Process-based forest models are important tools for predicting forest growth and their vulnerability to factors such as climate change or responses to management. One of the most widely used stand-level process-based models is the 3-PG model (Physiological Processes Predicting Growth), which is used for applications including estimating wood production, carbon budgets, water balance and susceptibility to climate change. Few 3-PG parameter sets are available for central European species and even fewer are appropriate for mixed-species forests. Here we estimated 3-PG parameters for twelve major central European tree species using 1418 long-term permanent forest monitoring plots from managed forests, 297 from un-managed forest reserves and 784 Swiss National Forest Inventory plots. A literature review of tree physiological characteristics, as well as regression analyses and Bayesian inference, were used to calculate the 3-PG parameters.

The Swiss-wide calibration, based on monospecific plots, showed a robust performance in predicting forest stocks such as stem, foliage and root biomass. The plots used to inform the Bayesian calibration resulted in posterior ranges of the calibrated parameters that were, on average, 69% of the prior range. The bias of stem, foliage and root biomass predictions was generally less than 20%, and less than 10% for several species. The parameter sets also provided reliable predictions of biomass and mean tree sizes in mixed-species forests. Given that the information sources used to develop the parameters included a wide range of climatic, edaphic and management conditions and long time spans (from 1930 to present), these species parameters for 3-PG are likely to be appropriate for most central European forests and conditions.

基于过程的森林模型是预测森林生长及其对气候变化或对管理的反应等因素的脆弱性的重要工具。3-PG模型（预测生长的生理过程）是使用最广泛的基于标准过程的模型之一，该模型用于估计木材产量，碳预算，水平衡和气候变化敏感性的应用。很少有3-PG参数集可用于中欧物种，而更少的适合于混合物种森林。在这里，我们使用来自管理森林的1418个长期永久森林监测区，来自非管理森林保护区的297个长期森林监测区和784个瑞士国家森林清单区，估计了12种中欧主要树种的3-PG参数。有关树木生理特性的文献综述，

在瑞士范围内的校准基于单特异性图，显示了在预测诸如茎，叶和根生物量等森林资源方面的强大性能。用于告知贝叶斯校准的曲线图产生的校准参数的后范围平均为先前范围的69％。茎，叶和根生物量预测的偏差通常小于20％，而对于几种物种，则小于10％。参数集还提供了混合物种森林中生物量和平均树木大小的可靠预测。鉴于用于制定参数的信息源包括范围广泛的气候，水文和管理条件以及较长的时间跨度（从1930年至今），因此3-PG的这些物种参数可能适用于大多数中欧森林和条件。