Landscape Ecology, Institute of Terrestrial Ecosystems, ETH Zurich, Zürich, Switzerland.
Landscape Ecology, Land Change Science, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.
Nat Commun. 2021 May 11;12(1):2724. doi: 10.1038/s41467-021-22630-1.
It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka-Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait-demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems.
长期以来,人们一直预期将功能特征与物种动态相关联将成为实现生态系统大规模可预测性的基石。如果存在这种关系,那么仅通过测量功能特征就可以对物种动态进行建模,从而改变我们利用基于过程的群落模型来预测物种丰富群落的状态和动态的能力。在这里,我们引入了一种新的方法,通过逆模型校准传递函数将经验功能特征与基于过程的模型的人口统计参数联系起来。作为一个案例研究,我们仅使用静态植物群落和功能特征数据对高多样性山地草原的改良Lotka-Volterra 模型进行参数化。经过校准的特征-种群动态关系具有生态解释性,并导致与观察到的群落结构非常吻合的物种丰度。我们得出结论,我们的新方法为弥合丰富生态系统中特征数据和基于过程的模型之间的差距提供了一种通用解决方案。