Integrating genomic data and species distribution modelling to infer the demographic history of oak (Quercus sp.) communities and forecast their responses to global change
One of the most important challenges of conservation biology is to predict how organisms will respond to the impacts of anthropogenic global change. Although the integration of genomic data and species distribution models has contributed to increase our knowledge on this respect, the scope of the obtained inferences has been very limited by the fact that most studies have focused on a single species and very rarely have analyzed entire communities. The objective of this project is to obtain genomic data to infer past demographic changes and forecast the responses of both species and entire communities to different hypothetical scenarios of climate change.
Specifically, we will use as study system oak (Quercus sp.) communities from California to i) infer the demographic history of the different species within the community and determine how different taxa have experienced similar or distinct responses to past climate changes (e.g. Pleistocene glaciations); ii) We will employ genomic data to test different models of gene flow that integrate both abiotic factors (climate, topography) and inter-specific interactions (competition, facilitation); iii) Finally, we will infer demographic parameters (carrying capacities, dispersal rates) for a representative number of species forming the different oak communities from California and use them to forecast their population trends in response to future climate change, which will help to predict potential processes of population fragmentation/connection and loss/gain of genetic diversity. Overall, this project aims to address the study of different demographic aspects to get more robust predictions about the consequences of global change at the level of genetic diversity, species and communities.