Data from: Forecasting changes in population genetic structure of alpine plants in response to global warming ...

• Main Authors: Jay, Flora, Manel, Stéphanie, Alvarez, Nadir, Durand, Eric Y., Thuiller, Wilfried, Holderegger, Rolf, Taberlet, Pierre, François, Olivier
• Format: Dataset
• Language: English
• Published: Dryad 2012
• Subjects: Arabis alpina L.; Saxifraga stellaris L.; Hedysarum hedysaroides L. Schinz & Thell. s.l.; Sesleria caerulea L. Ard; Androsace obtusifolia All.; Gentiana nivalis L.; Gypsophila repens L.; Cerastium uniflorum Clairv.; Loiseleuria procumbens L. Desv.; Juncus trifidus L.; Geum reptans L.; Luzula alpinopilosa Chaix Breistr.; Campanula barbata L.; Trifolium alpinum L.; Phyteuma hemisphaericum L.; Dryas octopetala L.; Geum montanum L.; Ligusticum mutellinoides Cr. Vill.; Hypochaeris uniflora Vill.; Holocene; Rhododendron ferrugineum L.; Dryas octopetala
• Online Access: https://dx.doi.org/10.5061/dryad.777jk760; https://datadryad.org/stash/dataset/doi:10.5061/dryad.777jk760

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways due to adaptation to their environment. Here, we introduced ancestry distribution models, i.e., statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25°C to 4°C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a northeast direction ... : DataMarker data, geographic, topographic and climatic information for 20 alpine plant species ...