IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v491y2024ics0304380024000759.html
   My bibliography  Save this article

The landscape altered the interaction between vegetation and climate in the desert oasis of Hotan River Basin, Xinjiang, China

Author

Listed:
  • Cai, Yimeng
  • Wu, Jiaxin
  • Yimiti, Tudi
  • Li, Zhouyuan
  • Yang, Xiuchun
  • Dong, Shikui

Abstract

In the arid region, the oasis is characterized by a desert substance and a mosaic of vegetation. The biophysical processes and interactions between vegetation and the local climate in this kind of region are determined by the macroscopic structure of the ecosystems, i.e. landscape patterns. To understand how these landscape patterns impact regional hydro-heat coupling across space and evolve over time, we utilized remote sensing observational data and methods to examine the relationships among these factors. In this case, we focused on the oasis along the upstream of the Hotan River Basin in the Taklamakan Desert in Xinjiang of western China and employed the satellite imagery datasets of Landsat from 1993 to 2019 to investigate the dynamics of vegetation–climate factors. Based on the land use and cover change datasets, the landscape pattern metrics, including patch density (PD), contagion index (CONTAG), fractal dimension (FRAC), were calculated to measure the landscape features on the different aspects, i.e. the fragmentation, the connectivity, and the complexity. With the algorithm of land surface energy balance, the land surface indicators, including the soil-adjusted vegetation index (SAVI), albedo, surface irradiance temperature (Ts), and evapotranspiration (ET), were calculated to represent the key process in the interaction of vegetation–climate. The temporal-spatial dynamics of the landscape patterns and the vegetation–climate metrics were mapped and demonstrated in a quantitative manner. The statistical results revealed that during the past decades, the agricultural land in the study area had significantly increased by 17 %. Grassland and shrubs had also expanded, while the desert area decreased from 82.57 % to 78.82 % of the total area, with an overall reduction rate of 1.4 %/10a. It was found the study area was getting warmer and dryer based on the general trends of Ts and ET observed during the period of 1993–2019. The agricultural land had the highest PD and CONTAG, and the lowest FRAC. The agricultural land had the lowest Ts and the highest ET. The results of structural equation model identified the decoupling effects of PD and CONTAG on the regional hydro-heat environment, while confirmed that FRAC had positive impact on the coupling between Ts and ET. Our study bridged the landscape pattern with the regional vegetation–climate interaction and provided the suggestions for the landscape planning and management for a more sustainable arid region.

