Communication Dans Un Congrès Année : 2023

A modelling tool to explore landscape management strategies to promote pest control and limit beet yellows disease spread

Résumé

The ban on the use of neonicotinoids makes it necessary to rethink the prophylaxis of beet crops. In recent years, outbreaks of green peach aphids (Myzus persicae), vectors of beet yellows viruses, have been observed, resulting in significant yield losses. A potentially effective lever to control aphid populations is the management of the agricultural landscape to limit the migration of aphids within fields and their dispersal between fields, and to promote the development and activity of natural enemies involved in pest biological control. The positive effect of landscape heterogeneity on biological control is now clearly accepted (Champlin-Kramer et al. 2011, Véres et al. 2013). However, while this general pattern is established, its translation into landscape management modalities is made difficult by the highly contextual nature of the processes involved (Karp et al. 2019). Landscape effects depend on the functional characteristics of pests and natural enemies (Martin et al. 2019), and can be strongly modulated by agricultural practices carried out locally in the fields (e.g., pesticide effects in Ricci et al. 2019). For highly polyphagous species such as M. persicae, it is necessary to think carefully about the mosaic of plants that make up the landscape, both host crops to pests and non-crop habitats. We developed a spatially explicit model to explore the potential effects of deploying agroecological infrastructures, diversifying crop rotation or reducing field size in reducing green peach aphid populations and the incidence of beet disease at the landscape level. On existing agricultural landscape (modelled using GIS data), the model simulates aphid population dynamics (growth, movement, biocontrol by natural enemies whose abundance is modulated by the surrounding landscape structure, wintering), and virus transmission between beet plants and aphids. The model operates on a daily time-step and over several years, and integrates climatic conditions and agricultural practices such as the use of pesticides and sowing schedules. A sensitivity analysis was carried out to determine the most sensitive parameters, which were calibrated using data from a multi-year survey of a monitoring network in France. In a second step, we tested the sensitivity of the model to landscape parameters. Finally, we tested contrasted scenarios of landscape management to identify the most effective ones for reducing disease incidence in the landscape. The outputs of the simulations will be used to discuss with stakeholders the conditions for the deployment of new management methods at the territorial scale.

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Dates et versions

hal-04668166 , version 1 (06-08-2024)

Identifiants

  • HAL Id : hal-04668166 , version 1

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Gaëlle van Frank, Olivier Therond, Aude Vialatte. A modelling tool to explore landscape management strategies to promote pest control and limit beet yellows disease spread. European Conference on Ecological Modelling, UFZ, Sep 2023, Leipzig, Germany. ⟨hal-04668166⟩
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