AdaPtive Potential of Alpine Tree Species to global change – APPATS

1) We will determine the genetic diversity within and between sampled sites for each species using ddRADseq technic. From the short reads, we will perform SNP/genotype calling and data cleaning essentially to remove paralogues.
2) We will compile physiological and morphometric traits (i.e. maximal height, trunk diameter, etc). Species diversity measurements are available thanks to the exhaustive species sampling from BioProFor, allowing to take into account community composition in our analysis. Abiotic measures describing the site conditions have already been taken on the sampled sites: temperature, hygrometry, and elevation.
3) Using our de-novo SNP dataset, we will first examine how genetic variability is distributed across the sampled areas. We will perform PCA, Fst and Clustering analysis in order to understand how the whole genome diversity is affected by geography (latitude, longitude). The outcome of this preliminary result is needed to define proper null hypothesis to efficiently test for selection in the subsequent analysis.
4) Association studies will be conducted to relate each allele frequency of a focal species to its phenotypic traits (i.e. wood density, growth rate), to its biotic environment (quantified for instance by the Shannon index) and to ecological variables (e.g., elevation, temperature, etc), taking into account the population genetic structure inferred previously from neutral markers. PCA- and Fst-based genome scans will also be applied in order to detect outliers loci departing from the genome-wide population structure. These analyses will reveal candidate SNPs within (or in linkage with) genes potentially involved in local adaptation process. Using multivariate analysis methods (redundancy analysis RDA, canonical analysis of principal coordinates CAP) on candidate SNPs, we will test for multigenic adaptation to critical local conditions of the environment that are known to be driven by climate change (i.e. aridity, species richness).

work in progress

work in progress

work in progress

Mediterranean and Alpine forests are among the most sensitive ecosystems to climate change. Significant progresses have been made in the prediction of their future response by the development of statistical and process-based models integrating functional traits. However, these approaches do not take the evolutionary potential of species into account. This project aims to fill this gap by assessing in-situ the adaptive potential - usually measured by common garden experiments - of four of the most abundant alpine tree species. To depict the potential response of these key species to selective pressure induced by climate change, individuals will be sampled along a large environmental gradient in plots with various diversity, and genotyped using SNP markers. Candidate SNPs for the local adaptation of trees will be detected with genome scans. Ultimately, these SNPs will allow detecting patterns of multigenic selection in response to critical local conditions impacted by climate change, either abiotic (aridity) or biotic (species richness).