Abstract
Knowledge on the adaptation of trees to rapid environmental changes is essential to preserve forests and their ecosystem services under climate change. Treeline populations are particularly suitable for studying adaptation processes in trees, as environmental stress together with reduced gene flow can enhance local adaptation. We investigated white spruce (Picea glauca) populations in Alaska on one moisture-limited and two cold-limited treeline sites with a paired plot design of one forest and one treeline population each, resulting in six plots. Additionally, one forest plot in the middle of the distribution range complements the study design. We combined spatial, climatic and dendrochronological data with neutral genetic marker of 2203 trees to investigate population genetic structure and drivers of tree growth. We used several individual-based approaches including random slope mixed-effects models to test the influence of genetic similarity and microenvironment on growth performance. A high degree of genetic diversity was found within each of the seven plots associated with high rates of gene flow. We discovered a low genetic differentiation between the three sites which was better explained by geographic distances than by environmental differences, indicating genetic drift as the main driver of population differentiation. Our findings indicated that microenvironmental features had an overall larger influence on growth performances than genetic similarity among individuals. The effects of climate on growth differed between sites but were smaller than the effect of tree size. Overall, our results suggest that the high genetic diversity of white spruce may result in a wider range of phenotypes which enhances the efficiency of selection when the species is facing rapid climatic changes. In addition, the large intra-individual variability in growth responses may indicate the high phenotypic plasticity of white spruce which can buffer short-term environmental changes and, thus, allow enduring the present changing climate conditions.
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