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Journal of Arid Land
Journal of Arid Land  2025, Vol. 17 Issue (1): 19-42    DOI: 10.1007/s40333-025-0093-8     CSTR: 32276.14.JAL.02500938
Research article     
Ecological security pattern construction using landscape ecological quality: A case study of Yanchi County, northern China
LI Junhao1,2, WANG Ya1,*(), SHI Gui2,3, PEI Xiaodong2,3, ZHANG Cong2,3, ZHOU Lihua2,3, YANG Guojing1
1Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
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Abstract  

Ecological security patterns are paramount to the advancement of an ecological civilization in China, aiming to enhance the stability and service functions of ecosystems to achieve sustainable regional development. However, current regional ecological protection efforts have not been effectively integrated into the regional development planning of ecological security pattern. This study systematically assessed the effectiveness of ecological protection projects in Yanchi County, Ningxia Hui Autonomous Region, China, through the evaluation of landscape ecological quality. Based on the evaluation results of landscape ecological quality, this study used morphological pattern analysis (MSPA), minimum cumulative resistance (MCR) model, and gravity model together to construct the ecological security pattern of Yanchi County. The findings revealed that from 1990 to 2020, with the implementation of ecological protection projects started from 2000, the landscape stability of Yanchi County first decreased and then increased, and the intensity of landscape disturbance first intensified but then decreased, indicating an improvement in the landscape ecological quality and a significant enhancement of the ecological environment in Yanchi County. The ecological security pattern of Yanchi County consisted of 10 ecological sources, 10 ecological source points, 23 ecological corridors, and 27 ecological nodes. The ecological security pattern of Yanchi County exhibited distinct spatial variations, with stronger ecological security observed in the southern part than in northern part of the county. The ecological sources were denser in the southern part than in the northern part of the county, and accordingly, the length of ecological corridors was shorter and denser in the southern than that in the northern part of the county. Based on the spatial distribution of landscape ecological quality and the characteristics of ecological security pattern of Yanchi County in 2020, we suggested Yanchi County to build four zones to optimize the ecological security pattern construction: the Haba Lake ecological conservation zone, the urban ecological planning zone, the ecological environment restoration zone, and the ecological security improvement zone. This study can provide essential guidance for the construction of ecological security pattern in farming-pastoral areas both in China and worldwide.

Key words： landscape ecological quality      landscape stability      landscape disturbance      ecological network      ecological source      ecological corridor      farming-pastoral area     
Received: 17 July 2024      Published: 31 January 2025
Corresponding Authors: *WANG Ya (E-mail: wangya2014@lzb.ac.cn)
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LI Junhao
WANG Ya
SHI Gui
PEI Xiaodong
ZHANG Cong
ZHOU Lihua
YANG Guojing
Cite this article:

LI Junhao, WANG Ya, SHI Gui, PEI Xiaodong, ZHANG Cong, ZHOU Lihua, YANG Guojing. Ecological security pattern construction using landscape ecological quality: A case study of Yanchi County, northern China. Journal of Arid Land, 2025, 17(1): 19-42.

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http://jal.xjegi.com/10.1007/s40333-025-0093-8     OR     http://jal.xjegi.com/Y2025/V17/I1/19

