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Global environmental change is pushing many socio-environmental systems towards critical thresholds, where ecological systems’ states are on the precipice of tipping points and interventions are needed to navigate or avert impending transitions. Flickering, where a system vacillates between alternative stable states, is an early warning signal of transitions to alternative ecological regimes. However, while flickering may presage an ecological tipping point, these dynamics also pose unique challenges for human adaptation. We link an ecological model that can exhibit flickering to a model of human environmental adaptation to explore the impact of flickering on the utility of adaptive agents. When adaptive capacity is low, flickering causes wellbeing to decline disproportionately. As a result, flickering dynamics move forward the optimal timing of a transformational change that can secure wellbeing despite environmental variability. The implications of flickering on communities faced with desertification, fisheries collapse, and ecosystem change are explored as possible case studies. Flickering, driven in part by climate change and extreme events, may already be impacting communities. Our results suggest that governance interventions investing in adaptive capacity or facilitating transformational change before flickering arises could blunt the negative impact of flickering as socio-environmental systems pass through tipping points.
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Mean-field theory for double-well systems on degree-heterogeneous networks
Many complex dynamical systems in the real world, including ecological, climate, financial and power-grid systems, often show critical transitions, or tipping points, in which the system’s dynamics suddenly transit into a qualitatively different state. In mathematical models, tipping points happen as a control parameter gradually changes and crosses a certain threshold. Tipping elements in such systems may interact with each other as a network, and understanding the behaviour of interacting tipping elements is a challenge because of the high dimensionality originating from the network. Here, we develop a degree-based mean-field theory for a prototypical double-well system coupled on a network with the aim of understanding coupled tipping dynamics with a low-dimensional description. The method approximates both the onset of the tipping point and the position of equilibria with a reasonable accuracy. Based on the developed theory and numerical simulations, we also provide evidence for multistage tipping point transitions in networks of double-well systems.
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- Award ID(s):
- 2052720
- PAR ID:
- 10390115
- Date Published:
- Journal Name:
- Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Volume:
- 478
- Issue:
- 2264
- ISSN:
- 1364-5021
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1098/rspa.2022.0350
