of Flavescence dorée.

Author: Hola Adrakey, Gavin J. Gibson, Sandrine Eveillard, Sylvie Malembic-Maher, and Frédéric Fabre
Published: 2023
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12. The Aeolus Data Innovation and Science Cluster.

Author: Isabell Krisch, Oliver Reitebuch, Jonas von Bismarck, Tommaso Parrinello, Michael Rennie, Fabian Weiler, Dorit Huber, Jos de Kloe, Alain Dabas, Anne Grete Straume-Lindner, Saleh Abdalla, Stefano Aprile, Sebastian Bley, Fabio Bracci, Simone Bucci, Massimo Cardaci, Werner Damman, Dave Donovan, Frithjof Ehlers, Frédéric Fabre, Peggy Fischer, Thomas Flament, Giacomo Gostinicchi, Lars Isaksen, Sebastian Jupin-Langlois, Thomas Kanitz, Adrien Lacour, Marta De Laurentis, Christian Lemmerz, Oliver Lux, Uwe Marksteiner, Gert-Jan Marseille, Nafiseh Masoumzadeh, Markus Meringer, Sander Niemeijer, Ines Nikolaus, Gaetan Perron, Bas J. Pijnacker Hordijk, Katja Reissig, Matic Savli, Karsten Schmidt, Ad Stoffelen, Dimitri Trapon, Michael Vaughan, Marcella Veneziani, Cristiano De Vincenti, and Benjamin Witschas
Published: 2021
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13. The Characterization of Pathotypes in Grapevine Downy Mildew Provides Insights into the Breakdown of Rpv3, Rpv10, and Rpv12 Factors in Grapevines

Author: Manon Paineau, Isabelle D. Mazet, Sabine Wiedemann-Merdinoglu, Frédéric Fabre, and François Delmotte
Subjects: Peronospora, Oomycetes, Vitis, Plant Science, Agronomy and Crop Science, Disease Resistance, Plant Diseases
Abstract: We describe a standard method for characterizing the virulence profile of Plasmopara viticola, the causal agent of grapevine downy mildew. We used 33 European strains to inoculate six grapevine varieties carrying the principal factors for resistance to downy mildew (Rpv1, Rpv3.1, Rpv3.2, Rpv5, Rpv6, Rpv10, and Rpv12) and the susceptible Vitis vinifera ‘Chardonnay’. For each interaction, we characterized the level of sporulation by image analysis and the intensity of the grapevine hypersensitive response by visual score. We propose a definition for the breakdown of grapevine quantitative resistances combining these two traits. Among the 33 strains analyzed, 28 are virulent on at least one resistance factor. We identified five different pathotypes across the 33 strains analyzed: two pathotypes overcoming a single resistance factor (vir3.1 and vir3.2) and three complex pathotypes overcoming multiple resistance factors (vir3.1,3.2; vir3.2,12; vir3.1,3.2,10). Our findings confirm the widespread occurrence of P. viticola strains overcoming the Rpv3 haplotypes (28 strains). We also detected the first breakdown of resistance to the Rpv10 by a strain from Germany and the breakdown of Rpv12 factors by a strain from Hungary. The pathotyping method proposed here and the associated differential host range lay the groundwork for the early detection of resistance breakdown in grapevines. This approach will also facilitate the monitoring of the evolution of P. viticola populations at large spatial scales. This is an essential step forward to promoting durable management of the resistant grapevine varieties currently available.
Published: 2022
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14. Improving sustainable crop protection using population genetics concepts

Author: Méline Saubin, Clémentine Louet, Lydia Bousset, Frédéric Fabre, Pascal Frey, Isabelle Fudal, Frédéric Grognard, Frédéric Hamelin, Ludovic Mailleret, Solenn Stoeckel, Suzanne Touzeau, Benjamin Petre, Fabien Halkett, Interactions Arbres-Microorganismes (IAM), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), BIOlogie et GEstion des Risques en agriculture (BIOGER), Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biological control of artificial ecosystems (BIOCORE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), ANR-18-CE32-0001,Clonix2D,Les conséquences génétiques de reproduction partiellement clonale dans les populations colonisant de nouveaux territoires(2018), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers
Subjects: Plant immunity, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM], Transient dynamics, Host-pathogen coevolution, [SDV]Life Sciences [q-bio], Genetics, Citation network, Genetic drift, Resistance durability, Ecology, Evolution, Behavior and Systematics, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract: accepted; International audience; Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (i) ‘plant breeding’ (generating new genetic material), (ii) ‘molecular interactions’ (exploring the molecular dialogue governing plant–pathogen interactions) and (iii) ‘epidemiology and evolution’ (explaining and forecasting of pathogen population dynamics resulting from selection pressure(s) exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary–epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars.
Published: 2023
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15. Canopy height estimation in French Guiana using LiDAR ICESat/GLAS data.

Author: Ibrahim Fayad, Nicolas N. Baghdadi, Jean-Stéphane Bailly, Nicolas Barbier, Valéry Gond, Mahmoud El Hajj, and Frédéric Fabre
Published: 2014
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16. Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana.

Author: Ibrahim Fayad, Nicolas N. Baghdadi, Valéry Gond, Jean-Stéphane Bailly, Nicolas Barbier, Mahmoud El Hajj, and Frédéric Fabre
Published: 2014
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17. A mechanistic-statistical approach to infer dispersal and demography from invasion dynamics, applied to a plant pathogen

Author: Méline Saubin, Jérome Coville, Constance Xhaard, Pascal Frey, Samuel Soubeyrand, Fabien Halkett, and Frédéric Fabre
Abstract: Dispersal, and in particular the frequency of long-distance dispersal (LDD) events, has strong implications for population dynamics with possibly the acceleration of the colonisation front, and for evolution with possibly the conservation of genetic diversity along the colonised domain. However, accurately inferring LDD is challenging as it requires both large-scale data and a methodology that encompasses the redistribution of individuals in time and space. Here, we propose a mechanistic-statistical framework to estimate dispersal from one-dimensional invasions. The mechanistic model takes into account population growth and grasps the diversity in dispersal processes by using either diffusion, leading to a reaction-diffusion (R.D.) formalism, or kernels, leading to an integro-differential (I.D.) formalism. The latter considers different dispersal kernels (e.g.Gaussian, Exponential, and Exponential-power) differing in their frequency of LDD events. The statistical model relies on dedicated observation laws that describe two types of samples, clumped or not. As such, we take into account the variability in both habitat suitability and occupancy perception. We first check the identifiability of the parameters and the confidence in the selection of the dispersal process. We observed good identifiability for nearly all parameters (Correlation Coefficient>0.95 between true and fitted values), except for occupancy perception (Correlation Coefficient = 0.83−0.85). The dispersal process that is the most confidently identified is Exponential-Power (i.e.fat-tailed) kernel. We then applied our framework to data describing an annual invasion of the poplar rust disease along the Durance River valley over nearly 200 km. This spatio-temporal survey consisted of 12 study sites examined at seven time points. We confidently estimated that the dispersal of poplar rust is best described by an Exponential-power kernel with a mean dispersal distance of 2.01 km and an exponent parameter of 0.24 characterising a fat-tailed kernel with frequent LDD events. By considering the whole range of possible dispersal processes our method forms a robust inference framework. It can be employed for a variety of organisms provided they are monitored in time and space along a one-dimension invasion.
Published: 2023
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18. Effects of pathogen sexual reproduction on the evolutionary and epidemiological control provided by deployment strategies for two major resistance genes in agricultural landscapes

Author: Marta Zaffaroni, Loup Rimbaud, Jean-François Rey, Julien Papaïx, and Frédéric Fabre
Abstract: SummaryResistant cultivars are of value for protecting crops from disease, but can be rapidly overcome by pathogens. Several strategies have been proposed to delay pathogen adaptation (evolutionary control), while maintaining effective protection (epidemiological control). Resistance genes can bei) combined in the same cultivar (pyramiding),ii) deployed in different cultivars sown in the same field (mixtures) or in different fields (mosaics), oriii) alternated over time (rotations). The outcomes of these strategies have been investigated principally in pathogens displaying pure clonal reproduction, but sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed.We improved the spatially explicit stochastic modellandsepito include pathogen sexual reproduction, and then investigate the effect of sexual reproduction on evolutionary and epidemiological outcomes across deployment strategies for two major resistance genes.Sexual reproduction only favours the establishment of a superpathogen when single mutant pathogens are present together at a sufficiently high frequency, as in mosaic and mixture strategies.We concluded that, although sexual reproduction may promote the establishment of a superpathogen, it did not affect the optimal strategy recommendations for a wide range of mutation probabilities, associated fitness costs, and landscape organisations (notably the cropping ratio of resistant fields).
Published: 2023
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19. Viability Statistics of GLAS/ICESat Data Acquired Over Tropical Forests.

Author: Nicolas N. Baghdadi, Mohammad El-Hajj, Jean-Stéphane Bailly, and Frédéric Fabre
Published: 2014
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20. Potential of Space-Borne LiDAR Sensors for Global Bathymetry in Coastal and Inland Waters.

