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Journal of Arid Land
Journal of Arid Land  2025, Vol. 17 Issue (6): 735-753    DOI: 10.1007/s40333-025-0102-y     CSTR: 32276.14.JAL.0250102y
Review article     
Construction and optimization of ecological security pattern in the mainstream of the Tarim River Basin, China
QIN Xiaolin1,2, LIU Wei1,3, LING Hongbo1,2,*(), ZHANG Guangpeng1,2, GONG Yanming1,2, MENG Xiangdong1,4, SHAN Qianjuan1,2
1State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3College of Water Conservancy & Architectural Engineering, Shihezi University, Shihezi 832003, China
4College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
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Abstract  

Scientifically constructing an ecological security pattern (ESP) is an important spatial analysis approach to improve ecological functions in arid areas and achieve sustainable development. However, previous research methods ignored the complex trade-offs between ecosystem services in the process of constructing ESP. Taking the mainstream of the Tarim River Basin (MTRB), China as the study area, this study set seven risk scenarios by applying Ordered Weighted Averaging (OWA) model to trade-off the importance of the four ecosystem services adopted by this study (water conservation, carbon storage, habitat quality, and biodiversity conservation), thereby identifying priority protection areas for ecosystem services. And then, this study identified ecological sources by integrating ecosystem service importance with eco-environmental sensitivity. Using circuit theory, the ecological corridors and nodes were extracted to construct the ESP. The results revealed significant spatial heterogeneity in the four ecosystem services across the study area, primarily driven by hydrological gradients and human activity intensity. The ESP of the MTRB included 34 ecological sources with a total area of 1471.38 km², 66 ecological corridors with a length of about 1597.45 km, 11 ecological pinch points, and 13 ecological barrier points distributed on the ecological corridors. The spatial differentiation of the ESP was obvious, with the upper and middle reaches of the MTRB having a large number of ecological sources and exhibiting higher clustering of ecological corridors compared with the lower reaches. The upper and middle reaches require ecological protection to sustain the existing ecosystem, while the lower reaches need to carry out ecological restoration measures including desertification control. Overall, this study makes up for the shortcomings of constructing ESP simply by spatial superposition of ecosystem service functions and can effectively improve the robustness and stability of ESP construction.

Key words： ecological source      ecological corridor      river corridor      ecological resistance surface      ecological node      ecological network      kernel density analysis     
Received: 26 October 2024      Published: 30 June 2025
Corresponding Authors: *LING Hongbo (E-mail: linghb@ms.xjb.ac.cn)
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QIN Xiaolin
LIU Wei
LING Hongbo
ZHANG Guangpeng
GONG Yanming
MENG Xiangdong
SHAN Qianjuan
Cite this article:

QIN Xiaolin, LIU Wei, LING Hongbo, ZHANG Guangpeng, GONG Yanming, MENG Xiangdong, SHAN Qianjuan. Construction and optimization of ecological security pattern in the mainstream of the Tarim River Basin, China. Journal of Arid Land, 2025, 17(6): 735-753.

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http://jal.xjegi.com/10.1007/s40333-025-0102-y     OR     http://jal.xjegi.com/Y2025/V17/I6/735

