To cope with climate change-induced alterations, forest ecosystems’ conservation and restoration require models that are both capable to incorporate current local-scale dynamics but also to anticipate future changes. These requirements may be fulfilled by robust assessments of response (i.e., species data such as forest inventories) and predictor (e.g., climate) variables. The aim of this study is to predict current and future probability of occurrence for 22 tree species comparing inventory and climate data at different spatial scales and test for model performance, reliability, and niche truncation.

中文翻译：

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使用本地物种数据构建的物种分布模型在当前时间表现更好，但存在生态位截断的问题


为了应对气候变化引起的变化，森林生态系统的保护和恢复需要既能够结合当前局部尺度动态，又能够预测未来变化的模型。这些要求可以通过对响应（即森林清查等物种数据）和预测变量（例如气候）变量的稳健评估来实现。本研究的目的是预测 22 个树种当前和未来的出现概率，比较不同空间尺度的清单和气候数据，并测试模型性能、可靠性和生态位截断。