1. Functional diversity assessments are crucial and increasingly used for understanding ecological processes and managing ecosystems. The functional diversity of a community is assessed by sampling traits at one or more scales (individuals, populations and species) and calculating a summary index of the variation in trait values. However, it remains unclear how the scales at which traits are sampled and the indices used to estimate functional diversity may alter the patterns observed and inferences about ecological processes.
2. For 40 plant and 61 ant communities, we assess functional diversity using six methods—spanning various mean‐based and probabilistic methods—that reflect common scenarios where different levels of detail are available in trait data. We test whether including trait variability at different scales (from individuals to species) alters functional diversity values calculated using the volume‐based and dissimilarity‐based indices, Functional Richness (FRic) and Rao, respectively. We further test whether such effects alter functional diversity patterns observed across communities and their relationships with environmental drivers such as abiotic gradients and occurrences of invasive species.
3. Intraspecific trait variability strongly determined FRic and Rao. Methods using only species' mean trait values to calculate FRic (convex hulls) and Rao (Gower‐based dissimilarity) distorted the patterns observed when intraspecific trait variability was considered. These distortions generated Type I and Type II errors for the effects of environmental factors structuring the plant and ant communities. A high sensitivity of FRic to individuals with extreme trait values was revealed in comparisons of different probabilistic methods including among‐individual and among‐population trait variability in functional diversity. In contrast, values of and ecological patterns in Rao were consistent among methods including different scales of intraspecific trait variability.
4. Our results show empirically that decisions about where traits are sampled and how trait variability is included in functional diversity can drastically change the patterns observed and conclusions about ecological processes. We recommend sampling the traits of multiple individuals per species and capturing their intraspecific trait variability using probabilistic methods. We discuss how intraspecific trait variability can be reasonably estimated and included in functional diversity in the common circumstance where only limited trait data are available.

中文翻译：

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包括种内性状变异性以避免功能多样性和生态推断的扭曲：自然组合的经验教训

1. 功能多样性评估至关重要，越来越多地用于了解生态过程和管理生态系统。通过在一个或多个尺度（个体，种群和物种）上对特征进行采样并计算特征值变化的汇总指数，可以评估社区的功能多样性。然而，目前尚不清楚特质的尺度和用于估计功能多样性的指数如何改变观察到的模式和对生态过程的推论。
2. 对于40个植物群落和61个蚂蚁群落，我们使用六种方法（涵盖各种基于均值和概率的方法）评估功能多样性，这些方法反映了在特征数据中可获得不同详细程度的常见情况。我们测试是否包括不同尺度（从个体到物种）的性状变异性是否会改变分别使用基于体积和基于不相似性的指数，功能丰富度（FRic）和Rao计算的功能多样性值。我们进一步测试了这种影响是否会改变整个社区观察到的功能多样性模式，以及它们与环境驱动因素（如非生物梯度和入侵物种的发生）之间的关系。
3. 种内性状变异性强烈决定了FRic和Rao。当考虑种内性状变异性时，仅使用物种平均特征值来计算FRic（凸包）和Rao（基于高尔的不相似性）的方法会使观察到的模式失真。这些扭曲由于构造植物和蚂蚁群落的环境因素的影响而产生了I型和II型错误。通过比较不同概率方法（包括功能多样性中个体间和群体间性状变异），揭示了FRic对具有极端特征值的个体的高度敏感性。相反，Rao的值和生态模式在包括不同尺度的种内性状变异性的方法之间是一致的。
4. 我们的结果从经验上表明，关于在何处采样特征以及如何在功能多样性中包括特征变异的决策可以极大地改变观察到的模式和有关生态过程的结论。我们建议对每个物种的多个个体的特征进行采样，并使用概率方法捕获其种内特征的变异性。我们讨论了如何在只能获得有限性状数据的常见情况下，合理地估计种内性状变异性并将其包括在功能多样性中。