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<p>Understanding vegetation dynamics in terrestrial ecosystems is critical under the pressures of global climate change and anthropogenic activities. This study analyzes vegetation dynamics from 2001 to 2024 in Türkiye’s 13 biodiverse terrestrial ecoregions using a multi-scale approach, focusing not only on the main drivers, but also on the interactive and context-specific role of these factors. Using the Google Earth Engine (GEE) platform and MODIS Normalized Difference Vegetation Index (NDVI) data, integrated through a structured multi-scale framework, we applied statistical methods including the Mann–Kendall test, Kruskal–Wallis test, and LOESS curves optimized with leave-one-out cross-validation (LOOCV) to objectively model non-linear dynamics. The results revealed statistically significant positive NDVI change tendencies in all 13 terrestrial ecoregions (Mann–Kendall test, <i>p</i> &lt; 0.05). Forest-dominated ecoregions exhibited the strongest greening, with Sen’s slope values reaching +0.0032 NDVI year⁻<sup>1</sup> in the Euxine–Colchic Broadleaf Forests, whereas steppe ecosystems showed more moderate increases (e.g., Central Anatolian Steppe: + 0.0019 NDVI year⁻<sup>1</sup>). Across elevation gradients, the most consistent and strongest greening occurred at mid-elevations (500–1500&#xa0;m; τ ≈ 0.40–0.65), while change tendencies weakened and became more heterogeneous at higher elevations. Land-cover-based analysis further showed that natural vegetation types exhibited the strongest nationwide tendencies (“Trees”: τ = 0.71; “Shrubland”: τ = 0.66), whereas anthropogenically influenced classes displayed weaker or regionally variable responses. Beyond documenting general greening patterns, the original contribution of this study lies in introducing a structured multi-scale framework that integrates long-term MODIS NDVI time series (2001–2024) with ecoregion, elevation, and land cover contexts. This approach enables the objective identification of ecosystem-specific and scale-dependent vegetation dynamics that cannot be captured by conventional single-scale or linear trend-based analyses commonly applied in previous studies in Türkiye.</p>

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Multi-scale greening dynamics in Türkiye’s Ecoregions (2001–2024): the effects of elevation and land cover on NDVI change tendencies

  • 期刊论文

  • 发表日期：

    2026年3月16日

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  • Fatih Işık,
  • Selim Eraslan

摘要

Understanding vegetation dynamics in terrestrial ecosystems is critical under the pressures of global climate change and anthropogenic activities. This study analyzes vegetation dynamics from 2001 to 2024 in Türkiye’s 13 biodiverse terrestrial ecoregions using a multi-scale approach, focusing not only on the main drivers, but also on the interactive and context-specific role of these factors. Using the Google Earth Engine (GEE) platform and MODIS Normalized Difference Vegetation Index (NDVI) data, integrated through a structured multi-scale framework, we applied statistical methods including the Mann–Kendall test, Kruskal–Wallis test, and LOESS curves optimized with leave-one-out cross-validation (LOOCV) to objectively model non-linear dynamics. The results revealed statistically significant positive NDVI change tendencies in all 13 terrestrial ecoregions (Mann–Kendall test, p < 0.05). Forest-dominated ecoregions exhibited the strongest greening, with Sen’s slope values reaching +0.0032 NDVI year⁻1 in the Euxine–Colchic Broadleaf Forests, whereas steppe ecosystems showed more moderate increases (e.g., Central Anatolian Steppe: + 0.0019 NDVI year⁻1). Across elevation gradients, the most consistent and strongest greening occurred at mid-elevations (500–1500 m; τ ≈ 0.40–0.65), while change tendencies weakened and became more heterogeneous at higher elevations. Land-cover-based analysis further showed that natural vegetation types exhibited the strongest nationwide tendencies (“Trees”: τ = 0.71; “Shrubland”: τ = 0.66), whereas anthropogenically influenced classes displayed weaker or regionally variable responses. Beyond documenting general greening patterns, the original contribution of this study lies in introducing a structured multi-scale framework that integrates long-term MODIS NDVI time series (2001–2024) with ecoregion, elevation, and land cover contexts. This approach enables the objective identification of ecosystem-specific and scale-dependent vegetation dynamics that cannot be captured by conventional single-scale or linear trend-based analyses commonly applied in previous studies in Türkiye.