Dataset and code for "Climate warming interacts with other global change drivers to influence plant phenology: a meta-analysis of experimental studies"

This is a dataset for the meta-analysis of "<strong>Climate warming interacts with other global change drivers to influence plant phenology: a meta-analysis of experimental studies</strong>". We found widespread interaction effects between global change drivers on multiple plant phenophases. The interactions W+IP and W+eCO₂ were frequently synergistic, whereas the interactions W+N and W+DP were mostly antagonistic. Using Web of Science, Google Scholar and the China National Knowledge Infrastructure, we collected a total of 9571 observations from 242 peer-reviewed articles that reported changes in plant sequential phenophases (leaf out, first flowering, fruiting and leaf coloring) under experimental manipulations of warming (W) and other global change drivers, including increased precipitation (IP), decreased precipitation (DP), nitrogen addition (N), and elevated CO₂ concentration (eCO₂), from 1990 until 2022. These global change experiments were located from 43.6° S to 79.1° N. We used a widely accepted bias-corrected method to quantify individual effects and the combined effects of global change drivers on plant sequential phenophases (effect size: Hedges' <em>g</em>). The interactive effect and main effect for judging the interaction types of combined effect were calculated as Hedges' <em>d</em>. All the statistical analysis were implemented in <em>R</em> version 4.2.2. The dataset and <em>R</em> code were both uploaded.

本数据集服务于题为《气候变暖与其他全球变化驱动因子协同影响植物物候（plant phenology）：一项实验研究的元分析（meta-analysis）》的研究。本研究发现全球变化驱动因子（global change drivers）间的交互效应广泛存在于多种植物物候期（plant phenophases）。其中，增温与降水增加（W+IP）、增温与CO₂富集（W+eCO₂）的交互效应多为协同作用，而增温与氮添加（W+N）、增温与降水减少（W+DP）的交互效应则多为拮抗作用。本研究通过Web of Science、Google Scholar及中国知网（China National Knowledge Infrastructure）检索文献，共收集了1990年至2022年间242篇经同行评议的学术论文，包含9571条观测记录。这些文献报道了实验操控增温（W）及其他全球变化驱动因子（包括降水增加IP、降水减少DP、氮添加N与CO₂富集eCO₂）下植物连续物候期（展叶、始花、结果与叶变色）的变化情况。这些全球变化实验的布设范围为南纬43.6°至北纬79.1°。我们采用学界广泛认可的偏差校正方法，量化全球变化驱动因子对植物连续物候期的单独效应与复合效应（效应量：Hedges' g）。用于判断复合效应交互类型的交互效应与主效应，均以Hedges' d作为计算指标。所有统计分析均在R 4.2.2版本中完成。本数据集与R代码均已上传。