Exploring trait–performance relationships of tree seedlings along experimentally manipulated light and water gradients
Yuanzhi Li, Yuan Jiang, Kangning Zhao, Chen Yang, Wei Wei, Bill Shipley, Chengjin Chu
Abstract
A foundational assumption of trait-based ecology is that individual performances should be predicted by its functional traits. However, the trait-performance relationships reported in literature were typically weak, probably due to the ignorance of interactions between traits and environments, intraspecific trait variability, and hard traits (directly linked to physiological processes of interest). We conducted an experiment of planting 900 seedlings of six tree species separately (one seedling per pot) along experimentally manipulated light and water gradients, monitored their survival and growth, and measured their morphological, photosynthetic, and hydraulic traits. Most trait-performance relationships depended on the environments, either marginally changing (weak trait × environment interaction) or even reversing (strong trait × environment interaction) along light or water gradients in our experiment. Such trait × environment interactions were more likely to be detected in growth models using individual-level traits than models using species mean traits, but seedling growth was not better modeled with individual-level traits than species mean traits. Additionally, none of the hard traits (photosynthetic and hydraulic traits) were better predictors than soft traits (morphological traits) modeling seedling growth and survival along light and water gradients. Our study highlights the necessities of considering trait × environment interactions when predicting response of plants to changing environments. The benefits of using individual-level traits or hard traits to predict plant performance might be reduced or even canceled if their measurement errors are not well controlled.