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Macroecology and Biogeography meeting

May 3rd to 6th 2023 - Universität Bayreuth

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Phenotypic plasticity and genetics in the adaptation of forest trees to climate change: results from large-scale provenance trials

Alessandro Di Fabio1, Jürgen Kreyling1
1 Experimental plant ecology, Universität Greifswald

P 1.9 in Poster Session Thursday (15:15-16:00)

Most climate models for the 21st century predict rates of change much faster than the natural capacity of forest trees to adapt through migration or natural selection. For this reason, it is likely that phenotypic plasticity will play an important role in the adaptation of forest trees to climate change during the course of the current century.

We investigated the phenotypic plasticity of three economically and ecologically important forest tree species (Fagus sylvatica, Picea abies, Pseudotsuga menziesii) by using large networks of international provenance trials.

The trials contain the same provenances grown under widely different climatic conditions, covering a significant proportion of the climatic range of the species, which enables to quantify the effects of climate on the growth performance of the provenances. We calculated a climatic distance for each tree, quantifying the difference between the climate at provenance origin and the climate of the trial site.

Furthermore, the availability of measurements of survival, height, and diameter for individual trees (and not averaged within each provenance) made it possible obtain additional information on the source of the variability in growth performance.

By calculating a phenotypic plasticity index for each provenance, and analysing the correlation between growth and the climatic distance, it was possible to determine if the variations in growth measured were due to genetic effects, environmental conditions, an interaction of the two, or intrinsic individual variability.

The results from our work elucidate the relative importance of genetic effects and plastic response in the species studied, and can be use by stakeholders to better inform their decision-making processes, allowing them to focus on the most relevant source of growth performance variability.

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