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Adaptive networks are a versatile approach to model phenomena such ascontagion and spreading dynamics, critical transitions and structure formationthat emerge from the dynamic coevolution of complex network structure and nodestates. Here, we study critical transitions in contagion dynamics on multilayeradaptive networks with dynamic node states and present an application to thegovernance of sustainable resource use. We focus on a three layer adaptivenetwork model, where a polycentric governance network interacts with a socialnetwork of resource users which in turn interacts with an ecological network ofrenewable resources. We uncover that sustainability is favored for slowinteraction timescales, large homophilic network adaptation rate (as long it isbelow the fragmentation threshold) and high taxation rates. Interestingly, wealso observe a trade-off between an eco-dictatorship (reduced model with asingle governance actor that always taxes unsustainable resource use) and thepolycentric governance network of multiple actors. In the latter setup,sustainability is enhanced for low but hindered for high tax rates compared tothe eco-dictatorship case. These results highlight mechanisms generatingemergent critical transitions in contagion dynamics on multilayer adaptivenetwork and show how these can be understood and approximated analytically,relevant for understanding complex adaptive systems from various disciplinesranging from physics and epidemiology to sociology and global sustainabilityscience. The paper also provides insights into potential critical interventionpoints for policy in the form of taxes in the governance of sustainablerenewable resource use that can inform more process-detailed social-ecologicalmodeling.

the european physical journal. special topics

The physics of governance networks: critical transitions in contagion  dynamics on multilayer adaptive networks with application to the sustainable  use of renewable resources