Fig. 1 Overview of terrain in Yanchi County. DEM, digital elevation model.
Data type Resolution Year Data source Reference
Land use type 30 m 1990, 2000, 2010, and 2020 Resource and Environmental Science Data Center, Chinese Academy of Sciences (https://www.resdc.cn/) Luo and Li (2021)
DEM 30 m 2020 Geospatial Data Cloud (https://www.gscloud.cn/) Yang et al. (2023)
Landsat TM 30 m 1990, 2000, and 2010 United States Geological Survey
(https://earthexplorer.usgs.gov/)		 Yang et al. (2024)
Landsat 8 OLI 30 m 2020 United States Geological Survey
(https://earthexplorer.usgs.gov/)		 Su et al. (2017)
County boundary - 2020 Resource and Environmental Science Data Center, Chinese Academy of Sciences (https://www.resdc.cn/) Wang et al. (2019)
Township boundary - 2015 Resource and Environmental Science Data Center, Chinese Academy of Sciences (https://www.resdc.cn/) Wei et al. (2020)
Administrative village boundary - 2013 Resource and Environmental Science Data Center, Chinese Academy of Sciences (https://www.resdc.cn/) Xu et al. (2019)
Distance to residential area 30 m 2020 National Geographic Information Resource Directory Service (https://www.webmap.cn/) Yang et al. (2021) and Li et al. (2022)
Distance to tertiary road 30 m 2020 National Geographic Information Resource Directory Service (https://www.webmap.cn/) Li et al. (2022)
Distance to ordinary railway 30 m 2020 National Geographic Information Resource Directory Service (https://www.webmap.cn/) Yin et al. (2011)
Table 1 Detailed description of data used in the study
Fig. 2 Research framework of this study. NDVI, normalized difference vegetation index; MSPA, morphological spatial pattern analysis; MCR, minimum cumulative resistance.
Dimension Indicator Subjective weight Objective weight Combined weight
Landscape stability Shannon's diversity index 0.25 0.20 0.22
Land use structure index 0.24 0.16 0.20
Normalized difference vegetation index (NDVI) 0.34 0.26 0.30
Landscape connectivity index 0.10 0.18 0.14
Landscape dominance index 0.07 0.21 0.14
Landscape disturbance Landscape fragmentation index 0.27 0.23 0.25
Construction land disturbance index 0.16 0.27 0.22
Land use dominance index 0.20 0.28 0.24
Landscape shape index 0.16 0.14 0.15
Landscape separation index 0.20 0.08 0.14
Table 2 List of indicators used to establish landscape ecological quality assessment system
Resistance factor Resistance value Weight
1.00 2.00 3.00 4.00 5.00 6.00
Land use type Forest land Water body Grassland Cultivated land Construction land Unused land 0.17
DEM (m) <1400 1400-1500 1500-1600 1600-1700 1700-1800 >1800 0.43
Distance to residential area (m) >20,000 16,000-20,000 12,000-16,000 8000-12,000 4000-8000 <4000 0.15
Distance to tertiary road (m) >2500 2000-2500 1500-2000 1000-1500 500-1000 <500 0.06
Distance to ordinary railway (m) >35,000 28,000-35,000 21,000-28,000 14,000-21,000 7000-14,000 <7000 0.19
Table 3 Weight of each resistance factor
No. of ecological source No. of ecological source
1 2 3 4 5 6 7 8 9 10
1 0.00 100.61 66.41 61.43 19.08 18.99 16.05 11.99 10.56 23.64
2 115.19 47.50 13.79 18.47 11.48 8.44 7.65 16.15
3 164.48 37.05 72.85 27.48 17.34 17.86 32.03
4 83.53 93.24 59.55 35.72 32.55 86.63
5 249.04 1239.78 166.94 323.61 212.03
6 118.16 46.85 78.06 69.05
7 383.43 653.34 234.71
8 198.89 302.52
9 93.22
10 0.00
Table 4 Interaction intensity between ecological sources
Fig. 3 Spatial distribution of landscape stability in Yanchi County in 1990 (a), 2000 (b), 2010 (c), and 2020 (d)
Fig. 4 Spatial distribution of landscape disturbance in Yanchi County in 1990 (a), 2000 (b), 2010 (c), and 2020 (d)
Fig. 5 Spatial distribution of landscape ecological quality in Yanchi County in 1990 (a), 2000 (b), 2010 (c), and 2020 (d)
Fig. 6 Spatial distribution of changes in landscape ecological quality in Yanchi County from 1990 to 2020. (a), 1990-2000; (b), 2000-2010; (c), 2010-2020; (d), 1990-2020.
Fig. 7 Distribution of landscape patch type (a) and ecological source (b) in Yanchi County in 2020. The number in Figure 7b is the serial number of ecological source identified by this study.
Fig. 8 Distribution of ecological resistance surface (a) and corridor (b) in Yanchi County in 2020. The number is the serial number of ecological source identified by this study.
Fig. 9 Ecological security pattern of Yanchi County in 2020. The number is the serial number of ecological source identified by this study.
Fig. 10 Spatial planning for ecological security pattern of Yanchi County. The number is the serial number of ecological source identified by this study.
No. of ecological source PII Area (km2)
1 4.97 139.72
2 21.79 271.54
3 2.49 18.01
4 12.69 203.78
5 18.96 11.12
6 31.41 228.62
7 20.47 26.03
8 16.00 13.80
9 3.78 24.01
10 37.36 297.00
Table S1 Patch importance index (PII) and area of each selected ecological source
Width (m) Type of corridor Item Cultivated land Forest land Grassland Water body Construction land Unused land
30.00 Important Area (km2) 1.90 1.44 8.65 0.04 0.09 0.45
Percentage (%) 15.12 11.46 68.81 0.32 0.72 3.58
General Area (km2) 3.47 4.66 15.42 0.27 0.23 1.49
Percentage (%) 13.59 18.25 60.38 1.06 0.90 5.83
60.00 Important Area (km2) 3.84 2.89 17.17 0.08 0.17 0.96
Percentage (%) 15.29 11.51 68.38 0.32 0.68 3.82
General Area (km2) 7.11 9.28 30.92 0.54 0.49 3.15
Percentage (%) 13.81 18.02 60.05 1.05 0.95 6.12
100.00 Important Area (km2) 6.52 4.72 28.20 0.13 0.33 1.77
Percentage (%) 15.65 11.33 67.67 0.31 0.79 4.25
General Area (km2) 12.20 15.03 51.16 0.84 0.85 5.80
Percentage (%) 14.21 17.50 59.57 0.98 0.99 6.75
200.00 Important Area (km2) 13.30 8.37 55.15 0.21 0.73 4.84
Percentage (%) 16.10 10.13 66.77 0.25 0.88 5.86
General Area (km2) 25.11 28.50 100.40 1.33 2.09 14.72
Percentage (%) 14.59 16.56 58.32 0.77 1.21 8.55
Table S2 Area and percentage of each land use type in different widths of ecological corridors
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