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Global sensitivity analysis of a dynamic vegetation model: Model sensitivity depends on successional time, climate and competitive interactions

机译：动态植被模型的全局敏感性分析：模型敏感度取决于连续时间，气候和竞争性互动

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Highlights?We assess the sensitivity of a state-of-the-art forest gap model across Europe.?Model sensitivity depends on successional time, climate and competition.?We provide specific recommendations for process improvements of forest gap models.AbstractAccurately predicting the dynamics of tree species productivity as well as their ranges at large scales is of key importance for assessing the impact of global change on forests. Dynamic vegetation models (DVMs), particularly forest gap models (FGMs), have been suggested as suitable tools for such joint predictions. However, DVMs generally feature a large number of parameters that need to be estimated and may cause considerable uncertainty in model outputs. In addition, model sensitivity may depend on environmental conditions, stand composition and development stage. We systematically evaluated the parameter sensitivity on simulated basal area of the state-of-the art FGM ForClim along a wide ecological gradient to analyze model behavior and identify key pa
机译：<！[cdata [ 突出显示 ？ 我们评估欧洲艺术最先进的森林差距模型的敏感性。 ？ 型号灵敏度取决于连续时间，气候与竞争。 ？ 我们为森林差距模型的流程改进提供了具体建议。 摘要 准确预测树动态物种生产力以及大规模的范围是评估全球变化对森林的影响的关键重要性。动态植被模型（DVM），特别是森林隙模型（FGMS），已被建议作为这种联合预测的合适工具。然而，DVM通常具有需要估计的大量参数，并且可能导致模型输出中的相当大的不确定性。此外，模型敏感度可能取决于环境条件，立式构成和发展阶段。我们系统地评估了沿着广泛的生态梯度沿着宽的生态梯度来分析模型行为和识别键PA的模拟基础区域的参数灵敏度

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