Reducing uncertainty in nitrogen budgets for African livestock systems - Rufino, Mariana C.; Brandt, P.; Herrero, Mario; Butterbach-Bahl, Klaus (IOP Publishing, 2014)
Livestock is poorly represented in N budgets for the African continent although some studies have examined livestock-related N flows at different levels. Livestock plays an important role in N cycling and therefore on N budgets including livestock-related flows. This study reviews the literature on N budgets for Africa to identify factors contributing to uncertainties. Livestock densities are usually modelled because of the lack of observational spatial data. Even though feed availability and quality varies across seasons, most studies use constant livestock excretion rates, and excreta are usually assumed to be uniformly distributed onto the land. Major uncertainties originate in the fraction of manure managed, and emission factors which may not reflect the situation of Africa. N budgets use coarse assumptions on production, availability, and use of crop residues as livestock feed. No flows between croplands–livestock and rangelands reflect the lack of data. Joint efforts are needed for spatial data collection of livestock data, crowdsourcing appears to be a promising option. The focus of the assessment of N budgets must go beyond croplands to include livestock and crop–livestock flows. We propose a nested systems definition of livestock systems to link local, regional level, and continental level and to increase the usefulness of point measurements of N losses. Scientists working at all levels should generate data to calibrate process-based models. Measurements in the field should not only concentrate on greenhouse gas emissions, but need to include crop and livestock production measurements, soil stock changes and other N loss pathways such as leaching, run-off and volatilization to assess management practices and trade-offs. Compared to the research done in other continents on N flows in livestock systems, there are few data for Africa, and therefore concerted effort will be needed to generate sufficient data for modelling.