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Introduction: Climate change (CC) and the increased occurrence of extreme climatic events pose a serious threat to crop yields and their stability worldwide. This study analyzed the CC mitigation potential of an alley cropping system on crop physiological stresses and growth as compared to a monoculture system. Materials and Methods: Growth of winter durum wheat, cultivated alone (agriculture) and in combination with hybrid walnut (agroforestry), was simulated with the Hi-sAFe agroforestry model, as driven by business-as-usual Intergovernmental Panel on Climate Change (IPCC) projections, split into three scenarios, representing Past (1951–1990), Present (1991–2030), and Future (2031–2070) climatic conditions. Crop growth and the occurrence of thermal, nitrogen, and water stresses were analyzed. Results: Cold-related stresses were modest in Past and almost disappeared over time. Heat, drought, and nitrogen stresses increased about twofold from Past to Future, but were reduced by 20–35% in agroforestry, already with medium-sized trees (diameter at breast height (DBH) of about 10–15 cm). Crop yields in agriculture increased from Past to the end of Present and then remained stable. This moderately decreased with tree age in agroforestry (especially in Future). Discussion: The impact of CC on the crop was buffered in agroforestry, especially for the most extreme climatic events. The mitigation of crop microclimate and the increased stability of crop yields highlight the potential of agroforestry as a CC adaptation strategy.
Francesco Reyes; Marie Gosme; Kevin Wolz; Isabelle Lecomte; Christian Dupraz. Alley Cropping Mitigates the Impacts of Climate Change on a Wheat Crop in a Mediterranean Environment: A Biophysical Model-Based Assessment. Agriculture 2021, 11, 356 .
AMA StyleFrancesco Reyes, Marie Gosme, Kevin Wolz, Isabelle Lecomte, Christian Dupraz. Alley Cropping Mitigates the Impacts of Climate Change on a Wheat Crop in a Mediterranean Environment: A Biophysical Model-Based Assessment. Agriculture. 2021; 11 (4):356.
Chicago/Turabian StyleFrancesco Reyes; Marie Gosme; Kevin Wolz; Isabelle Lecomte; Christian Dupraz. 2021. "Alley Cropping Mitigates the Impacts of Climate Change on a Wheat Crop in a Mediterranean Environment: A Biophysical Model-Based Assessment." Agriculture 11, no. 4: 356.
In the face of climate change, more frequent drought events are expected in the Mediterranean regions. Alley cropping is an agroforestry practice that represents a promising adaptation strategy to sustain yield productivity under drier conditions. However, the presence of trees limits the productivity of the intercrop by reducing light availability and by competing for soil water resources, which could potentially exacerbate the yield losses due to drought conditions. Furthermore, the effects of co‐occurring drought and shade stresses on annual crops are still poorly understood. To tackle this issue, we performed a rainfall manipulation experiment on winter pea (Pisum sativum L.) grown in full‐sun conditions (agricultural control) and under different levels of shade in a 25‐year walnut‐based alley cropping system located in southern France. We evaluated first the effect of trees on light and water availability, and we then studied the effects of early drought (135 mm excluded from April to the end of May) and light conditions on crop performances and yield components. At 3.5 m from the tree line, light availability was reduced on average by 19% at south and 35% at north of trees over the entire crop cycle and mostly after tree budburst. The impact of trees on soil water content in the crop root zone was weak thanks to the good complementarity of the respective root systems. Under normal rainfall conditions, tree shade decreased pea yield from −25% to −77% compared to full‐sun conditions. In case of spring drought, pea yield was decreased by −22% in full‐sun conditions. The negative effect of tree shade was reduced and decreased pea yield only by −1% to −47%. Under the most intense shade conditions, pea yield was even higher under drought than in normal rainfall conditions. The analysis of crop dynamics and yield components revealed that the vegetative development of pea ceased under drought to the benefit of biomass allocation towards the reproductive organs. Pea yield was less impacted by tree shade under spring drought because yield elaboration relied less on the success of pod set, sensitive to shade and, more on grain filling, improved in case of early drought event. This study supports the hypothesis that agroforestry systems may be more resilient in the case of early drought.
Guillaume Blanchet; Karim Barkaoui; Mattia Bradley; Christian Dupraz; Marie Gosme. Interactions between drought and shade on the productivity of winter pea grown in a 25‐year‐old walnut‐based alley cropping system. Journal of Agronomy and Crop Science 2021, 1 .
