Towards low carbon agriculture: Systematic-narratives of climate-smart agriculture mitigation potential in Africa - Weniga Anuga, Samuel; Chirinda, Ngonidzashe; Nukpezah, Daniel; Ahenkan, Albert; Andrieu, Nadine; Gordon, Christopher (Elsevier, 2020)
The agricultural sector is the second major source of climate change globally, contributing to anthropogenic Greenhouse Gas (GHG) emissions. In low-to-middle income countries, estimations indicate future increases in agricultural emissions. Climate-Smart Agriculture (CSA) has an express opportunity to transform agriculture across the globe. In Africa, CSA targets focused on resilience building and food security with less emphasis on the GHG mitigation potential. Nevertheless, to make CSA conclusive as an express low emission development strategy in Africa, understanding the mitigation potential in this context is paramount. Through a systematic-narrative review approach conducted on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), the study aimed to identify opportunities to mitigate GHG emissions in Africa. We observed that the distribution of studies that quantitatively assessed the GHG emissions of CSA practices was disproportionate across Africa. For instance, out of twenty studies evaluated, nine were conducted in Southern Africa; three in East Africa, and the rest distributed among Central, Western, and North Africa. Observed in the studies, advanced livestock breeding and feeding, organic nitrogen input, improved pastures and switching land-use practices, all contributed to GHG emission reduction. As limited experimental evidence exist on the GHG mitigation potential for some of the CSA alternatives including agroforestry, rotational farming, improved livestock breed and intensification of ruminants' diet, we recommend further experimental studies into these alternatives in more locations/contexts in Africa. Also, progress on the mitigation pillar is still limited in Africa due to lack of the necessary analytical infrastructure to conduct the needed measurements. We call for urgent investments into laboratory facilities and skills training to improve data collection and quality.