Spatiotemporal evolution and drivers of production-living-ecological land in the northern Tianshan Mountains using complex network analysis

The unbalanced development of production-living-ecological land (PLEL) on the northern slope of the Tianshan Mountains has led to a series of environmental and ecological problems. Clarifying the evolution of spatial and temporal patterns and driving mechanisms of the PLEL is highly important for promoting the optimization of land use functions and sustainable development in this region. Previous research has focused primarily on the area or probability of conversion between different types of PLEL, neglecting the overall structural characteristics of the PLEL system. It is difficult to quantify the connectivity and importance of each PLEL type within the entire PLEL system, making it challenging to identify key PLEL types. Furthermore, quantitative characterization of the PLEL system stability is lacking. Accordingly, in this paper, PLEL conversion networks were constructed on the basis of complex network theory, and the dynamic evolution of the PLEL was analyzed from a systemic and holistic perspective. Network metrics (weighted degree, integrated node centrality, and average path length) were calculated to identify key types of PLEL, analyze the main conversion processes of PLEL, and quantify the stability of the PLEL system. The results indicated that: (1) In the PLEL system, ecological land occupied a dominant position but gradually declined between 2000 and 2023. (2) The grassland ecological land, agricultural production land, and ranching production land all had high integrated node centrality and were identified as key types in the PLEL conversion network from 2000 to 2023. (3) The conversion of grassland ecological land, ecological accommodation land, and ranching production land into agricultural production land were the main process of PLEL conversion, with conversion ratios of 53%, 28%, and 16%, respectively. (4) The average path length of the PLEL conversion network from 2000 to 2023 was 1.153, indicating that the overall stability of the PLEL system was poor and that the conversion between PLEL types was easy. (5) The PLEL evolution was the combined result of natural, economic, and social factors. This study demonstrated that complex network models can effectively identify key regulatory land types within the PLEL system. Furthermore, the system's high instability serves as a warning that the current PLEL development model is unsustainable. This insight provides a crucial scientific basis for precise spatial management and ecological security safeguards on the northern slope of the Tianshan Mountains.

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Publication Details

Journal
Scientific Reports
Published
2026-01-27
DOI
https://doi.org/10.1038/s41598-026-35910-x
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatiotemporal evolution and drivers of production-living-ecological land in the northern Tianshan Mountains using complex network analysis

Farong Huang, Xiaomeng Yin, Zhaohua Liu, Zhaotong Zhang et al.
Scientific Reports
Land Use and Ecosystem Services
article

Spatiotemporal evolution and drivers of production-living-ecological land in the northern Tianshan Mountains using complex network analysis

Farong Huang, Xiaomeng Yin, Zhaohua Liu, Zhaotong Zhang, Hongqi Zhang
article en

Abstract

The unbalanced development of production-living-ecological land (PLEL) on the northern slope of the Tianshan Mountains has led to a series of environmental and ecological problems. Clarifying the evolution of spatial and temporal patterns and driving mechanisms of the PLEL is highly important for promoting the optimization of land use functions and sustainable development in this region. Previous research has focused primarily on the area or probability of conversion between different types of PLEL, neglecting the overall structural characteristics of the PLEL system. It is difficult to quantify the connectivity and importance of each PLEL type within the entire PLEL system, making it challenging to identify key PLEL types. Furthermore, quantitative characterization of the PLEL system stability is lacking. Accordingly, in this paper, PLEL conversion networks were constructed on the basis of complex network theory, and the dynamic evolution of the PLEL was analyzed from a systemic and holistic perspective. Network metrics (weighted degree, integrated node centrality, and average path length) were calculated to identify key types of PLEL, analyze the main conversion processes of PLEL, and quantify the stability of the PLEL system. The results indicated that: (1) In the PLEL system, ecological land occupied a dominant position but gradually declined between 2000 and 2023. (2) The grassland ecological land, agricultural production land, and ranching production land all had high integrated node centrality and were identified as key types in the PLEL conversion network from 2000 to 2023. (3) The conversion of grassland ecological land, ecological accommodation land, and ranching production land into agricultural production land were the main process of PLEL conversion, with conversion ratios of 53%, 28%, and 16%, respectively. (4) The average path length of the PLEL conversion network from 2000 to 2023 was 1.153, indicating that the overall stability of the PLEL system was poor and that the conversion between PLEL types was easy. (5) The PLEL evolution was the combined result of natural, economic, and social factors. This study demonstrated that complex network models can effectively identify key regulatory land types within the PLEL system. Furthermore, the system's high instability serves as a warning that the current PLEL development model is unsustainable. This insight provides a crucial scientific basis for precise spatial management and ecological security safeguards on the northern slope of the Tianshan Mountains.

Scientific ReportsVol. 16(1)
Hebei University of Economics and Business (CN), Chinese Academy of Sciences (CN), Xinjiang Institute of Ecology and Geography (CN), Changji University (CN), Center For Remote Sensing (United States) (US), Institute of Geographic Sciences and Natural Resources Research (CN), Hebei Normal University (CN), Hebei GEO University (CN)
Chinese Academy of Sciences, Hebei Normal University, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
Openalex Percentile: Top 84%
Land Use and Ecosystem Services
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