Institute for Complex Systems and Mathematical Biology, King's College, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom.
Chaos. 2021 Feb;31(2):023118. doi: 10.1063/5.0036051.
Nonlinear stochastic complex networks in ecological systems can exhibit tipping points. They can signify extinction from a survival state and, conversely, a recovery transition from extinction to survival. We investigate a control method that delays the extinction and advances the recovery by controlling the decay rate of pollinators of diverse rankings in a pollinators-plants stochastic mutualistic complex network. Our investigation is grounded on empirical networks occurring in natural habitats. We also address how the control method is affected by both environmental and demographic noises. By comparing the empirical network with the random and scale-free networks, we also study the influence of the topological structure on the control effect. Finally, we carry out a theoretical analysis using a reduced dimensional model. A remarkable result of this work is that the introduction of pollinator species in the habitat, which is immune to environmental deterioration and that is in mutualistic relationship with the collapsed ones, definitely helps in promoting the recovery. This has implications for managing ecological systems.
生态系统中的非线性随机复杂网络可能会出现临界点。它们可以表示从生存状态到灭绝的转变，反之亦然，从灭绝到生存的恢复转变。我们研究了一种控制方法，通过控制不同等级的传粉者在传粉者-植物随机互惠复杂网络中的衰减率，来延迟灭绝并促进恢复。我们的研究基于自然栖息地中出现的经验网络。我们还研究了控制方法如何受到环境和人口噪声的影响。通过将经验网络与随机网络和无标度网络进行比较，我们还研究了拓扑结构对控制效果的影响。最后，我们使用简化的二维模型进行了理论分析。这项工作的一个显著结果是，在栖息地中引入对环境恶化具有免疫力并且与已崩溃物种互惠共生的传粉物种，肯定有助于促进恢复。这对管理生态系统具有重要意义。
