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Nonlinear Effects of Land-Use Conflicts in Xinjiang: Critical Thresholds and Implications for Optimal Zoning

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  • Jinhua Wu

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

  • Can Wang

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

  • Xiong He

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510320, China)

  • Chunshan Zhou

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510320, China)

  • Hongwei Wang

    (School of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China)

Abstract

Land-use conflicts (LUCs) are pivotal in assessing human–land interaction, reflecting the intricate interplay between natural and anthropogenic drivers. However, existing studies often overlook nuanced non-linear responses and critical threshold recognition, focusing solely on linear correlations between isolated factors and LUCs. This study, situated in Xinjiang, China’s arid and semiarid region, introduces a novel analytical framework and threshold application model for LUCs. Integrating land-use and socioeconomic data, we quantified LUCs using Fragstats, correlation analysis, and restricted cubic spline (RCS) regression. Exploring non-linear dynamics between LUCs and 14 potential drivers, including natural and anthropogenic factors, we identified critical thresholds. LUC zones were delineated using a four-quadrant method, allowing tailored mitigation strategies. Our findings reveal Xinjiang’s distinct LUC spatial pattern, with intense conflicts surrounding mountainous areas and milder conflicts in basin regions, showing marked diminishment from 2000 to 2020. RCS effectively identifies LUC thresholds, indicating persisting severity pre- or post-specific thresholds. Xinjiang’s LUCs are categorized into key control areas, urgent regulation zones, elastic development territories, and moderate optimization regions, each with significant regional disparities. Tailored optimization suggestions mitigate linear analysis limitations, providing a fresh perspective on land zoning optimization. This research supports comprehensive land management and planning in Xinjiang, China.

Suggested Citation

  • Jinhua Wu & Can Wang & Xiong He & Chunshan Zhou & Hongwei Wang, 2024. "Nonlinear Effects of Land-Use Conflicts in Xinjiang: Critical Thresholds and Implications for Optimal Zoning," Land, MDPI, vol. 13(5), pages 1-24, May.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:612-:d:1387691
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    References listed on IDEAS

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    1. Bertinelli, Luisito & Strobl, Eric & Zou, Benteng, 2008. "Economic development and environmental quality: A reassessment in light of nature's self-regeneration capacity," Ecological Economics, Elsevier, vol. 66(2-3), pages 371-378, June.
    2. Paul Fearnhead & Guillem Rigaill, 2019. "Changepoint Detection in the Presence of Outliers," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 169-183, January.
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