AMA StyleGuillaume Blanchet, Karim Barkaoui, Mattia Bradley, Christian Dupraz, Marie Gosme. Interactions between drought and shade on the productivity of winter pea grown in a 25‐year‐old walnut‐based alley cropping system. Journal of Agronomy and Crop Science. 2021; ():1.
Chicago/Turabian StyleGuillaume Blanchet; Karim Barkaoui; Mattia Bradley; Christian Dupraz; Marie Gosme. 2021. "Interactions between drought and shade on the productivity of winter pea grown in a 25‐year‐old walnut‐based alley cropping system." Journal of Agronomy and Crop Science , no. : 1.
Since 2006, an increasing number of French vineyards have chosen to convert to organic farming. One major change in vineyard practices includes replacing chemical pesticides with copper and sulfur-based products in line with Council Regulation (EC) No. 834/2007. This change can make overall management and pest and disease control more difficult and potentially lead to yield losses. From 2013 to 2016, a network of 48 vineyard plots, in southern France, under conventional management and in conversion to organic farming were monitored throughout the three-year conversion phase to investigate the grapevine phytosanitary management of four major pests and diseases and variations in control efficiency. The severity of downy and powdery mildew, grape berry moths, and Botrytis bunch rot were assessed and linked to the protection strategy. The findings showed that pests and diseases were controlled in the third year of conversion at similar efficiency levels as in conventional farming. However, the first two years of conversion were a transitional and less successful period during which higher incidences of cryptogamic diseases were observed. This demonstrates a need for winegrowers to receive more in-depth technical advice and support, especially on pest and disease control, during this critical transition period.
Anne Merot; Marc Fermaud; Marie Gosme; Nathalie Smits. Effect of Conversion to Organic Farming on Pest and Disease Control in French Vineyards. Agronomy 2020, 10, 1047 .
AMA StyleAnne Merot, Marc Fermaud, Marie Gosme, Nathalie Smits. Effect of Conversion to Organic Farming on Pest and Disease Control in French Vineyards. Agronomy. 2020; 10 (7):1047.
Chicago/Turabian StyleAnne Merot; Marc Fermaud; Marie Gosme; Nathalie Smits. 2020. "Effect of Conversion to Organic Farming on Pest and Disease Control in French Vineyards." Agronomy 10, no. 7: 1047.
Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.
Christian Dupraz; Kevin Wolz; Isabelle Lecomte; Grégoire Talbot; Grégoire Vincent; Rachmat Mulia; François Bussière; Harry Ozier-Lafontaine; Sitraka Andrianarisoa; Nick Jackson; Gerry Lawson; Nicolas Dones; Hervé Sinoquet; Betha Lusiana; Degi Harja; Susy Domenicano; Francesco Reyes; Marie Gosme; Meine Van Noordwijk. Hi-sAFe: A 3D Agroforestry Model for Integrating Dynamic Tree–Crop Interactions. Sustainability 2019, 11, 2293 .
AMA StyleChristian Dupraz, Kevin Wolz, Isabelle Lecomte, Grégoire Talbot, Grégoire Vincent, Rachmat Mulia, François Bussière, Harry Ozier-Lafontaine, Sitraka Andrianarisoa, Nick Jackson, Gerry Lawson, Nicolas Dones, Hervé Sinoquet, Betha Lusiana, Degi Harja, Susy Domenicano, Francesco Reyes, Marie Gosme, Meine Van Noordwijk. Hi-sAFe: A 3D Agroforestry Model for Integrating Dynamic Tree–Crop Interactions. Sustainability. 2019; 11 (8):2293.
Chicago/Turabian StyleChristian Dupraz; Kevin Wolz; Isabelle Lecomte; Grégoire Talbot; Grégoire Vincent; Rachmat Mulia; François Bussière; Harry Ozier-Lafontaine; Sitraka Andrianarisoa; Nick Jackson; Gerry Lawson; Nicolas Dones; Hervé Sinoquet; Betha Lusiana; Degi Harja; Susy Domenicano; Francesco Reyes; Marie Gosme; Meine Van Noordwijk. 2019. "Hi-sAFe: A 3D Agroforestry Model for Integrating Dynamic Tree–Crop Interactions." Sustainability 11, no. 8: 2293.
