Optimization of coupling and global collapse in diffusively coupled socio-ecological resource exploitation networks
arXiv:2010.13466 · doi:10.1088/1367-2630/abe0db
Abstract
Single- and multi-layer complex networks have been proven as a powerful tool to study the dynamics within social, technological,or natural systems. An often observed common goal there is to optimize these systems for specific purposes by minimizing certain costs while maximizing a desired output. Acknowledging that especially real-world systems from the coupled socio-ecological realm are highly intertwined this work exemplifies that in such systems the optimization of a certain subsystem, e.g., to increase the resilience against external pressure in an ecological network, may unexpectedly diminish the stability of the whole coupled system. For this purpose we utilize an adaptation of a previously proposed conceptual bilayer network model composed of an ecological network of diffusively coupled resources co-evolving with a social network of interacting agents that harvest these resources and learn each other's strategies depending on individual success. We derive an optimal coupling strength that prevents a collapse in as many resources as possible if one assumes that the agents' strategies remain constant over time. However, we then show that if agents socially learn and adapt strategies according to their neighbors' success, this optimal coupling strength is revealed to be a critical parameter above which the probability for a global collapse in terms of irreversibly depleted resources is high -- an effect that we denote the tragedy of the optimizer. We thus find that measures which stabilize the dynamics within a certain part of a larger co-evolutionary system may unexpectedly cause the emergence of novel undesired globally stable states. Our results therefore underline the importance of holistic approaches for managing socio-ecological systems because stabilizing effects which focus on single subsystems may be counter-beneficial for the system as a whole.
References in corpus (27)
- Statistical physics of social dynamics
- Epidemic processes in complex networks
- Synchronization in complex networks
- Multilayer Networks
- The Kuramoto model in complex networks
- Epidemic dynamics on an adaptive network
- Thresholds for epidemic spreading in networks
- The physics of spreading processes in multilayer networks
- Nonequilibrium phase transition in the coevolution of networks and opinions
- The Multilayer Nature of Ecological Networks
- Network Synchronization, Diffusion, and the Paradox of Heterogeneity
- A generalized model of social and biological contagion
- Human strategy updating in evolutionary games
- Measuring large-scale social networks with high resolution
- Comparative analysis of existing models for power-grid synchronization
- Investigating the topology of interacting networks - Theory and application to coupled climate subnetworks
- A Random Growth Model for Power Grids and Other Spatially Embedded Infrastructure Networks
- Coexistence and Survival in Conservative Lotka-Volterra Networks
- Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World-Earth modeling framework
- Macroscopic description of complex adaptive networks co-evolving with dynamic node states
- The impact of model detail on power grid resilience measures
- Detecting degree symmetries in networks
- Node-weighted interacting network measures improve the representation of real-world complex systems
- Zealotry Effects on Opinion Dynamics in the Adaptive Voter Model
- Diffusion-induced instability and chaos in random oscillator networks
- Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
- The physics of governance networks: critical transitions in contagion dynamics on multilayer adaptive networks with application to the sustainable use of renewable resources