Stock Michiel, Hoebeke Laura, De Baets Bernard
KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Gent, Belgium.
Entropy (Basel). 2021 Jun 2;23(6):703. doi: 10.3390/e23060703.
Shannon's entropy measure is a popular means for quantifying ecological diversity. We explore how one can use information-theoretic measures (that are often called indices in ecology) on joint ensembles to study the diversity of species interaction networks. We leverage the little-known balance equation to decompose the network information into three components describing the species abundance, specificity, and redundancy. This balance reveals that there exists a fundamental trade-off between these components. The decomposition can be straightforwardly extended to analyse networks through time as well as space, leading to the corresponding notions for alpha, beta, and gamma diversity. Our work aims to provide an accessible introduction for ecologists. To this end, we illustrate the interpretation of the components on numerous real networks. The corresponding code is made available to the community in the specialised Julia package EcologicalNetworks.jl.
香农熵度量是量化生态多样性的一种常用方法。我们探讨了如何在联合集合上使用信息论度量（在生态学中通常称为指数）来研究物种相互作用网络的多样性。我们利用鲜为人知的平衡方程将网络信息分解为描述物种丰度、特异性和冗余性的三个组成部分。这种平衡表明这些组成部分之间存在着基本的权衡。这种分解可以直接扩展到对网络在时间和空间上的分析，从而引出了α、β和γ多样性的相应概念。我们的工作旨在为生态学家提供一个易于理解的介绍。为此，我们在众多真实网络上说明了这些组成部分的解释。相应的代码通过专门的Julia包EcologicalNetworks.jl向社区提供。