Laure Hossard; Marie Gosme; Véronique Souchère; Marie-Hélène Jeuffroy. Linking cropping system mosaics to disease resistance durability. Ecological Modelling 2015, 307, 1 -9.
AMA StyleLaure Hossard, Marie Gosme, Véronique Souchère, Marie-Hélène Jeuffroy. Linking cropping system mosaics to disease resistance durability. Ecological Modelling. 2015; 307 ():1-9.
Chicago/Turabian StyleLaure Hossard; Marie Gosme; Véronique Souchère; Marie-Hélène Jeuffroy. 2015. "Linking cropping system mosaics to disease resistance durability." Ecological Modelling 307, no. : 1-9.
The pathozone (volume of soil surrounding subterranean plant organs within which a propagule must occur if it is to have any chance of infecting the organ) is usually described by statistical models lacking biological meaning. For this reason, pathozone results might be difficult to interpret and the estimated parameters cannot be re‐used in other studies. We developed a model with parameters reflecting life‐history traits concerning primary infections of soilborne pathogens. The model was then fitted to experimental data obtained from eight isolates of Gaeumannomyces graminis var. tritici, causal agent of take‐all disease of wheat. Our model provided not only a mechanistic description for the pathozone dynamics, but also a better fit to the data than four other models published in the literature. Although the isolates displayed phenotypic variability in terms of pathozone dynamics, these differences did not map onto the G1 and G2 genetic subgroups known to occur in Ggt populations.
M. Gosme; L. Lebreton; A. Sarniguet; P. Lucas; C.A. Gilligan; D.J. Bailey. A new model for the pathozone of the take-all pathogen,Gaeumannomyces graminisvar.tritici. Annals of Applied Biology 2013, 163, 359 -366.
AMA StyleM. Gosme, L. Lebreton, A. Sarniguet, P. Lucas, C.A. Gilligan, D.J. Bailey. A new model for the pathozone of the take-all pathogen,Gaeumannomyces graminisvar.tritici. Annals of Applied Biology. 2013; 163 (3):359-366.
Chicago/Turabian StyleM. Gosme; L. Lebreton; A. Sarniguet; P. Lucas; C.A. Gilligan; D.J. Bailey. 2013. "A new model for the pathozone of the take-all pathogen,Gaeumannomyces graminisvar.tritici." Annals of Applied Biology 163, no. 3: 359-366.
Linking spatial pattern and process is a difficult task in landscape ecology because spatial patterns of populations result from complex factors such as individual traits, the spatio-temporal variation of the habitat, and the relationships between the target species and other species. Mechanistic models provide tools to bridge this gap but they are seldom used to study the influence of landscape patterns on biological processes. In this paper, we develop a methodological approach based on sensitivity and multivariate analyses to investigate the relationship between the biological parameters of species and landscape characteristics. As a case study, we used a tritrophic system that includes a host plant (oilseed rape, Brassica napus L.), a pest of the host plant (the pollen beetle, Meligethes aeneus F.), and the main parasitoid of the pest (Tersilochus heterocerus). This tritrophic system was recently represented by a model (Mosaic-Pest) that is spatially explicit at the landscape scale and that includes 32 biological parameters. In the current study, model simulations were compared with observed data from 35 landscapes differing in configuration. Sensitivity analysis using the Morris method identified those biological parameters that were highly sensitive to landscape configuration. Then, multivariate analyses revealed how a parameter's influence on model output could be affected by landscape composition. Comparison of simulated and observed data helped us decrease the uncertainty surrounding the estimated values of the literature-derived parameters describing beetle dispersal and stage transition of the parasitoid at emergence. The advantages of using multivariate sensitivity analyses to disentangle the links between patterns and processes in landscape-scale spatially explicit models are discussed
Fabrice Vinatier; Marie Gosme; Muriel Valantin-Morison. Explaining host–parasitoid interactions at the landscape scale: a new approach for calibration and sensitivity analysis of complex spatio-temporal models. Landscape Ecology 2012, 28, 217 -231.
AMA StyleFabrice Vinatier, Marie Gosme, Muriel Valantin-Morison. Explaining host–parasitoid interactions at the landscape scale: a new approach for calibration and sensitivity analysis of complex spatio-temporal models. Landscape Ecology. 2012; 28 (2):217-231.