Author: Hani Abdallah, Jean-Stéphane Bailly, Nicolas N. Baghdadi, Nathalie Saint-Geours, and Frédéric Fabre
Published: 2013
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21. Wa-LiD: A New LiDAR Simulator for Waters.

Author: Hani Abdallah, Nicolas N. Baghdadi, Jean-Stéphane Bailly, Yves Pastol, and Frédéric Fabre
Published: 2012
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22. Promoting crop pest control by plant diversification in agricultural landscapes: A conceptual framework for analysing feedback loops between agro-ecological and socio-economic effects

Author: Aude Vialatte, Anaïs Tibi, Audrey Alignier, Valérie Angeon, Laurent Bedoussac, David A. Bohan, Douadia Bougherara, Alain Carpentier, Bastien Castagneyrol, Stéphane Cordeau, Pierre Courtois, Jean-Philippe Deguine, Jérôme Enjalbert, Frédéric Fabre, Fabienne Féménia, Hélène Fréville, Frédéric Goulet, Régis Grateau, Benoît Grimonprez, Nicolas Gross, Mourad Hannachi, Philippe Jeanneret, Laure Kuhfuss, Pierre Labarthe, Marie Launay, Marianne Lefebvre, Virginie Lelièvre, Stéphane Lemarié, Gilles Martel, Abel Masson, Mireille Navarrete, Manuel Plantegenest, Virginie Ravigné, Adrien Rusch, Frédéric Suffert, Abdoulaye Tapsoba, Olivier Therond, Sophie Thoyer, Vincent Martinet, Dynamiques et écologie des paysages agriforestiers (DYNAFOR), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Direction de l'Expertise scientifique collective, de la Prospective et des Etudes, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de recherche d'Écodéveloppement (ECODEVELOPPEMENT), AGroécologie, Innovations, teRritoires (AGIR), Institut National Polytechnique (Toulouse) (Toulouse INP), École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville (ENSFEA), Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'Economie de l'Environnement - Montpellier - UMR 5211 (CEE-M), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Structures et Marché Agricoles, Ressources et Territoires (SMART-LERECO), AGROCAMPUS OUEST-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Peuplements végétaux et bioagresseurs en milieu tropical (UMR PVBMT), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de La Réunion (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Innovation et Développement dans l'Agriculture et l'Alimentation (UMR Innovation), Département Environnements et Sociétés (Cirad-ES), Economie Publique (ECO-PUB), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d’Etudes et de Coopération Juridique Interdisciplinaire (CECOJI), Université de Poitiers, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Sciences pour l'Action et le Développement : Activités, Produits, Territoires (SADAPT), Agroscope, University of St Andrews [Scotland], Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), Groupe de Recherche Angevin en Economie et Management (GRANEM), Institut National de l'Horticulture et du Paysage-AGROCAMPUS OUEST-Université d'Angers (UA), Département agronomie et sciences de l'environnement pour les agroécosystèmes (AgroEcoSystem), Laboratoire d'Economie Appliquée de Grenoble (GAEL), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Biodiversité agroécologie et aménagement du paysage (UMR BAGAP), AGROCAMPUS OUEST-Ecole supérieure d'Agricultures d'Angers (ESA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AgroParisTech, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plant Health Institute of Montpellier (UMR PHIM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), BIOlogie et GEstion des Risques en agriculture (BIOGER), Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Agronomie et Environnement - Antenne Colmar (LAE-Colmar ), Laboratoire Agronomie et Environnement (LAE), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'Economie de l'Environnement - Montpellier (CEE-M), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Centre d’études et de coopération juridique interdisciplinaire - Université de Poitiers (CECOJI-UP), Université d'Angers (UA)-AGROCAMPUS OUEST-Institut National de l'Horticulture et du Paysage, Ecole supérieure d'Agricultures d'Angers (ESA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de Montpellier (UM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, French Office for Biodiversity (OFB) through the national ECOPHYTO plan, David A. Bohan, Alex J. Dumbrell, Adam J. Vanbergen, Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AGROCAMPUS OUEST, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut National de l'Horticulture et du Paysage-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université d'Angers (UA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Ecole supérieure d'Agricultures d'Angers (ESA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Gestion des ressources renouvelables et environnement (UPR GREEN), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université d'Angers (UA)-AGROCAMPUS OUEST, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de l'Horticulture et du Paysage
Subjects: 2. Zero hunger, 0106 biological sciences, 13. Climate action, 11. Sustainability, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, 04 agricultural and veterinary sciences, 15. Life on land, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 01 natural sciences, 010606 plant biology & botany, [SHS]Humanities and Social Sciences
Abstract: International audience; Given the negative environmental effects of conventional agricultural techniques, the need for biodiversity-friendly agriculture systems that rely more on ecosystem services and less on chemical inputs is becoming increasingly urgent. In this paper, we focus on crop protection strategies that are alternatives to the use of pesticides. Diversification of the plant component of agricultural areas at different space and time scales has been presented as a powerful socio-economic and agro-ecological mechanism for the sustainable control of pests. Our interdisciplinary group of scientific experts examined the literature on the ecological effects of plant diversification on pests and their natural enemies, as well as the social science literature on the conditions for farmers to adopt the corresponding practices, to assess the potential offered by plant diversification.We developed a conceptual framework that connects the agro-ecological and socio-economic components of an agricultural landscape in a dynamic loop accounting for interactions among elements at different spatial and temporal scales and their feedback effects. This article presents this framework and illustrates its application to the case of wheat production and protection. By explicitly connecting each level of agro-ecological organization with the potential socio-economic drivers and limitations underpinning the adoption and implementation of plant diversification in landscapes, this framework makes it possible to ana yse the synergies and antagonisms between different modes of diversification and the conditions of their deployment. Exploring this framework is a prerequisite to the identification of opportunities and key feed-back loops for designing diversification strategies that unlock the agro-ecological potential of f uture production systems. We conclude that there is a need for interdisciplinary research in experimental landscapes involving farmers and other local stakeholders to design sustainable future agricultural landscapes that deliver high levels of biological control services..
Published: 2022
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23. An epi‐evolutionary model for predicting the adaptation of spore‐producing pathogens to quantitative resistance in heterogeneous environments

Author: Ramsès Djidjou-Demasse, Frédéric Fabre, Sébastien Lion, Arnaud Ducrot, Quentin Richard, Jean-Baptiste Burie, Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Mathématiques Appliquées du Havre (LMAH), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM), Conseil Interprofessionnel du Vin de BordeauxMarie-Curie FP7 COFUND People Programme. Grant Number: FP7-609398, ANR-16-CE35-0012,STEEP,Structuration spatiale, traitements et épidémiologie évolutive des parasites(2016), ANR-18-CE32-0004,ArchiV,Architecture génétique des caractères quantitatifs dans les interactions plante-virus: conséquences pour la gestion des variétés résistantes et/ou tolérantes à l'échelle du paysage.(2018), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])
Subjects: 0106 biological sciences, quantitative resistance, Evolution, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], Biology, integro-differential equations, 01 natural sciences, 03 medical and health sciences, basic reproduction number, Genetics, QH359-425, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Resistance (ecology), fungi, integro‐differential equations, Original Articles, Spore, adaptive dynamics, Evolutionary biology, spore‐producing pathogens, spore-producing pathogens, Original Article, Adaptation, General Agricultural and Biological Sciences, Basic reproduction number, resistance durability, 010606 plant biology & botany
Abstract: International audience; We have modeled the evolutionary epidemiology of spore-producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection-age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits determining its infection efficiency and a time-varying sporulation curve taking into account lesion aging. We first derived a general expression of the basic reproduction number urn:x-wiley:17524571:media:eva13328:eva13328-math-0001 for fungal pathogens in heterogeneous environments. We show that the evolutionary attractors of the model coincide with local maxima of urn:x-wiley:17524571:media:eva13328:eva13328-math-0002 only if the infection efficiency is the same on all host types. We then studied the contribution of three basic resistance characteristics (the pathogenicity trait targeted, resistance effectiveness, and adaptation cost), in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar), to (i) pathogen diversification at equilibrium and (ii) the shaping of transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance affecting only the sporulation curve will always lead to a monomorphic population, whereas dimorphism (i.e., pathogen diversification) can occur if resistance alters infection efficiency, notably with high adaptation costs and proportions of the resistant cultivar. Accordingly, the choice of the quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the time to emergence of the evolutionary attractor best adapted to the resistant cultivar tends to be shorter when resistance affects infection efficiency than when it affects sporulation. Conversely, from an epidemiological perspective, epidemiological control is always greater when the resistance affects infection efficiency. This highlights the difficulty of defining deployment strategies for quantitative resistance simultaneously maximizing epidemiological and evolutionary outcomes.
Published: 2022
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24. ALADIN laser frequency stability and its impact on the Aeolus wind error

