Project Abstract

Forests cover approximately 25% of Europe, roughly 117 million ha, and are important reservoirs of genetic diversity, playing a decisive role in climate change mitigation through adaptation. The efficiency of mitigation will depend on the amounts of adaptive variability available in the different ecosystems of Europe and their response to new selective pressures. In this project, we will use a combination of high-throughput sequencing/genotyping of ecologically relevant genes and quantitative genetics experiments to evaluate levels of standing genetic variation and selective effects in natural forests. At the same time, we will characterise the environmental conditions to which the populations investigated are exposed and elucidate differences in morphological and functional traits in trees growing under different environmental conditions. We will also analyse the spatial distribution of phenotypes and genotypes, and their associated spatial ecological variability, in model European forest systems. To better generalise our findings and ensure practical applications, we have selected widespread and contrasted groups of forest trees (Pinus halepensis, P. pinaster, Abies alba, Picea abies, Quercus petraea and Q. robur). We have also considered major environmental drivers and relevant adaptive traits likely to respond to them, in view of expected future climate changes. The main environmental drivers considered here are drought, low temperatures and fire regime. These environmental drivers were chosen according to climate change predictions for Europe, which suggest notable changes in temperature, precipitation and in the frequency and intensity of heat waves. Because fire risks and climate are closely linked, future climate changes will certainly increase the length of the season with fire risk and the frequency of extreme events within fire seasons, even in regions that were not subjected to fire until now. Climate changes will directly affect local adaptation patterns across Europe, in particular at northern and southern latitudes. Permanent experimental plots (including 5-6 replicates by ecological gradient) will be installed in model forest systems in Spain, France, Italy, Germany and Sweden, providing additional value to this proposal, as well as field stations for long-term ecological genetic research in a variety of biomes widely represented in Europe. Another original contribution of this proposal is that we will focus on processes at the local scale. The advantage of using replicated experimental sites experiencing contrasted environmental challenges (stressed versus unstressed) but that are still within the reach of gene flow (typically large in trees, up to several kilometres) is that confounding factors, especially demographic history, gene pool origin or micro-local differences, should be minimized. Finally, the knowledge raised in this project will be used to evaluate the impact of future environmental change on European forests, using modelling platforms and statistical inference at the stand level. Our research achievements will contribute to current international initiatives to assess biodiversity at all levels of organization by identifying candidate genes of potential ecological significance in keystone tree species. We expect to provide the scientific community, especially evolutionary biologists and ecologists, with a deeper understanding of the importance of tree genetic diversity (at candidate genes and quantitative traits) for the sustainability of forest ecosystems and how this variation is structured in nature and will respond to environmental change. In addition, we will provide forest managers, nature conservationists and policy makers with indicators and guidelines to manage forest ecosystems and resources that are under pressure from global change and with effective tools for adaptive diversity monitoring using high-throughput genotyping techniques.

LinkTree: Linking genetic variability with ecological responses to environmental changes: forest trees as model systems
Project Leader: Santiago C. González-Martínez (CIFOR-INIA, Spain)
Web Manager: Gabriele Bucci (IGV-FI/CNR, Italy)