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Spatio-Temporal Dynamics and Drivers of Ecosystem Service Bundles in the Altay Region: Implications for Sustainable Land Management

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  • Suyan Yi

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

  • Hongwei Wang

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

  • Ling Xie

    (College of Environment and Resources, Guangxi Normal University, Guilin 541004, China)

  • Can Wang

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

  • Xin Huang

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

Abstract

Understanding the dynamics of ecosystem services (ESs) in arid landscapes and socio-ecological systems is crucial for sustainable development and human well-being. This study uses the Invest model to quantify the spatio-temporal changes in four key ecosystems services in Altay from 1990 to 2020: water yield (water yield), carbon stock (carbon stock), soil retention (soil retention), and habitat quality (habitat quality). The trade-offs/synergies between different ESs were investigated via Spearman’s correlation analysis. Ecosystem service bundles (ESBs) were mapped using self-organizing mapping (SOM), and the key drivers of ES relationships and the spatio-temporal dynamics of ESBs were revealed through redundancy analysis. The results showed that water yield increased by 33.7% and soil retention increased by 1.2%, while carbon stock and habitat quality decreased by 3.5% and 1.24%, respectively. The spatial distribution pattern had a clear zonal pattern, with the northern mountainous areas higher than the southern desert areas. The six pairs of ESs, in general, showed mainly low trade-off and high synergistic relationships, with trade-offs between water yield and carbon stock, soil retention and habitat quality, and a decreasing trend of trade-offs over time. Four types of ESBs were distinguished, and the compositional differences and spatial distribution within each ESB were determined by interactions between ESs and landscape types. There are complex non-linear relationships between the drivers and the four ESBs in different years. Before 2010, ecological factors were the key drivers influencing the spatio-temporal changes in ESBs, whereas social and environmental factors combined to drive changes in ESB allocations after 2010. Additionally, this study found that the implementation of conservation measures, such as reforestation and sustainable land management practices, positively influenced the provision of ecosystem services in the Altay region. These findings underscore the importance of integrating conservation efforts into land use planning and decision-making processes to ensure the sustainable delivery of ecosystem services in arid landscapes.

Suggested Citation

  • Suyan Yi & Hongwei Wang & Ling Xie & Can Wang & Xin Huang, 2024. "Spatio-Temporal Dynamics and Drivers of Ecosystem Service Bundles in the Altay Region: Implications for Sustainable Land Management," Land, MDPI, vol. 13(6), pages 1-16, June.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:6:p:805-:d:1409698
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    References listed on IDEAS

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    1. Stephen Polasky & Erik Nelson & Derric Pennington & Kris Johnson, 2011. "The Impact of Land-Use Change on Ecosystem Services, Biodiversity and Returns to Landowners: A Case Study in the State of Minnesota," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(2), pages 219-242, February.
    2. Zhao, Mingyue & Peng, Jian & Liu, Yuanxin & Li, Tianyi & Wang, Yanglin, 2018. "Mapping Watershed-Level Ecosystem Service Bundles in the Pearl River Delta, China," Ecological Economics, Elsevier, vol. 152(C), pages 106-117.
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