Data from: Herbivory limits success of vegetation restoration globally

Herbivory limits success of vegetation restoration globally. Restoring vegetation in degraded ecosystems is an increasingly common practice for promoting biodiversity and ecological function, but successful implementation is hampered by an incomplete understanding of the processes limiting restoration success. By assembling terrestrial and aquatic studies globally (2594 experimental tests from 610 articles), we reveal substantial herbivore control of vegetation under restoration. Herbivores at restoration sites reduced vegetation abundance more strongly (by 89%, on average) than at relatively undegraded sites, and suppressed, rather than fostered, plant diversity. These effects were particularly pronounced in regions with higher temperatures and lower precipitation. Temporally excluding targeted herbivores or introducing their predators improved restoration by magnitudes similar to or greater than managing plant competition or facilitation. Thus, managing herbivory is a promising strategy for enhancing vegetation restoration efforts.

This ZIP file contains the following datasets and code for the above paper:

1) Xu_ConsumerEffects.xlsx This file contains the Global Consumer Effects dataset (and several subsets)
2) Xu_PlantInteractions.xlsx This file contains the Global Plant Interactions and Restoration dataset
3) Code_Xu_Restoration_Ms.R This file contains examples of main R code used. 

See the Supplementary Materials of the paper for methods used to collect and analyze these data.

草食作用（Herbivory）制约全球范围内植被修复的成效。在退化生态系统中开展植被修复是提升生物多样性与生态功能的日益普遍的实践，但由于对制约修复成功的过程机制认知不足，其顺利实施常受到阻碍。
本研究整合了全球范围内的陆地与水生相关研究（涵盖来自610篇文献的2594项实验测试），揭示了草食动物对修复阶段植被的显著调控作用。修复样地中的草食动物对植被生物量的抑制效果更强，平均降幅达89%，远高于相对未退化样地；同时它们会抑制而非促进植物多样性。这类效应在温度更高、降水更低的区域尤为显著。
暂时性移除目标草食动物或引入其天敌所带来的修复效果提升幅度，与调控植物竞争或促进作用的效果相当甚至更优。因此，调控草食作用是强化植被修复工作的极具前景的策略。

本压缩包包含本论文配套的如下数据集与代码：
1) Xu_ConsumerEffects.xlsx：该文件包含全球消费者效应数据集（及若干子集）
2) Xu_PlantInteractions.xlsx：该文件包含全球植物互作与修复数据集
3) Code_Xu_Restoration_Ms.R：该文件包含核心R代码示例。

有关数据收集与分析的具体方法，请参见论文的补充材料。