Eco-evolutionary data fusion approaches to predict the evolutionary potential of European and Oriental fir species (Abies spp.) facing climate change

Chapter 1: Using paleo-ecological data and spatially explicit population genetic simulations to predict

the genetic diversity of European and Oriental fir species (Abies spp.) across their range.

Chapter 2: Detecting the genomic signature of climate adaptation in European and Oriental fir species.

Existing and novel genetic data will be generated for European and Oriental fir species in the

framework of MyGardenOfTrees and used to detect the signature of selection to past climatic changes

as unusual population differentiation and unusually high spatial autocorrelation in population allele

frequencies in comparison to simulated data (Chapter 1). The main novelty of this work will be using

biologically meaningful, spatially explicit, null hypothesis when detecting loci under selection.

Chapter 3: Fusion of phenotypic and genomic data to predict optimal fir provenances under future

climate scenarios across Europe. Using novel trait data (germination, survival and early growth)

generated in the framework of MyGardenOfTrees, in combination with the genomic data (Chapter 2), a

genomic prediction model will be developed using machine learning approaches and implemented as a

web tool. The aim of this chapter will be to bring together the different results from the three Chapters

and develop guidelines for an adaptive forest management approach for silver fir.