Suggested Citation

  • Cai, Yimeng & Wu, Jiaxin & Yimiti, Tudi & Li, Zhouyuan & Yang, Xiuchun & Dong, Shikui, 2024. "The landscape altered the interaction between vegetation and climate in the desert oasis of Hotan River Basin, Xinjiang, China," Ecological Modelling, Elsevier, vol. 491(C).
    • Handle: RePEc:eee:ecomod:v:491:y:2024:i:c:s0304380024000759
    DOI: 10.1016/j.ecolmodel.2024.110687
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380024000759
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2024.110687?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michel Wortmann & Doris Duethmann & Christoph Menz & Tobias Bolch & Shaochun Huang & Jiang Tong & Zbigniew W. Kundzewicz & Valentina Krysanova, 2022. "Projected climate change and its impacts on glaciers and water resources in the headwaters of the Tarim River, NW China/Kyrgyzstan," Climatic Change, Springer, vol. 171(3), pages 1-24, April.
    2. Ruiqi Li & Lei Dong & Jiang Zhang & Xinran Wang & Wen-Xu Wang & Zengru Di & H. Eugene Stanley, 2017. "Simple spatial scaling rules behind complex cities," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
    3. Bingbo Gao & Jianyu Yang & Ziyue Chen & George Sugihara & Manchun Li & Alfred Stein & Mei-Po Kwan & Jinfeng Wang, 2023. "Causal inference from cross-sectional earth system data with geographical convergent cross mapping," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massing, Till & Puente-Ajovín, Miguel & Ramos, Arturo, 2020. "On the parametric description of log-growth rates of cities’ sizes of four European countries and the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    2. He, Yifan & Zhao, Chen & Zeng, An, 2022. "Ranking locations in a city via the collective home-work relations in human mobility data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Zhu, Xuzhen & Wang, Ruijie & Wang, Zexun & Chen, Xiaolong & Wang, Wei & Cai, Shimin, 2019. "Double-edged sword effect of edge overlap on asymmetrically interacting spreading dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 617-624.
    4. Ruiqi Li & Lingyun Lu & Weiwei Gu & Shaodong Ma & Gang Xu & H. Eugene Stanley, 2020. "Assessing the attraction of cities on venture capital from a scaling law perspective," Papers 2011.06287, arXiv.org.
    5. Peña, Guillermo & Puente-Ajovín, Miguel & Ramos, Arturo & Sanz-Gracia, Fernando, 2022. "Log-growth rates of CO2: An empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    6. Bishawjit Mallick & Chup Priovashini & Jochen Schanze, 2023. "“I can migrate, but why should I?”—voluntary non-migration despite creeping environmental risks," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    7. Xu, Gang & Xu, Zhibang & Gu, Yanyan & Lei, Weiqian & Pan, Yupiao & Liu, Jie & Jiao, Limin, 2020. "Scaling laws in intra-urban systems and over time at the district level in Shanghai, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    8. Yang, Yan-Hong & Shao, Ying-Hui & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Revisiting the weak-form efficiency of the EUR/CHF exchange rate market: Evidence from episodes of different Swiss franc regimes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 734-746.
    9. Fábio Duarte & Ricardo Álvarez, 2019. "The data politics of the urban age," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-7, December.
    10. Xiaojian Yu & Zhiqing Zhao, 2021. "Fractal Characteristic Evolution of Coastal Settlement Land Use: A Case of Xiamen, China," Land, MDPI, vol. 11(1), pages 1-12, December.
    11. He, Zhengbing, 2020. "Spatial-temporal fractal of urban agglomeration travel demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    12. Shiro Horiuchi, 2021. "Bridging of different sites by bohemians and tourists: analysis by agent-based simulation," Journal of Computational Social Science, Springer, vol. 4(2), pages 567-584, November.
    13. He, Yifan & Zeng, An, 2024. "Expanding bottlenecks reveals hidden bottlenecks and leads to more congested city centers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    14. Daniel Zünd & Luís M A Bettencourt, 2019. "Growth and development in prefecture-level cities in China," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-15, September.
    15. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Zhi, Danyue & Song, Dongdong & Chen, Yan & de Bok, Michiel & Tavasszy, Lóránt A. & Gao, Ziyou, 2023. "Uncovering and modeling the hierarchical organization of urban heavy truck flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    16. Wang, Ning-Ning & Jin, Zhen & Wang, Ya-Jing & Di, Zeng-Ru, 2020. "Epidemics spreading in periodic double layer networks with dwell time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Chao Fan & Yang Yang & Ali Mostafavi, 2024. "Neural embeddings of urban big data reveal spatial structures in cities," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    18. Wang, Chen & Chu, Zhongzhu & Gu, Wei, 2021. "Assessing the role of public attention in China's wastewater treatment: A spatial perspective," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    19. Niu, Baozhuang & Chen, Yuyang & Zeng, Fanzhuo, 2023. "One step further for procurement cooperation: Will the industry leader benefit from its competitive manufacturer's joint determination of consumption quality?," European Journal of Operational Research, Elsevier, vol. 311(3), pages 989-1008.
    20. Pengjun Zhao & Hao Wang & Qiyang Liu & Xiao-Yong Yan & Jingzhong Li, 2024. "Unravelling the spatial directionality of urban mobility," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:491:y:2024:i:c:s0304380024000759. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.