论文标题

在复杂网络中倾斜级联的临界阈值如何条件:将微观链接到宏观尺度

How motifs condition critical thresholds for tipping cascades in complex networks: Linking Micro- to Macro-scales

论文作者

Wunderling, Nico, Stumpf, Benedikt, Krönke, Jonathan, Staal, Arie, Tuinenburg, Obbe A., Winkelmann, Ricarda, Donges, Jonathan F.

论文摘要

在这项研究中,我们研究了特定的微相互作用结构(基序)如何影响在风格化倾斜元件网络上的小费级联反应的发生。我们比较了Erdös-rényi网络中喀斯喀特的特性,以及亚马逊雨林的典范水分回收网络。在这些网络中,决定性的小规模基序是馈电回路,二次进料前环,零环和相邻环路。 在所有图案中,馈电回路图案在小费级联反应中脱颖而出,因为它降低了启动级联反应所需的关键耦合强度,而不是其他基序。我们发现,对于此基序,临界耦合强度的降低比一对小费元件的临界耦合少11%。对于高度连接的网络,我们的分析表明,耦合的馈电回路与临界耦合强度的降低90%相吻合。 对于亚马逊中高度聚集的水分回收网络,我们观察到四个研究的基序中的每个基序中的每个小主题都非常脆弱。发现基序的发生是比随机Erdös-rényi网络高的数量级。 这强调了本地互动结构对全球级联反应的重要性以及整个网络的稳定性。

In this study, we investigate how specific micro interaction structures (motifs) affect the occurrence of tipping cascades on networks of stylized tipping elements. We compare the properties of cascades in Erdös-Rényi networks and an exemplary moisture recycling network of the Amazon rainforest. Within these networks, decisive small-scale motifs are the feed forward loop, the secondary feed forward loop, the zero loop and the neighboring loop. Of all motifs, the feed forward loop motif stands out in tipping cascades since it decreases the critical coupling strength necessary to initiate a cascade more than the other motifs. We find that for this motif, the reduction of critical coupling strength is 11% less than the critical coupling of a pair of tipping elements. For highly connected networks, our analysis reveals that coupled feed forward loops coincide with a strong 90% decrease of the critical coupling strength. For the highly clustered moisture recycling network in the Amazon, we observe regions of very high motif occurrence for each of the four investigated motifs suggesting that these regions are more vulnerable. The occurrence of motifs is found to be one order of magnitude higher than in a random Erdös-Rényi network. This emphasizes the importance of local interaction structures for the emergence of global cascades and the stability of the network as a whole.

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