Department of Ecological Modeling, Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany.
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103, Leipzig, Germany.
Sci Rep. 2020 Aug 6;10(1):13198. doi: 10.1038/s41598-020-70052-8.
Network analysis is an important tool to analyze the structure of complex systems such as tropical forests. Here, we infer spatial proximity networks in tropical forests by using network science. First, we focus on tree neighborhoods to derive spatial tree networks from forest inventory data. In a second step, we construct species networks to describe the potential for interactions between species. We find remarkably similar tree and species networks among tropical forests in Panama, Sri Lanka and Taiwan. Across these sites only 32 to 51% of all possible connections between species pairs were realized in the species networks. The species networks show the common small-world property and constant node degree distributions not yet described and explained by network science. Our application of network analysis to forest ecology provides a new approach in biodiversity research to quantify spatial neighborhood structures for better understanding interactions between tree species. Our analyses show that details of tree positions and sizes have no important influence on the detected network structures. This suggests existence of simple principles underlying the complex interactions in tropical forests.
网络分析是分析复杂系统(如热带森林)结构的重要工具。在这里,我们利用网络科学推断热带森林的空间邻近网络。首先,我们关注树木的邻居关系,从森林清查数据中得出空间树木网络。在第二步中,我们构建物种网络来描述物种之间潜在的相互作用。我们发现巴拿马、斯里兰卡和中国台湾的热带森林之间存在非常相似的树木和物种网络。在这些地点,物种网络中仅实现了物种对之间所有可能连接的 32%至 51%。物种网络显示了常见的小世界特性和常数节点度分布,这还没有被网络科学所描述和解释。我们将网络分析应用于森林生态学,为生物多样性研究提供了一种新方法,用于量化空间邻域结构,以更好地理解树种之间的相互作用。我们的分析表明,树木位置和大小的细节对检测到的网络结构没有重要影响。这表明,在热带森林复杂的相互作用背后存在简单的原则。