School of Earth, Environmental and Biological Sciences, Queensland University of Technology (QUT), Brisbane, Queensland 4001, Australia.
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903 Birmensdorf, Switzerland.
Proc Biol Sci. 2019 Jul 24;286(1907):20190429. doi: 10.1098/rspb.2019.0429.
Plant traits are commonly used to predict ecosystem-level processes, but the validity of such predictions is dependent on the assumption that trait variability between species is greater than trait variability within a species-the robustness assumption. Here, we compare leaf trait intraspecific and interspecific variability depending on geographical differences between sites and 5 years of experimental herbivore exclusion in two vegetation types of subalpine grasslands in Switzerland. Four leaf traits were measured from eight herbaceous species common to all 18 sites. Intraspecific trait variability differed significantly depending on site and herbivory. However, the amount and structure of variability depended on the trait measured and whether considering leaf traits separately or multiple leaf traits simultaneously. Leaf phosphorus concentration showed the highest intraspecific variability, while specific leaf area showed the highest interspecific variability and displayed intraspecific variability only in response to herbivore exclusion. Species identity based on multiple traits was not predictable. We find intraspecific variability is an essential consideration when using plant functional traits as a common currency not just species mean traits. This is particularly true for leaf nutrient concentrations, which showed high intraspecific variability in response to site differences and herbivore exclusion, a finding which suggests that the robustness assumption does not always hold.
植物特征通常被用于预测生态系统层面的过程,但这种预测的有效性取决于一个假设,即物种之间的特征可变性大于物种内部的特征可变性——稳健性假设。在这里,我们根据瑞士两个亚高山草原植被类型中地点之间的地理差异和 5 年的实验性食草动物排除,比较了叶片特征的种内和种间可变性。从所有 18 个地点共有的 8 种草本植物中测量了 4 种叶片特征。种内特征变异性显著取决于地点和食草动物。然而,可变性的数量和结构取决于所测量的特征,以及是单独考虑叶片特征还是同时考虑多个叶片特征。叶片磷浓度表现出最高的种内可变性,而比叶面积表现出最高的种间可变性,并且仅在响应食草动物排除时表现出种内可变性。基于多种特征的物种身份是不可预测的。我们发现,当将植物功能特征用作通用货币而不仅仅是物种平均特征时,种内可变性是一个必不可少的考虑因素。对于叶片养分浓度来说尤其如此,它对地点差异和食草动物排除的反应表现出很高的种内可变性,这一发现表明稳健性假设并不总是成立。