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A spatiotemporal model for predicting grain aphid population dynamics and optimizing insecticide sprays at the scale of continental France

Abstract : We expose here a detailed spatially explicit model of aphid population dynamics at the scale of a whole country (Metropolitan France). It is based on convection-diffusionreaction equations, driven by abiotic and biotic factors. The target species is the grain aphid, Sitobion avenae F., considering both its winged and apterousmorphs. In this preliminary work, simulations for year 2004 (an outbreak case) produced realistic aphid densities, and showed that both spatial and temporal S. avenae population dynamics can be represented as an irregular wave of population peak densities from southwest to northeast of the country, driven by gradients or differences in temperature, wheat phenology, and wheat surfaces. This wave pattern fits well to our knowledge of S. avenae phenology. The effects of three insecticide spray regimes were simulated in five different sites and showed that insecticide sprays were ineffective in terms of yield increase after wheat flowering. After suitable validation, which will require some further years of observations, the model will be used to forecast aphid densities in real time at any date or growth stage of the crop anywhere in the country. It will be the backbone of a decision support system, forecasting yield losses at the level of a field. The model intends then to complete the punctual forecasting provided by older models by a comprehensive spatial view on a large area and leads to the diminution of insecticide sprayings in wheat crops.
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-00999523
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Submitted on : Tuesday, June 3, 2014 - 4:31:59 PM
Last modification on : Monday, July 6, 2020 - 3:39:56 PM

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Mamadou Ciss, Nicolas Parisey, Fabrice Moreau, Charles-Antoine Dedryver, Jean-Sébastien Pierre. A spatiotemporal model for predicting grain aphid population dynamics and optimizing insecticide sprays at the scale of continental France. Environmental Science and Pollution Research, Springer Verlag, 2014, 21 (7), pp.4819-4827. ⟨10.1007/s11356-013-2245-1⟩. ⟨hal-00999523⟩

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