The impact of trait number and correlation on functional diversity metrics in real-world ecosystems

作者：Timothy Ohlert, Kaitlin Kimmel, Meghan L. Avolio, Cynthia Chang, Elisabeth J. Forrestel, Benjamin P. Gerstner, Sarah E. Hobbie, Peter B. Reich, Kenneth D. Whitney, Kimberly J. Komatsu · 发表于：PLoS ONE · 年份：2024 · DOI：10.1371/journal.pone.0306342 · 被引用次数：10 · 研究领域：Plant and animal studies、Ecology and Vegetation Dynamics Studies、Animal Ecology and Behavior Studies

The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work with simulated communities and trait distributions shows sensitivity of functional diversity measures to the number and correlation of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. To address this gap, we used data from six grassland plant communities in Minnesota and New Mexico, USA to test how the number of traits and the correlation between traits used in the calculation of eight functional diversity indices impact the magnitude of functional diversity metrics in real plant communities. We found that most metrics were sensitive to the number of traits used to calculate them, but functional dispersion (FDis), kernel density estimation dispersion (KDE dispersion), and Rao's quadratic entropy (Rao's Q) maintained consistent rankings of communities across the range of trait numbers. Despit...