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<p>Understanding the climatic heterogeneity of Nigeria is essential for evaluating ecosystem vulnerability, climate‑risk exposure, and hydrological stability. However, existing classifications remain limited by sparse meteorological observations and predominantly single‑variable approaches. This study aims to provide a comprehensive, data‑driven eco‑climatic regionalisation of Nigeria, explicitly addressing the lack of multivariate and validated climatic frameworks that capture compound hydro‑ecological interactions. The strong north–south hydrothermal gradients of Nigeria, together with increasing climate variability, make it a critical location for developing a refined climatic zoning framework. Conventional classifications, including threshold‑based systems, often mask intra‑regional variability and fail to resolve ecological stress patterns. This study integrates four decades (1981–2024) of MODIS vegetation stress indicators, including Moisture Stress Index (MSI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), with ERA5‑Land precipitation, temperature, soil moisture, solar radiation, and runoff datasets. Principal Component Analysis (PCA) was applied to extract dominant climatic–ecological gradients, followed by K‑means clustering to delineate homogeneous eco‑climatic regions, while quantitative validation against the Köppen–Geiger classification (Cohen’s Kappa and Adjusted Rand Index) was performed to assess robustness and added value. Five coherent climatic regimes emerged along a distinct north–south gradient. Moisture availability was identified as the primary driver of climatic differentiation, with the semi‑arid northern zones exhibiting the highest moisture stress (MSI = 0.96) and the lowest vegetation health (VHI = 39.5). Humid southern regions displayed the lowest stress levels (MSI = 0.40–0.53) and higher VHI (&gt; 53), while the Middle Belt formed a transitional ecotone with balanced hydro‑thermal conditions. Statistical validation (ANOVA, <i>p</i> &lt; 0.001) and clustering diagnostics confirm that these regions are both distinct and internally consistent, while approximately 68% spatial agreement with Köppen–Geiger indicates systematic refinement rather than redundancy. The results provide a refined spatial differentiation and ecologically relevant climatic classification of Nigeria to date. By integrating vegetation response with atmospheric and hydrological variables, this study advances climatic regionalisation beyond conventional approaches and establishes a validated, high-resolution framework. The findings support drought-resilient agriculture in the north, flood- and water-resource management in the south, and improved climate-risk assessment across transitional zones.</p> Graphical Abstract <p></p> <p>Based on the graphical abstract, this study presents an integrated multivariate framework for delineating ecological zones across Nigeria using four (4) decades (1981–2024) of MODIS and ERA5-Land datasets. It begins with a map of the study area, highlighting the pronounced latitudinal hydroclimatic gradients that structure the environmental conditions in Nigeria. The workflow then introduces the two major input datasets: MODIS land surface products and ERA5 Land reanalysis variables, which were systematically harmonised by spatial resampling onto a common 0.1° grid to ensure analytical comparability. Environmental stress indices derived from MODIS (Moisture Stress Index, Temperature Condition Index, and Vegetation Health Index), together with multivariate hydroclimatic variables from ERA5-Land (precipitation, temperature, soil moisture, solar radiation, and runoff), were processed to characterise long-term climatic and eco-physiological dynamics. Principal Component Analysis (PCA) was employed to extract dominant climatic–ecological gradients, enabling substantial dimensionality reduction and revealing strong moisture-driven north–south contrasts. Subsequently, hierarchical and K-means clustering algorithms were applied to partition Nigeria into five internally coherent eco-climatic zones, ranging from arid and semi-arid domains in the north to humid tropical systems in the south, with the Middle Belt forming a distinct transitional ecotone. In general, the study presents a robust, data-driven ecological classification framework that integrates compound vegetation–temperature–moisture interactions and provides a scientific foundation for climate-risk assessment, sustainable agricultural planning, biodiversity monitoring, and environmental management across Nigeria.</p>