Chicago/Turabian StyleFabrice Vinatier; Marie Gosme; Muriel Valantin-Morison. 2012. "Explaining host–parasitoid interactions at the landscape scale: a new approach for calibration and sensitivity analysis of complex spatio-temporal models." Landscape Ecology 28, no. 2: 217-231.
The area under organic farming is increasing in many countries. The effect of a significant increase in the proportion of organic agriculture on pest (sensu lato) populations at the landscape scale is unknown and will depend on both the production of propagules in organic fields and the risk of pest dispersal between fields. In this study, we observed the dynamics of four foliar diseases, aphids, and weeds in 216 wheat fields over 2 years in northern France. We used the survey data to estimate the local effect of how a field was managed (organic or conventional) and the presence or absence of adjacent organic fields (neighbourhood effect) on pest abundance in that field. Because conventional and organic may be considered extremes along a continuum of management practices, a large survey was undertaken of management practices to ensure that the fields were classified according to the actual cropping practices. The presence or absence of organic certification was determined to be the only relevant criterion for classifying cropping practices. The results of proportional odds mixed models showed that some pests responded to local crop management: leaf blotch incidence and aphid density were significantly lower while weed diversity and abundance were higher in organic fields. Only aphids and leaf blotch responded to the neighbourhood effect: the presence of organic fields in the neighbourhood decreased the number of aphids in both organic and conventional fields and decreased leaf blotch incidence but only in conventional fields. These results indicate that the increase in organic acreage in landscapes will not increase pest problems in the short term under the conditions of the study (low disease pressure). (C) 2012 Elsevier B.V. All rights reserved
Marie Gosme; Maguie de Villemandy; Mathieu Bazot; Marie-Hélène Jeuffroy. Local and neighbourhood effects of organic and conventional wheat management on aphids, weeds, and foliar diseases. Agriculture, Ecosystems & Environment 2012, 161, 121 -129.
AMA StyleMarie Gosme, Maguie de Villemandy, Mathieu Bazot, Marie-Hélène Jeuffroy. Local and neighbourhood effects of organic and conventional wheat management on aphids, weeds, and foliar diseases. Agriculture, Ecosystems & Environment. 2012; 161 ():121-129.
Chicago/Turabian StyleMarie Gosme; Maguie de Villemandy; Mathieu Bazot; Marie-Hélène Jeuffroy. 2012. "Local and neighbourhood effects of organic and conventional wheat management on aphids, weeds, and foliar diseases." Agriculture, Ecosystems & Environment 161, no. : 121-129.
The intensification of agriculture has led to a loss of biodiversity and subsequently to a decrease in ecosystem services, including regulation of pests by natural enemies. Biological regulation of pests is a complex process affected by both landscape configuration and agricultural practices. Although modeling tools are needed to design innovative integrated pest management strategies that consider tritrophic interactions at the landscape scale, landscape models that consider agricultural practices as levers to enhance biological regulation are lacking. To begin filling this gap, we developed a grid-based lattice model called Mosaic-Pest that simulates the spatio-temporal dynamics of Meligethes aeneus, a major pest of oilseed rape, and its parasitoid, Tersilochus heterocerus through a landscape that changes through time according to agricultural practices. The following agricultural practices were assumed to influence the tritrophic system and were included in the model: crop allocation in time and space, ploughing, and trap crop planting. To test the effect of agricultural practices on biological regulation across landscape configurations, we used a complete factorial design with the variables described below and ran long-term simulations using Mosaic-Pest. The model showed that crop rotation and the use of trap crop greatly affected pollen beetle densities and parasitism rates while ploughing had only a small effect. The use of Mosaic-Pest as a tool to select the combination of agricultural practices that best limit the pest population is discussed.
Fabrice Vinatier; Marie Gosme; Muriel Valantin-Morison. A tool for testing integrated pest management strategies on a tritrophic system involving pollen beetle, its parasitoid and oilseed rape at the landscape scale. Landscape Ecology 2012, 27, 1421 -1433.
AMA StyleFabrice Vinatier, Marie Gosme, Muriel Valantin-Morison. A tool for testing integrated pest management strategies on a tritrophic system involving pollen beetle, its parasitoid and oilseed rape at the landscape scale. Landscape Ecology. 2012; 27 (10):1421-1433.
