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A qualitative pest modeling platform, named Injury Profile Simulator (IPSIM), provides a tool to design aggregative hierarchical network models to predict the risk of pest injuries, including diseases, on a given crop based on variables related to cropping practices as well as soil and weather environment at the field level. The IPSIM platform enables modelers to combine data from various sources (literature, survey, experiments, and so on), expert knowledge, and simulation to build a network-based model. The overall structure of the platform is fully described at the IPSIM-Web website ( www6.inra.fr/ipsim ). A new module called IPSIM-Wheat-brown rust is reported in this article as an example of how to use the system to build and test the predictive quality of a prediction model. Model performance was evaluated for a dataset comprising 1,788 disease observations at 13 French cereal-growing regions over 15 years. Accuracy of the predictions was 85% and the agreement with actual values was 0.66 based on Cohen's κ. The new model provides risk information for farmers and agronomists to make scientifically sound tactical (within-season) decisions. In addition, the model may be of use for ex post diagnoses of diseases in commercial fields. The limitations of the model such as low precision and threshold effects as well as the benefits, including the integration of different sources of information, transparency, flexibility, and a user-friendly interface, are discussed.
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Basidiomycota/patogenicidad , Susceptibilidad a Enfermedades , Internet , Modelos Estadísticos , Enfermedades de las Plantas/parasitología , Triticum/microbiología , Agricultura , Simulación por Computador , Productos Agrícolas , Enfermedades de las Plantas/inmunología , Enfermedades de las Plantas/microbiología , Triticum/inmunología , Interfaz Usuario-ComputadorRESUMEN
The structure of pathogen populations is an important driver of epidemics affecting crops and natural plant communities. Comparing the composition of two pathogen populations consisting of assemblages of genotypes or phenotypes is a crucial, recurrent question encountered in many studies in plant disease epidemiology. Determining whether there is a significant difference between two sets of proportions is also a generic question for numerous biological fields. When samples are small and data are sparse, it is not straightforward to provide an accurate answer to this simple question because routine statistical tests may not be exactly calibrated. To tackle this issue, we built a computationally intensive testing procedure, the generalized Monte Carlo plug-in test with calibration test, which is implemented in an R package available at https://doi.org/10.5281/zenodo.635791 . A simulation study was carried out to assess the performance of the proposed methodology and to make a comparison with standard statistical tests. This study allows us to give advice on how to apply the proposed method, depending on the sample sizes. The proposed methodology was then applied to real datasets and the results of the analyses were discussed from an epidemiological perspective. The applications to real data sets deal with three topics in plant pathology: the reproduction of Magnaporthe oryzae, the spatial structure of Pseudomonas syringae, and the temporal recurrence of Puccinia triticina.
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Basidiomycota/fisiología , Magnaporthe/fisiología , Modelos Estadísticos , Enfermedades de las Plantas/estadística & datos numéricos , Plantas/microbiología , Pseudomonas syringae/fisiología , Calibración , Conjuntos de Datos como Asunto , Genotipo , Fenotipo , Enfermedades de las Plantas/microbiologíaRESUMEN
In a cross-infection experiment, we investigated how seasonal changes can affect adaptation patterns in a Zymoseptoria tritici population. The fitness of isolates sampled on wheat leaves at the beginning and at the end of a field epidemic was assessed under environmental conditions (temperature and host stage) to which the local pathogen population was successively exposed. Isolates of the final population were more aggressive, and showed greater sporulation intensity under winter conditions and a shorter latency period (earlier sporulation) under spring conditions, than isolates of the initial population. These differences, complemented by lower between-genotype variability in the final population, exhibited an adaptation pattern with three striking features: (i) the pathogen responded synchronously to temperature and host stage conditions; (ii) the adaptation concerned two key fitness traits; (iii) adaptation to one trait (greater sporulation intensity) was expressed under winter conditions while, subsequently, adaptation to the other trait (shorter latency period) was expressed under spring conditions. This can be interpreted as the result of short-term selection, driven by abiotic and biotic factors. This case study cannot yet be generalized but suggests that seasonality may play an important role in shaping the variability of fitness traits. These results further raise the question of possible counterselection during the interepidemic period. While we did not find any trade-off between clonal multiplication on leaves during the epidemic period and clonal spore production on debris, we suggest that final populations could be counterselected by an Allee effect, mitigating the potential impact of seasonal selection on long-term dynamics.
