Understanding vegetation seasonality and its driving mechanisms improves decision-making in the management of ecological systems in a warming global climate. Using multiple statistical methods (i.e., trend analysis, abrupt changes, and partial correlation analysis), this study analyzed the spatiotemporal variations in the Normalized Difference Vegetation Index (NDVI) in the Equatorial Africa (EQA) region and their responses to climate factors from 1982 to 2021. The NDVI values declined at a rate of 0.00023 year⁻¹, while the precipitation (P) and mean temperature (TMEAN) values increased at rates of 0.22 mm year⁻¹ and 0.22 °C year⁻¹, respectively. The mean minimum temperature (TMIN) had a higher rate of 0.2 °C year⁻¹ than the mean maximum temperature (TMAX) at 0.02 °C year⁻¹. An abrupt change analysis showed that the TMAX, P, and NDVI breakpoints occurred in 2000, 2002, and 2009, respectively; TMEAN and TMIN breakpoints occurred in 2001. The NDVI trends declined in forest and cropland areas but increased in shrubland and grassland areas. The summer NDVI trends declined for all vegetation types and were reversed in the winter season. The NDVI positively correlated with the P (r = 0.50) and TMEAN (r = 0.60). All seasonal analyses varied across four seasons. A temporal analysis was conducted using partial correlation analysis (PCR), and the results revealed that TMIN had a greater impact on the NDVI (PCR = −0.45), followed by the TMAX (PCR = 0.31) and then the P (PCR = −0.19). The annual trend showed that areas with significant greening were consistent with stronger wetter and weaker warming trends. Both precipitation and temperature showed a positive relationship with vegetation in semi-arid and arid regions but a negative relationship with humid regions. Our findings improve our insight into scientific knowledge on ecological conservation.

This study investigated the actual evapotranspiration (AET) and potential evapotranspiration (PET) seasonality, trends, abrupt changes, and driving mechanisms with global sea surface temperature (SST) and atmospheric circulation patterns over Equatorial Africa (EQA) during 1980–2020. The spatiotemporal characteristics of mean ET were computed based on a 40-year average at annual and seasonal scales. The Mann-Kendall statistical test, the Sen slope test, and the Bayesian test were used to analyze trends and detect abrupt changes. The results showed that the mean annual PET (AET) for 1980–2020 was 110 (70) mm. Seasonal mean PET (AET) values were 112 (72) in summer, 110 (85) in autumn, 109 (84) in winter, and 110 (58) in spring. The MK test showed an increasing (decreasing) rate, and the Sen slope identified upward (downward) at a rate of 0.35 (0.05) mm yr⁻¹⁰. The PET and AET abrupt change points were observed to happen in 1995 and 2000. Both dry and wet regions showed observed weak (strong) correlation coefficient values of 0.3 (0.8) between PET/AET and climate factors, but significant spatiotemporal differences existed. Generally, air temperature, soil moisture, and relative humidity best explain ET dynamics rather than precipitation and wind speed. The regional atmospheric circulation patterns are directly linked to ET but vary significantly in space and time. From a policy perspective, these findings may have implications for future water resource management.

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day⁻¹10a⁻¹. Other climate variables increased at different rates: SM at 0.02 mmday⁻¹10a⁻¹, E at 0.03 mm day⁻¹10a⁻¹, Ep at 0.02 mm day⁻¹ 10a⁻¹, TMIN and TMAX at 0.01 °C day⁻¹10a⁻¹. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions.