Trade-Offs, Synergies, and Driving Factors of Ecosystem Services in the Urban–Rural Fringe of Beijing at Multiple Scales

Chang Wang, Siyuan Wang, Bing Qi, Chuling Jiang, Weiyang Sun, Yilun Cao and Yunyuan Li ()
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Chang Wang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Siyuan Wang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Bing Qi: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Chuling Jiang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Weiyang Sun: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Yilun Cao: School of Architecture, Southeast University, Nanjing 210096, China
Yunyuan Li: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China

Land, 2025, vol. 14, issue 5, 1-26

Abstract: Urban–rural fringe areas are critical transition zones where ecological functions and human activities interact intensely, often leading to complex spatial patterns and trade-offs among ecosystem services (ESs). Understanding these patterns and their socio-ecological drivers across multiple spatial scales is essential for sustainable land-use planning and ecosystem management. This study, using the urban–rural fringe (URF) of Beijing as an example, quantified eight representative ecosystem services at the 1 km grid, 3 km grid, and township scales. It employed hotspot analysis, Moran’s Index, and the Spearman correlation to analyze trade-offs and synergies (TOSs) among ESs. The study also applied a self-organizing map and the NbClust function to identify and determine the optimal number of ecosystem service bundles (ESBs) for ecological functional zoning. Redundancy analysis was used to explore the impacts of six socio-ecological drivers on the spatial distribution of ESs. The results revealed the following: (1) The spatial distribution of ESs in Beijing’s URF exhibits clustering and cross-scale variations, with spatial clustering intensifying as the scale expands. (2) TOSs among ESs vary in strength and direction across the three spatial scales. (3) The primary drivers of TOSs at all three scales are the normalized vegetation index and annual precipitation. (4) Based on the supply intensity of various ESs, the study area was classified into four types of ESBs across the three scales: ecologically restricted areas, food production areas, ecologically balanced areas, and high-quality ecological areas. The township scale is more conducive to planning and management, while the 1 km and 3 km grid scales are more helpful for understanding the relationship between land use and ESs.

Keywords: green space; bundle; landscape planning; socio-ecological factors; decision-making (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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