Data from: Strong and weak environmental perturbations cause contrasting restructure of ant transportation networks

Dynamic transportation networks are embedded in all levels of biological
organisation. Ever-growing anthropogenic disturbances and an increasingly
variable climate highlight the importance of understanding how these
networks restructure under environmental perturbations. Polydomous wood
ants provide a convenient model system to study the resilience of
self-organising multi-source multi-sink transportation networks. We used
ten years of longitudinal empirical data on both unperturbed and
experimentally manipulated colony networks to develop and validate a
comprehensive dynamic simulation model to study network restructuring
after resource removal. We performed simulation experiments to study the
effects of excluding food sources with varying importance, either
temporarily or permanently, imitating pulse and press perturbations of the
networks. We found that removing heavily used resources, corresponding to
a strong targeted perturbation, persistently decreased network efficiency,
unlike random or weak perturbations. We also found that strong
perturbations had excessively adverse effects on robustness and function,
reducing the networks’ ability to withstand potential future
perturbations. When transportation networks develop around the efficient
use of a few key resources, they may be unable to quickly recover from the
loss of these through self-organized restructuring. Our findings highlight
the importance of considering the interaction of perturbation strength and
network structure in studying transportation network dynamics.

动态运输网络（dynamic transportation networks）嵌入于所有层级的生物组织之中。日益加剧的人为干扰与愈发多变的气候，凸显了探究这类网络在环境扰动下如何重构的重要意义。多巢木蚁（polydomous wood ants）为研究自组织多源多汇运输网络（self-organising multi-source multi-sink transportation networks）的恢复力提供了便捷的模式系统。我们依托十年来针对未受干扰与实验操控蚁群网络的纵向实证数据，开发并验证了一款用于研究资源移除后网络重构的综合动态模拟模型。我们开展了模拟实验，以探究暂时或永久移除重要性各异的食物源——即模拟该网络的脉冲型与压型扰动——所产生的效应。研究发现，相较于随机或弱扰动，移除高频使用的资源（对应强靶向扰动）会持续降低网络效率。此外，强扰动会对鲁棒性（robustness）与网络功能造成过度的负面影响，削弱网络抵御潜在未来扰动的能力。当运输网络围绕少数关键资源的高效利用形成时，它们或无法通过自组织重构快速弥补这些资源的损失。我们的研究结果强调，在开展运输网络动态研究时，需兼顾扰动强度与网络结构之间的交互作用。