紧急结构拓扑对适应性植物-动物网络稳定性的影响

IF 1.9 4区 生物学 Q2 BIOLOGY
Min Su, Zhongyi Wang, Qi Ma
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引用次数: 0

摘要

植物物种与传粉者和食草动物相互作用,形成了一个3-guild的生态网络,其中包括互惠和拮抗的子网络。这些植物与动物的相互作用通常通过适应性相互作用转换而进化,这往往会促进物种的丰富。在本研究中,我们构建了一个自适应的植物-动物网络,并探讨了来自不同行会的物种之间的相互作用重新布线如何影响这个3行会网络的结构和稳定性。我们的研究结果表明,相互作用的重新布线动态地重塑了网络结构,互惠和拮抗子网络之间的植物度中心性相关性成为群落稳定的关键决定因素。值得注意的是,由交互交换驱动的极端中心性相关性会破坏网络稳定性。相比之下,适度的相关性增强了弹性,使优化的网络比随机分配的网络更健壮。这些结果强调了相互作用转换在形成3-guild生态网络结构和稳定性中的重要性。此外,这些发现提供了机制证据,表明植物的通用性从根本上影响了优化网络中的恢复力,这是通过食草动物防御和传粉者吸引之间的进化权衡来调节的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impacts of emergent structural topologies on the stability of an adaptive plant-animal network
Plant species, interacting with both pollinators and herbivores, form a 3-guild ecological network that encompasses mutualistic and antagonistic subnetworks. These plant-animal interactions typically evolve through adaptive interaction switching, which tends to promote species abundance. In this study, we constructed an adaptive plant-animal network and explored how interaction rewiring among species from different guilds influences the structure and stability of this 3-guild network. Our findings reveal that interaction rewiring dynamically reshapes network architecture, with plant degree centrality correlations between mutualistic and antagonistic subnetworks emerging as a critical determinant of community stability. Notably, extreme centrality correlations, driven by interaction switching, can undermine network stability. In contrast, moderate correlations enhance resilience, rendering optimized networks more robust than their randomly assigned counterparts. These results underscore the importance of interaction switching in shaping the structure and stability of 3-guild ecological networks. Moreover, these findings provide mechanistic evidence that plant generalism fundamentally influences resilience in optimized networks, mediated through the evolutionary trade-off between herbivore defense and pollinator attraction.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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