Trees do not respond to climatic conditions uniformly, but instead show individualistic growth responses. The extent of and causes behind this within-stand variability represents significant uncertainty in predictions of how forests will respond to future climate change. We analyzed patterns of individualistic tree growth within two types of conifer stands of Central Europe – high-elevation Picea abies and low-elevation Pinus sylvestris forests. We quantified the relative effect of age, size, and topographic conditions on variability in growth patterns and climate-growth responses using principal component analysis and linear models, considering both year-to-year and decadal growth variability. Our results show that Picea abies stands with dominant temperature limitation exhibit greater growth coherency than Pinus sylvestris stands characterized by drought-limited growth. Growth variability and individual climate-growth responses in both forest types were mainly driven by tree size and age, while the effect of topographic conditions was less important. The effect of size and age variables was dominant considering decadal growth trends, whereas intermediate importance of topographic variables was observed for high-frequency growth variability and climate-growth responses. Our results highlight that between-tree variability in climatic signal and growth trends also reflects the specific distribution of the age/size and topographic parameters within the stand. We suggest careful selection of datasets used for large-scale assessments of growth trends and climate-growth responses which should consider the age and size representation of sampled trees.

树木对气候条件的反应不是统一的，而是表现出个人主义的生长反应。林分内部变异的程度和原因表明，在预测森林将如何应对未来气候变化方面存在很大的不确定性。我们分析了中欧两种针叶林林分中个人主义树木生长的模式-高海拔的云杉冷杉和低海拔的樟子松森林。我们使用主成分分析和线性模型，同时考虑了年际和年代际的增长变异性，量化了年龄，大小和地形条件对增长方式和气候增长响应变异性的相对影响。我们的结果表明，云杉具有主要温度限制的林分表现出比樟子松更大的生长连贯性干旱限制生长的林分。两种森林类型中的生长变异性和个体气候生长响应主要由树木的大小和年龄决定，而地形条件的影响则不那么重要。考虑到年代际增长趋势，大小和年龄变量的影响是主要的，而对于高频增长的可变性和气候增长响应，地形变量的重要性却是中等的。我们的结果表明，树间气候信号的变化和生长趋势也反映了林分内年龄/大小和地形参数的特定分布。我们建议仔细选择用于大规模评估生长趋势和气候增长响应的数据集，这些数据集应考虑采样树的年龄和大小表示。