<p>As a critical ecological-economic nexus along China’s Belt and Road Initiative, the Kashgar region exemplifies tensions between rapid socioeconomic development and ecological fragility in arid Central Asia. Landscape degradation monitoring in arid regions is severely constrained by data scarcity; most studies rely on 15–20&#xa0;year windows insufficient for detecting decadal-scale threshold behaviors. This study fills a critical research gap by integrating multi-method landscape analysis with a relatively long 43-year land use record (1980–2023). Our integrated analytical framework combines land use dynamic degree, intensity indices, transfer matrices, landscape fragmentation metrics, and spatial autocorrelation analysis, with all results validated through sensitivity analyses (parameterization robustness Spearman rs &gt; 0.96; scale robustness rs &gt; 0.93). We quantified unidirectional anthropogenic landscape reorganization: cultivated and construction land expanded 3,671.78 km<sup>2</sup> and 973.41 km<sup>2</sup> respectively, while natural landscapes (forest, grassland, water bodies) collectively declined 2,115.82 km<sup>2</sup>. Construction land displayed the highest transformation intensity (8.41% annual dynamic degree), with peak land use intensity coinciding with China’s Western Development Strategy (2000–2010: Δ<i>La</i> = 3.31, <i>R</i> = 2.14%). Quantitative landscape fragmentation escalated markedly: patch density increased 68% (0.056 → 0.095/km<sup>2</sup>), shape complexity increased 33% (LSI: 56.097 → 74.590), and spatial connectivity declined 3.25% (CONTAG: 66.870% → 64.698%). Transfer analysis demonstrated that construction land exhibited a persistent unidirectional inflow imbalance, while unused land showed a consistent unidirectional outflow imbalance; other land types underwent bidirectional transitions. Landscape ecological security exhibited distinctive three-phase dynamics (improvement → degradation → recovery) with strong persistent spatial autocorrelation (<i>Moran’s I</i>: 0.78–0.81, p &lt; 0.001), generating stable "high-high" clusters in oases and vulnerable "low-low" clusters in desert margins. Quantified attribution analysis (Grey Relational Analysis, Spearman correlations) revealed that GDP growth was the strongest driver of construction land expansion (GRG = 0.87), while population growth was the primary driver of cultivated land expansion (GRG = 0.85). Our preliminary observations suggest a potential monitoring reference zone (Δ<i>La</i> ≈ 2.5–3.5 per decade) for early-warning systems; rigorous cross-regional validation is essential before establishing universal thresholds. Persistence of ecological degradation into 2010–2020 despite reduced land use change (<i>LC</i>: 1.20% → 0.15%) indicates hysteresis dynamics in arid systems. This 43-year dataset and validated analytical framework provide critical baseline data and evidence-based quantitative thresholds for early-warning systems and territorial spatial planning in ecologically fragile arid zones.</p>

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Multi-decadal landscape dynamics and ecological security trajectories driven by 43-year land use changes in Kashgar, an arid border region of Northwest China

  • Mailikai Aimaiti,
  • Xianyong Meng

摘要

As a critical ecological-economic nexus along China’s Belt and Road Initiative, the Kashgar region exemplifies tensions between rapid socioeconomic development and ecological fragility in arid Central Asia. Landscape degradation monitoring in arid regions is severely constrained by data scarcity; most studies rely on 15–20 year windows insufficient for detecting decadal-scale threshold behaviors. This study fills a critical research gap by integrating multi-method landscape analysis with a relatively long 43-year land use record (1980–2023). Our integrated analytical framework combines land use dynamic degree, intensity indices, transfer matrices, landscape fragmentation metrics, and spatial autocorrelation analysis, with all results validated through sensitivity analyses (parameterization robustness Spearman rs > 0.96; scale robustness rs > 0.93). We quantified unidirectional anthropogenic landscape reorganization: cultivated and construction land expanded 3,671.78 km2 and 973.41 km2 respectively, while natural landscapes (forest, grassland, water bodies) collectively declined 2,115.82 km2. Construction land displayed the highest transformation intensity (8.41% annual dynamic degree), with peak land use intensity coinciding with China’s Western Development Strategy (2000–2010: ΔLa = 3.31, R = 2.14%). Quantitative landscape fragmentation escalated markedly: patch density increased 68% (0.056 → 0.095/km2), shape complexity increased 33% (LSI: 56.097 → 74.590), and spatial connectivity declined 3.25% (CONTAG: 66.870% → 64.698%). Transfer analysis demonstrated that construction land exhibited a persistent unidirectional inflow imbalance, while unused land showed a consistent unidirectional outflow imbalance; other land types underwent bidirectional transitions. Landscape ecological security exhibited distinctive three-phase dynamics (improvement → degradation → recovery) with strong persistent spatial autocorrelation (Moran’s I: 0.78–0.81, p < 0.001), generating stable "high-high" clusters in oases and vulnerable "low-low" clusters in desert margins. Quantified attribution analysis (Grey Relational Analysis, Spearman correlations) revealed that GDP growth was the strongest driver of construction land expansion (GRG = 0.87), while population growth was the primary driver of cultivated land expansion (GRG = 0.85). Our preliminary observations suggest a potential monitoring reference zone (ΔLa ≈ 2.5–3.5 per decade) for early-warning systems; rigorous cross-regional validation is essential before establishing universal thresholds. Persistence of ecological degradation into 2010–2020 despite reduced land use change (LC: 1.20% → 0.15%) indicates hysteresis dynamics in arid systems. This 43-year dataset and validated analytical framework provide critical baseline data and evidence-based quantitative thresholds for early-warning systems and territorial spatial planning in ecologically fragile arid zones.