Agroecological typology of farming households and sustainable agricultural practices in the Equatorial High-Altitude Zone of South-Kivu, Eastern DRC

In the Equatorial High-Altitude Zone (EHAZ) of South Kivu, eastern Democratic Republic of Congo, smallholder farmers face severe land degradation and climate vulnerability, yet patterns of agroecological practice adoption remain insufficiently characterized. A stratified sample of 374 households in the high-altitude parts of Kalehe, Kabare and Walungu was surveyed on the adoption of sixteen practices during cropping season B of 2025. A typology was built by principal component analysis (PCA), Ward hierarchical clustering and K-means consolidation. Factors associated with type membership were analysed with a bias-reduced multinomial logistic regression (MNLR), and adoption constraints were compared across types with χ² or Fisher tests adjusted by Holm's method. Six principal components (64.0% of the variance) were retained for clustering. Four farmer types were identified: Type 1 (19.8%), conservation-oriented systems combining contour farming, minimum tillage, agroforestry and mulching with little use of external inputs; Type 2 (36.9%), soil-fertility systems based on composting, residue incorporation and minimum tillage, with limited soil cover; Type 3 (11.2%), integrated systems with high adoption of nearly all practices, including external-input practices; and Type 4 (32.1%), soil-cover systems relying on composting, mulching and cover crops but rarely using physical conservation or external inputs. Practices formed four co-adoption families (resource-intensive, physical soil management, ecological regulation and foundational practices). Type membership was associated mainly with territory and farm-structural characteristics (land position, farm size, perceived soil fertility and, for Type 2, hired labor), but not with age, gender or farming experience; Kalehe households were found almost only in Types 1 and 3. Lack of resources was most frequently reported in Types 1 (97.3%) and 4 (88.3%), lack of information in Types 1 (97.3%) and 2 (85.5%), high workload in Type 2 (68.1%), and lack of interest in Types 4 (85.0%) and 1 (71.6%). These findings show that farmers combine practices into territory-specific packages and face type-specific constraints. Extension programmes should therefore be differentiated by farmer type, combining access to resources, training and participatory approaches that take farmers' preferences into account.