Sylvain Poggi
Institut national de la recherche agronomique
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Featured researches published by Sylvain Poggi.
Landscape Ecology | 2015
Camille Puech; Sylvain Poggi; Stéphanie Aviron
AbstractFarming practices are rarely considered in the description of agricultural landscapes. However, the variety of cropping systems creates a particular kind of heterogeneity which can strongly affect the diversity of species living in agro-ecosystems, and consequently the ecosystem services they provide. In this study, we investigate the effects of landscape composition and configuration of organic and conventional farming practices on three groups of aphids’ natural enemies, compared to field habitat quality and land cover heterogeneity. A field survey was carried out in 2012 and 2013 in western France (Brittany). Ladybirds, carabid beetles and parasitoids were sampled in 40 pairs of organic and conventional winter wheat fields, distributed along a landscape gradient of organic farming areas. The relationships between farming practices and natural enemies were investigated with a PLS-path modeling approach, hardly ever used in ecology but presenting numerous advantages to analyze multivariate systems. Results showed that abundance and species richness of natural enemies were mainly affected by local farming practices, with a higher diversity in organic fields. To a lesser extent, landscapes also affected natural enemies, but only in relation to the length and configuration of hedgerows. Our results open up avenues for the design of agricultural landscapes since our results suggest that natural enemy diversity can be enhanced without a specific organization of organic fields. We discuss methodological issues regarding the description and the analysis of farming practices at the landscape scale. We argue that such investigations require high quality maps covering large spatial extents, and the use of statistical tools providing a good handling of complex relationships occurring in agro-ecosystems.
PLOS ONE | 2016
Ronan Le Cointe; Thomas E. Simon; Patrick Delarue; Maxime R. Hervé; Melen Leclerc; Sylvain Poggi
Reducing our reliance on pesticides is an essential step towards the sustainability of agricultural production. One approach involves the rational use of pesticides combined with innovative crop management. Most control strategies currently focus on the temporal aspect of epidemics, e.g. determining the optimal date for spraying, regardless of the spatial mechanics and ecology of disease spread. Designing innovative pest management strategies incorporating the spatial aspect of epidemics involves thorough knowledge on how disease control affects the life-history traits of the pathogen. In this study, using Rhizoctonia solani/Raphanus sativus as an example of a soil-borne pathosystem, we investigated the effects of a chemical control currently used by growers, Monceren® L, on key epidemiological components (saprotrophic spread and infectivity). We tested the potential “shield effect” of Monceren® L on pathogenic spread in a site-specific application context, i.e. the efficiency of this chemical to contain the spread of the fungus from an infected host when application is spatially localized, in our case, a strip placed between the infected host and a recipient bait. Our results showed that Monceren® L mainly inhibits the saprotrophic spread of the fungus in soil and may prevent the fungus from reaching its host plant. However, perhaps surprisingly we did not detect any significant effect of the fungicide on the pathogen infectivity. Finally, highly localized application of the fungicide—a narrow strip of soil (12.5 mm wide) sprayed with Monceren® L—significantly decreased local transmission of the pathogen, suggesting lowered risk of occurrence of invasive epidemics. Our results highlight that detailed knowledge on epidemiological processes could contribute to the design of innovative management strategies based on precision agriculture tools to improve the efficacy of disease control and reduce pesticide use.
PLOS ONE | 2014
Thomas E. Simon; Ronan Le Cointe; Patrick Delarue; Stéphanie Morlière; Françoise Montfort; Maxime R. Hervé; Sylvain Poggi
Spread of soil-borne fungal plant pathogens is mainly driven by the amount of resources the pathogen is able to capture and exploit should it behave either as a saprotroph or a parasite. Despite their importance in understanding the fungal spread in agricultural ecosystems, experimental data related to exploitation of infected host plants by the pathogen remain scarce. Using Rhizoctonia solani / Raphanus sativus as a model pathosystem, we have obtained evidence on the link between ontogenic resistance of a tuberizing host and (i) its susceptibility to the pathogen and (ii) after infection, the ability of the fungus to spread in soil. Based on a highly replicable experimental system, we first show that infection success strongly depends on the host phenological stage. The nature of the disease symptoms abruptly changes depending on whether infection occurred before or after host tuberization, switching from damping-off to necrosis respectively. Our investigations also demonstrate that fungal spread in soil still depends on the host phenological stage at the moment of infection. High, medium, or low spread occurred when infection was respectively before, during, or after the tuberization process. Implications for crop protection are discussed.
Agriculture, Ecosystems & Environment | 2014
Camille Puech; Alexandre Joannon; Sylvain Poggi; Stéphanie Aviron
Ecology | 2011
Frédéric M. Hamelin; Magda Castel; Sylvain Poggi; Didier Andrivon; Ludovic Mailleret
Agriculture, Ecosystems & Environment | 2016
Stéphanie Aviron; Sylvain Poggi; Yann-David Varennes; Amélie Lefevre
Ecological Modelling | 2015
Yoann Bourhis; Sylvain Poggi; Youcef Mammeri; Anne-Marie Cortesero; Anne Le Ralec; Nicolas Parisey
Ecological Complexity | 2016
Nicolas Parisey; Yoann Bourhis; Lionel Roques; Samuel Soubeyrand; Benoît Ricci; Sylvain Poggi
Ecological Modelling | 2018
Benoit Bellot; Sylvain Poggi; Yoann Bourhis; Nicolas Parisey
Ecological Modelling | 2018
Benoît Ricci; Sandrine Petit; Charlotte Allanic; Marie Langot; Nicolas Parisey; Sylvain Poggi