Plasticity of functional traits and optimality of biomass allocation in elevational ecotypes of Arabidopsis halleri grown at different soil nutrient availabilities.

ABSTRACT

In mountainous areas, plant distribution is constrained by various environmental stresses. Plasticity and constancy in plant functional traits may relate to optimal strategies at respective habitats and to ecotypic differentiation along elevation. Although plant biomass allocation has been extensively studied in relation to adaptation to soil nutrient availability along elevation, its optimality is still poorly understood. We examined soil nutrient availability in the field and conducted growth analysis for two elevational ecotypes of Arabidopsis halleri grown under different nutrient availabilities. We determined plasticity in morphological and physiological traits and evaluated optimal biomass allocation using an optimality model. Our field investigation indicated that soil nitrogen (N) availability increased rather than decreased with increasing elevation. Our growth analysis revealed that lowland ecotype was more plastic in morphological variables and N concentrations, whereas the highland ecotype was more plastic in other physiological variables such as the net assimilation rate (NAR). The leaf mass ratio (LMR) in the lowland ecotype was moderately plastic at the whole range of N availabilities, whereas LMR in the highland ecotype was very plastic at higher N availabilities only. The optimality model indicated that the LMR of the lowland ecotype was nearly optimal throughout the range of studied N availabilities, whereas that of the highland ecotype was suboptimal at low N availability. These results suggest that highland ecotype is adapted only to high N availability, whereas the lowland ecotype is adapted to a relatively wide range of N availabilities as a result of natural selection in their respective habitats. We conclude that an adaptive differentiation has occurred between the two ecotypes and plasticity in the biomass allocation is directly related to its optimization in changing environments.