Department of Biology, University of North Carolina at Greensboro, Greensboro, NC, USA.
Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD, USA.
Sci Data. 2024 Jul 18;11(1):795. doi: 10.1038/s41597-024-03637-x.
In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species' responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide.
在不断变化的世界中，了解植物群落对全球变化驱动因素的响应对于预测未来生态系统的组成和功能至关重要。植物功能性状有望成为许多生态系统（包括草原）的重要预测工具；然而，它们的使用需要完整的植物群落和功能性状数据。然而，这些数据在全球数据库中的代表性非常有限，尤其是在少数几种常用性状和常见物种之外。在这里，我们介绍了 CoRRE 性状数据，涵盖了 17 个性状（9 个分类，8 个连续），预计将预测全球变化对 173 个科的 4079 种维管植物物种的影响，这些物种分布在全球 390 个草原实验中。该数据集包含了通过全面文献检索获得的所有 4079 种植物的完整分类性状记录，以及 2927 种植物亚组中几乎完整的（99.97%）连续性状值的估算值。这些数据将揭示全球草原中种群、群落和生态系统对全球变化响应的机制。