Fig. 1 Overview the spatial distribution of land use in the mainstream of the Tarim River Basin (MTRB) in 2020. The image is from the Resource and Environmental Science Data Center, Chinese Academy of Sciences (https://www.resdc.cn/).
Data item Data source Resolution
Land cover GlobeLand 30 (https://www.globeland30.org/) 30 m
Digital elevation model (DEM) Geospatial Data Cloud (https://www.gscloud.cn) 30 m
Slope Geospatial Data Cloud (https://www.gscloud.cn) 30 m
Temperature MOD11A2 product (https://ladsweb.modaps.eosdis.nasa.gov) 1 km
Precipitation Global Resource Data Cloud (www.gis5g.com) 1 km
Surface reflectance MOD09A1 product
(https://ladsweb.modaps.eosdis.nasa.gov/)		 500 m
Net primary production (NPP) EARTHDATA (https://ladsweb.modaps.eosdis.nasa.gov/) 500 m
Distance to road (primary road, secondary road, and railway) Open Street Map (http://www.openstreetmap.org/) 500 m
Distance to water body Open Street Map (http://www.openstreetmap.org/) 500 m
Groundwater depth The Tarim River Basin Management Bureau 500 m
River network density Open Street Map (http://www.openstreetmap.org/) 500 m
Table 1 Detailed description of data used in the study
Fig. 2 Construction and optimization framework of ecological security pattern (ESP). DEM, digital elevation model; SMI, salinization monitoring index; DMI, desertification monitoring index; LVI, landscape vulnerability index; LDI, landscape disturbance index.
Land use type Cabove (t C/hm2) Cbelow (t C/hm2) Csoil (t C/hm2) Cdead (t C/hm2)
Cropland 3.47 4.12 86.22 1.24
Woodland 36.97 10.91 121.35 2.48
Grassland 0.58 5.13 85.02 0.22
Water body 0.76 0.54 0.00 0.00
Construction land 1.88 1.74 0.00 0.00
Unutilized land 0.54 1.04 43.39 0.00
Table 2 Carbon density of different land use types in the mainstream of the Tarim River Basin (MTRB)
Resistance factor Resistance value Weight
1.00 2.00 3.00 4.00 5.00
Land cover Woodland and water body Grassland Cropland Unutilized land Construction land 0.3415
DEM (m) 765-795 795-825 825-885 885-975 >975 0.0660
Slope (°) 0-5 5-15 15-25 25-35 35-53 0.2168
Distance to road (primary road, secondary, and railway) (m) >700 400-700 300-400 100-300 <100 0.2823
Distance to water body (m) <100 100-300 300-500 500-1000 >1000 0.0934
Table 3 Resistance value of each ecological resistance factor involved in this study
Fig. 3 Spatial distribution of ecosystem service in the MTRB in 2020. (a), water conservation; (b), carbon storage; (c), habitat quality; (d), biodiversity conservation.
Fig. 4 Spatial distribution of ecosystem service importance in the MTRB in 2020
Fig. 5 Spatial distribution of SMI (a), DMI (b), LVI (c), and LDI (d) in the MTRB in 2020
Fig. 6 Spatial distribution of eco-environmental sensitivity in the MTRB in 2020
Scenario Ecological risk Weight Ecological trade-off
Water conservation Carbon storage Habitat quality Biodiversity conservation
1 0.0001 0.0000 0.0000 0.0000 1.0000 0.0000
2 0.1000 0.0000 0.0550 0.0010 0.9440 0.0740
3 0.5000 0.0620 0.3120 0.1880 0.4380 0.6770
4 1.0000 0.2500 0.2500 0.2500 0.2500 1.0000
5 2.0000 0.5000 0.1590 0.2070 0.1340 0.6610
6 10.0000 0.8710 0.0390 0.0620 0.0280 0.1720
7 10,000.0000 1.0000 0.0000 0.0000 0.0000 0.0000
Table 4 Ecological risk and trade-offs between ecosystem services under different scenarios
Scenario Ecological risk Weight Conservation efficiency
Water conservation Carbon storage Habitat quality Biodiversity conservation
1 0.0001 1.2070 1.2310 1.4890 1.2720 1.3000
2 0.1000 1.2320 1.2560 1.5120 1.2980 1.3250
3 0.5000 1.3010 1.5530 1.7780 1.4220 1.5140
4 1.0000 1.4490 1.6500 1.8160 1.8770 1.6980
5 2.0000 1.5460 1.6670 1.8210 2.2830 1.8290
6 10.0000 1.5350 1.6610 1.8060 2.5510 1.8880
7 10,000.0000 1.5370 1.6540 1.8020 2.5850 1.8950
Table 5 Ecosystem service conservation efficiency under different scenarios
Fig. 7 Effect of the minimum patch area threshold on the number (a) and area proportion (b) of patches
Fig. 8 Spatial distribution of ecological sources in the MTRB in 2020
Fig. 9 Spatial distribution of ecological resistance surface in the MTRB in 2020
Fig. 10 Distribution of ESP in the MTRB
Fig. 11 Optimized layout of ecological corridors with river corridors in the MTRB in 2020
Fig. 12 Distribution of the ESP with the importance of ecological corridors in the MTRB in 2020
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