Coordination of intra and inter-species leaf traits according to leaf phenology and plant age for three temperate broadleaf species with different shade tolerances

Abstract

Intraspecific leaf economic spectrum (LES) traits vary considerably with leaf phenology and plant age, but whether these trait patterns significantly vary between species with different shade tolerances at local scales has rarely been examined. The presence of LES within species at local scales has recently been debated; however, the conclusions are far from universal, and whether the trait-trait relationships are modulated by leaf phenology and plant age needs to be tested. We measured six leaf traits (i.e., specific leaf area, leaf dry matter content, leaf thickness, mass-based leaf nitrogen content, leaf phosphorus content and ratio of nitrogen and phosphorus contents) among different leaf phenological stages (young, mature and old leaves) and plant ages (adult and sapling) for three temperate broadleaf species with different levels of shade tolerance. Intraspecific trait variation depended on the species and traits, and interspecies trait variation patterns were inconsistent with the LES prediction. Specific leaf area significantly decreased as the shade tolerance of a species increased, which was in contrast with the global LES prediction. Additionally, 38% and 28% of intraspecific trait variation was explained by leaf phenology and plant age, respectively, for the overall leaf traits of the three species. Generally, global LES held at the local scale, but trait-trait relationships were strongly modulated by leaf phenology and plant age. The intraspecific trait variation among the leaf phenology and plant age stages was driven by the LES axis and leaf thickness, respectively. We highlight the importance of leaf phenology and plant age on intraspecific trait variation and trait-trait relationships. We provide direct evidence of the LES at a local spatial scale and a seasonally temporal scale, but variations in LES traits are not always reliable for predicting the resource-use strategies of plants at local scales.