Chicago/Turabian StyleFabrice Vinatier; Marie Gosme; Muriel Valantin-Morison. 2012. "A tool for testing integrated pest management strategies on a tritrophic system involving pollen beetle, its parasitoid and oilseed rape at the landscape scale." Landscape Ecology 27, no. 10: 1421-1433.
Increasing the use of synthetic fertilisers and pesticides in agroecosystems has led to higher crop yields, accompanied by a decline in biodiversity at the levels of field, cropping system and farm. Biodiversity decline has been favoured by changes at landscape level such as regional farm specialisation, increases in field size, and the removal of hedgerows and woodlots. The loss of biodiversity in agroecosystems has increased the need for external inputs because beneficial functions are no longer provided by beneficial species as natural enemies of crop pests and ecosystem engineers. This trend has led to a strong reliance on petrochemicals in agroecosystems. However, many scientists have been arguing for more than two decades that this reliance on petrochemicals could be considerably reduced by a better use of biotic interactions. This article reviews options to increase beneficial biotic interactions in agroecosystems and to improve pest management and crop nutrition whilst decreasing petrochemical use. Four agronomic options are presented. First, it has been shown that the choice of cultivar, the sowing date and nitrogen fertilisation practices can be manipulated to prevent interactions between pests and crop, in either time or space. Nevertheless, the efficacy of these manipulations may be limited by pest adaptation. Second, beneficial biotic interactions may result from appropriate changes to the habitats of natural enemies and ecosystem engineers, mediated by soil and weed management. Here, knowledge is scarce, and indirect and complex effects are poorly understood. Third, changes achieved by crop diversification and, fourth, by landscape adaptation are promising. However, these practices also present drawbacks that may not necessarily be outweighed by beneficial effects. Overall, these four management approaches provide a powerful framework to develop sustainable agronomic practices. (Résumé d'auteur
Safia Médiène; Muriel Valantin-Morison; Jean-Pierre Sarthou; Stéphane De Tourdonnet; Marie Gosme; Michel Bertrand; Jean Roger-Estrade; Jean-Noël Aubertot; Adrien Rusch; Natacha Motisi; Céline Pelosi; Thierry Doré. Agroecosystem management and biotic interactions: a review. Agronomy for Sustainable Development 2011, 31, 491 -514.
AMA StyleSafia Médiène, Muriel Valantin-Morison, Jean-Pierre Sarthou, Stéphane De Tourdonnet, Marie Gosme, Michel Bertrand, Jean Roger-Estrade, Jean-Noël Aubertot, Adrien Rusch, Natacha Motisi, Céline Pelosi, Thierry Doré. Agroecosystem management and biotic interactions: a review. Agronomy for Sustainable Development. 2011; 31 (3):491-514.
Chicago/Turabian StyleSafia Médiène; Muriel Valantin-Morison; Jean-Pierre Sarthou; Stéphane De Tourdonnet; Marie Gosme; Michel Bertrand; Jean Roger-Estrade; Jean-Noël Aubertot; Adrien Rusch; Natacha Motisi; Céline Pelosi; Thierry Doré. 2011. "Agroecosystem management and biotic interactions: a review." Agronomy for Sustainable Development 31, no. 3: 491-514.
The importance of the spatial aspect of epidemics has been recognized from the outset of plant disease epidemiology. The objective of this study was to determine if the host spatial structure influenced the spatio-temporal development of take-all disease of wheat, depending on the inoculum spatial structure. Three sowing patterns of wheat (broadcast sowing, line sowing and sowing in hills) and three patterns of inoculum (uniform, aggregated and natural infestation) were tested in a field experiment, repeated over 2 years. Disease (severity, root disease incidence, plant disease incidence and, when applicable, line and hill incidences) was assessed seven times during the course of each season and the spatial pattern was characterized with incidence-incidence relationships. In the naturally infested plots, disease levels at all measurement scales were significantly higher in plots sown in hills, compared to plots sown in line, which were in turn significantly more diseased than plots with broadcast sowing. Disease aggregation within roots and plants was stronger in line and hill sowing than in broadcast sowing. Analysis of the disease gradient in the artificially infested plots showed that the disease intensified (local increase of disease level) more than it extensified (spatial spread of the disease), the effect of the introduced inoculum was reduced by 95% at a distance of 15 cm away from the point of infestation. Yield was not significantly affected by sowing pattern or artificial infestation.
