Aug 2026· Discover Environment· Vol 4· 0 citations· 70 references
Abstract
The savanna ecological zones of Nigeria are vulnerable to eco-climatic anomalies driven by climate change and land degradation. Despite previous studies on individual climate stressors, few have developed sub-national spatial Eco-Climatic Resilience Indices (ECRI) that integrate both biophysical and socio-economic dimensions across the region, thereby limiting targeted climate adaptation planning. This study applied Mann–Kendall rainfall trend analysis and the Sen slope test to rainfall data acquired from the Nigeria Meteorological Agency (NIMET) across 19 stations from 1971 to 2023. A four-stage cluster sampling design was employed to sample 2400 farming households from 48 communities in the study regions. A Principal Component Analysis (PCA) was applied to reduce the dimensionality of the data from 46 variables across climatic anomalies, ecological anomalies, exposure, sensitivity, adaptation capacity, and transformative adaptation capacity. Community PCA scores were interpolated and integrated into the composite ECRI, which was then classified into five resilience zones. The findings revealed a spatial mixed trend in rainfall as stations in the Sudan-Sahelian savanna showed both significant and insignificant upward trends, with the highest rate of change recorded in Kano (+17.89 mm/year), while stations in the Guinea Savanna indicated a significant and insignificant downward trend, with the highest rate of change recorded in Makurdi (−26.43 mm/year). Although the stations in the Sudan-Sahelian showed upward rainfall trends, the ECRI map depicted a north–south resilience gradient, with very low resilience across the Sahelian savanna to the north and very high resilience across the Guinea Savanna to the south. Overall, the climate and ecological stressors were strongly related (r = 0.82). These findings imply that increased rainfall does not necessarily translate into improved climate resilience. The varying resilience levels depicted by ECRI signal the need for state and location-specific transformation/adaptation strategies to build individual, community, and state capacity for more resilient livelihoods across the study region and similar regions with comparable socio-economic and climate characteristics.
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.
Afeez Alabi Salami, M. Togo, Zehra Işık et al.· Earth Systems and Environmen...· 0 citations
Understanding how sustained warming reshapes ecological boundaries remains a critical challenge in climate-ecosystem research, particularly across climate-sensitive regions of sub-Saharan Africa. Although temperature increases and land-cover change have been widely documented, the causal mechanisms linking climate variability to the redistribution of agro-ecological zones (AEZs) remain limited. Here we integrate multi-decadal land surface temperature (LST) and precipitation (PRE) datasets (1975-2025) with correlation analysis and nonlinear causal inference methods, including Extended Convergent Cross Mapping (ECCM) and its geographical extension (EGCCM), to examine climate-driven ecological restructuring in Ghana. Results reveal a significant warming trend of +2.39°C (≈0.47°C decade-1; p < 0.05), while precipitation shows strong inter-decadal variability without a significant long-term trend. During the same period, savanna systems expanded from 74,945 km2 to 128,355 km2, whereas forest ecosystems declined from 91,895 km2 to 60,070 km2. ECCM and EGCCM analyses identify temperature as the dominant driver of AEZ redistribution, demonstrating that sustained warming is reorganizing ecological boundaries and accelerating savanna-forest transitions across West Africa. These findings provide a causal and spatially explicit basis for prioritizing climate adaptation and land management strategies in regions most vulnerable to warming-driven ecological change.
Augustine O. K. N. Mensah, Shuoben Bi, Emmanuel Yeboah et al.· Journal of Environmental Man...· 0 citations
Climate change poses increasing risks to human systems, necessitating effective adaptation to enhance resilience. This study investigates spatial adaptation to climate change in Udon Thani Province, Thailand, a region highly vulnerable to climate variability yet with strong potential for developing context-specific adaptation practices. The objectives were to assess climate-related risks and examine community- based adaptation strategies. An integrative approach was applied, combining long-term meteorological records, secondary data from relevant agencies, and primary data from interviews with community leaders. Analyses focused on climate trends, spatial impacts, and community adaptive capacity. Results indicate a consistent increase in mean annual temperature and a decline in relative humidity, alongside high interannual rainfall variability, contributing to increasingly hot and dry conditions. The rising heat index suggests escalating health risks. Climate impacts are spatially heterogeneous, affecting ecosystems, local economies, and livelihoods differently across areas, with notable implications for the agricultural and tourism sectors. Adaptive capacity varies among communities and is influenced by leadership effectiveness, social cohesion, access to resources and knowledge, and external institutional support. These findings underscore the need for spatially differentiated and context-specific adaptation strategies to strengthen resilience under ongoing climate change.
