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

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  • Shikuku, Kelvin M.
  • Valdivia, Roberto O.
  • Paul, Birthe K.
  • Mwongera, Caroline
  • Winowiecki, Leigh
  • Läderach, Peter
  • Herrero, Mario
  • Silvestri, Silvia

Abstract

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

Suggested Citation

  • Shikuku, Kelvin M. & Valdivia, Roberto O. & Paul, Birthe K. & Mwongera, Caroline & Winowiecki, Leigh & Läderach, Peter & Herrero, Mario & Silvestri, Silvia, 2017. "Prioritizing climate-smart livestock technologies in rural Tanzania: A minimum data approach," Agricultural Systems, Elsevier, vol. 151(C), pages 204-216.
    • Handle: RePEc:eee:agisys:v:151:y:2017:i:c:p:204-216
    DOI: 10.1016/j.agsy.2016.06.004
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    5. Twine, Edgar E. & Omore, Amos & Githinji, Julius, 2018. "Uncertainty in milk production by smallholders in Tanzania and its implications for investment," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(1).
    6. Paul, B.K. & Epper, C.A. & Tschopp, D.J. & Long, C.T.M. & Tungani, V. & Burra, D. & Hok, L. & Phengsavanh, P. & Douxchamps, S., 2022. "Crop-livestock integration provides opportunities to mitigate environmental trade-offs in transitioning smallholder agricultural systems of the Greater Mekong Subregion," Agricultural Systems, Elsevier, vol. 195(C).
    7. Hameeda Sultan & Jinyan Zhan & Wajid Rashid & Xi Chu & Eve Bohnett, 2022. "Systematic Review of Multi-Dimensional Vulnerabilities in the Himalayas," IJERPH, MDPI, vol. 19(19), pages 1-20, September.
    8. Germer, Leah A. & van Middelaar, Corina E. & Oosting, Simon J. & Gerber, Pierre J., 2023. "When and where are livestock climate-smart? A spatial-temporal framework for comparing the climate change and food security synergies and tradeoffs of Sub-Saharan African livestock systems," Agricultural Systems, Elsevier, vol. 210(C).
    9. Sabine Homann-Kee Tui & Katrien Descheemaeker & Roberto O. Valdivia & Patricia Masikati & Gevious Sisito & Elisha N. Moyo & Olivier Crespo & Alex C. Ruane & Cynthia Rosenzweig, 2021. "Climate change impacts and adaptation for dryland farming systems in Zimbabwe: a stakeholder-driven integrated multi-model assessment," Climatic Change, Springer, vol. 168(1), pages 1-21, September.
    10. World Bank Group, 2019. "Cote d’Ivoire Climate-Smart Agriculture Investment Plan [Plan d’Investissement d’une Agriculture Intelligente face au Climat en Côte d’Ivoire]," World Bank Publications - Reports 32745, The World Bank Group.

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