Marie Gosme; Philippe Lucas. Effect of host and inoculum patterns on take-all disease of wheat incidence, severity and disease gradient. European Journal of Plant Pathology 2010, 129, 119 -131.
AMA StyleMarie Gosme, Philippe Lucas. Effect of host and inoculum patterns on take-all disease of wheat incidence, severity and disease gradient. European Journal of Plant Pathology. 2010; 129 (1):119-131.
Chicago/Turabian StyleMarie Gosme; Philippe Lucas. 2010. "Effect of host and inoculum patterns on take-all disease of wheat incidence, severity and disease gradient." European Journal of Plant Pathology 129, no. 1: 119-131.
Pesticide use should be reduced for sustainable agriculture. Low-input cropping systems, centered on hardy varieties that maintain their yield in the presence of pests, allow pesticide use to be reduced. Since yield potential is generally lower for hardy varieties than for high-yielding varieties, a balance must be found between production and pesticide reduction. In order to compute the optimal partitioning of agricultural area between intensive and low-input cropping systems, we present a model that allows yield and gross margins to be computed at the landscape scale, as a function of the proportion of the area under intensive and low-input systems. The model shows that two cases must be distinguished, depending on inoculum production by each of the coexisting systems. If the low-input system produces less inoculum (e.g. because resistant varieties are used), coexistence can be optimal, whereas if the low-input system produces more inoculum (e.g. because tolerant varieties are used), it is best to devote the whole area to a single system. The model gives the gross margin for each cropping system as a function of the proportion of low-input systems – and so predicts the proportion to which the farmers’ choices will lead – and illustrates the use of different (simplified) policies that would ensure that the optimum proportion is reached
Marie Gosme; Frédéric Suffert; Marie-Hélène Jeuffroy. Intensive versus low-input cropping systems: What is the optimal partitioning of agricultural area in order to reduce pesticide use while maintaining productivity? Agricultural Systems 2010, 103, 110 -116.
AMA StyleMarie Gosme, Frédéric Suffert, Marie-Hélène Jeuffroy. Intensive versus low-input cropping systems: What is the optimal partitioning of agricultural area in order to reduce pesticide use while maintaining productivity? Agricultural Systems. 2010; 103 (2):110-116.
Chicago/Turabian StyleMarie Gosme; Frédéric Suffert; Marie-Hélène Jeuffroy. 2010. "Intensive versus low-input cropping systems: What is the optimal partitioning of agricultural area in order to reduce pesticide use while maintaining productivity?" Agricultural Systems 103, no. 2: 110-116.
Primary and secondary infections are important processes in the epidemiology of plant diseases but can be difficult to quantify experimentally as they often occur at the same time. This problem is all the more challenging in the case of soil-borne diseases, as most processes are hidden in the soil and destructive sampling is time-consuming and makes it difficult to obtain enough observations of disease progress. Here we show how a combination of experimentation and modelling can be used in order to obtain parameters for primary and secondary infections for take-all disease of wheat. First, an experiment with one infected seedling and varying numbers of target seedlings allowed us to estimate the probability of secondary infection by growth of the mycelium through the soil and by growth via the crown of the plant. Several equations were tested for the contact term between susceptible and infectious roots. Secondly, an experiment with primary inoculum placed at different depths allowed us to estimate the probability of primary infection, taking into account secondary infections and the time needed for the roots to reach inoculum depth. In both experiments, the use of simple models was effective in isolating the desired effect from uncontrollable effects occurring in the soil. The probability of secondary infection through the crown was higher than the probability of infection through soil, and the contact term following the mass action or Reed-Frost equation gave a better fit to the data than the other equations tested. The probability of primary infection was higher when inoculum was placed just below the soil surface than when it was placed deeper in the soil.
Marie Gosme; Philippe Lucas. Combining experimentation and modelling to estimate primary and secondary infections of take-all disease of wheat. Soil Biology and Biochemistry 2009, 41, 1523 -1530.
AMA StyleMarie Gosme, Philippe Lucas. Combining experimentation and modelling to estimate primary and secondary infections of take-all disease of wheat. Soil Biology and Biochemistry. 2009; 41 (7):1523-1530.
Chicago/Turabian StyleMarie Gosme; Philippe Lucas. 2009. "Combining experimentation and modelling to estimate primary and secondary infections of take-all disease of wheat." Soil Biology and Biochemistry 41, no. 7: 1523-1530.
Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.
