Data and code from: Neighborhood diversity increases tree growth in experimental forests more in wetter climates but not in wetter years

Using records of growth of tree individuals from 15 tree-diversity experiments across four biomes. We examine how neighborhood-scale (defined as a focal tree and the adjacent trees) taxonomic and functional diversity effects on tree growth vary with climate spatially (across sites) and temporally (within sites).The dataset contains information for each experiment, interannual climate data, and species-level trait data used in this study. The climate data of annual climate precipitation (P) and potential evapotranspiration (PET) were downloaded from ERA5Land, and SPEI were accessed from the global SPEI dataset. Trait data were mainly obtained from the Plant Trait Database (TRY), Botanical Information and Ecology Network⁸⁰, and the global wood density database.<br>The R code files are also attached for running hierarchical Bayesian models, using Markov chain Monte Carlo (MCMC) sampling techniques in JAGS (version 4.3.2) and R (version 4.4.0) via the rjags package.

本研究采用来自4个生物群区的15项树木多样性实验的树木个体生长记录，探究邻域尺度（定义为目标树木及其相邻树木）下的分类多样性与功能多样性对树木生长的影响如何随空间（不同样地间）与时间（样地内部逐年）的气候条件发生变化。本数据集包含本研究所用的各项实验的相关信息、年际气候数据以及物种水平功能性状数据。其中，年降水量（P）与潜在蒸散量（PET）的气候数据下载自ERA5Land数据集，标准化降水蒸散指数（SPEI）来源于全球SPEI数据集；功能性状数据主要取自植物性状数据库（TRY）、植物信息与生态网络数据库⁸⁰以及全球木材密度数据库。本研究同时附带了用于运行分层贝叶斯模型的R代码文件，该模型通过rjags包调用JAGS（4.3.2版本）与R（4.4.0版本）中的马尔可夫链蒙特卡洛（MCMC）采样技术实现。