Author: Oliver Lux, Christian Lemmerz, Fabian Weiler, Thomas Kanitz, Denny Wernham, Gonçalo Rodrigues, Andrew Hyslop, Olivier Lecrenier, Phil McGoldrick, Frédéric Fabre, Paolo Bravetti, Tommaso Parrinello, and Oliver Reitebuch
Subjects: Earthwork. Foundations, space lasers, wind data quality, TA715-787, Environmental engineering, TA170-171, frequency stability, Aeolus, Physics::Atmospheric and Oceanic Physics
Abstract: The acquisition of atmospheric wind profiles on a global scale was realized by the launch of the Aeolus satellite, carrying the unique Atmospheric LAser Doppler INstrument (ALADIN), the first Doppler wind lidar in space. One major component of ALADIN is its high-power, ultraviolet (UV) laser transmitter, which is based on an injection-seeded, frequency-tripled Nd:YAG laser and fulfills a set of demanding requirements in terms of pulse energy, pulse length, repetition rate, and spatial and spectral beam properties. In particular, the frequency stability of the laser emission is an essential parameter which determines the performance of the lidar instrument as the Doppler frequency shifts to be detected are on the order of 108 smaller than the frequency of the emitted UV light. This article reports the assessment of the ALADIN laser frequency stability and its influence on the quality of the Aeolus wind data. Excellent frequency stability with pulse-to-pulse variations of about 10 MHz (root mean square) is evident for over more than 2 years of operations in space despite the permanent occurrence of short periods with significantly enhanced frequency noise (> 30 MHz). The latter were found to coincide with specific rotation speeds of the satellite's reaction wheels, suggesting that the root cause are micro-vibrations that deteriorate the laser stability on timescales of a few tens of seconds. Analysis of the Aeolus wind error with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) model winds shows that the temporally degraded frequency stability of the ALADIN laser transmitter has only a minor influence on the wind data quality on a global scale, which is primarily due to the small percentage of wind measurements for which the frequency fluctuations are considerably enhanced. Hence, although the Mie wind bias is increased by 0.3 m s−1 at times when the frequency stability is worse than 20 MHz, the small contribution of 4 % from all Mie wind results renders this effect insignificant (< 0.1 m s−1) when all winds are considered. The impact on the Rayleigh wind bias is negligible even at high frequency noise. Similar results are demonstrated for the apparent speed of the ground returns that are measured with the Mie and Rayleigh channel of the ALADIN receiver. Here, the application of a frequency stability threshold that filters out wind observations with variations larger than 20 or 10 MHz improves the accuracy of the Mie and Rayleigh ground velocities by only 0.05 and 0.10 m s−1, respectively, however at the expense of useful ground data.
Published: 2021

25. Models of plant resistance deployment

Author: Frédéric Fabre, Julien Papaïx, Luke G. Barrett, Benoît Moury, Loup Rimbaud, Christian Lannou, Peter H. Thrall, Unité de Pathologie Végétale (PV), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CSIRO Agriculture and Food (CSIRO), Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biostatistique et Processus Spatiaux (BioSP), BIOlogie et GEstion des Risques en agriculture (BIOGER), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), GRDC grant CSP00192, AFB Ecophyto II-Leviers Territoriaux Project Médée (2020–2022), INRA-CSIRO linkage program, and ANR-18-CE32-0004,ArchiV,Architecture génétique des caractères quantitatifs dans les interactions plante-virus: conséquences pour la gestion des variétés résistantes et/ou tolérantes à l'échelle du paysage.(2018)
Subjects: Crops, Agricultural, 0106 biological sciences, Plant Science, Computational biology, adaptation, Biology, 01 natural sciences, host–microbe interaction, 03 medical and health sciences, evolution, Disease Resistance, Plant Diseases, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Resistance (ecology), 15. Life on land, simulation, immunity, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, Software deployment, durability, Adaptation, 010606 plant biology & botany
Abstract: International audience; Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.
Published: 2021
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26. The quasi-universality of nestedness in the structure of quantitative plant-parasite interactions

Author: Boissot N, Marcel T, Dogimont C, Marie-Laure Pilet-Nayel, Juliette Doumayrou, S. Perrot, Josselin Montarry, Caffier, Chanéac S, Cantet M, Cindy E. Morris, Justafré I, Audergon J, M. Buisson, Paineau M, François Delmotte, Ben Krima S, Frédéric Fabre, Grimault, C. Constant, Omrani M, Sylvain Fournet, Benoît Moury, Losdat D, Baudracco-Arnas S, Ruellan Y, Jaunet T, Bertrand F, Lefebvre, Unité de Pathologie Végétale (PV), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique et Amélioration des Fruits et Légumes (GAFL), Laboratoires ASL, BIOlogie et GEstion des Risques en agriculture (BIOGER), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Bayer seeds SAS, Gautier semences, Institut de Recherche en Horticulture et Semences (IRHS), Université d'Angers (UA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Takii France SAS, Sakata Vegetables Europe, Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, 0971 Gip Geves SNES Angers, Institut National de la Recherche Agronomique (INRA)-Accueil GEVES (Accueil GEVES)-Groupe d'étude et de controle des variétés et des semences (GEVES)-Gip Geves SNES Angers (Gip Geves SNES Angers), HM. CLAUSE [France], Vilmorin, Rijk Zwaan, Partenaires INRAE, PROGRAILIVE project (grant 808 RBRE160116CR0530019), Institut Carnot PLANT2PRO, Comité Interprofessionnel des Vins de Bordeaux 810 (CIVB), the INRAE departments 'Santé des Plantes et Environnement' (project APÔGÉ and PhD thesis of Safa Ben Krima) and 'Génétique et Amélioration des Plantes', the INRAE métaprogramme SMaCH (Sustainable Management of Crop Health), the French Ministry of Agriculture and Food for projects 'Recherche et mise au point de méthodes pour évaluer des résistances variétales durables à des agents pathogènes' (CTPS project C2008-29), 'Nouvelles sources de résistance à Aphis gossypii chez le melon' (CTPS project C06/02) and 'Caractérisation de la virulence de Podosphaera xanthii, agent causal de l’oïdium du melon, et développement d’un système de codification des races' (CTPS project C-2012-10)., ANR-12-ADAP-0009,GANDALF,Génomique et adaptation des traits de vie des champignons impliqués dans les interactions plante-pathogène(2012), ANR-18-CE32-0004,ArchiV,Architecture génétique des caractères quantitatifs dans les interactions plante-virus: conséquences pour la gestion des variétés résistantes et/ou tolérantes à l'échelle du paysage.(2018), ANR-11-BTBR-0002,PeaMUST,Adaptation multistress et régulations biologiques pour l'amélioration du rendement et de la stabilité du pois protéagineux(2011), ANR-17-EURE-0007,SPS-GSR,Ecole Universitaire de Recherche de Sciences des Plantes de Paris-Saclay(2017), ANR-05-PADD-0005,CEDRE,Exploitation durable de résistances aux maladies chez les végétaux(2005), Université d'Angers (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, PROGRAILIVE project (grant RBRE160116CR0530019) funded by the Bretagne region, France, INRAE departments 'Santé des Plantes et Environnement' (project APÔGÉ and PhD thesis of Safa Ben Krima) and 'Génétique et Amélioration des Plantes', INRAE métaprogramme SMaCH (Sustainable Management of Crop Health), French Ministry of Agriculture and Food for projects 'Recherche et mise au point de méthodes pour évaluer des résistances variétales durables à des agents pathogènes' (CTPS project C2008-29), 'Nouvelles sources de résistance à Aphis gossypii chez le melon' (CTPS project C06/02) and 'Caractérisation de la virulence de Podosphaera xanthii, agent causal de l’oïdium du melon, et développement d’un système de codification des races' (CTPS project C-2012-10)., and Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: 0106 biological sciences, bipartite network, Plant resistance, pathogenicity, plant parasite, bipartite network, nestedness, modularity, nestedness, Plant Immunity, Plant resistance, Context (language use), Biology, Quantitative trait locus, 01 natural sciences, 03 medical and health sciences, pathogenicity, plant parasite, modularity, 030304 developmental biology, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 0303 health sciences, Modularity (networks), Resistance (ecology), Host (biology), fungi, food and beverages, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, Evolutionary biology, Trait, Nestedness, 010606 plant biology & botany
Abstract: A previous version of this article has been peer-reviewed and recommended by Peer Community In Evolutionary Biology (https://doi.org/10.24072/pci.evolbiol.100132); International audience; Understanding the relationships between host range and pathogenicity for parasites, and between the efficiency and scope of immunity for hosts are essential to implement efficient disease control strategies. In the case of plant parasites, most studies have focused on describing qualitative interactions and a variety of genetic and evolutionary models has been proposed in this context. Although plant quantitative resistance benefits from advantages in terms of durability, we presently lack models that account for quantitative interactions between plants and their parasites and the evolution of these interactions. Nestedness and modularity are important features to unravel the overall structure of host-parasite interaction matrices. Here, we analysed these two features on 32 matrices of quantitative pathogenicity trait data gathered from 15 plant-parasite pathosystems consisting of either annual or perennial plants along with fungi or oomycetes, bacteria, nematodes, insects and viruses. The performance of several nestedness and modularity algorithms was evaluated through a simulation approach, which helped interpretation of the results. We observed significant modularity in only six of the 32 matrices, with two or three modules detected. For three of these matrices, modules could be related to resistance quantitative trait loci present in the host. In contrast, we found high and significant nestedness in 30 of the 32 matrices. Nestedness was linked to other properties of plant-parasite interactions. First, pathogenicity trait values were explained in majority by a parasite strain effect and a plant accession effect, with no or minor parasite-plant interaction term. Second, correlations between the efficiency and scope of the resistance of plant genotypes, and between the host range breadth and pathogenicity level of parasite strains were overall positive. This latter result questions the efficiency of strategies based on the deployment of several genetically-differentiated cultivars of a given crop species in the case of quantitative plant immunity.
Published: 2021
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27. Stratégies paysagères pour déployer efficacement et durablement la résistance : modèles et prédictions

