Analyzing the Interrelationships among Various Ecosystem Services from the Perspective of Ecosystem Service Bundles in Shenyang, China

Shuang Gan, Yu Xiao, Keyu Qin, Jingya Liu, Jie Xu, Yangyang Wang, Yingnan Niu, Mengdong Huang and Gaodi Xie
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Shuang Gan: Graduate School of Media and Governance, Shonan Fujisawa Campus, Keio University, Fujisawa 252-0882, Japan
Yu Xiao: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Keyu Qin: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Jingya Liu: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Jie Xu: School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
Yangyang Wang: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yingnan Niu: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Mengdong Huang: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Gaodi Xie: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Land, 2022, vol. 11, issue 4, 1-17

Abstract: An understanding of the relationships among multiple ecosystem services (ES) facilitates ecosystem management and decision-making. The study of ES bundles can well explain the complex interactions between different ES in a region. Shenyang is a significant economic development and food production area in Northeast China, with a diverse range of ES types. In this study, we quantified eleven ES from Shenyang, China (two provisioning services, eight regulating services, and one cultural service). The trade-offs and synergies among ES were analyzed by Spearman’s correlation analysis. The ES bundles were identified using principal component analysis and k-means cluster analysis. Finally, the random forest method was employed to identify the driving factors affecting the ES bundles. The results showed: (1) all ES in Shenyang improved between 2000 and 2019; (2) the most obvious trade-off was found between sand fixation and water conservation; (3) the ES in the study region could be clustered into five different ES bundles which were primarily affected by land-use type; and (4) social-ecological factors largely explained and predicted the formation and distribution of ES bundles. The study provides reference information for the management and optimization of Shenyang’s ecosystems and land use regulation.

Keywords: ecosystem service bundle; trade-off; synergy; socio-ecological factors; spatial analysis (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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