Spatial differentiation of ecosystem service value in an arid region: A case study of the Tarim River Basin, Xinjiang

• Published in: Ecological indicators Vol. 151; p. 110249
• Main Authors: Kulaixi, Zulipiya, Chen, Yaning, Wang, Chuan, Xia, Qianqian
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2023; Elsevier
• Subjects: Ecosystem service value; Geographical detector model; Spatiotemporal variation; Tarim River Basin; QRB; RS; Pre; PS; TRB; WRB; El; BL; WB; ESDA; FR; NDVI; NPP; Tarim River Basin; GDP; DW; UL; LUI; LULC; Spatiotemporal variation; ESV; Geographical detector model; EP; GS; VC; ES; CR; Pop; HAI; RSS; KRRB; DRB; KRB; Ecosystem service value; Tem
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2023.110249

•More intensive land use activities were observed in the TRB during 1990–2018.•The ESV of five sub-basins of the TRB showed a decreasing trend during 1990–2018, which was mainly caused by the decrease in regulating services;•ESV had a strong positive spatial correlation in the study area, and most grid cells were within “High-High” (HH) or “Low-Low” (LL) aggregation areas.•The spatial differentiation of ESV in the TRB was influenced by a combination of natural, anthropogenic, as well as socioeconomic factors. Ecosystem service value (ESV) in arid regions is subject to multiple factors, and the main factors affecting ESV may vary in different regions. However, there are fewer studies concerned with the spatial heterogeneity of the factors influencing ESV in arid regions. In this study, we selected five typical sub-basins of the Tarim River Basin (TRB), including the Kashghar (KRB), the Weigan (WRB), the Dinah (DRB), the Keriya (KRRB), and the Qarqan (QRB) river basins, as research objects to investigate the ESV. Firstly, we estimated the ESV by utilizing the LULC data sets and benefits transfer methods. Next, we conducted a systematic analysis of the spatial variations of ESV. Finally, we analyzed the driving factors of spatial variation of ESV using a geographical detector model. Our results show that: (1) During 1990–2018, various land use types underwent complex dynamic transformations, including the conversion of grassland and water bodies into cropland and unused land. (2) Over the 29-year study period, the five studied TRB sub-basins show a decreasing trend in total ESV during 1990–2018, with the largest reduction observed in KRRB (-230.64 × 107 USD), followed by WRB (-105.43 × 107 USD), and the smallest in QRB (-10.31 × 107 USD). Moreover, environment depuration (ED), climate regulation (CR), hydrological regulation (HR), and soil conservation (SC) were the key components of high service value in the study area. (3) The spatial distribution of ESV demonstrated strong positive spatial autocorrelation, with high and low values clustering on a spatial scale. Our analysis of driving forces revealed that spatial differentiation is the result of a synergistic effect of natural factors such as elevation, temperature, and precipitation, as well as anthropogenic and socioeconomic factors. Based on the results obtained, our study serves as a crucial foundation for implementing necessary measures aimed at achieving ecological security and promoting sustainable development in the TRB area.