Cover crops can provide a wide range of ecosystem services including soil water conservation, improved soil nutrient supply and retention, and enhanced crop yields. However, achieving these services in dryland cropping systems can be highly challenging, and cover crops may carry a greater risk of causing ecosystem disservices. Assessment of the balance of ecosystem services vs disservices is critical for understanding the potential role of cover crops within dryland cropping systems. The objective of this meta-analysis was to assess the effects of cover cropping in drylands on soil water and soil mineral nitrogen content at sowing of subsequent cash crops and their yields compared to control fallows. A total of 38 articles were examined, for a total of 1006 cash crop yield, 539 soil water, and 516 soil mineral nitrogen independent studies, spanning the period 1994–2021. On average, cover cropping reduced cash crop yield by 7%, soil water content by 18%, and soil mineral nitrogen by 25%, with significant variation across climates, soil types, and crop management conditions. Subsequent cash crop yields changed by +15, +4, −12, and −11% following cover crops in tropical, continental, dry, and temperate dryland climates, respectively. The most significant yield benefits were proportionate to soil water content and soil mineral nitrogen at the time of cash crop sowing. This is the first meta-analysis to demonstrate that minimum annual precipitation of ~700 mm represents a “break-even” point to realize significant cash crop yield benefits of cover cropping compared to control fallows in dryland environments. The successful incorporation of cover crops into dryland cropping systems requires careful planning based on context-specific biophysical conditions to minimize trade-offs between ecosystem services and disservices.

Field trials were carried out in the Sudan Savannah of Nigeria to assess the usefulness of CERES-Maize crop model as a decision support tool for optimizing maize production through manipulation of plant dates. The calibration experiments comprised of twenty maize varieties planted during the dry and rainy seasons of 2014 and 2015 at Bayero University Kano and Audu Bako College of Agriculture Danbatta. The trials for model evaluation were conducted in 16 different farmer fields across the Sudan (Bunkure and Garun - Mallam) and Northern Guinea (Tudun-Wada and Lere) Savannas using two of the calibrated varieties under 4 different sowing dates. The model accurately predicted grain yield, harvest index, and biomass of both varieties with low RMSE values (below 5% of mean), high d-index (above 0.8) and high r-square (above 0.9) for the calibration trials. The time series data (tops weight, stem and leaf dry weights) were also predicted with high accuracy (% RMSEn above 70%, d-index above 0.88). Similar results were also observed for the evaluation trials, where all variables were simulated with high accuracies. Estimation efficiencies (EF) values above 0.8 were observed for all the evaluation parameters. Seasonal and sensitivity analyses on Typic Plinthiustalfs and Plinthic Kanhaplustults in the Sudan and Northern Guinea Savannas were conducted. Results showed that planting extra early maize varieties in late July and early maize in mid-June leads to production of highest grain yields in the Sudan Savanna. In the Northern Guinea Savanna planting extra-early maize in mid-July and early maize in late July produced the highest grain yields. Delaying planting in both Agro-ecologies until mid-August leads to lower yields. Delaying planting to mid-August led to grain yield reduction of 39.2% for extra early maize and 74.4% for early maize in the Sudan Savanna. In the Northern Guinea Savanna however, delaying planting to mid-August resulted in yield reduction of 66.9% and 94.3% for extra-early and early maize respectively.