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Hiding for surviving? Last-glacial maximum phylogeography to inform spatially-explicit predictions on the ability of Alpine biota to migrate as a response to climate change in the Swiss Alps. Current biodiversity patterns in the northern hemisphere have primarily been shaped by climatic fluctuations that took place during the Pleistocene. While the identification of glacial refugia and post-glacial migration routes has long been a major focus in historical biogeography, the question of where species currently restricted to Alpine areas in particular persisted during the Ice Age has long appeared as a striking puzzle. The development of spatially explicit models of coalescence, which consider movement of individuals and genes while attempting to connect current patterns of genetic variation with the evolution of the species range over time, opens an avenue of research to address such questions and inform current attempts at assessing the ability of species to track areas of suitable climate. The main objective of the GEN4MIG project is to integrate fine-scale ecological modelling and spatially-explicit coalescence simulations to address the following questions: Where did Alpine biota survive the Last Glacial Maximum period? At which rate did effective recolonization occur, and how do these rates differ within and among biota characterized by contrasting dispersal syndromes? What are the chances for biota, given species niche requirements and dispersal limitations, to successfully track areas of suitable climate at the landscape scale in the next decades? Fine scale distribution data and genetic mapping of genome-wide molecular variation will be generated for selected Alpine species from all groups of land plants (including mosses, liverworts and ferns) and trophically-linked insects in the Western Swiss Alps. Species Distribution Models built from micro-climatic, edaphic, geographic predictors and, in the case of trophically-linked insects, host-plant distributions, will inform spatially explicit coalescence simulations that will be implemented to test competing scenarios of post-glacial recolonization and generate estimates of population size and migration rates. Species Distribution Models and migration rates will finally be integrated in spatially-explicit dynamic dispersal simulations of species migrations as a response to ongoing and future climate changes.
The geographical distributions of bryophyte species remain incompletely known, especially in the Tropics. This project aims at determining the ranges of tropical liverwort species based on a synthesis of all biogeographically relevant information.