Marie Gosme; Philippe Lucas. Disease Spread Across Multiple Scales in a Spatial Hierarchy: Effect of Host Spatial Structure and of Inoculum Quantity and Distribution. Phytopathology® 2009, 99, 833 -839.
AMA StyleMarie Gosme, Philippe Lucas. Disease Spread Across Multiple Scales in a Spatial Hierarchy: Effect of Host Spatial Structure and of Inoculum Quantity and Distribution. Phytopathology®. 2009; 99 (7):833-839.
Chicago/Turabian StyleMarie Gosme; Philippe Lucas. 2009. "Disease Spread Across Multiple Scales in a Spatial Hierarchy: Effect of Host Spatial Structure and of Inoculum Quantity and Distribution." Phytopathology® 99, no. 7: 833-839.
Disease spread occurs at several spatial scales, e.g., from field to field, plant to plant, and leaf to leaf. So far, epidemiological models have largely overlooked the multiscale nature of epidemics. Here, we propose a model that simulates disease spread across multiple scales in a nested hierarchy. The model is based on the central ideas of hierarchy theory, i.e., (i) the system is decomposed vertically into levels and horizontally into holons (elements at one level, which are complete systems when seen from the lower level), and (ii) higher levels are characterized by slower processes than lower levels. The model is individual-based, the individuals being the holons, which are either susceptible or infected. At each level, infections within one holon (i.e., infections between holons of the level below) occur independently from the other holons: infections between holons happen at the higher level. The self-similarity of the model structure and processes across all levels allows implementing the model with a simple recursive algorithm. The behavior of the model was studied using methods commonly applied to field data. Aggregation of the disease was characterized through the incidence-incidence relationship and the binomial power law, in order to study the effect of infectiousness at each level on disease aggregation. Sensitivity analyses showed that disease incidences at all levels were influenced by the infectiousness at any level, but infectiousness at higher levels had more effect than infectiousness at lower levels. It was also shown that increasing the probability of infection at a given level increased aggregation at higher level(s) and decreased aggregation at lower level(s). The results were consistent between incidence-incidence relationship and power law analysis, but the incidence-incidence relationship was more sensitive in detecting the differences in aggregation between treatments.
Marie Gosme; Philippe Lucas. Cascade: An Epidemiological Model to Simulate Disease Spread and Aggregation Across Multiple Scales in a Spatial Hierarchy. Phytopathology® 2009, 99, 823 -832.
AMA StyleMarie Gosme, Philippe Lucas. Cascade: An Epidemiological Model to Simulate Disease Spread and Aggregation Across Multiple Scales in a Spatial Hierarchy. Phytopathology®. 2009; 99 (7):823-832.
Chicago/Turabian StyleMarie Gosme; Philippe Lucas. 2009. "Cascade: An Epidemiological Model to Simulate Disease Spread and Aggregation Across Multiple Scales in a Spatial Hierarchy." Phytopathology® 99, no. 7: 823-832.
The spatial dimension of plant disease development has often been neglected by most epidemiologists, despite its importance. Yet several tools are available for analysis and modeling of epidemics, both in time and space. Methods for spatial analysis include clustering index calculation, distribution fitting, power law, relationships between incidences at different spatial scales, mapping, geostatistics, and distance indices with SADIE software. The tools for spatio-temporal modeling include spatially explicit or spatially implicit models. Among the spatially explicit models, we find reaction-diffusion, network, or individual-based models, cellular automata, and lattice models, including some metapopulation models. Spatially implicit models are based on the introduction of a correction factor, the percolation theory, or statistical approximations. This review presents a rough guide to spatio-temporal approaches, in the hope that their use will become widespread in the community of epidemiologists, even among nonspecialists in spatial information. The tools that can be used to analyze and model the spatial structure of epidemics are reviewed in the context of their application to phytopathology. The diffusion of this information should promote a better understanding of epidemics and the design of innovative management strategies.
Marie Gosme. Comment analyser la structure spatiale et modéliser le développement spatio-temporel des épiphyties? Canadian Journal of Plant Pathology 2008, 30, 4 -23.
AMA StyleMarie Gosme. Comment analyser la structure spatiale et modéliser le développement spatio-temporel des épiphyties? Canadian Journal of Plant Pathology. 2008; 30 (1):4-23.