Author: Loup Rimbaud, Julien Papaïx, Frédéric Fabre, Unité de Pathologie Végétale (PV), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biostatistique et Processus Spatiaux (BioSP), Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Christian Lannou, Dominique Roby, Virginie Ravigné, Mourad Hannachi, Benoit Moury, and DECOGNET, VERONIQUE
Subjects: [SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy, épidémiologié végétale, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, Résistance aux maladies, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, durabilité des résistances, [SDV.GEN.GPL] Life Sciences [q-bio]/Genetics/Plants genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, Paysage agricole, épidémiologie végétale, pathologie végétale, [SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, ComputingMilieux_MISCELLANEOUS, gènes de résistance, modélisation
Abstract: International audience
Published: 2021

28. Des vignes, des invasions et des résistances

Author: François Delmotte, Frédéric Fabre, Anne-Sophie Miclot, Manon Paineau, Christophe Schneider, Laurent Deliere, Fabre, Frédéric, Christian Lannou, Dominique Roby, Virginie Ravigné, Mourad Hannachi, Benoît Moury, Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Santé de la vigne et qualité du vin (SVQV), and Université de Strasbourg (UNISTRA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience; Des vignes, des invasions et des résistances Chapitre tiré de l'ouvrage « L'immunité des plantes » Edition Quae, 2021.
Published: 2021

29. Modéliser les interactions du vivant, en lien avec les milieux et les contextes socio-économiques

Author: Chantal Gascuel, Francoise Lescourret, Herve Monod, Lionel Roques, David Bohan, Evelyne Costes, Pierre Courtois, Frédéric Fabre, Philippe Faverdin, Alain Franc, Thierry Hoch, Florence Phocas, Jean-Philippe Steyer, Marc Tchamitchian, Sol Agro et hydrosystème Spatialisation (SAS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de recherche Plantes et Systèmes de Culture Horticoles (PSH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département mathématiques, informatique, sciences de la donnée et technologies du numérique (MathNum), Biostatistique et Processus Spatiaux (BioSP), Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Amélioration Génétique et Adaptation des Plantes méditerranéennes et Tropicales Corse - Antenne Corse (AGAP-Corse), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'Economie de l'Environnement - Montpellier (CEE-M), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), from patterns to models in computational biodiversity and biotechnology (PLEIADE), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Unité de recherche d'Écodéveloppement (ECODEVELOPPEMENT), Caquet, Thierry Gascuel, Chantal Tixier-Boichard, Michèle Coordination éditoriale, EL Mjiyad, Noureddine, Caquet, Thierry Gascuel, Chantal Tixier-Boichard, Michèle Coordination éditoriale, AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'Economie de l'Environnement - Montpellier - UMR 5211 (CEE-M), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract: International audience; L’agroécologie a été choisie par l’Inra comme l’un des chantiers de prospective interdisciplinaire destiné à identifier les fronts de recherche en réponse à de grands défis sociétaux. Quatre-vingt chercheurs ont dressé un bilan, et proposé des pistes de recherche pour l’agroécologie, et cet ouvrage en synthétise les principales conclusions. L’agroécologie, en tant que discipline scientifique, remettant l’écologie au centre de la conception des systèmes agricoles, est maintenant bien présente. Diversifier le vivant dans des agroécosystèmes est une visée à large spectre, pour les rendre plus robustes, plus résilients. Les recherches en génétique et en écologie du paysage sont mobilisées pour que l’agroécologie utilise des leviers de la parcelle au paysage. La modélisation des systèmes agroécologiques se développe pour mieux comprendre les interactions biotiques et abiotiques multiples, les prédire, et commencer à piloter certains systèmes. La diversification du vivant dans la production agricole (espèces, variétés, successions culturales, etc.) conduit à des produits plus variés. Les conséquences seront importantes sur les filières, ou plus exactement sur les systèmes agri-alimentaires, allant du mode de production aux produits consommés. Ces changements s’inscrivent sur le long terme. La transition agroécologique, adaptative, se coconstruisant avec les acteurs, est en soi un sujet de recherche, et pourra s’appuyer sur des dispositifs expérimentaux, des exploitations agricoles, des territoires d’innovation.
Published: 2020

30. Impact of genetic drift, selection and accumulation level on virus adaptation to its host plants

Author: Ludovic Mailleret, Elsa Rousseau, Frédéric Fabre, Lucie Tamisier, Olivier Bouchez, Gregory Girardot, Marion Szadkowski, Catherine Zanchetta, Benoît Moury, Frédéric Grognard, Alain Palloix, and Vincent Simon
Subjects: 0106 biological sciences, 0301 basic medicine, 2. Zero hunger, Genetics, education.field_of_study, biology, Population, food and beverages, Soil Science, Plant Science, biology.organism_classification, 01 natural sciences, Virus, 03 medical and health sciences, 030104 developmental biology, Genetic drift, Potato virus Y, Effective population size, Plant virus, Plant breeding, Adaptation, education, Agronomy and Crop Science, Molecular Biology, 010606 plant biology & botany
Abstract: The efficiency of plant major resistance genes is limited by the emergence and spread of resistance-breaking mutants. Modulation of the evolutionary forces acting on pathogen populations constitutes a promising way to increase the durability of these genes. We studied the effect of four plant traits affecting these evolutionary forces on the rate of resistance breakdown (RB) by a virus. Two of these traits correspond to virus effective population sizes (Ne ) at either plant inoculation or during infection. The third trait corresponds to differential selection exerted by the plant on the virus population. Finally, the fourth trait corresponds to within-plant virus accumulation (VA). These traits were measured experimentally on Potato virus Y (PVY) inoculated to a set of 84 pepper doubled-haploid lines, all carrying the same pvr23 resistance gene, but having contrasting genetic backgrounds. The lines showed extensive variation for the rate of pvr23 RB by PVY and for the four other traits of interest. A generalized linear model showed that three of these four traits, with the exception of Ne at inoculation, and several pairwise interactions between them had significant effects on RB. RB increased with increasing values of Ne during plant infection or VA. The effect of differential selection was more complex because of a strong interaction with VA. When VA was high, RB increased as the differential selection increased. An opposite relationship between RB and differential selection was observed when VA was low. This study provides a framework to select plants with appropriate virus evolution-related traits to avoid or delay RB.
Published: 2018
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31. Submicronic LiNi1/3Mn1/3Co1/3O2 synthesized by co-precipitation for lithium ion batteries - Tailoring a classic process for enhanced energy and power density

Author: David Peralta, Sébastien Patoux, Elise Gutel, Didier Bloch, Benjamin Amestoy, Jérémie Salomon, Adrien Boulineau, Jean-François Colin, Carole Bourbon, and Frédéric Fabre
Subjects: Battery (electricity), Materials science, Renewable Energy, Sustainability and the Environment, Coprecipitation, Energy Engineering and Power Technology, chemistry.chemical_element, Nanoparticle, Nanotechnology, 02 engineering and technology, Electrolyte, 010402 general chemistry, 021001 nanoscience & nanotechnology, Electrochemistry, 01 natural sciences, Cathode, 0104 chemical sciences, law.invention, chemistry, law, Lithium, Electrical and Electronic Engineering, Physical and Theoretical Chemistry, 0210 nano-technology, Power density
Abstract: Some scientific studies report that the use of nanosized cathode materials can improve the electrochemical performances of a battery. In fact, these materials can open new and important perspectives for cathode materials such as their use for power applications or for technologies for which an optimized interface with the electrolyte is required (e.g all solid state battery or polymer battery). However, the high scale production and the processing of these powders to obtain dense electrodes are difficult. In this study, submicronic particles of LiNi1/3Mn1/3Co1/3O2 are synthesized using an easy and scalable coprecipitation synthesis protocol. Isolated particles of 200 nm are obtained and are fully characterized. The non-agglomerated morphology of this material improves the accessibility of the lithium insertion planes, and consequently, the high C-rate behavior is clearly improved as compared to classic agglomerate materials. The difficult processing of submicronic particles is overcome thanks to an environmentally-friendly water-based formulation. Proof-of-concept Li-ion cells have been realized. Although submicronic particles are used, the cell is manufactured with a cathode loading of 18.8 mg cm−2 which is relevant for commercial application.
Published: 2018
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32. The quasi-universality of nestedness in the structure of quantitative plant-parasite interactions