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Adaptación Fisiológica/genética , Ascomicetos/genética , Aptitud Genética , Estaciones del Año , Triticum/microbiología , Ascomicetos/aislamiento & purificación , Ascomicetos/fisiología , Ambiente , Genotipo , Interacciones Huésped-Patógeno , Fenotipo , Enfermedades de las Plantas/microbiología , Hojas de la Planta , Esporas Fúngicas , TemperaturaRESUMEN
The thermal performance curve is an ecological concept relating the phenotype of organisms and temperature. It requires characterization of the leaf temperature for foliar fungal pathogens. Epidemiologists, however, use air temperature to assess the impacts of temperature on such pathogens. Leaf temperature can differ greatly from air temperature, either in controlled or field conditions. This leads to a misunderstanding of such impacts. Experiments were carried out in controlled conditions on adult wheat plants to characterize the response of Mycosphaerella graminicola to a wide range of leaf temperatures. Three fungal isolates were used. Lesion development was assessed twice a week, whereas the temperature of each leaf was monitored continuously. Leaf temperature had an impact on disease dynamics. The latent period of M. graminicola was related to leaf temperature by a quadratic relationship. The establishment of thermal performance curves demonstrated differences among isolates as well as among leaf layers. For the first time, the thermal performance curve of a foliar fungal pathogen has been established using leaf temperature. The experimental setup we propose is applicable, and efficient, for other foliar fungal pathogens. Results have shown the necessity of such an approach, when studying the acclimatization of foliar fungal pathogens.
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Ascomicetos/fisiología , Hojas de la Planta/microbiología , Hojas de la Planta/fisiología , Temperatura , Triticum/microbiología , Triticum/fisiología , Ascomicetos/aislamiento & purificación , Enfermedades de las Plantas/microbiología , Esporas Fúngicas/fisiologíaRESUMEN
BACKGROUND AND AIMS: Experiments have shown that biotrophic fungi divert assimilates for their growth. However, no attempt has been made either to account for this additional sink or to predict to what extent it competes with both grain filling and plant reserve metabolism for carbon. Fungal sink competitiveness with grains was quantified by a mixed experimental-modelling approach based on winter wheat infected by Puccinia triticina. METHODS: One week after anthesis, plants grown under controlled conditions were inoculated with varying loads. Sporulation was recorded while plants underwent varying degrees of shading, ensuring a range of both fungal sink and host source levels. Inoculation load significantly increased both sporulating area and rate. Shading significantly affected net assimilation, reserve mobilization and sporulating area, but not grain filling or sporulation rates. An existing carbon partitioning (source-sink) model for wheat during the grain filling period was then enhanced, in which two parameters characterize every sink: carriage capacity and substrate affinity. Fungal sink competitiveness with host sources and sinks was modelled by representing spore production as another sink in diseased wheat during grain filling. KEY RESULTS: Data from the experiment were fitted to the model to provide the fungal sink parameters. Fungal carriage capacity was 0·56 ± 0·01 µg dry matter °Cd(-1) per lesion, much less than grain filling capacity, even in highly infected plants; however, fungal sporulation had a competitive priority for assimilates over grain filling. Simulation with virtual crops accounted for the importance of the relative contribution of photosynthesis loss, anticipated reserve depletion and spore production when light level and disease severity vary. The grain filling rate was less reduced than photosynthesis; however, over the long term, yield loss could double because the earlier reserve depletion observed here would shorten the duration of grain filling. CONCLUSIONS: Source-sink modelling holds the promise of accounting for plant-pathogen interactions over time under fluctuating climatic/lighting conditions in a robust way.
