School of Mathematics, Statistics and Physics, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK.
Institute for Biochemistry and Biology, University of Potsdam, 14476, Potsdam, Germany.
J Math Biol. 2022 Aug 12;85(3):20. doi: 10.1007/s00285-022-01783-7.
Although ecological networks are typically constructed based on a single type of interaction, e.g. trophic interactions in a food web, a more complete picture of ecosystem composition and functioning arises from merging networks of multiple interaction types. In this work, we consider tripartite networks constructed by merging two bipartite networks, one mutualistic and one antagonistic. Taking the interactions within each sub-network to be distributed randomly, we consider the stability of the dynamics of the network based on the spectrum of its community matrix. In the asymptotic limit of a large number of species, we show that the spectrum undergoes an eigenvalue phase transition, which leads to an abrupt destabilisation of the network as the ratio of mutualists to antagonists is increased. We also derive results that show how this transition is manifest in networks of finite size, as well as when disorder is introduced in the segregation of the two interaction types. Our random-matrix results will serve as a baseline for understanding the behaviour of merged networks with more realistic structures and/or more detailed dynamics.
虽然生态网络通常是基于单一类型的相互作用构建的,例如食物网中的营养相互作用,但通过合并多种相互作用类型的网络,可以更全面地了解生态系统的组成和功能。在这项工作中,我们考虑通过合并两个二分网络来构建三分网络,一个是互利的,另一个是拮抗的。假设每个子网内的相互作用是随机分布的,我们根据其社区矩阵的谱来考虑网络动态的稳定性。在大量物种的渐近极限下,我们表明,随着互利共生体与拮抗共生体的比例增加,谱经历了特征值相变,这导致网络突然失稳。我们还推导出了一些结果,展示了在有限大小的网络中以及在两种相互作用类型的隔离中引入无序时,这种转变是如何表现出来的。我们的随机矩阵结果将为理解具有更现实结构和/或更详细动力学的合并网络的行为提供基准。