论文标题

生态网络中的简单结构

Simplicial structures in ecological networks

论文作者

Raj, Udit, Upadhyay, Shashankaditya, Karmakar, Moumita, Bhattacharya, Sudeepto

论文摘要

生态网络是相应生态系统中特定类型相互作用的形式表示。传统上,此类网络被建模为在生态系统的基本单元之间独家编码成对的相互作用,并使用图理论方法代表和分析。但是,许多现实世界的生态系统可能会在其单位之间娱乐非二元,多核关系,而成对交互方法不能捕获,但是需要高阶交互框架,因此无法使用图理论框架对相应的生态网络进行建模。这项工作给出了生态网络的结构定义,适用于对相应生态系统的基本单元之间的所有相互作用订单进行建模,包括并超越了成对相互作用框架。通过将相应的生态网络建模为定义之后的简单络合物,研究了一些精选生态系统之间的碳中介。图中心度度量的概念已扩展到简单的中心性,并且已经计算了这些网络在复合物的各个结构水平上的一些重要集中度度量。中心度度量揭示了有价值的结构信息,包括有关那些更可能参与高阶相互作用的顶点的信息,并告知这些高阶网络的顶点等级是否存在基于图中心和简单的中心度测度的差异。

An ecological network is a formal representation of a specific type of interaction in a corresponding ecosystem. Such networks have traditionally been modelled as encoding exclusively pairwise interactions among the fundamental units of ecosystems and have been represented and analysed using graph-theoretic methods. However, many real-world ecosystems may entertain non-binary, polyadic relations between their units, which cannot be captured by the pairwise interaction methods, but require higher-order interaction framework, and consequently the corresponding ecological networks cannot be modelled using graph-theoretic framework. This work gives a structural definition of ecological network suitable for modelling all orders of interactions between the fundamental units of the corresponding ecological system, including and going beyond the pairwise interaction framework. Carbon mediation between units of some select ecosystems are studied by modelling the corresponding ecological networks as simplicial complexes following the definition. The concept of graph centrality measure has been extended to simplicial centrality, and some important centrality measures of these networks at various structural levels of the complexes have been calculated. The centrality measures reveal valuable structural information including information about those vertices that are more likely to participate in higher-order interactions, as well as inform whether there is a difference in the ranks of vertices for these higher-order networks based on graph centrality and simplicial centrality measures.

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