Monchalus Pitisinchoochai, Patikorn Sriphirom· E3S Web of Conferences· 0 citations
In the context of global climate change, analyzing the evolution patterns of climate and extreme hydrological events in rural watersheds, and evaluating the adaptability of green agricultural production methods, are crucial for building climate-resilient agricultural systems. Taking the Chen Village Green Agriculture Demonstration Zone in Jiangsu Province as the research object, this study integrates historical observations and multi-scenario reanalysis data to systematically reveal the spatiotemporal evolution characteristics of regional climate and extreme precipitation during the historical period of 1961-2021 and the future period of 2030-2060. Furthermore, by coupling crop growth with meteorological and soil hydrological processes, this study innovatively constructs an Agricultural Production Hydro-Climatic Suitability Index (P) and an Agricultural Water Resource Risk Index (R), quantitatively identifying risk thresholds and response potentials of regional agricultural production under multiple scenarios. The results indicate that: (1) A significant warming trend is observed for the future period of 2030-2060, while precipitation and extreme precipitation changes show clear scenario dependence; under SSP585, reduced precipitation and declining available water resources become more prominent. (2) The constructed suitability index P shows a significant positive correlation with crop yield (r = 0.9), demonstrating good representational accuracy. Under climate pressure, P values in all future scenarios decrease significantly compared to the historical mean (0.43), revealing the strong inhibitory effect of climate change on agricultural production. (3) The Agricultural Water Resource Risk Index (R) shows pronounced scenario differentiation: under the Conventional farming scenario, the historical mean R value is 0.89, while future R values increase to 0.99, 1.03, 1.52, and 6.86 under SSP126, SSP245, SSP370, and SSP585, respectively. Under medium- and low-emission scenarios, the risk is mainly associated with precipitation-related extremes, whereas under high-emission scenarios, drought-related risk increases due to sharply reduced available water resources and intensified irrigation deficits. (4) The Green agriculture scenario demonstrates significant regulatory potential, effectively reducing the annual average irrigation water demand by 10.6-27.4% and mitigating climate risks.
Junwei Ding, Yi Wang, Yule Liu et al.· Scientific Reports· 0 citations
In the current era, climate change has emerged as a fundamental threat to African agriculture, driven by increasingly erratic climatic patterns such as prolonged rainfall, decadal droughts, and escalating thermal stress. This review evaluates contemporary agricultural productivity by gathering and analyzing empirical data from academic publications and credible online resources indexed between 2015 and 2025. The primary objective is to delineate the impacts of climatic instability on yield trajectories and food system accessibility. Utilizing a regional comparative framework, the study examines 10 African nations (two per geographic region) to identify localized and pan‐African trends. Data synthesis from Scopus, Web of Science, and Google Scholar reveals that climatic variations have fundamentally undermined food security, contributing to famine, economic displacement, and the erosion of rural livelihoods. Key barriers to effective adaptation were identified as financial incapacity, weak institutional synergy, and a deficit in research and development infrastructure. Consequently, this review highlights the urgent need for a multifaceted resilience strategy that harmonizes indigenous adaptation practices, advanced genomics technology, application of artificial intelligence, and digital climate‐smart technologies. Strengthening food security will require not only technological adoption but also robust policy frameworks, incentivized investment, infrastructural development, and the expansion of extension services to bridge the gap between climate research and on‐farm implementation.
C. Okonkwo, K. T. Mawcha, Rumbidzai Changwa et al.· Plant-Environment Interactio...· 0 citations
Urban green spaces (UGSs) are vital for enhancing a city’s resilience and livability; however, their functionality is increasingly jeopardized by drought, particularly in water-scarce regions. This study evaluates drought impact on UGSs in Metropolitan Adelaide, Australia, a representative semi-arid urban system, using satellite-derived Normalized Difference Vegetation Index (NDVI) time-series data spanning 2000–2020. Vegetation dynamics were analyzed through Seasonal-Trend decomposition using Loess (STL), standardized anomaly assessment, lagged Pearson correlation, Ordinary Least Squares (OLS) regression, and Mann–Kendall trend analysis. To isolate climatically sensitive signals, 29 urban lawn patches were examined separately from mixed urban canopy, given their shallow root systems and direct dependence on surface moisture. NDVI declined by approximately 0.09 units during the Millennium Drought (2001–2009), with summer greenness deficits reaching 24% below the 20-year benchmark. Temperature was the dominant driver of lawn NDVI variability (r = −0.863, R2 = 74.5%), substantially exceeding the effect of rainfall (r = 0.156, R2 = 2.4%). El Niño–Southern Oscillation (ENSO) cycles modulated vegetation responses, with La Niña years supporting recovery and El Niño years amplifying decline. Post-drought recovery remained incomplete, with NDVI deficits of 8–20% persisting through 2020; full recovery was observed only in 2017, coinciding with the highest recorded summer rainfall. No significant directional trend was detected over the full study period (Mann–Kendall τ = 0.005, p = 0.908). These findings demonstrate that heat, rather than water limitation alone, is the primary driver of vegetation stress in urban systems, highlighting the benefits of integrated management strategies that address both warming and moisture deficits to sustain urban green infrastructure under future climate conditions. We introduce the concept of “urban greenery drought,” referring to a form of vegetation stress in managed urban landscapes where greenness is reduced primarily by elevated temperature and atmospheric demand despite water availability.
S. Chavoshi Borujeni, Alfredo R. Huete, Biswajeet Pradhan et al.· Remote Sensing· 0 citations