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 Livestock are primary source of GHG emissions from
agriculture in Africa, but impacts of COVID-19 pandemic on
emissions have not been studied
 We conduct a panel survey and use crowd-sourced data on
effects of COVID-19 on GHG emissions for pastoralist
systems in Northern Kenya
 Three-part framework for assessing effects of COVID-19 on
livestock GHG emissions:
 Changes in herd size
 Changes in feed availability
 Changes in animal movement
A long, dry season of COVID-19 in
sub-Saharan Africa? The environmental
impacts of the pandemic in the livestock
sector in Northern Kenya
Insert images or graphs in different locations in
the margins
Michael W. Graham (m.graham@cgiar.org)
Lutz Merbold (l.merbold@cgiar.org)
Nathan D. Jensen (n.jensen@cgiar.org)
Philemon Chelanga (p.chelanga@cgiar.org)
International Livestock Research Institute (ILRI)
Nairobi, Kenya
Locations for panel surveys of key stakeholders in Samburu County, Kenya
Context
• Government restrictions on human and animal
movement within Kenya and across international
borders, as well as associated socio-economic
impacts, may impact GHG emissions from livestock
• Pastoralist systems depend on movement for access
to resources across seasons
• COVID-19 may differ from other external shocks
(e.g., drought) because it primarily affects mobility
Our three-part framework
CLIMATE & NATURAL
RESOURCE USE
CH4 N2O
Smaller herd
Lower emissions
1. Herd size
Larger herd
Higher emissions
Methods and Objectives
• Use panel and crowd-sourced (KAZNET) data to
assess COVID-19 effects on livestock GHG
emissions from pastoralist systems in Samburu
County, Northern Kenya, following three-part
framework
• Develop guidelines for estimating changes in GHG
emissions due to future shocks (e.g., zoonotic
disease outbreaks, climatic events)
2. Feed availability
Less feed available
Lower emissions
More feed available
Higher emissions
3. Animal movement
Less movement
Lower emissions
More movement
Higher emissions
N2O
CH4
N2O
CH4
N2O
CH4
CH4 N2O N2O
CH4
N2O
CH4
CH4 N2O N2O
CH4
N2O
CH4

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A long, dry season of COVID-19 in sub-Saharan Africa? The environmental impacts of the pandemic in the livestock sector in northern Kenya

  • 1. This document is licensed for use under the Creative Commons Attribution 4.0 International Licence. August 2020  Livestock are primary source of GHG emissions from agriculture in Africa, but impacts of COVID-19 pandemic on emissions have not been studied  We conduct a panel survey and use crowd-sourced data on effects of COVID-19 on GHG emissions for pastoralist systems in Northern Kenya  Three-part framework for assessing effects of COVID-19 on livestock GHG emissions:  Changes in herd size  Changes in feed availability  Changes in animal movement A long, dry season of COVID-19 in sub-Saharan Africa? The environmental impacts of the pandemic in the livestock sector in Northern Kenya Insert images or graphs in different locations in the margins Michael W. Graham (m.graham@cgiar.org) Lutz Merbold (l.merbold@cgiar.org) Nathan D. Jensen (n.jensen@cgiar.org) Philemon Chelanga (p.chelanga@cgiar.org) International Livestock Research Institute (ILRI) Nairobi, Kenya Locations for panel surveys of key stakeholders in Samburu County, Kenya Context • Government restrictions on human and animal movement within Kenya and across international borders, as well as associated socio-economic impacts, may impact GHG emissions from livestock • Pastoralist systems depend on movement for access to resources across seasons • COVID-19 may differ from other external shocks (e.g., drought) because it primarily affects mobility Our three-part framework CLIMATE & NATURAL RESOURCE USE CH4 N2O Smaller herd Lower emissions 1. Herd size Larger herd Higher emissions Methods and Objectives • Use panel and crowd-sourced (KAZNET) data to assess COVID-19 effects on livestock GHG emissions from pastoralist systems in Samburu County, Northern Kenya, following three-part framework • Develop guidelines for estimating changes in GHG emissions due to future shocks (e.g., zoonotic disease outbreaks, climatic events) 2. Feed availability Less feed available Lower emissions More feed available Higher emissions 3. Animal movement Less movement Lower emissions More movement Higher emissions N2O CH4 N2O CH4 N2O CH4 CH4 N2O N2O CH4 N2O CH4 CH4 N2O N2O CH4 N2O CH4