Climate Variability and Its Influence on Vegetation Dynamics in Tanzania

Abstract

Understanding how climate variability drives tropical vegetation is critical for sustainable land management and climate-change adaptation. This study aimed to characterize the spatiotemporal distribution and trends of vegetation using the Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), CHIRPS rainfall, and MODIS-derived Evapotranspiration (ET) in Tanzania from 2000 to 2024 and quantify the relative influence of climatic drivers on observed vegetation dynamics. Datasets were accessed via Google Earth Engine and processed with Savitzky–Golay noise filtering and spatial harmonization to generate annual and seasonal time series. Long-term trends were assessed using Sen’s slope estimator and Mann–Kendall significance tests, while vegetation cover was quantified through Fractional Vegetation Cover (FVC). Results showed heterogeneous rainfall increase during DJFMA (December to April) and MAM (March to May), 9.6 mm/year and 5.2 mm/year respectively. EVI and FVC revealed mixed vegetation trajectories: central, southeastern, and western regions experienced degradation, whereas southwestern and northeastern highlands and parts of the northern coast showed greening. Correlation and lag analyses indicate LST exerts the strongest immediate suppressive effect (ρ = -0.78, p < 0.05), while rainfall and ET influence both instantaneous growth and multi-year recovery (rainfall: ρ = 0.64 at year 0, ρ = 0.54 at year 5; ET: ρ = 0.72 at year 0, ρ = 0.56 at year 5).  These findings demonstrate that vegetation dynamics in Tanzania are governed by a dual climatic control system: the acute, immediate sensitivity of vegetation to surface thermal conditions and a protracted, multi-year recovery potential driven by antecedent rainfall.  The study underscores the necessity of integrated management frameworks that combine immediate heat-mitigation strategies to counter LST-induced suppression with multi-year water-governance policies that leverage the five-year ecological memory of rainfall and ET. Such evidence-based interventions are critical for stabilizing vegetation trajectories and enhancing ecosystem resilience across Tanzania’s climate-vulnerable landscapes.