Assessing the greenhouse gas mitigation effect of removing bovine trypanosomiasis in Eastern Africa

M MacLeod, V Eory, W Wint, A Shaw, PJ Gerber, G Cecchi, R Mattioli, A Sykes, T Robinson

Research output: Contribution to journalArticle

4 Citations (Scopus)
16 Downloads (Pure)

Abstract

Abstract: Increasing the production of meat and milk within sub-Saharan Africa should provide significant food security benefits. However, greenhouse gas (GHG) emissions represent a challenge, as cattle production in the region typically has high emissions intensity (EI), i.e., high rates of GHG emissions per unit of output. The high EI is caused by the relatively low production efficiencies in the region, which are in turn partly due to endemic cattle diseases. In theory, improved disease control should increase the efficiency and decrease the emissions intensity of livestock production; however quantitative analysis of the potential GHG mitigation effects of improved disease control in Africa is lacking. This paper seeks to respond to this by using a hybrid modelling approach to quantify the production and emissions effects of removing trypanosomiasis from East African cattle production systems. The emissions are quantified for each cattle production system using an excel version of GLEAM, the Food and Agriculture Organization’s Global Livestock Environmental Assessment Model. The results indicate that removing trypanosomiasis leads to a reduction in the emissions intensity per unit of protein produced of between 0% and 8%, driven mainly by the increases in milk yields and cow fertility rates. Despite the limitations, it is argued that the approach provides considerable scope for modelling the GHG impacts of disease interventions.
Original languageEnglish
Pages (from-to)1633 - 1647
Number of pages15
JournalSustainability
Volume10
Issue number5
Early online date18 May 2018
DOIs
Publication statusFirst published - 18 May 2018

Bibliographical note

2082611
1032210

Keywords

  • Cattle health
  • Climate change
  • GLEAM
  • Livestock modelling
  • Sustainable intensification

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