Long-term Experimental Forest Growth and Drought Data

These data were compiled in order to represent long-term (multi-decadal) forest growth across eight different experimental forests in the United States, each with replicated levels of density treatments, as well as an important drought index correlated to growth. Forests around the world are experiencing severe droughts and elevated competitive intensity due to increased tree density. These data can be utilized to not only examine differences in within-stand competition, as well the trends and impact of drought in different forests across a broad climatic gradient, but also the influence of interactions between drought and competition on forest growth. Growth is measured as a treatment level, annual basal area increment (BAI, mm2/year). The self-calibrated Palmer Drought Severity Index (scPDSI) was used as index of annual scale drought severity and related to growth patterns.

本数据集旨在表征美国8处不同实验林的长期（数十年尺度）森林生长状况，各实验林均设置了重复的林分密度处理梯度，同时包含与林木生长相关的关键干旱指数。当前全球森林正面临严峻干旱威胁，同时因林木密度提升，林内竞争强度亦显著加剧。本数据集不仅可用于探究不同气候梯度下各林分的林内竞争差异、干旱趋势及其影响，还可分析干旱与竞争的交互作用对森林生长的调控效应。林木生长以处理组水平的年断面积增长量（basal area increment, 缩写BAI, mm²/年）进行量化。本研究采用自校准帕默尔干旱强度指数（self-calibrated Palmer Drought Severity Index, 缩写scPDSI）作为年度尺度干旱强度的表征指标，并将其与林木生长模式进行关联分析。