Resilience and sustainable development goals based social-ecological indicators and assessment of coastal urban areas ——A case study of Dapeng New District, Shenzhen, China

The coastal area, with its fragile environment and the characteristics of both marine and terrestrial, is getting increasing attention globally, highlighting a critical need to form a systematic management framework. The objectives of this article are to illustrate the status quo of Chinese regional ecological civilization and land-sea integrated development, then combine resilience theory and sustainable development goals (SDGs) of United Nations together for selecting social-ecological indicators to build a resilience assessment matrix applying to the coastal urban area, further explore the core mechanisms of coastal resilience evolution. Accordingly, we suggest a new method of evaluation matrix with 12 indicators, representing the function of the target system in four phases (prepare, absorb, recover and adapt) and three domains (economic, natural resources and eco-environment) respectively, which focusing on the dynamic progress instead of the static situation of the typical and unique urbanizing area is exactly one of its improvements in comparison with other existing assessment tools. The key findings reveal the dificient resilience of Dapeng New District in dealing with the rapid urbanization stressor, as well as its asymmetrical performance among three subsystems within the temporal scope of 2014–2016. Another contribution reflected in the regime shifts of land-sea integration, which uncovers the states of critical functions in the target system, correspondingly outlines how to integrate the land use, water management, and biodiversity conservation into resilience-based management and sustainability for the coastal zone, namely the Land-Water-Biodiversity Nexus. Our scope is taking the typical coastal zone, Shenzhen Dapeng New District, Greater Bay Area of China, as an example, and to promote the research technology in other coastal urban regions.