Agroforestry is widely promoted as an ecosystem-based adaptation strategy to enhance climate resilience, restore degraded landscapes, and support smallholder livelihoods. However, empirical evidence on how project-supported agroforestry interventions influence tree species composition, stocking density, and biomass accumulation remains limited. This study assessed tree and shrub diversity, stocking density, and aboveground biomass across different agroforestry practices in Kayonza District, Eastern Rwanda, comparing project intervention sites supported by the LDCF II Ecosystem-based Adaptation approach project with no intervention areas. Using systematic band transects covering 26 sampling units, all woody species were inventoried and measured for diameter and height, and aboveground biomass was estimated using an allometric equation. A total of 39 species were recorded in no-intervention areas and 36 species in intervention areas, with both systems dominated by a small number of widely preferred species, including Eucalyptus spp., Grevillea robusta, Mangifera indica, Persea americana, Euphorbia tirucalli, and Senna spp. Tree and shrub density was four times higher in intervention areas (172 stems hasup-1/sup) than in non-intervention areas (43 stems hasup-1/sup), while diameter class distributions were dominated by small trees (10cm DBH) in both zones. Despite smaller average tree sizes, intervention areas exhibited substantially higher aboveground biomass (15.33 t hasup-1/sup) compared to no-intervention areas (4.51 t hasup-1/sup), largely due to higher stocking density and wider adoption of biomass-efficient practices. Scattered trees on farm consistently ranked highest in biomass contribution across both zones. These findings demonstrate that targeted agroforestry interventions can rapidly enhance landscape-level biomass and carbon sequestration potential, even at early stages of tree establishment. To sustain and maximize these benefits, future interventions should prioritize agroforestry practice diversification, adaptive management, greater integration of native species and long-term monitoring to balance productivity, biodiversity, and income.
Sebasore et al. (Fri,) studied this question.