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. 2021 Dec 2;4:1352. doi: 10.1038/s42003-021-02867-8

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — A visual intuition is provided to depict how network structure is associated with a particular resilience value. a Network resilience is calculated by iteratively isolating fractions of nodes in the network, f, eventually leaving N isolated nodes. b Following every iteration, the Shannon diversity of the component size distribution is calculated, in this case starting at f = 0 (one connected component), and increasing until every node is disconnected, f = 1. c Increasing the fraction of nodes that have been isolated creates a curve of increasing entropy values, which is used to compute the network resilience, as in Eq. (2). d An example of the prospective resilience of the network shown in (a). New nodes are iteratively added to the original network, with m links attached randomly or preferentially based on the degree of nodes in the network.