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

Abstract

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 co-vary 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 Fagus sylvatica range and to estimate each trait contribution to explain 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 Fagus sylvatica L. recorded in BeechCOSTe52 (>150,000 trees). Firstly, we performed linear mixed-effect models that related trait variation and co-variation 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 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 intra-specific 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 characterised by decreasing radial growth (mainly shaped by precipitation-related variables in our model); considering trait co-variation improved single-trait predictions. Main conclusions: Population responses to climate across large geographical gradients are trait-dependent, indicating that multi-trait combinations are needed to understand species' sensitivity to climate change and its variation across distribution ranges.

Greater capacity to exploit warming temperatures in northern populations of European beech is partly driven by delayed leaf senescence

“…Our results also revealed larger differences among populations for both BB and LS in the Slovakian trial than in the German one (Fig. 3), confirming that, in addition to genetic effects, the environment plays an important role in the phenological response of beech (Vitasse et al 2013; Gárate-Escamilla et al 2019).…”

“…We transformed the observational stages (phenophases), and score data (qualitative measurements) for BB and LS to Julian days by fitting the phenophases (Fig. 3; Table S2 and S3) for each tree in every trial using the Weibull function (Robson et al 2011; Gárate-Escamilla et al 2019). These data were used to obtain the day of the year (DOY) when BB was attained in spring (stage 2.5; Fig.…”

“…We also inspected gradients of GSL for the six populations by plotting GSL against the environmental variable of the trial selected in the model (ET) and population under current conditions. We predicted the date of LS for the future climate scenario RCP 8.5 using our LS model and the date of BB for the same provenances, achieved using our BB model (Gárate-Escamilla et al 2019), and plotted the predicted future GSL against ET, for each of the populations.…”

“…In beech, BB responds to a combination of chilling and forcing temperature requirements (Heide 1993; Falusi and Calamassi 2012; Kramer et al 2017), and to photoperiod (Heide 1993; Caffarra and Donnelly 2011; Basler and Körner 2012), with the strength of these drivers changing along environmental gradients. For instance, BB is more affected by photoperiod in colder populations, and by chilling requirements in warmer populations (Gárate-Escamilla et al 2019). Studies of LS in beech suggest that: (i) temperature may be a more important cue than photoperiod when nutrients and water are not limiting (Fu et al 2018); (ii) non-senescent green leaves are prematurely lost as a result of severe drought conditions (Bréda et al 2006); (iv) early BB correlates with early LS (Fu et al 2014; Chen et al 2018; Zohner et al 2018); (v) leaves first start to change color in autumn from the upper part of the canopy, suggesting that hydraulic conductance or the amount of solar radiation received over the growing season may play a role in triggering LS (Gressler et al 2015; Lukasová et al 2019), although this could also be related to an hormonal effect (Zhang et al 2011).…”

ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity

“…Because traits and their relation with fitness can change across climatic gradients, projections are highly dependent on the trait used. In some cases, higher values of fitnessrelated traits correspond to species occurrence (Benito Garz on et al, 2011;Chakraborty et al, 2018), but in other cases species occurrence is explained by the complex relationship among various traits over the species range (G arate Escamilla et al, 2019). For example, phenological traits might delimit species ranges at high latitudes, at least for those species in which photoperiod actively constrains phenology (Way & Montgomery, 2015).…”