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Basidiomycota/patogenicidad , Triticum/microbiología , Basidiomycota/fisiología , Interacciones Huésped-Patógeno , Esporas Fúngicas/patogenicidad , Esporas Fúngicas/fisiologíaRESUMEN
The efficiency of plant resistance to fungal pathogen populations is expected to decrease over time, due to their evolution with an increase in the frequency of virulent or highly aggressive strains. This dynamics may differ depending on the scale investigated (annual or pluriannual), particularly for annual crop pathogens with both sexual and asexual reproduction cycles. We assessed this time-scale effect, by comparing aggressiveness changes in a local Zymoseptoria tritici population over an 8-month cropping season and a 6-year period of wheat monoculture. We collected two pairs of subpopulations to represent the annual and pluriannual scales: from leaf lesions at the beginning and end of a single annual epidemic and from crop debris at the beginning and end of a 6-year period. We assessed two aggressiveness traits-latent period and lesion size-on sympatric and allopatric host varieties. A trend toward decreased latent period concomitant with a significant loss of variability was established during the course of the annual epidemic, but not over the 6-year period. Furthermore, a significant cultivar effect (sympatric vs. allopatric) on the average aggressiveness of the isolates revealed host adaptation, arguing that the observed patterns could result from selection. We thus provide an experimental body of evidence of an epidemiological trade-off between the intra- and interannual scales in the evolution of aggressiveness in a local plant pathogen population. More aggressive isolates were collected from upper leaves, on which disease severity is usually lower than on the lower part of the plants left in the field as crop debris after harvest. We suggest that these isolates play little role in sexual reproduction, due to an Allee effect (difficulty finding mates at low pathogen densities), particularly as the upper parts of the plant are removed from the field, explaining the lack of transmission of increases in aggressiveness between epidemics.
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Outcomes of host-pathogen coevolution are influenced by migration rates of the interacting species. Reduced gene flow with increasing spatial distance between populations leads to spatial genetic structure, as predicted by the isolation by distance (IBD) model. In wind-dispersed plant-pathogenic fungi, a significant spatial genetic structure is theoretically expected if local spore dispersal is more frequent than long-distance dispersal, but this remains to be documented by empirical data. For 29 populations of the oilseed rape fungus Leptosphaeria maculans sampled from two French regions, genetic structure was determined using eight minisatellite markers. Gene diversity (H = 0.62-0.70) and haplotypic richness (R = 0.96-1) were high in all populations. No linkage disequilibrium was detected between loci, suggesting the prevalence of panmictic sexual reproduction. Analysis of molecular variance showed that > 97% of genetic diversity was observed within populations. Genetic differentiation was low among populations (F(st) < 0.05). Although direct methods previously revealed short-distance dispersal for L. maculans, our findings of no correlation between genetic and geographic distances among populations illustrate that the IBD model does not account for dispersal of the fungus at the spatial scale we examined. These results indicate high gene flow among French populations of L. maculans, suggesting high dispersal rates and/or large effective population sizes, two characteristics giving the pathogen high evolutionary potential against the deployment of resistant oilseed rape cultivars.
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Ascomicetos/genética , Ascomicetos/aislamiento & purificación , Brassica napus/microbiología , Evolución Molecular , Enfermedades de las Plantas/microbiología , Ascomicetos/clasificación , Variación Genética , Repeticiones de Minisatélite , Datos de Secuencia Molecular , FilogeniaRESUMEN
Variables with values in the circle or indexed by the circle have been studied in order to investigate questions in ecology, epidemiology, climatology and oceanography for example. To model circular variables with rough behaviors, the use of Gaussian random processes (GRPs) can be particularly convenient as will be seen in this paper. The roughness of a GRP being mainly determined by its correlation function, a circular correlation function convenient for rough processes is proposed. These mathematical tools are applied to describe the anisotropic spread of an airborne plant disease from a point source: a hierarchical model including two circular GRPs is built and used to analyze data coming from a field experiment. This random-effect model is fitted to data using a Monte-Carlo expectation-maximization (MCEM) algorithm.
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Modelos Estadísticos , Distribución Normal , Enfermedades de las Plantas , Anisotropía , Francia , Método de Montecarlo , Triticum/microbiologíaRESUMEN
Fungi represent an essential component of biodiversity, not only because of the large number of species, but also for their ecological, evolutionary and socio-economic significance. Yet, until recently, fungi received scant consideration in ecology, especially invasion ecology. Their under-representation is largely the result of a lack of scientific knowledge of fungal biodiversity and ecology. With the exception of pathogenic fungi, which cause emergent infectious diseases, the impact of fungal invasions is often difficult to quantify owing to limited baseline data on fungal communities. Here, we aim to raise awareness among mycologists and ecologists of the fungal dimension of invasions and of the need to intensify research in fungal ecology to address issues of future introductions.