image: Classification of coastal tipping points(a) Bifurcation-driven tipping point, (b) Noise-driven tipping point, (c) Rate-driven tipping point, (d) Shock-driven tipping point, (e) Space-driven tipping point, and (f) Information-driven tipping point
Credit: ©Science China Press
A team led by Zhaoyuan Yu and Linwang Yuan from Nanjing Normal University has introduced a groundbreaking unified mathematical description model for coastal tipping points. Published in SCIENCE CHINA Earth Sciences, the work addresses the escalating risks in coastal zones, critical interfaces between land and sea that host diverse ecosystems like wetlands, estuaries, and coral reefs.
Under dual pressures from climate change and human activities, coastal areas face intensifying threats such as sea-level rise, shoreline erosion, wetland loss, and ecological collapse. These changes can push systems past tipping points, triggering abrupt, often irreversible shifts. Unlike global climate tipping points, coastal ones exhibit strong regional traits, influenced by coupled physical, ecological, and social subsystems. The researchers built their model on dynamical systems theory, incorporating spatiotemporal diffusion tensors and interaction fluxes to embed land-sea couplings and multi-scale dynamics. This enables precise representation of nonlinear responses, thresholds, and hysteresis. They classified tipping points into six types: bifurcation-driven (gradual parameter shifts causing instability), noise-driven (random fluctuations amplifying vulnerabilities), shock-driven (sudden extreme events), rate-driven (rapid forcing overwhelming adaptation), space-driven (spatial heterogeneity sparking cascades), and information-driven (knowledge gaps delaying responses).
To validate the framework, the team used large language models to analyze literature on 91 global coastal cases, revealing widespread yet uneven distribution, hotspots in densely populated or ecologically fragile regions. These insights underscore the need for integrated "classification-identification-response" strategies, including better data integration and adaptive governance. The study provides a robust foundation for predicting and mitigating coastal regime shifts, safeguarding ecosystems and communities worldwide.
See the article:
Yu Z, Liang Z, Wang J, Liu Z, Du P, Zhao B, Yuan L. 2025. Unified description model and typology classification of coastal tipping points. Science China Earth Sciences, 68(11): 3482–3494, https://doi.org/10.1007/s11430-025-1698-8
Journal
Science China Earth Sciences