Correlations between leaf economics, hydraulic, and shade-tolerance traits among co-occurring individual trees

Abstract

Leaf economics, hydraulic, and shade-tolerance traits involve different resource-use strategies, and are critical for interactive plants, yet it remains unclear whether co-occurring individuals modulate the coupling relationships between these trait dimensions. To address this knowledge gap, we measured four leaf economics, five hydraulic, and two shade-tolerant traits in leaf and wood tissues across 90 individuals from 26 tree species in two subtropical forests in Eastern China. Confirmatory factor analysis (CFA) and Principal Component Analysis (PCA) were employed to explore multi-trait relationships. With respect to leaf economics traits, leaf nitrogen concentrations were positively associated with leaf stomatal density and conductance, leaf-specific hydraulic conductivity, and twig vessel diameter. However, leaf phosphorus concentrations were negatively associated with leaf-specific hydraulic conductivity. The specific leaf area was negatively associated with the light exposure index, light saturation point, and leaf Huber value. Regarding hydraulic traits, twig vessel diameters were positively correlated with the light saturation point and light exposure index. Stomatal conductance was positively associated with the light saturation point, whereas leaf-specific hydraulic conductivity was positively associated with the light exposure index. The first two PCA axes explained 54.23% of the total trait variation. The first axis of the multi-trait variation was mainly explained by leaf habits and represented the trade-offs between acquisitive hydraulic economics and cheap leaf economics. The second axis of the multi-trait variation was mainly explained by plant growth form, and defined the trade-offs between weak shade tolerance and cheap leaf area construction. In conclusion, our results provide evidence for the coupling relationships between leaf economics, hydraulic, and shade-tolerant traits among co-occurring individuals. This study also highlights that bivariate trait relationships based on large-scale interspecific surveys may be the opposite of that within-community scales.