*NERC E3* Estimating the rate of adaptation of forest trees to new environments

The question of how best to prepare our forests for the challenge of climate change is a hotly debated topic around the world, stimulated by current pressure to plant and restore forest for timber production, carbon sequestration and habitat creation. Although tree species have been shown to have high levels of genetic diversity and adaptive potential, meaning an evolutionary response to changing conditions is possible, their typically long generation times may create an adaptive lag and it has been argued that ‘pre-adapted’ genotypes should be transferred into current populations in anticipation of climate shifts. However, there is considerable disagreement regarding the need for such transfers, given the associated risks of maladaptation to contemporary conditions, accidental transfer of pests or pathogens, and the likelihood that imported genetic diversity would in any case add only marginally to highly diverse local gene pools.

An alternative course of action is, as far as possible, to use locally adapted seed sources for restoration or new plantings, with accompanying measures to ensure recruitment and turnover of the population and hence enable adaptive change. To determine which of these approaches should be adopted, a question critical for the early development of clear policy on forest management under climate change, it would be valuable to explore and demonstrate the rate at which tree species can adapt to new environments. This project will aim to tackle this question using Scots pine (Pinus sylvestris) as a model.

Recent work has shown fine scale adaptation to existing environmental gradients in Scots pine, in populations established since postglacial colonisation (Salmela et al., 2011, Donnelly et al., 2016). However, similar local adaptation may have occurred much faster following recent transfers of seed to southern Britain, North America and New Zealand where the species grows as an exotic and has naturalised. The project will make use of well characterised seed transfers to test for the signature of adaptation and to estimate the potential for future change.

This project will challenge the successful candidate to address the question of how fast tree species can adapt to novel environments. The student will design and conduct laboratory and field experiments and make use of historical data to generate novel findings. The project will contribute to the national debate on appropriate seed choice through publication in peer reviewed journals and translating findings into language accessible to practitioners and policymakers. The student will have the opportunity to train in a broad range of techniques, from field-based work in forests and experimental plantings, through molecular biology lab work to modelling of rates of genetic change under natural selection. Given its policy prominence, the project will also demand the development of skills in communication and dissemination of scientific results to a range of audiences.

Key Research Questions
1. Have populations of introduced tree species measurably adapted to new environments?
2. Does the estimated rate of evolution of tree species indicate a capacity to adapt to predicted environmental change?
3. How fast did UK tree populations adapt following post-glacial colonisation?

Methodology.
The project will make use primarily of common garden experiments based on seed collections obtained from populations of forest trees in home and introduced environments. The experiments would be established and run in glasshouses at CEH Edinburgh. Datasets would encompass measurement of a range of early growth traits including phenology of initiation and cessation of growth, morphology, responses to stress. In parallel, characterisation of UK tree populations using new molecular markers will be undertaken to reconstruct the pattern and mode of establishment of the post-glacial population. Simulation modelling using molecular data may be employed to estimate timing of population establishment, and likely rate of adaptation to new site conditions given the contemporary state of adaptive divergence.