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Biology subjects

Buee, M.

Publications and source records attributed to Buee, M..

2 recordsLinked to original sources

Evidences of a component Allee effect for an invasive pathogen: Hymenoscy-phus fraxineus, the ash dieback agent

Invasive pathogens are a major threat to forest health especially in managed forest with low diversity. The die-back of European Fraxinus spp. caused by the fungus Hymenoscyphus fraxineus is the latest example of pathogen invasion causing widespread damage. Host resistance and environment, in particular stand factors were shown to strongly impact disease severity on European ash. The fact that H. fraxineus reproduce mostly through heterothallic sexual reproduction suggest that an Allee effect could limit the mating success at low host densities, thus limiting inoculum production and disease development. Populations of H. fraxineus were monitored during the fruiting period in a network of stands across a host density gradient in forest and non-forest environment. Ash dieback, basal area of ash, density of infected ash leaf debris (rachis) and apothecia in the litter and ascospores load in the air were determined in the different environments during two years. We showed significant differences between forest and non-forest environment with ash dieback, infection rate and inoculum production higher in forest settings. Host density significantly affected disease development, with crown dieback, density of infected rachis in the litter and inoculum production increasing with host density. We also demonstrated that fruiting rate, i.e. the number of apothecia per infected rachis dry weight, is strongly dependent on infected rachis density. Inoculum production is therefore limited at low host densities. Such a component Allee effect could be important in H. fraxineus epidemiology and invasion dynamic.

pathology↗

Microbial networks inferred from metabarcoding data lack replicability: consequences for next-generation biomonitoring

Plant-associated microbial interaction networks protect plants against disease. There is, therefore, a need to monitor in real time their responses to environmental changes to predict disease risk and adjust crop protection strategies. Next-Generation Biomonitoring (NGB) proposes to reconstruct automatically these networks from metabarcoding data, to complement ecological community properties commonly used for ecosystem health assessment. This study aimed to evaluate the benefits and shortcomings of community-level and network-level properties for biomonitoring. We specifically investigated whether microbial networks inferred from metabarcoding data show robust responses to agricultural practices, using the grapevine microbiota as a study system. Our results demonstrate a strong footprint of the agricultural practice on the metabarcoding data, when analyzed at the community level. The richness, diversity and evenness of fungal communities were significantly higher in organic than conventional plots. The cropping system also affected the composition of grapevine foliar fungal communities significantly. Contrary to our expectations, microbial networks were less sensitive to changes in agricultural practices than microbial communities, confirming that NGB should not only consider network-level properties but also community-level properties. Moreover, we found that microbial networks lacked replicability within a cropping system but that consensus networks, built from several network replicates, could generate relevant hypotheses of microbial interactions. As things stand, community-level properties appear to be a more reliable and statistically powerful monitoring option than network-level properties. Future developments, especially in network inference methods, are likely to challenge our findings and help to improve the monitoring of the ecosystem services provided by the plant microbiota.

ecology↗