Pradervand Jean Nicolas, Dubuis Anne, Pellissier Loïc, Guisan Antoine, Randin Christophe F. (2014), Very high resolution environmental predictors in species distribution models: Moving beyond topography?, in Progress in Physical Geography
, 38(1), 79-96.
Pellissier Loïc, Espíndola Anahí, Pradervand Jean Nicolas, Dubuis Anne, Pottier Julien, Ferrier Simon, Guisan Antoine (2013), A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties, in Journal of Biogeography
, 40(10), 1939-1946.
Pagni Marco, Niculita-Hirzel Helene, Pellissier Loic, Dubuis Anne, Xenarios Ioannis, Guisan Antoine, Sanders Ian R., Goudet Jerome, Guex Nicolas (2013), Density-based hierarchical clustering of pyro-sequences on a large scale-the case of fungal ITS1, in BIOINFORMATICS
, 29(10), 1268-1274.
Pellissier Loïc, Pinto-Figueroa Eric A., Niculita-Hirzel Hélène, Moora Mari, Villard Lucas, Goudét Jérôme, Guex Nicolas, Pagni Marco, Xenarios Loannis, Sanders Ian R., Guisan Antoine (2013), Plant species distributions along environmental gradients: Do belowground interactions with fungi matter?, in Frontiers in Plant Science
, 4(DEC), 9p.
Pellissier Loïc, Niculita-Hirzel Hélène, Dubuis Anne, Pagni Marco, Guex Nicolas, Ndiribe Charlotte, Salamin Nicolas, Xénarios Ioannis, Goudét Jérôme, Sanders Ian R., Guisan Antoine (2013), Soil fungal communities of grasslands are environmentally structured at a regional scale in the Alps, in Molecular Ecology
, 23(17), 4274-4290.
Vicente J. Randin C.F. Pottier J. Gonçalves J. Broennimann O. Lomba A. Honrado J. Guisan A., A framework for assessing the scale of influence of environmental factors on ecological patterns, in Ecological Complexity
Mod H.K. le Roux P.C. Guisan A. Luoto M., Biotic interactions boost spatial models of species richness, in Ecography
Merow C. Smith M.J. Edwards T.C. Guisan A. McMahon S. Normand S. Thuiller W. Wuest R. Zimmer, What do we gain from simplicity versus complexity in species distribution models?, in Ecography
Background. A project is currently under way that investigates community assembly and biotic interactions in mountain meadows communities, and how these could be integrated into predictions of species distributions. More than 900 plots were sampled for plants and among these >150 for butterflies and bumblebees across a 700 km2 mountainous study area in the Western Swiss Alps. Species traits and phylogeny data are additionally available for the >250 most abundant plant species and >130 butterfly species. This study should improve our understanding of how plant and insect communities assemble in geographic space, under current and future climate. In this context, soils were also surveyed in the same plant communities (2008-2009), resulting in soil being sampled in >250 distinct sites along a wide elevation gradient. For 205 of these soil samples, DNA extractions were conducted in addition to standard biogeochemical analyses, yielding a set of soil DNA samples of unprecedented large size. To our knowledge, no other dataset exists that is as exhaustive, and spatially-explicit at such very high spatial resolution (potentially <1m) and large extent (>700km2). Pyrosequencing of soil DNA is currently ongoing only for fungal communities, but other biotic groups could also be investigated.Aim. Here, we intend to extend the pyrosequencing of soil DNA to microbial communities and then test several hypotheses on the geographic distribution and ecology of fungal and microbial soil communities, and their relationship to macro-organisms (plants, insects). We intend more particularly to answer the main, still largely unanswered question: Do soil fungi and bacteria taxa exhibit biogeographic patterns? Or alternatively, are all taxa everywhere? If they do exhibit non-random geographic and environmental patterns, are these similar to those of macro-organisms? If similar, then how interdependent are distributions of micro- and macro-organisms? If distinct, then what factors are responsible for the divergence? And more specifically, which factors explains the distribution of microbial taxa in such mountain landscape? Do they affect - and if so how - the assembly of macro-organisms like plants? Finally, we will use all findings to assess the potential impact of climate and landuse changes on microbial communities.Methods. The DNA samples already extracted for the 205 2 m x 2 m plots described above will be used as initial input. A first PhD project (subproject 1) will focus on obtaining high-throughput sequencing data of bacterial communities, using high-depth phylogenetic analysis to obtain genus and species level classifications and microbial community composition. Together with data on fungal communities, it will then be to analyze their distribution and ecology with computer intensive bioinformatic and advanced statistical methods, in combination with vegetation composition, soil conditions, and topo-climatic and landuse characteristics. If needed, complementary field sampling may be performed. A second PhD project (subproject 2) will focus on developing a very high-resolution spatial modelling framework and use it to assess and predict the distribution of microbial operational taxonomic units and their assemblages under current and future climate. Funding requested. Funding is only requested for the PhD student of subproject 1 and for lab consumables including ultra high throughput sequencing. The second PhD student in subproject 2 will be entirely granted by UNIL as matching funds to this ProDoc project.Expected value of the proposed project. With this project, we aim at providing a better understanding of: (i) the biogeography and ecology of soil microorganisms, especially on factors - environmental or historic - shaping soil microbial communities in the Alps; (ii) the relation between soil microorganisms and plant species assemblages; (iii) how climate and land use changes may impact on micro-organisms distribution and communities. Coupled with results from the separate BioAssemble project (plants, soils, insects), these results will additionally be used to provide a comprehensive assessment of biodiversity distribution and ecosystem functioning in such mountain environments, with huge implications for assessing the sensitivity of these systems to ongoing anthropogenic global change.