Determining if the vast soil health degradations across the seven major soil groups (orders) of Sub-Saharan Africa (SSA) can be managed on the basis of a one-size-fits-all or location-specific approach is limited by a lack of soil group-based understanding of soil health degradations. We used the relationship between changes in nematode population dynamics relative to food and reproduction (enrichment, EI) and resistance to disturbance (structure, SI) indices to characterize the soil food web (SFW) and soil health conditions of Ferralsol, Lithosol and Nitosol soil groups in Ghana, Kenya and Malawi. We applied bivariate correlations of EI, SI, soil pH, soil organic carbon (SOC), and texture (sand, silt and clay) to identify integrated indicator parameters, and principal component analysis (PCA) to determine how all measured parameters, soil groups, and countries align. A total of 512 georeferenced soil samples from disturbed (agricultural) and undisturbed (natural vegetation) landscapes were analyzed. Nematode trophic group abundance was low and varied by soil group, landscape and country. The resource-limited and degraded SFW conditions separated by soil groups and by country. EI and SI correlation with SOC varied by landscape, soil group or country. PCA alignment showed separation of soil groups within and across countries. The study developed the first biophysicochemical proof-of-concept that the soil groups need to be treated separately when formulating scalable soil health management strategies in SSA.
Impact Assessment on Adoption of Soil Health Cards for Fertilizer Management in Tiruvallur District