Author: Benoît, Moury, primary, Jean-Marc, Audergon, additional, Sylvie, Baudracco-Arnas, additional, Safa, Ben Krima, additional, François, Bertrand, additional, Nathalie, Boissot, additional, Mireille, Buisson, additional, Valérie, Caffier, additional, Mélissa, Cantet, additional, Sylvia, Chanéac, additional, Carole, Constant, additional, François, Delmotte, additional, Catherine, Dogimont, additional, Juliette, Doumayrou, additional, Frédéric, Fabre, additional, Sylvain, Fournet, additional, Valérie, Grimault, additional, Thierry, Jaunet, additional, Isabelle, Justafré, additional, Véronique, Lefebvre, additional, Denis, Losdat, additional, Marcel Thierry, C., additional, Josselin, Montarry, additional, Morris Cindy, E., additional, Mariem, Omrani, additional, Manon, Paineau, additional, Sophie, Perrot, additional, Marie-Laure, Pilet-Nayel, additional, and Youna, Ruellan, additional
Published: 2021
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33. Quantitative trait loci in pepper control the effective population size of two RNA viruses at inoculation

Author: Elsa Rousseau, Alain Palloix, Frédéric Grognard, Ludovic Mailleret, Sebastien Barraillé, Marion Szadkowski, Benoît Moury, Lucie Tamisier, Frédéric Fabre, Ghislaine Nemouchi, Unité de Pathologie Végétale (PV), Institut National de la Recherche Agronomique (INRA), Génétique et Amélioration des Fruits et Légumes (GAFL), Institut Sophia Agrobiotech (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Biological control of artificial ecosystems (BIOCORE), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), BAP (Biologie et Amélioration des Plantes) department, SMaCH (Sustainable Management of Crop Health) metaprogramme of INRA, Région Provence-Alpes-Côte d’Azur (PACA), Station de Pathologie Végétale (AVI-PATHO), Unité de recherche Génétique et amélioration des fruits et légumes (GALF), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Unité de pathologie végétale (UR 407) INRA Avignon, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), Institut des Sciences de la Vigne et du Vin (ISVV)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Capsicum annuum, 0106 biological sciences, 0301 basic medicine, [SDV]Life Sciences [q-bio], Potyvirus, Population, Quantitative trait locus, Cucumovirus, 01 natural sciences, Virus, Cucumber mosaic virus, 03 medical and health sciences, Virology, virus infection, bottlenecks, Potato virus Y, education, Gene, ComputingMilieux_MISCELLANEOUS, Plant Diseases, Genetics, education.field_of_study, biology, fungi, food and beverages, biology.organism_classification, Plant Leaves, 030104 developmental biology, quantitative trait loci, Capsicum, effective population size, 010606 plant biology & botany
Abstract: We thank the staff of the INRAE Experimental facilities of the Plant Pathology research unit (IEPV, https://doi.org/10.15454/8DGF-QF70) for their involvement in field experiments; International audience; Infection of plants by viruses is a complex process involving several steps: inoculation into plant cells, replication in inoculated cells and plant colonization. The success of the different steps depends, in part, on the viral effective population size (Ne), defined as the number of individuals passing their genes to the next generation. During infection, the virus population will undergo bottlenecks, leading to drastic reductions in Ne and, potentially, to the loss of the fittest variants. Therefore, it is crucial to better understand how plants affect Ne. We aimed to (i) identify the plant genetic factors controlling Ne during inoculation, (ii) understand the mechanisms used by the plant to control Ne and (iii) compare these genetic factors with the genes controlling plant resistance to viruses. Ne was measured in a doubled-haploid population of Capsicum annuum. Plants were inoculated with either a Potato virus Y (PVY) construct expressing the green fluorescent protein or a necrotic variant of Cucumber mosaic virus (CMV). Newas assessed by counting the number of primary infection foci on cotyledons for PVY or the number of necrotic local lesions on leaves for CMV. The number of foci and lesions was correlated (r=0.57) and showed a high heritability (h2=0.93 for PVY and h2=0.98 for CMV). The Ne of the two viruses was controlled by both common quantitative trait loci (QTLs) and virus-specific QTLs, indicating the contribution of general and specific mechanisms. The PVY-specific QTL colocalizes with a QTL that reduces PVY accumulation and the capacity to break down a major-effect resistance gene.
Published: 2017
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34. Chapitre 10. Aménagement de paysages pour la santé des plantes basé sur des modèles

Author: Julien Papaïx, Hugues Boussard, Corentin Barbu, and Frédéric Fabre
Subjects: Geography
Published: 2019
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35. Chapitre 5. Analyses statistiques des relations entre mosaïque paysagère et processus écologiques

Author: Corentin Barbu, Julien Papaïx, Frédéric Fabre, Aude Ernoult, Claire Lavigne, Audrey Alignier, and Sylvain Poggi
Subjects: Geography
Published: 2019
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36. Virus epidemics, plant-controlled population bottlenecks and the durability of plant resistance

Author: Frédéric Fabre, Frédéric Grognard, Elsa Rousseau, Benoît Moury, Mélanie Bonneault, Ludovic Mailleret, Station de Pathologie Végétale (AVI-PATHO), Institut National de la Recherche Agronomique (INRA), Biological control of artificial ecosystems (BIOCORE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Santé et agroécologie du vignoble (SAVE), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Université Côte d'Azur (UCA), ANR-13-BSV7-0011,FunFit,Une approche basée sur les traits d'histoire de vie des champignons phytopathogènes pour faire le lien entre fitness individuelle et stratégies écologiques.(2013), Unité de Pathologie Végétale (PV), Institut Sophia Agrobiotech (ISA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Santé et agroécologie du vignoble (UMR SAVE), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), French Agence Nationale de la Recherche (ANR) under grant ANR-13-BSV7-0011 (project FunFit), SMaCH (Sustainable Management of Crop Health) metaprogramme of INRA., Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, quantitative resistance, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], Biology, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Virus, Bottleneck, 03 medical and health sciences, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Cultivar, Plant traits, population bottleneck, Epidemics, yield increase, Disease Resistance, Plant Diseases, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Models, Statistical, business.industry, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], fungi, Outbreak, food and beverages, Articles, Plants, 15. Life on land, stochastic epidemic model, qualitative resistance, Biotechnology, Plant Breeding, Population bottleneck, Infectious disease (medical specialty), Viruses, General Agricultural and Biological Sciences, Epidemic model, business, resistance durability, Virus Physiological Phenomena, 010606 plant biology & botany
Abstract: Plant qualitative resistances to viruses are natural exhaustible resources that can be impaired by the emergence of resistance-breaking (RB) virus variants. Mathematical modelling can help determine optimal strategies for resistance durability by a rational deployment of resistance in agroecosystems. Here, we propose an innovative approach, built up from our previous empirical studies, based on plant cultivars combining qualitative resistance with quantitative resistance narrowing population bottlenecks exerted on viruses during host-to-host transmission and/or within-host infection. Narrow bottlenecks are expected to slow down virus adaptation to plant qualitative resistance. To study the effect of bottleneck size on yield, we developed a stochastic epidemic model with mixtures of susceptible and resistant plants, relying on continuous-time Markov chain processes. Overall, narrow bottlenecks are beneficial when the fitness cost of RB virus variants in susceptible plants is intermediate. In such cases, they could provide up to 95 additional percentage points of yield compared with deploying a qualitative resistance alone. As we have shown in previous works that virus population bottlenecks are at least partly heritable plant traits, our results suggest that breeding and deploying plant varieties exposing virus populations to narrowed bottlenecks will increase yield and delay the emergence of RB variants. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
Published: 2019
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37. Analyses statistiques des relations entre mosaïque paysagère et processus écologiques

Author: Corentin Barbu, Julien Papaix, Frédéric Fabre, Stéphanie Aviron, Claire Lavigne, Audrey Alignier, Aude Ernoult, Sylvain Poggi, Agronomie, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Biostatistique et Processus Spatiaux (BioSP), Institut National de la Recherche Agronomique (INRA), Santé et agroécologie du vignoble (UMR SAVE), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Biodiversité agroécologie et aménagement du paysage (UMR BAGAP), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST-Ecole supérieure d'Agricultures d'Angers (ESA), Unité de recherche Plantes et Systèmes de Culture Horticoles (PSH), Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Sandrine Petit, Claire Lavigne, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Ecole supérieure d'Agricultures d'Angers (ESA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), and Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST
Subjects: [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [INFO]Computer Science [cs], [MATH]Mathematics [math], [SHS]Humanities and Social Sciences
Abstract: Partie 1. Structuration et fonctionnement écologique des paysages agricoles Chapitre 5; International audience
Published: 2019

38. An epi-evolutionary model to predict spore-producing pathogens adaptation to quantitative resistance in heterogeneous environments

Author: Ramsès Djidjou-Demasse, Frédéric Fabre, Quentin Richard, Sébastien Lion, Jean-Baptiste Burie, and Arnaud Ducrot
Subjects: 0106 biological sciences, 0303 health sciences, education.field_of_study, Resistance (ecology), Host (biology), Strain (biology), Population, Diversification (marketing strategy), Biology, 01 natural sciences, 03 medical and health sciences, Evolutionary biology, Trait, Adaptation, education, Basic reproduction number, 030304 developmental biology, 010606 plant biology & botany
Abstract: We model the evolutionary epidemiology of spore-producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection-age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits describing its infection efficiency and a time-varying sporulation curve taking into account lesion ageing. We first derive a general expression of the basic reproduction number ℛ0for fungal pathogens in heterogeneous environments. We show that evolutionary attractors of the model coincide with local maxima of ℛ0only if the infection efficiency is the same on all host types. We then study how three basic resistance characteristics (pathogenicity trait targeted, resistance effectiveness, and adaptation cost) in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar) (i) lead to pathogen diversification at equilibrium and (ii) shape the transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance impacting only the sporulation curve will always lead to a monomorphic population, while dimorphism (i.e. pathogen diversification) can occur with resistance altering infection efficiency, notably with high adaptation cost and proportion of R cultivar. Accordingly, the choice of quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the emergence time of the evolutionary attractor best adapted to the R cultivar tends to be shorter when the resistance impacts infection efficiency than when it impacts sporulation. In contrast, from an epidemiological perspective, the epidemiological control is always higher when the resistance impacts infection efficiency. This highlights the difficulty of defining deployment strategies of quantitative resistance maximising at the same time epidemiological and evolutionary outcomes.
Published: 2018
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39. Small Bottleneck Size in a Highly Multipartite Virus during a Complete Infection Cycle

Author: Frédéric Fabre, Yannis Michalakis, Gaël Thébaud, Mircea T. Sofonea, Romain Gallet, Anne Sicard, Stéphane Blanc, Biologie et Génétique des Interactions Plante-Parasite (UMR BGPI), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Santé Végétale (SV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Evolution Théorique et Expérimentale (MIVEGEC-ETE), Perturbations, Evolution, Virulence (PEV), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), French national research funding agency (ANR-Nano) : ANR-14-CE02-0014-01, SPE department of INRA, IRD research institute, CNRS research institute, and Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Paul-Valéry - Montpellier 3 (UM3)
Subjects: 0301 basic medicine, bottleneck, [SDV]Life Sciences [q-bio], Immunology, Biology, Microbiology, Genome, Bottleneck, law.invention, 03 medical and health sciences, Genetic drift, Effective population size, law, Virology, aphid transmission, Animals, Plant Diseases, Aphid, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Host (biology), Nanovirus, food and beverages, FBNSV, biology.organism_classification, Insect Vectors, Vicia faba, Multipartite, 030104 developmental biology, Transmission (mechanics), Genetic Diversity and Evolution, Evolutionary biology, Aphids, Insect Science, DNA, Viral, multipartite virus, effective population size
Abstract: Multipartite viruses package their genomic segments independently and thus incur the risk of being unable to transmit their entire genome during host-to-host transmission if they undergo severe bottlenecks. In this paper, we estimated the bottleneck size during one infection cycle of Faba bean necrotic stunt virus (FBNSV), an octopartite nanovirus whose segments have been previously shown to converge to particular and unequal relative frequencies within host plants and aphid vectors. Two methods were used to derive this estimate, one based on the probability of transmission of the virus and the other based on the temporal evolution of the relative frequency of markers for two genomic segments, one frequent and one rare (segment N and S, respectively), both in plants and vectors. Our results show that FBNSV undergoes severe bottlenecks during aphid transmission. Further, even though the bottlenecks are always narrow under our experimental conditions, they slightly widen with the number of transmitting aphids. In particular, when several aphids are used for transmission, the bottleneck size of the segments is also affected by within-plant processes and, importantly, significantly differs across segments. These results indicate that genetic drift not only must be an important process affecting the evolution of these viruses but also that these effects vary across genomic segments and, thus, across viral genes, a rather unique and intriguing situation. We further discuss the potential consequences of our findings for the transmission of multipartite viruses. IMPORTANCE Multipartite viruses package their genomic segments in independent capsids. The most obvious cost of such genomic structure is the risk of losing at least one segment during host-to-host transmission. A theoretical study has shown that for nanoviruses, composed of 6 to 8 segments, hundreds of copies of each segment need to be transmitted to ensure that at least one copy of each segment was present in the host. These estimations seem to be very high compared to the size of the bottlenecks measured with other viruses. Here, we estimated the bottleneck size during one infection cycle of FBNSV, an octopartite nanovirus. We show that these bottlenecks are always narrow (few viral particles) and slightly widen with the number of transmitting aphids. These results contrast with theoretical predictions and illustrate the fact that a new conceptual framework is probably needed to understand the transmission of highly multipartite viruses.
Published: 2018
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40. Peut-on se passer du cuivre en protection des cultures biologiques ? Rapport d'expertise scientifique collective

Author: Didier Andrivon, Marc Bardin, Cédric Bertrand, Laurent Brun, Xavier Daire, Véronique DECOGNET, Frédéric Fabre, Christian Gary, Anne-Sophie Grenier, Josselin Montarry, Philippe Nicot, Philippe Reignault, Lucius Tamm, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de Pathologie Végétale (PV), Institut National de la Recherche Agronomique (INRA), ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Unité Expérimentale Recherches Intégrées - Gotheron (UERI), Agroécologie [Dijon], Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Santé et agroécologie du vignoble (UMR SAVE), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Université du Littoral Côte d'Opale (ULCO), Research Institute of Organic Agriculture - Forschungsinstitut für biologischen Landbau (FiBL), Commanditaire : Institut Technique de l'Agriculture Biologique (France), Partenaires : Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT), and Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)
Subjects: résistance variétale, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Phytopathology and phytopharmacy, pratique agronomique, stimulateur de défense des plantes, expertise collective, lutte biologique, champignon phytopathogène, biocide, Phytopathologie et phytopharmacie, Agricultural sciences, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, produit phytosanitaire, agriculture biologique, cuivre, variété résistante, méthode de lutte, impact environnemental, mildiou de la vigne, phytophthora infestans, pathologie végétale, tavelure du pommier, agent de lutte biologique, Sciences agricoles
Abstract: Rapport de l’Expertise scientifique collective réalisée par l’INRA à la demande du métaprogramme INRA "Gestion durable de la santé des cultures" et de l'Institut technique de l'agriculture biologique
Published: 2018

41. Epidemiological and evolutionary management of plant resistance: optimizing the deployment of cultivar mixtures in time and space in agricultural landscapes

Author: Ludovic Mailleret, Benoît Moury, Frédéric Fabre, Elsa Rousseau, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Institut Sophia Agrobiotech (ISA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Biological control of artificial ecosystems (BIOCORE), Institut National de la Recherche Agronomique (INRA)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Unité de Pathologie Végétale (PV), Institut National de la Recherche Agronomique (INRA), Agence Nationale de la Recherche ('VirAphid' (ANR-10-STRA-0001)), INRA (project 'TakeControl' of the metaprogramme Smach), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Station de Pathologie Végétale (AVI-PATHO), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA), and Fabre, Frédéric
Subjects: agroecosystem, [SDV]Life Sciences [q-bio], prévention des maladies, evolutionary epidemiology, [SPI]Engineering Sciences [physics], durabilité des résistances, landscape epidemiology, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Cultivar, épidémiologie végétale, [MATH]Mathematics [math], pathologie végétale, 2. Zero hunger, résistance variétale, education.field_of_study, mélange de variétés, Ecology, mosaic strategy, disease prevention, rotation des cultures, gène de résistance, agroécosystème, qualitative resistance, Agricultural sciences, heterogeneity of selection, General Agricultural and Biological Sciences, resistance durability, Agricultural landscapes, modèle spatialisé, Landscape epidemiology, Population, Context (language use), Biology, resistance gene, Genetics, education, Ecology, Evolution, Behavior and Systematics, Resistance (ecology), functional connectivity, Original Articles, 15. Life on land, maladie des plantes, Software deployment, rotation strategy, gestion du paysage, évolution génétique des populations, Sciences agricoles, Landscape connectivity, rotation of crops
Abstract: International audience; The management of genes conferring resistance to plant–pathogens should make it possible to control epidemics (epidemiological perspective) and preserve resistance durability (evolutionary perspective). Resistant and susceptible cultivars must be strategically associated according to the principles of cultivar mixture (within a season) and rotation (between seasons). We explored these questions by modeling the evolutionary and epidemiological processes shaping the dynamics of a pathogen population in a landscape composed of a seasonal cultivated compartment and a reservoir compartment hosting pathogen year-round. Optimal deployment strategies depended mostly on the molecular basis of plant–pathogen interactions and on the agro-ecological context before resistance deployment, particularly epidemic intensity and landscape connectivity. Mixtures were much more efficient in landscapes in which between-field infections and infections originating from the reservoir were more prevalent than within-field infections. Resistance genes requiring two mutations of the pathogen avirulence gene to be broken down, rather than one, were particularly useful when infections from the reservoir predominated. Combining mixture and rotation principles were better than the use of the same mixture each season as (i) they controlled epidemics more effectively in situations in which within-field infections or infections from the reservoir were frequent and (ii) they fulfilled the epidemiological and evolutionary perspectives.
Published: 2015
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42. Role of the composition of lithium-rich layered oxide materials on the voltage decay

Author: Pierre Feydi, Loïc Simonin, Frédéric Fabre, Mohamed Chakir, Jean-François Colin, Justin Bouvet, David Peralta, Sébastien Patoux, Marlène Chapuis, and Adrien Boulineau
Subjects: Materials science, Renewable Energy, Sustainability and the Environment, Coprecipitation, Analytical chemistry, Oxide, Energy Engineering and Power Technology, chemistry.chemical_element, High voltage, Electrochemistry, Cathode, law.invention, chemistry.chemical_compound, Partial charge, chemistry, Chemical engineering, law, Lithium, Electrical and Electronic Engineering, Physical and Theoretical Chemistry, Voltage
Abstract: Lithium-rich layered oxide is known to be one of the most promising positive electrode materials for high energy Li-ion batteries. Some publications report specific capacities higher than 250 mAh/g but the fade of the average potential during electrochemical cycling is an important drawback for commercial use of this material. The objective of this work is to study the origin of this potential decay during cycling of lithium-rich compounds. For this purpose, the electrochemical behavior of xLi 2 MnO 3 ·(1−x)LiNi 0.5 Mn 0.5 O 2 (with x = 1, 0.7, 0.5, 0.27) materials synthesized using coprecipitation route have been compared. For this study, complete or partial charge and discharge cycles have been performed in the 2.5 V–4.8 V voltage range. The results can be briefly summarized as follows: the potential decay is mainly provoked by several phenomena occurring at low potential, this growth being induced by the charging of lithium-rich at high voltage (>4.15 V). Whatever the compositions, same phenomena are involved, only the kinetics is modified.
Published: 2015
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43. The Number of Target Molecules of the Amplification Step Limits Accuracy and Sensitivity in Ultradeep-Sequencing Viral Population Studies

Author: Stéphane Blanc, Frédéric Fabre, Yannis Michalakis, Romain Gallet, Biologie et Génétique des Interactions Plante-Parasite (UMR BGPI), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Evolution Théorique et Expérimentale (MIVEGEC-ETE), Perturbations, Evolution, Virulence (PEV), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), French National Research Funding Agency (ANR) : ANR-14-CE02-0014-01, CNRS, IRD, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut de Recherche pour le Développement (IRD [France-Ouest]), Université de Montpellier (UM), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), and Institut des Sciences de la Vigne et du Vin (ISVV)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut National de la Recherche Agronomique (INRA)
Subjects: 0301 basic medicine, Virologie, number of target molecules, Immunology, Population, Computational biology, Microbiology, Genome, DNA sequencing, faba bean, 03 medical and health sciences, FBNSV, Medicago truncatula, next-generation sequencing, rolling-circle amplification, sequencing accuracy, sequencing sensitivity, Virology, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, education, pathologie végétale, education.field_of_study, Genetic diversity, Vegetal Biology, biology, Microbiology and Parasitology, food and beverages, biology.organism_classification, Microbiologie et Parasitologie, Multipartite, 030104 developmental biology, Population bottleneck, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Genetic Diversity and Evolution, Rolling circle replication, Insect Science, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Biologie végétale
Abstract: The invention of next-generation sequencing (NGS) techniques marked the coming of a new era in the detection of the genetic diversity of intrahost viral populations. A good understanding of the genetic structure of these populations requires, first, the ability to identify the different isolates or variants and, second, the ability to accurately quantify them. However, the initial amplification step of NGS studies can impose potential quantitative biases, modifying the variant relative frequencies. In particular, the number of target molecules (NTM) used during the amplification step is vastly overlooked although of primary importance, as it sets the limit of the accuracy and sensitivity of the sequencing procedure. In the present article, we investigated quantitative biases in an NGS study of populations of a multipartite single-stranded DNA (ssDNA) virus at different steps of the procedure. We studied 20 independent populations of the ssDNA virus faba bean necrotic stunt virus (FBNSV) in two host plants, Vicia faba and Medicago truncatula . FBNSV is a multipartite virus composed of eight genomic segments, whose specific and host-dependent relative frequencies are defined as the “genome formula.” Our results show a significant distortion of the FBNSV genome formula after the amplification and sequencing steps. We also quantified the genetic bottleneck occurring at the amplification step by documenting the NTM of two genomic segments of FBNSV. We argue that the NTM must be documented and carefully considered when determining the sensitivity and accuracy of data from NGS studies. IMPORTANCE The advent of next-generation sequencing (NGS) techniques now enables study of the genetic diversity of viral populations. A good understanding of the genetic structure of these populations first requires the ability to identify the different isolates or variants and second requires the ability to accurately quantify them. Prior to sequencing, viral genomes need to be amplified, a step that potentially imposes quantitative biases and modifies the viral population structure. In particular, the number of target molecules (NTM) used during the amplification step is of primary importance, as it sets the limit of the accuracy and sensitivity of the sequencing procedure. In this work, we used 20 replicated populations of the multipartite faba bean necrotic stunt virus (FBNSV) to estimate the various limitations of ultradeep-sequencing studies performed on intrahost viral populations. We report quantitative biases during rolling-circle amplification and the NTM of two genomic segments of FBNSV.
Published: 2017
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44. Molecular and biological characterization of two potyviruses infecting lettuce in southeastern France

Author: Brigitte Maisonneuve, Pauline Millot, Frédéric Fabre, Alexandra Schoeny, Karine Berthier, Karine Nozeran, Vincent Simon, Cécile Desbiez, Benoît Moury, Mark Tepfer, Hervé Lecoq, Catherine Wipf-Scheibel, Gregory Girardot, Charlotte Chandeysson, Isabelle Bornard, Eric Verdin, Patrick Gognalons, Hervé Lot, Unité de Pathologie Végétale (PV), Institut National de la Recherche Agronomique (INRA), Génétique et Amélioration des Fruits et Légumes (GAFL), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Institut Jean-Pierre Bourgin (IJPB), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, SPE department of INRA, Station de Pathologie Végétale (AVI-PATHO), Unité de recherche Génétique et amélioration des fruits et légumes (GALF), and Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE)
Subjects: 0301 basic medicine, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Lactuca spp, sud est france, host range, Lactuca, Plant Science, Horticulture, Asteraceae, culture légumière de plein champ, caractérisation moléculaire, resistance, 03 medical and health sciences, Cichorium endivia, caractérisation biologique, laitue, phytopathogenic virus, potyvirus, Botany, Genetics, aphid transmission, Turnip mosaic virus, Lactuca perennis, transmission par vecteur, pathologie végétale, virus phytopathogène, Lactuca virosa, biology, fungi, Potyvirus, Lactuca serriola, food and beverages, biology.organism_classification, 030112 virology, Lactuca saligna, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, lettuce, résistance génétique, Agronomy and Crop Science
Abstract: International audience; Several potyviruses affect lettuce (Lactuca sativa) and chicory (Cichorium spp.) crops worldwide and are important constraints for production because of the direct losses that they induce and/or because of their seed transmission. Here, the molecular and biological properties are described of two potyviruses that were recently isolated from lettuce plants showing mosaic or strong necrotic symptoms in an experimental field in southeastern France. The first potyvirus belongs to the species Endive necrotic mosaic virus and is present in a large number of wild plant species, especially Tragopogon pratensis. It is unable to infect lettuce cultivars with a resistance to Turnip mosaic virus that is present in many European cultivars and probably conferred by the Tu gene. The second potyvirus belongs to the tentative species lettuce Italian necrotic virus and was not observed in wild plants. It infected all tested lettuce cultivars. Wild accessions of Lactuca serriola, Lactuca saligna, Lactuca virosa and Lactuca perennis were identified as resistant to one or the other potyvirus and could be used for resistance breeding in lettuce. No resistance against these two potyviruses was observed in the tested Cichorium endivia cultivars. In contrast, all tested Cichorium intybus cultivars or accessions were resistant.
Published: 2017
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45. Steady state concentration for a phenotypic structured problem modeling the evolutionary epidemiology of spore producing pathogens

Author: Ramsès Djidjou-Demasse, Frédéric Fabre, Arnaud Ducrot, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), European Project: 609398,EC:FP7:PEOPLE,FP7-PEOPLE-2013-COFUND,AGREENSKILLSPLUS(2014), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), and Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0301 basic medicine, analyse phénotypique, Population, Context (language use), evolutionary epidemiology, Space (mathematics), 03 medical and health sciences, Attractor, population dynamics, Quantitative Biology::Populations and Evolution, Statistical physics, Uniqueness, education, Mathematics, concentration phenomenon, education.field_of_study, Applied Mathematics, [SDE.ES]Environmental Sciences/Environmental and Society, dynamique des populations, 030104 developmental biology, spore producing pathogens, Modeling and Simulation, Kernel (statistics), Mutation (genetic algorithm), épidémiologie, Steady state (chemistry), [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract: In this paper, we construct a model to describe the evolutionary epidemiology of spore producing asexual plant pathogens in a homogeneous host population. By considering the evolution in the space of the pathogen phenotypic values, we derive an integro-differential equation with nonlocal mutation terms. Our first main result is concerned with the existence and uniqueness of the endemic steady state of the model. Next assuming that the mutation kernel depends on a small parameter [Formula: see text] (the variance of the dispersion into the space of the pathogen phenotypic values), we investigate the concentration properties of the endemic steady state in the space of phenotypic values. In the context of this work, several Evolutionary Attractors (EAs) (as defined in classical adaptive dynamics) may exist. However, in rather general situations, our results show that only one EA persists when the populations are at equilibrium and when [Formula: see text] is small enough. Our analysis strongly relies on a refined description of the spectral properties of some integral operator with a highly concentrated kernel. We conclude the paper by presenting some numerical simulations of the model to illustrate this concentration phenomenon.
Published: 2017
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46. Vectors as motors (of virus evolution)

