Affiliation:
1. College of Ecology and the Environment Xinjiang University Urumchi PR China
2. School of Ecological and Environmental Sciences East China Normal University Shanghai PR China
3. Plant Ecology and Phytochemistry Group, Institute of Biology Leiden University Leiden The Netherlands
4. Institute for Global Change Biology, School for Environment and Sustainability University of Michigan Ann Arbor 48109 Michigan USA
Abstract
AbstractPremisePrevious work searching for sexual dimorphism has largely relied on the comparison of trait mean vectors between sexes in dioecious plants. Whether trait scaling (i.e., the ratio of proportional changes in covarying traits) differs between sexes, along with its functional significance, remains unclear.MethodsWe measured 10 vegetative traits pertaining to carbon, water, and nutrient economics across 337 individuals (157 males and 180 females) of the diocious species Eurya japonica during the fruiting season in eastern China. Piecewise structural equation modeling was employed to reveal the scaling relationships of multiple interacting traits, and multivariate analysis of (co)variance was conducted to test for intersexual differences.ResultsThere was no sexual dimorphism in terms of trait mean vectors across the 10 vegetative traits in E. japonica. Moreover, most relationships for covarying trait pairs (17 out of 19) exhibited common scaling slopes between sexes. However, the scaling slopes for leaf phosphorus (P) vs. nitrogen (N) differed between sexes, with 5.6‐ and 3.0‐fold increases of P coinciding with a 10‐fold increase of N in male and female plants, respectively.ConclusionsThe lower ratio of proportional changes in P vs. N for females likely reflects stronger P limitation for their vegetative growth, as they require greater P investments in fruiting. Therefore, P vs. N scaling can be a key avenue allowing for sex‐specific strategic optimization under unequal reproductive requirements. This study uncovers a hidden aspect of secondary sex character in dioecious plants, and highlights the use of trait scaling to understand sex‐defined economic strategies.