Biomass allocation and leaf-root trait coordination of dominant ferns in a subtropical forest

The coordinated variation between plant biomass allocation and organ functional traits is central to understanding resource-use strategies. However, relevant studies have focused predominantly on angiosperms, and the whole-plant trait coordination structure in ancient fern lineages remains unclear.

In this study, we simultaneously measured biomass allocation fractions, stoichiometric traits (C, N, P, C:N, C:P, N:P) and morphological traits (SLA, LDMC, etc.) in both leaves and roots of seven co-occurring subtropical forest fern species. Using correlation analyses at the individual and species levels, partial least squares path modeling (PLS-PM) and Mantel tests, we examined the allocation-stoichiometry-morphology cascade pathway and cross-organ coordination patterns.

The results showed that: (1) a significant pathway exists in leaves, with allocation influencing morphology via stoichiometry-higher leaf biomass investment was associated with lower N and P concentrations and more conservative leaf morphology, consistent with the leaf economics spectrum; (2) in roots, the positive direct effect of allocation on morphology was offset by a negative indirect effect mediated by reduced nutrient concentrations, resulting in a near-zero total effect, supporting the multidimensionality of the root economics space; (3) cross-organ coordination was relatively strong for stoichiometric traits (Mantel's r = 0.69) but weak for morphological traits (r = 0.31), indicating dimension-dependent coordination; (4) the above trait relationships were significant at the individual level but mostly disappeared at the species level, suggesting that intraspecific variation may contribute importantly to community functional patterns.

This study reveals a cascade structure of whole-plant trait organization in ferns, provides new evidence for the applicability of the leaf economics spectrum in ancient vascular plants, and highlights the need for experimental validation with a broader sampling scope to establish causality.