Data from: Individual-level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space

Global environmental change can influence ecosystem processes directly or through changes in the trait composition of natural communities. Traits are individual-level features of organisms, and theory predicts that diversity in traits should relate to ecosystem processes. Validated indices that account for both intra- and interspecific trait variation in multidimensional trait space are lacking. In this article, we highlight how an individual-level perspective requires new concepts for trait diversity (TD) and we validate a set of measures suitable to study trait richness, evenness and divergence at the individual scale. First, we tested a selection of multivariate indices for trait richness, evenness and divergence from the literature (FRic, FEve, FDis and the Rao coefficient) using simulated and real individual-level data. We compared the observed changes in the tested indices with those predicted from their expected/required behaviour (i.e. increase or decrease under specific manipulation of community trait structure) and found unsatisfactory results only for FRic and FEve, whereas FDis and the Rao coefficient showed the expected changes. Therefore, we propose two novel concepts and related indices for individual-level trait richness (TOP = trait onion peeling) and evenness (TED = trait even distribution). TOP represents the sum of all successive convex hull areas touching all individuals (points) within a multidimensional trait distribution. TED is a measure of how evenly distributed are individuals within the multidimensional trait space. It is calculated comparing the probability distributions of pairwise distances between individuals and between points of a perfectly even reference distribution. We tested TOP and TED on the same simulated and real data as above, and results indicated appropriate behaviour for TOP (trait richness) and TED (trait evenness). By validating TD indices in an individual-level context, this study contributes to the expansion of functional ecology towards individual-level dynamics. Future comprehensive investigations of individual trait differences in natural communities may improve our understanding of the pathways by which environmental changes affect ecosystem functioning through biodiversity change.

全球环境变化可直接影响生态系统过程，亦可通过改变自然群落的性状组成引发间接效应。性状是生物体的个体水平特征，相关理论预测性状多样性（trait diversity, TD）应与生态系统过程存在关联。目前学界尚未建立可同时考量多维性状空间中种内与种间性状变异的经过验证的指数体系。本文阐明了以个体为中心的研究视角亟需全新的性状多样性概念，并验证了一组适用于个体尺度下性状丰富度、均匀度与分化度研究的测度方法。首先，我们依托模拟数据与真实个体水平数据，对现有文献中提出的多变量性状丰富度、均匀度与分化度指数（涵盖FRic、FEve、FDis及Rao系数）开展了测试。我们将各测试指数的观测变化，与基于其预期行为（即对群落性状结构进行特定操作时的增减趋势）预测的变化进行对比，结果仅FRic与FEve的表现未达预期，而FDis与Rao系数则呈现出符合预期的变化规律。据此，我们提出了两个全新的概念与对应测度指数，分别用于个体水平的性状丰富度（TOP = trait onion peeling，即性状洋葱剥皮法）与均匀度（TED = trait even distribution，即性状均匀分布指数）。TOP指多维性状分布中，覆盖所有个体（数据点）的所有连续凸包（convex hull）面积之和。TED用于衡量多维性状空间内个体的分布均匀程度，其计算逻辑为对比个体间两两距离的概率分布，与完美均匀参考分布下的点间两两距离概率分布。我们使用与前文一致的模拟数据与真实数据对TOP与TED进行测试，结果表明这两个指数在性状丰富度与性状均匀度的测度上均表现符合预期。本研究通过在个体水平框架下验证性状多样性指数，推动功能生态学（functional ecology）向个体水平动态研究方向拓展。未来针对自然群落中个体性状差异的全面探究，将有助于我们更深入地理解环境变化通过生物多样性变化影响生态系统功能的具体路径。