The response of ecosystem services to ecological spatial network patterns in China’s arid and semi-arid regions

• Recognizing ESN patterns from spatial self-organization of vegetation communities. • Spatiotemporal changes in ESN evaluate the effectiveness of ecological engineering. • Regional vegetation restoration enhances ecosystem stability in arid regions. • Shrublands exhibit higher ecological value in line and star patterns. China’s arid and semi-arid regions are facing severe land degradation. To combat desertification, China has launched large-scale ecological engineering, such as the Three-North Shelterbelt Program (TNSP). This study aims to uncover the feedback mechanisms of ecological spatial networks on ecological engineering effectiveness and analyze the spatial patterns of ecological sources and their ecosystem service responses. It also optimizes techniques for sand fixation, carbon sequestration, and desertification prevention. This study uses multi-source remote sensing and vector data (1986–2021) and complex network theory to extract ecological spatial networks and analyze TNSP’s spatiotemporal trends. The network motif discovery algorithm identifies spatial patterns and explores the relationships between pattern structure, distribution, and topological properties. Finally, it analyzes the response mechanisms between spatial patterns and ecosystem functions. The results show that since the TNSP’s implementation, the number of ecological sources (up by 653, with an area increase of 78,014 km 2 ) and corridors (up by 1,579, with a length increase of 29,591 km) have increased. Spatiotemporal changes in ecological networks reflect ecological engineering effectiveness and guide future optimization. The star, core-linked loop, and triangle patterns can enhance network stability. The star pattern exhibits the highest degree (4.66) and betweenness centrality (53,086), while the triangle and core-linked loop patterns have higher clustering coefficients of 0.315 and 0.250, respectively. Forests demonstrate the strongest sand fixation and carbon sequestration capacities across different patterns . Shrub sources under linear and star patterns significantly enhance ecological value and network stability.

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Publication Details

Journal
Ecological Indicators
Published
2025-03-01
DOI
https://doi.org/10.1016/j.ecolind.2025.113300
Citations
9
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
9.95
Controls
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article

The response of ecosystem services to ecological spatial network patterns in China’s arid and semi-arid regions

Mookhor Khishigjargal, Jikai Zhao, Weijie Sun, Buyanbaatar Avirmed et al.
9 citations
Ecological Indicators
Land Use and Ecosystem Services
9.95
article

The response of ecosystem services to ecological spatial network patterns in China’s arid and semi-arid regions

Mookhor Khishigjargal, Jikai Zhao, Weijie Sun, Buyanbaatar Avirmed, Qiang Yu, Yilin Liu, Huanjia Cui, Yu Wang, Naranbat Dambadarjaa, Ganbold Bayanmunkh, Sharavjamts Oyuntuya
article en
9 citations

Abstract

• Recognizing ESN patterns from spatial self-organization of vegetation communities. • Spatiotemporal changes in ESN evaluate the effectiveness of ecological engineering. • Regional vegetation restoration enhances ecosystem stability in arid regions. • Shrublands exhibit higher ecological value in line and star patterns. China’s arid and semi-arid regions are facing severe land degradation. To combat desertification, China has launched large-scale ecological engineering, such as the Three-North Shelterbelt Program (TNSP). This study aims to uncover the feedback mechanisms of ecological spatial networks on ecological engineering effectiveness and analyze the spatial patterns of ecological sources and their ecosystem service responses. It also optimizes techniques for sand fixation, carbon sequestration, and desertification prevention. This study uses multi-source remote sensing and vector data (1986–2021) and complex network theory to extract ecological spatial networks and analyze TNSP’s spatiotemporal trends. The network motif discovery algorithm identifies spatial patterns and explores the relationships between pattern structure, distribution, and topological properties. Finally, it analyzes the response mechanisms between spatial patterns and ecosystem functions. The results show that since the TNSP’s implementation, the number of ecological sources (up by 653, with an area increase of 78,014 km 2 ) and corridors (up by 1,579, with a length increase of 29,591 km) have increased. Spatiotemporal changes in ecological networks reflect ecological engineering effectiveness and guide future optimization. The star, core-linked loop, and triangle patterns can enhance network stability. The star pattern exhibits the highest degree (4.66) and betweenness centrality (53,086), while the triangle and core-linked loop patterns have higher clustering coefficients of 0.315 and 0.250, respectively. Forests demonstrate the strongest sand fixation and carbon sequestration capacities across different patterns . Shrub sources under linear and star patterns significantly enhance ecological value and network stability.

Ecological IndicatorsVol. 172
Mongolian University of Life Sciences (MN), Beijing Forestry University (CN), State Forestry and Grassland Administration (CN)
Life in Land
Openalex Percentile: Top 2%
Land Use and Ecosystem Services
9.95
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