Mingxia Yang

Soil acidity threatens food production in the tropics. The effect of increasing ammonium-based fertilizer (INF) on soil pH was assessed in sub-Saharan Africa (SSA). A total of 9043 soil data from Africa soil information services, past INF use, and two future scenarios of INF use (business as usual (BAU) and equitable diet (EqD)) were used to determine soil pH variations from 1980 to 2022 and to predict soil PH variations from 2022 to 2050. Random forest and extreme gradient boosting algorithms and soil-forming factor covariates were used for the spatio-temporal soil pH predictions. Topsoil acidification was shown to be significant, with mean annual decrements of 0.014, 0.024, and 0.048 from 1980 to 2022, 2022 to 2050 (BAU), and 2022 to 2050 (EqD), respectively. Over the past 42 years, croplands with soil pH < 6.5 have declined significantly, and soil acidification is predicted to become severe by 2050 in the BAU and EqD scenarios. This was indicated by a predicted 3% increase in croplands at risk of aluminum toxicity (soil pH < 5.5) from 66 × 10⁶ ha in 2022 to 78.5 × 10⁶ ha in 2050. The drivers of the spatial variations in the soil pH between 1980 and 2050 were the MAP, basic cation, clay content, SOC, and nitrogen fertilizers. The evaluation metrics of the 10-fold cross-validation showed that the root mean squared errors (RMSEs) of the soil pH from 1980 to 2022, as well as the predicted soil PH from 2022 to 2050 (BAU) and 2022 to 2050 (EqD), were 0.53 pH units, 0.54 pH units, and 0.56 pH units, respectively, with coefficients of determination (R²) of 0.63, 0.64, and 0.66. The findings of this study can be used for the establishment of management strategies for increasing INF use in acidic soils.

Acidic soils (pH < 5.5) cover roughly 30% of Sub-Saharan Africa. Low nitrogen fertilizer application (15 kg N ha⁻¹ yr⁻¹) has no effect on soil acidification in Sub-Saharan Africa (SSA). However, the effect of optimized fertilizer use on soil acidification (H⁺) in SSA crops remains unknown. This study intended to predict the spatial variation of H⁺ caused by optimized fertilizer use using data from 5782 field trials in SSA cropland. We used ensemble machine learning to predict spatial variation (H⁺) after measuring the inputs and outputs of major elements and their effect on H⁺ production. The results revealed that H⁺ ranged spatially from 0 to 16 keq H⁺ ha⁻¹ yr⁻¹. The most protons (H⁺) were produced by cassava, banana, and Irish potatoes systems with 12.0, 9.8, and 8.9 keq H⁺ ha⁻¹ yr⁻¹, respectively. The results of the 10-fold cross validation for the soil acidification model were a coefficient of determination (R²) of 0.6, a root mean square error (RMSE) of 2.1, and a mean absolute error (MAE) of 1.4. Net basic cation loss drives soil acidification under optimized fertilizer application and climate covariates had a higher relative importance than other covariates. Digital soil mapping can produce soil acidification maps for sustainable land use and management plans.