Biology subjects

Rimbaud, L.

Publications and source records attributed to Rimbaud, L..

8 recordsLinked to original sources

bioRxiv2025

Balancing disease control efficacy, resistance durability, and economic outcomes: Insights from a participatory modeling study integrating grapevine cultivar deployment timing with fungicide treatments

1In this study, we developed, assessed and compared strategies for deploying disease-resistant grapevine cultivars in partnership with a wine cooperative in South-West France. In four collaborative workshops, cooperative managers and multidisciplinary researchers jointly designed six feasible deployment strategies. These scenarios, implemented within real vineyards, involve planting resistant cultivars (RC) in vineyards (i) more than 30 years old, (ii) on 3.3% of the older plots each year or (iii) on plots located in no-treatment zone (due to proximity to watercourses or human dwellings), with and without a fixed maximum percentage of resistant cultivars in the vineyard. The strategies were evaluated with the landsepi model, which simulates the spread and evolution of pathogens across agricultural landscapes in response to host resistance deployment. The assessment criteria included downy mildew control efficacy, resistance durability, decrease in fungicide use, and economic benefits for individual vineyards and the cooperative. These scenarios led us to study more specifically the effects of two little-studied factors: (i) the presence or absence of fungicide applications and (ii) the massive or progressive introduction of resistant cultivars. Fungicide application substantially decreases the risk of resistance breakdown and complements the epidemiological control provided by resistant cultivars, particularly when the fitness costs of virulence are low. The probability of pathogens adapted to RC becoming established was generally lower with progressive than massive RC introduction; however, when establishment did occur, the time to establishment was shorter for progressive strategies at a cropping ratio [≥] 50%. Ultimately, the choice of RC introduction strategy had a minimal overall impact on disease control due to compensatory epidemiological and evolutionary processes, including dilution effects, and the probability and timing of resistance breakdown. These results are discussed in the broader framework of action-research approaches and the challenges and opportunities for resistant cultivar adoption by vine-growers. Our study highlights the potential of participatory approaches for developing practical, scientifically grounded strategies for sustainable viticulture.

evolutionary biology↗

bioRxiv2025

CMV can spread through plant to plant contact: implications for experimental practice

Cucumber mosaic virus (CMV) is a major plant pathogen with a worldwide distribution and the widest host range among all known plant viruses. It affects numerous crop species and can cause symptoms that significantly reduce yield. CMV is primarily transmitted by aphids and more sporadically through seeds. It is frequently studied in laboratory settings with the aim of developing effective control strategies. In many experiments, infected plants are placed in direct contact with healthy ones assuming that CMV cannot be transmitted in this way. However, this has not been formally demonstrated. Therefore, this study aimed to assess whether CMV can be transmitted through plant-to-plant contact. Infected plants were first rubbed against healthy ones and then left in contact for 28 days. Target plants were subsequently tested using DAS-ELISA to detect potential transmission. We applied this protocol in two separate experiments totalizing 15 combinations of plant species including pepper (Capsicum annuum) and five weed species commonly found in Espelette pepper fields (Capsella bursa-pastoris, Cerastium glomeratum, Stellaria media, Stachys arvensis and Trifolium repens). We found that CMV could be transmitted through contact between pepper and all tested weed species except T. repens. These findings highlight the importance of verifying whether a virus is capable of contact transmission before carrying out experiments in conditions that could lead to such contacts. In case of transmission, appropriate precautions will be crucial to avoid unintended transmissions.

plant biology↗

bioRxiv2024

Combining single-gene-resistant and pyramided cultivars in agricultural landscape compromises the benefits of pyramiding in most, but not all, productions situations

ContextWhile resistant cultivars are valuable in safeguarding crops against diseases, they can be rapidly overcome by pathogens. Numerous strategies have been proposed to delay pathogen adaptation (evolutionary control), while still ensuring effective protection (epidemiological control). Resistance genes can be deployed in 1) single-gene-resistant cultivars sown in the same field (mixture strategy) or in different fields (mosaic strategy), 2) a pyramided cultivar (pyramiding strategy) or 3) hybrid strategies that combine the three previous strategies. In addition, the spatial scale at which resistant cultivars are deployed can affect the plant-pathogens interaction: small fields are thought to reduce pest density and disease transmission. ObjectivesWe aim to compare these strategies, focusing on the effects of the simultaneous deployment of single-gene-resistant and pyramided cultivars sharing resistance genes in an agricultural landscape. We also investigate the impact of field size. MethodsWe used the spatially-explicit stochastic model landsepi to compare the evolutionary and epidemiological control across spatial scales and deployment strategies for two major resistance genes. ResultsThe evolutionary control provided by the pyramiding strategy is at risk when single-gene-resistant cultivars are concurrently planted in the landscape (hybrid strategies). The probabilities of pathogen mutation and the corresponding fitness costs play a crucial role in determining the feasibility of planting pyramided cultivars alongside single-gene-resistant ones. Instead, field size did not affect strategies recommendation. ConclusionsPlanting pyramided cultivars alongside single-gene-resistant ones should be avoided. Socio-economic perspectives for the adoption of resistance management strategies are discussed.

evolutionary biology↗

bioRxiv2023

Effects of pathogen sexual reproduction on the evolutionary and epidemiological control provided by deployment strategies for two major resistance genes in agricultural landscapes.

O_LIResistant 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 sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed. C_LIO_LIWe improved the spatially explicit stochastic model landsepi to 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. C_LIO_LISexual 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. C_LIO_LIWe 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). C_LI

evolutionary biology↗

bioRxiv2022

Durable resistance or efficient disease control?Adult Plant Resistance (APR) at the heart of the dilemma

AO_SCPLOWBSTRACTC_SCPLOWAdult plant resistance (APR) is an incomplete and delayed protection of plants against pathogens. At first glance, such resistance should be less efficient than classical major-effect resistance genes, which confer complete resistance from seedling stage, to reduce epidemics. However, by allowing some leaky levels of disease, APR genes are predicted to be more durable than major genes because they exert a weaker selection pressure on pathogens towards adaptation to resistance. However, the impact of partial efficiency and delayed mode of action of APR on the evolutionary and epidemiological outcomes of resistance deployment has never been tested. Using the demogenetic, spatially explicit, temporal, stochastic model landsepi, this study is a first attempt to investigate how resistance efficiency, age at the time of resistance activation and target pathogenicity trait jointly impact resistance durability and disease control at the landscape scale. Our numerical experiments explore the deployment of APR in a simulated agricultural landscape, alone or together with a major resistance gene. As a case study, the mathematical model has been parameterised for rust fungi (genus Puccinia) of cereal crops, for which extensive data are available. Our simulations confirm that weak efficiency and delayed activation of APR genes reduce the selection pressure applied on pathogens and their propensity to overcome resistance, but do not confer effective protection. On the other hand, stronger APR genes (which increase selection pressure on the pathogen) may be quickly overcome but have the potential to provide some disease protection in the short-term. This is attributed to strong competition between different pathogen genotypes and the presence of fitness costs of adaptation, especially when APR genes are deployed together with a major resistance gene via crop mixtures or rotations.

evolutionary biology↗

bioRxiv2021

The role of interference between vectors in control of plant diseases

Aphids are the primary vector of plant viruses. Transient aphids, which probe several plants per day, are considered to be the principal vectors of non-persistently transmitted (NPT) viruses. However, resident aphids, which can complete their life cycle on a single host and are affected by agronomic practices, can transmit NPT viruses as well. Moreover, they can interfere both directly and indirectly with transient aphids, eventually shaping plant disease dynamics. By mean of an epidemiological model, originally accounting for ecological principles and agronomic practices, we explore the consequences of fertilization and irrigation, pesticide deployment and roguing of infected plants on the spread of viral diseases in crops. Our results indicate that the spread of NPT viruses can be i) both reduced or increased by fertilization and irrigation, depending on whether the interference is direct or indirect; ii) counter-intuitively increased by pesticide application and iii) reduced by roguing infected plants. We show that a better understanding of vectors interactions would enhance our understanding of disease transmission, supporting the development of disease management strategies. Author summaryA range of both experimental and theoretical studies show that the behaviour and population dynamics of insects depend strongly upon interactions with other insect species. These interactions have the potential to greatly affect the dynamics of insect-vectored plant disease, as transmission of viruses is intimately dependent on the local density of vectors, as well as how they select and move between potential host plants. Surprisingly, the effects of interaction between vector species on epidemics remains little studied and even worse understood, probably because experimentation is costly and difficult. Here, we present a model which permits to investigate the effect of interaction between a virus, two vector species, and the host plant on the spread of viral disease in crops. In this study, our model is used to explore the consequences of common agronomic practices on epidemics. Our study highlights the importance of exploring vectors interactions to enhance the understanding of disease transmission, supporting the development of disease management strategies.

ecology↗

bioRxiv2018

Heuristic optimisation of the management strategy of a plant epidemic using sequential sensitivity analyses

O_LIOptimisation of management strategies of epidemics is often limited by constraints on experiments at large spatiotemporal scales. A promising approach consists in modelling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimisation of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach based on sequential use of sensitivity analysis. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach and plum), and its management in orchards, mainly based on surveillance and tree removal.\nC_LIO_LIOur approach is based on three sensitivity analyses which respectively aim to: i) identify the key parameters of a spatiotemporal model simulating disease spread and control; ii) approach optimal values for the key parameters; iii) refine the optimisation.\nC_LIO_LIWe highlight the importance of carefully designing the removal procedure, and propose improved strategies with regard to an economic criterion accounting for both the cost of the different control measures and the benefit generated by productive trees.\nC_LIO_LIWe expect that our general approach will help policymakers to design sustainable and cost-effective strategies for the management of infectious diseases.\nC_LI

epidemiology↗

bioRxiv2018

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges.\n\nTherefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters.\n\nThis article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.\n\nAuthor summaryThere are many recent examples which demonstrate the evolutionary potential of plant pathogens to overcome the resistances deployed in agricultural landscapes to protect our crops. Increasingly, it is recognised that how resistance is deployed spatially and temporally can impact on rates of pathogen evolution and resistance breakdown. Such deployment strategies are mainly based on the combination of several sources of resistance at different spatiotemporal scales. However, comparison of these strategies in a predictive sense is not an easy task, owing to the logistical difficulties associated with experiments involving the spread of a pathogen at large spatio-temporal scales. Moreover, both the durability of a strategy and the epidemiological protection it provides to crops must be assessed since these evaluation criteria are not necessarily correlated. Surprisingly, no current simulation model allows a thorough comparison of the different options. Here we describe a spatio-temporal model able to simulate a wide range of deployment strategies and resistance sources. This model, implemented in the R package landsepi, facilitates assessment of both epidemiological and evolutionary outcomes across simulated scenarios. In this work, the model is used to investigate the combination of different sources of resistance against fungal diseases such as rusts of cereal crops.

evolutionary biology↗