Predicting the minimum scale of urban ecological space based on socio-ecological systems analysis

Wuyang Hong; Chuangchang Liao; Renzhong Guo; Qi An; Xiaoming Li; Tao Ma

doi:10.1016/j.scitotenv.2022.160912

Predicting the minimum scale of urban ecological space based on socio-ecological systems analysis

Sci Total Environ. 2023 Mar 10:863:160912. doi: 10.1016/j.scitotenv.2022.160912. Epub 2022 Dec 13.

Authors

Wuyang Hong¹, Chuangchang Liao¹, Renzhong Guo¹, Qi An², Xiaoming Li³, Tao Ma⁴

Affiliations

¹ School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518000, China; Research Institute for Smart Cities, Shenzhen University, Shenzhen 518000, China.
² Architecture College, Harbin Institute of Technology, Shenzhen 518000, China; Shenzhen Bureau of Planning and Natural Resources, Shenzhen 518000, China.
³ School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518000, China; Research Institute for Smart Cities, Shenzhen University, Shenzhen 518000, China. Electronic address: lixming@szu.edu.cn.
⁴ School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518000, China.

PMID: 36526169
DOI: 10.1016/j.scitotenv.2022.160912

Abstract

Determining the minimum scale of ecological space that is sufficient for sustainable urban development is one of the difficult tasks in quantitative urban ecological research. In this study, we first expounded on the basic concept of the minimum scale of urban ecological space and reviewed the research status. Supported by the theory of "aggregation and dispersion" in landscape ecology, we converted the task of scale prediction into spatial accounting-oriented scenario simulation. We then proposed a method to predict the scale, based on an analysis of socio-ecological systems, and constructed a research framework of "construction constraint analysis - ecological importance evaluation scale prediction." The rules to discriminate the optimal scenario and the characteristics indices of the network were also proposed. Second, we selected Shenzhen City as a representative study object and constructed 87 ecological networks under different scenarios, based on the construction constraints and spatial distribution of ecosystem services, identified from the multi-source data in the study area. By calculating and comparing the network efficiency and clustering coefficient, we concluded that the network under the m39 scenario has the optimal connection efficiency and structural stability. We finally obtained a threshold of 48.85 % as the minimum proportion of ecological land in Shenzhen. We expect that this result can help improve the rationality of decision-making in urban spatial planning and governance.

Keywords: Complex network; Minimum scale of ecological space; Prediction algorithm; Shenzhen; Socio-ecological systems.