Author: Benoît Moury, Frédéric Fabre, Fabre, Frédéric, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Station de Pathologie Végétale (AVI-PATHO), Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), and Unité de Pathologie Végétale (PV)
Subjects: 0301 basic medicine, moustique, Biodiversité et Ecologie, Virologie, selection, virus, Biology, Dengue virus, medicine.disease_cause, Virus, Biodiversity and Ecology, 03 medical and health sciences, Genetic drift, Virology, Genotype, evolution, medicine, évolution des populations, Vector (molecular biology), Selection (genetic algorithm), vecteur de virus, Genetics, Genetic diversity, 030102 biochemistry & molecular biology, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], dengue, humanities, 3. Good health, 030104 developmental biology, Viral evolution, genetic drift, revue d'article, parameter estimation, effective population size
Abstract: International audience; A recommendation of: Lequime S, Fontaine A, Gouilh MA, Moltini-Conclois I and Lambrechts L. 2016. Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes. PloS Genetics 12: e1006111 doi: 10.1371/journal.pgen.1006111
Published: 2017
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47. Mosaics often outperform pyramids: insights from a model comparing strategies for the deployment of plant resistance genes against viruses in agricultural landscapes

Author: Frédéric Fabre, Ramsès Djidjou-Demasse, Benoît Moury, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Unité de Pathologie Végétale (PV), Institut National de la Recherche Agronomique (INRA), CIVB project ‘Recherche, expérimentation, études et outils’, European Project: 609398, Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), and Station de Pathologie Végétale (AVI-PATHO)
Subjects: 0301 basic medicine, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Physiology, échelle du paysage, Plant Science, Plant Viruses, landscape epidemiology, pyramids of plant resistance, regional deployment strategy, stratégie de lutte, épidémiologie végétale, pathologie végétale, Disease Resistance, 2. Zero hunger, Ecology, durabilité des méthodes de lutte, food and beverages, Agriculture, gène de résistance, agricultural landscape, Host-Pathogen Interactions, Regression Analysis, Seasons, résistance génétique, Agricultural landscapes, Landscape epidemiology, Plant disease resistance, Biology, Genes, Plant, modelling, 03 medical and health sciences, phytopathogenic virus, resistance gene, Plant virus, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Computer Simulation, Gene, Plant Diseases, modélisation, paysage agricole, virus phytopathogène, Resistance (ecology), Models, Theoretical, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, major resistance gene, 030104 developmental biology, Evolutionary biology, Software deployment, durable disease resistance, évolution génétique des populations, mosaic of plant resistance, Landscape connectivity
Abstract: The breakdown of plant virus resistance genes is a major issue in agriculture. We investigated whether a set of resistance genes would last longer when stacked into a single plant cultivar (pyramiding) or when deployed individually in regional mosaics (mosaic strategy). We modeled the genetic and epidemiological processes shaping the demogenetic dynamics of viruses under a multilocus gene-for-gene system, from the plant to landscape scales. The landscape consisted of many fields, was subject to seasonality, and of a reservoir hosting viruses year-round. Strategy performance depended principally on the fitness costs of adaptive mutations, epidemic intensity before resistance deployment and landscape connectivity. Mosaics were at least as good as pyramiding strategies in most production situations tested. Pyramiding strategies performed better only with slowly changing virus reservoir dynamics. Mosaics are more versatile than pyramiding strategies, and we found that deploying a mosaic of three to five resistance genes generally provided effective disease control, unless the epidemics were driven mostly by within-field infections. We considered the epidemiological and evolutionary mechanisms underlying the greater versatility of mosaics in our case study, with a view to providing breeders and growers with guidance as to the most appropriate deployment strategy.
Published: 2017
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48. Decision Support Systems

Author: Frédéric Fabre, Charles-Antoine Dedryver, Santé et agroécologie du vignoble (UMR SAVE), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, van Emden, H.F., Harrington, R., Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Subjects: [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2017

49. Beneficial influence of succinic anhydride as electrolyte additive on the self-discharge of 5 V LiNi0.4Mn1.6O4 cathodes

Author: Vasily Tarnopolskiy, Dominic Bresser, Stefano Passerini, Frédéric Fabre, Marlène Rey, Lionel Picard, Martina Nádherná, and Julian Kalhoff
Subjects: Renewable Energy, Sustainability and the Environment, Inorganic chemistry, Succinic anhydride, Energy Engineering and Power Technology, chemistry.chemical_element, 02 engineering and technology, Electrolyte, 010402 general chemistry, 021001 nanoscience & nanotechnology, Electrochemistry, 01 natural sciences, 0104 chemical sciences, chemistry.chemical_compound, chemistry, Ionic liquid, Lithium, Electrical and Electronic Engineering, Physical and Theoretical Chemistry, 0210 nano-technology, Self-discharge, Ethylene carbonate, Faraday efficiency
Abstract: The self-discharge mechanism of LiNi0.4Mn1.6O4, investigated by electrochemical methods, is mostly attributed to oxidative electrolyte decomposition due to the high lithium (de-)insertion potentials, since the material insertion capacity appears to be fully reversible upon subsequent galvanostatic cycling. A series of 40 different compounds, such as for instance fluorinated ethylene carbonate, 1,3-propane sultone, lithium bis(oxalato)borate (LiBOB), or a variety of ionic liquids, was investigated as suitable electrolyte additives to form a stable LNMO/electrolyte interphase in order to prevent the self-discharge by the continuous oxidative electrolyte decomposition. Among these, only one compound, namely succinic anhydride, revealed to have a beneficial effect on the self-discharge of LNMO based cathodes, while showing an enhanced coulombic efficiency and a decreased capacity loss per cycle. Additionally, the modification of the LNMO particles surface by adding succinic anhydride to the electrolyte was confirmed by performing ex situ SEM and XPS analysis of galvanostatically cycled electrodes.
Published: 2013
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50. Temporal niche differentiation of parasites sharing the same plant host: oak powdery mildew as a case study

Author: Marie-Laure Desprez-Loustau, Ludovic Mailleret, Frédéric Fabre, Frédéric Hamelin, Anne Bisson, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMR SAVE), Institut des Sciences de la Vigne et du Vin (ISVV)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut National de la Recherche Agronomique (INRA), Biological control of artificial ecosystems (BIOCORE), Institut National de la Recherche Agronomique (INRA)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), ANR‐13‐BSV7‐0011, Agence Nationale de la Recherche, Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB), Unité Mixte de Recherche en Santé Végétale (INRA/ENITA) (UMRSV), Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)-Institut des Sciences de la Vigne et du Vin (ISVV), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA), Institut Sophia Agrobiotech (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), ANR-13-BSV7-0011,FunFit,Une approche basée sur les traits d'histoire de vie des champignons phytopathogènes pour faire le lien entre fitness individuelle et stratégies écologiques.(2013), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA), and Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, media_common.quotation_subject, Population, Niche, 010603 evolutionary biology, 01 natural sciences, Competition (biology), Erysiphe alphitoides, Competitive exclusion principle, lcsh:QH540-549.5, semidiscrete model, coexistence, semi-discrete model, pathogen, epidemiology, trade-off, seasonality, trade‐off, education, Ecology, Evolution, Behavior and Systematics, media_common, education.field_of_study, Ecology, biology, Host (biology), Niche differentiation, périodicité, biology.organism_classification, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, épidémiologie, lcsh:Ecology, Powdery mildew, 010606 plant biology & botany, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract: Plant diseases are often caused by complexes of closely related parasite species. The coexistence of species sharing the same niche challenges the competitive exclusion principle. Here we performed the mathematical analysis of a generic model of sibling parasite species coexistence based on seasonality. We showed that coexistence through temporal niche partitioning is biologically plausible as it occurred in a significant part of the parameter space of the model. Moreover, the reversal of species relative frequencies (i.e. the most frequent species at the beginning of the season becoming the last frequent at the end) can occur without compromising the long%term coexistence of the two species. We provided data showing that this reversal pattern does repeat over years in the case of two sibling species responsible for oak powdery mildew (Erysiphe alphitoides and Erysiphe quercicola) in Europe. Last, the model was fitted to the data and satisfactorily described the population dynamics of oak powdery mildew species. The seasonal succession of these two plant pathogen species provides one of the few examples of coexistence by temporal niche partitioning at the scale of the season caused by exploitative competition. We discuss whether evolutionary branching may have led to temporal niche differentiation in this system.
Published: 2016
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