International audienceA large number of studies have tried to understand the determinants of local species richness, i.e. α-diversity. Studies dealing with β-diversity are considerably less numerous but their number has increased in the recent years. In this study, we assessed the relative importance of local and landscape (i.e. composition and connectivity) variables in explaining α- and β-diversities (species turnover and nestedness) of three highly diverse groups, differing in mobility and dispersal: plants, spiders, and carabids. Sampling took place in 2013, using suction samplers for arthropods and phytosociological relevés for vegetation, in 77 hay meadows distributed along 200 km of the Loire Valley (France). We found plant α-diversity to be driven by local factors, whereas spider and carabid α-diversities were mostly determined by landscape factors (by composition and connectivity, respectively). Nestedness was negligible for the three groups. Plant β-diversity was also mainly influenced by local factors, whereas spider β-diversity was driven by landscape factors (composition and connectivity, equally). Surprisingly, carabid β-diversity was mainly influenced by local factors and landscape connectivity. Despite these differences, plant, spider, and carabid β-diversities were not different, suggesting comparable dispersal abilities and/or a low connectivity at large scale, which is in accordance with the high species turnover observed here. Managing biodiversity in meadows consequently necessitates acting at local and landscape scales, the first targeting plants and the second arthropod

International audiencetVegetation is a major environmental factor influencing habitat selection in bird species. High resolutionmapping of vegetation cover is essential to model the distribution of populations and improve the man-agement of breeding habitats. However, the task is challenging for grassland birds because microhabitatvariations relevant at the territory scale cannot be measured continuously over large areas to delineateareas of higher suitability. Remote sensing may help to circumvent this problem. We addressed thisissue by using SPOT 5 imagery and phytosociological data. We mapped grassland vegetation in a flood-plain using two methods. We (i) mapped the continuous Ellenberg index of moisture and (ii) identified5 vegetation classes distributed across the wetness gradient. These two methods produced consistentoutput maps, but they also provided complementary results. Ellenberg index is a valuable proxy for soilmoisture while the class approach provided more information about vegetation structure, and possiblytrophic resources. In spite of the apparent uniformity of meadows, our data show that birds do not settlerandomly along the moisture and vegetation gradients. Overall birds tend to avoid the driest vegetationclasses, i.e. the highest grounds. Thus, vegetation maps based on remote sensing could be valuable toolsto study habitat selection and niche partition in grassland bird communities. It is also a valuable tool forconservation and habitat management