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Multivariate Eco‑Climatic Zoning of Nigeria Using Four Decades of MODIS and ERA5‑Land Data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Afeez Alabi Salami,
  • Muchaiteyi Togo,
  • Zehra Işık,
  • Mehmet Ali Çelik

摘要

Understanding the climatic heterogeneity of Nigeria is essential for evaluating ecosystem vulnerability, climate‑risk exposure, and hydrological stability. However, existing classifications remain limited by sparse meteorological observations and predominantly single‑variable approaches. This study aims to provide a comprehensive, data‑driven eco‑climatic regionalisation of Nigeria, explicitly addressing the lack of multivariate and validated climatic frameworks that capture compound hydro‑ecological interactions. The strong north–south hydrothermal gradients of Nigeria, together with increasing climate variability, make it a critical location for developing a refined climatic zoning framework. Conventional classifications, including threshold‑based systems, often mask intra‑regional variability and fail to resolve ecological stress patterns. This study integrates four decades (1981–2024) of MODIS vegetation stress indicators, including Moisture Stress Index (MSI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), with ERA5‑Land precipitation, temperature, soil moisture, solar radiation, and runoff datasets. Principal Component Analysis (PCA) was applied to extract dominant climatic–ecological gradients, followed by K‑means clustering to delineate homogeneous eco‑climatic regions, while quantitative validation against the Köppen–Geiger classification (Cohen’s Kappa and Adjusted Rand Index) was performed to assess robustness and added value. Five coherent climatic regimes emerged along a distinct north–south gradient. Moisture availability was identified as the primary driver of climatic differentiation, with the semi‑arid northern zones exhibiting the highest moisture stress (MSI = 0.96) and the lowest vegetation health (VHI = 39.5). Humid southern regions displayed the lowest stress levels (MSI = 0.40–0.53) and higher VHI (> 53), while the Middle Belt formed a transitional ecotone with balanced hydro‑thermal conditions. Statistical validation (ANOVA, p < 0.001) and clustering diagnostics confirm that these regions are both distinct and internally consistent, while approximately 68% spatial agreement with Köppen–Geiger indicates systematic refinement rather than redundancy. The results provide a refined spatial differentiation and ecologically relevant climatic classification of Nigeria to date. By integrating vegetation response with atmospheric and hydrological variables, this study advances climatic regionalisation beyond conventional approaches and establishes a validated, high-resolution framework. The findings support drought-resilient agriculture in the north, flood- and water-resource management in the south, and improved climate-risk assessment across transitional zones.

Graphical Abstract

Based on the graphical abstract, this study presents an integrated multivariate framework for delineating ecological zones across Nigeria using four (4) decades (1981–2024) of MODIS and ERA5-Land datasets. It begins with a map of the study area, highlighting the pronounced latitudinal hydroclimatic gradients that structure the environmental conditions in Nigeria. The workflow then introduces the two major input datasets: MODIS land surface products and ERA5 Land reanalysis variables, which were systematically harmonised by spatial resampling onto a common 0.1° grid to ensure analytical comparability. Environmental stress indices derived from MODIS (Moisture Stress Index, Temperature Condition Index, and Vegetation Health Index), together with multivariate hydroclimatic variables from ERA5-Land (precipitation, temperature, soil moisture, solar radiation, and runoff), were processed to characterise long-term climatic and eco-physiological dynamics. Principal Component Analysis (PCA) was employed to extract dominant climatic–ecological gradients, enabling substantial dimensionality reduction and revealing strong moisture-driven north–south contrasts. Subsequently, hierarchical and K-means clustering algorithms were applied to partition Nigeria into five internally coherent eco-climatic zones, ranging from arid and semi-arid domains in the north to humid tropical systems in the south, with the Middle Belt forming a distinct transitional ecotone. In general, the study presents a robust, data-driven ecological classification framework that integrates compound vegetation–temperature–moisture interactions and provides a scientific foundation for climate-risk assessment, sustainable agricultural planning, biodiversity monitoring, and environmental management across Nigeria.