Prioritizing climate-smart livestock technologies in rural Tanzania: A minimum data approach

摘要: Crop-livestock production systems play an important role in the livelihoods of many rural communities sub-Saharan Africa (SSA) but are vulnerable to adverse impacts climate change. Understanding which farming options will give highest return on investment light change is critical information for decision-making. While there continued testing adaptation using on-farm experiments, simulation models remain tools ‘ex-ante’ assessments proposed climate-smart agricultural technologies (CSA). This study used Ruminant model and Trade-offs Analysis Multi-Dimensional Impact Assessment (TOA-MD) assess how improved livestock management affect three pillars CSA: increased productivity, food security, reduced greenhouse gas (GHG) emissions. Our sample was stratified into: 1) households with local cow breeds (n = 28); 2) dairy 70); 3) without cows 66). Results showed that predicted adoption rates feeding among (stratum were likely be higher compared only 1). Both those had income security. However, overall poverty reduction modest cows. Expected methane emissions intensity declined strategies both stratum 1 2, greater observed when 2 received additional breed. Providing a not keeping substantial economic gains. Additional research is, however, needed understand why farms currently do have cows, may determine if feasible.