Range-wide variation in local adaptation and phenotypic plasticity of fitness-related traits in Fagus sylvatica and their implications under climate change

Aim To better understand and more realistically predict future species distribution ranges, it is critical to account for local adaptation and phenotypic plasticity in populations' responses to climate. This is challenging because local adaptation and phenotypic plasticity are trait-dependent and traits covary along climatic gradients, with differential consequences for fitness. Our aim is to quantify local adaptation and phenotypic plasticity of vertical and radial growth, leaf flushing and survival across the range of Fagus sylvatica and to estimate the contribution of each trait to explaining the species' occurrence. Location Europe. Time period 1995-2014; 2070. Major taxa studied Fagus sylvatica L. Methods We used vertical and radial growth, flushing phenology and mortality of F. sylvatica L. recorded in the BeechCOSTe52 database (>150,000 trees). Firstly, we performed linear mixed-effect models that related trait variation and covariation to local adaptation (related to the planted populations' climatic origin) and phenotypic plasticity (accounting for the climate of the plantation), and we made spatial predictions under current and representative concentration pathway (RCP 8.5) climates. Secondly, we combined spatial trait predictions in a linear model to explain the occurrence of the species. Results The contribution of plasticity to intraspecific trait variation is always higher than that of local adaptation, suggesting that the species is less sensitive to climate change than expected; different traits constrain beech's distribution in different parts of its range: the northernmost edge is mainly delimited by flushing phenology (mostly driven by photoperiod and temperature), the southern edge by mortality (mainly driven by intolerance to drought), and the eastern edge is characterized by decreasing radial growth (mainly shaped by precipitation-related variables in our model); considering trait covariation improved single-trait predictions. Main conclusions Population responses to climate across large geographical gradients are dependent on trait x environment interactions, indicating that each trait responds differently depending on the local environment.