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<p>Land-use function (LUF) transitions driven by rapid urbanization have intensified trade-offs among production, living, and ecological systems, particularly in ecologically fragile arid regions. However, the spatial heterogeneity and nonlinear driving mechanisms underlying these interactions remain insufficiently understood at fine scales. This study investigates the urban agglomeration on the northern slope of the Tianshan Mountains (China) from 2000 to 2020 using a 1&#xa0;km grid-based analytical framework integrating Geographically Weighted Regression (GWR), Boosted Regression Trees (BRT), and Self-Organizing Map (SOM) clustering. Results show pronounced spatiotemporal variability in LUF interactions. Synergies between production and living functions generally strengthened over time, whereas relationships between living and ecological functions remained predominantly trade-off dominated. The production–ecological relationship shifted from synergy to trade-off and partially recovered under ecological restoration policies. Significant spatial heterogeneity was observed across functional interactions, reflecting strong landscape gradients from oasis-plain-mountain systems. BRT results reveal that LUF trade-offs are driven by a combination of natural and socio-economic factors, including elevation, precipitation, GDP, and transportation accessibility, exhibiting clear nonlinear and threshold effects. Critical thresholds vary across functional pairs, indicating regime shifts in land-use system behavior under changing environmental conditions. Overall, the integrated framework effectively captures multiscale spatial heterogeneity and nonlinear mechanisms of LUF interactions, providing a quantitative basis for optimized spatial planning and differentiated land management strategies in arid urban agglomerations.</p>

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Analysis of trade-off synergies of land use functions and their influencing factors in arid zones

  • 期刊论文

  • 发表日期：

    2026年7月31日

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  • Fangfang Han,
  • Alimujiang Kasimu,
  • Anwaer Maimaitiming

摘要

Land-use function (LUF) transitions driven by rapid urbanization have intensified trade-offs among production, living, and ecological systems, particularly in ecologically fragile arid regions. However, the spatial heterogeneity and nonlinear driving mechanisms underlying these interactions remain insufficiently understood at fine scales. This study investigates the urban agglomeration on the northern slope of the Tianshan Mountains (China) from 2000 to 2020 using a 1 km grid-based analytical framework integrating Geographically Weighted Regression (GWR), Boosted Regression Trees (BRT), and Self-Organizing Map (SOM) clustering. Results show pronounced spatiotemporal variability in LUF interactions. Synergies between production and living functions generally strengthened over time, whereas relationships between living and ecological functions remained predominantly trade-off dominated. The production–ecological relationship shifted from synergy to trade-off and partially recovered under ecological restoration policies. Significant spatial heterogeneity was observed across functional interactions, reflecting strong landscape gradients from oasis-plain-mountain systems. BRT results reveal that LUF trade-offs are driven by a combination of natural and socio-economic factors, including elevation, precipitation, GDP, and transportation accessibility, exhibiting clear nonlinear and threshold effects. Critical thresholds vary across functional pairs, indicating regime shifts in land-use system behavior under changing environmental conditions. Overall, the integrated framework effectively captures multiscale spatial heterogeneity and nonlinear mechanisms of LUF interactions, providing a quantitative basis for optimized spatial planning and differentiated land management strategies in arid urban agglomerations.