Chicago/Turabian StyleMarie Gosme. 2008. "Comment analyser la structure spatiale et modéliser le développement spatio-temporel des épiphyties?" Canadian Journal of Plant Pathology 30, no. 1: 4-23.
Point pattern analysis (fitting of the beta‐binomial distribution and binary form of power law) was used to describe the spatial pattern of natural take‐all epidemics (caused by Gaeumannomyces graminis var. tritici) on a second consecutive crop of winter wheat in plots under different cropping practices that could have an impact on the quantity and spatial distribution of primary inoculum, and on the spread of the disease. The spatial pattern of take‐all was aggregated in 48% of the datasets when disease incidence was assessed at the plant level and in 83% when it was assessed at the root level. Clusters of diseased roots were in general less than 1 m in diameter for crown roots and 1–1·5 m for seminal roots; when present, clusters of diseased plants were 2–2·5 m in diameter. Anisotropy of the spatial pattern was detected and could be linked to soil cultivation. Clusters did not increase in size over the cropping season, but increased spatial heterogeneity of the disease level was observed, corresponding to local disease amplification within clusters. The relative influences of autonomous spread and inoculum dispersal on the size and shape of clusters are discussed.
Marie Gosme; L. Willocquet; P. Lucas. Size, shape and intensity of aggregation of take-all disease during natural epidemics in second wheat crops. Plant Pathology 2007, 56, 87 -96.
AMA StyleMarie Gosme, L. Willocquet, P. Lucas. Size, shape and intensity of aggregation of take-all disease during natural epidemics in second wheat crops. Plant Pathology. 2007; 56 (1):87-96.
Chicago/Turabian StyleMarie Gosme; L. Willocquet; P. Lucas. 2007. "Size, shape and intensity of aggregation of take-all disease during natural epidemics in second wheat crops." Plant Pathology 56, no. 1: 87-96.
In order to investigate potential links existing between Gaeumannomyces graminis var. tritici (Ggt) population structure and disease development during polyetic take‐all epidemics in sequences of Ggt host cereals, seven epidemics in fields with different cropping histories were monitored during the seasons 2001/2002 (two fields), 2002/2003 (two fields) and 2003/2004 (three fields). Take‐all incidence and severity were measured at stem elongation and Ggt populations were characterized. The 73 isolates collected in the two fields in 2001/2002 were distributed into two multilocus genotypes, G1 and G2 according to amplified fragment length polymorphism analysis. A monolocus molecular marker amplified by F‐12 random amplification polymorphism DNA primer sizing between 1.9 and 2.0 kb that gave strictly the same distinction between the two multilocus genotypes was further applied to measure G1/G2 frequencies among Ggt populations in all fields (266 isolates). The ratios of G1 to G2 differed between fields with different cropping histories. A linear relationship between G2 frequency among Ggt populations and disease severity at stem elongation was measured during the three cropping seasons. When take‐all decline was observed, G2 frequencies were low in first wheat crops, highest in short‐term sequences and intermediate in longer sequences of consecutive crops of Ggt host cereals. This pattern could be the result of population selection by environmental conditions, in particular by microbial antagonism during the parasitic phase of the fungus. In order to better understand take‐all epidemic dynamics, the distinction between these two genotypes could be a basis to develop models that link approaches of quantitative epidemiology and advances in population genetics of Ggt.
Lionel Lebreton; Marie Gosme; Philippe Lucas; Anne-Yvonne Guillerm-Erckelboudt; Alain Sarniguet. Linear relationship between Gaeumannomyces graminis var. tritici (Ggt) genotypic frequencies and disease severity on wheat roots in the field. Environmental Microbiology 2006, 9, 492 -499.
AMA StyleLionel Lebreton, Marie Gosme, Philippe Lucas, Anne-Yvonne Guillerm-Erckelboudt, Alain Sarniguet. Linear relationship between Gaeumannomyces graminis var. tritici (Ggt) genotypic frequencies and disease severity on wheat roots in the field. Environmental Microbiology. 2006; 9 (2):492-499.
Chicago/Turabian StyleLionel Lebreton; Marie Gosme; Philippe Lucas; Anne-Yvonne Guillerm-Erckelboudt; Alain Sarniguet. 2006. "Linear relationship between Gaeumannomyces graminis var. tritici (Ggt) genotypic frequencies and disease severity on wheat roots in the field." Environmental Microbiology 9, no. 2: 492-499.