Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Agricultural Systemsarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Agricultural Systems
Article . 2021 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

A framework for assessing the effects of shock events on livestock and environment in sub-Saharan Africa: The COVID-19 pandemic in Northern Kenya

Authors: Michael William Graham; Philemon Chelanga; Nathaniel D. Jensen; Sonja Leitner; Francesco Fava; Lutz Merbold;

A framework for assessing the effects of shock events on livestock and environment in sub-Saharan Africa: The COVID-19 pandemic in Northern Kenya

Abstract

Abstract CONTEXT Livestock are the primary source of greenhouse gas (GHG) emissions from agriculture in most African countries, but there is a paucity of baseline data and monitoring of GHG emissions from livestock in Africa, particularly for extreme or shock events. The COVID-19 pandemic represents a novels shock to livestock systems and may result in indirect effects on livestock emissions and other Sustainable Development Goals (SDGs). Due to the pandemic in 2020, extensive pastoralist livestock systems in Northern Kenya were subjected to restrictions on movement, increased costs of transportation, and closure of livestock markets. OBJECTIVE The objective of this study was to assess the indirect effects of the COVID-19 pandemic on GHG emissions from livestock systems in Northern Kenya using proxy data and a three-part framework based on changes in 1) herd size, 2) feed availability, and 3) livestock movement. METHODS We evaluated changes in GHG emissions from livestock systems in Northern Kenya due to the COVID-19 pandemic based on proxy data from crowd-sourced market data, household panel surveys, and remote sensing data on Normalized Difference Vegetation Index (NDVI). Proxy data were obtained before the pandemic in 2019 and after the pandemic in 2020 to compare between years and evaluate the indirect effects of the pandemic and associated restrictions on livestock GHG emissions using the three-part framework. RESULTS AND CONCLUSIONS Overall GHG emissions from livestock in Northern Kenya have decreased due to the pandemic and this was largely driven by reductions in herd size. This reduction in GHG emissions occurred despite an increase in GHG emissions from livestock associated with higher feed availability. Decreased livestock movement due to the pandemic contributed to reductions in GHG emissions from livestock, but such reductions were likely to be small due to limited need for livestock to travel longer distances under the prevailing conditions of high feed availability. SIGNIFICANCE This research shows that assessments of changes in GHG emissions from livestock systems due to shock events can be conducted successfully based on proxy data and the three-part framework developed here. We found that shock events, such as the COVID-19 pandemic, may lead to unexpected results with respect to the direction and magnitude of changes in livestock emissions depending on contextual factors and environmental conditions. Thus, we call for more spatially explicit and continued data collection to assess and monitor the consequences of shock events on GHG emissions from livestock and related SDGs in Africa.

Country
Italy
Subjects by Vocabulary

Microsoft Academic Graph classification: Sustainable development business.industry Natural resource economics Pastoralism Climate change Context (language use) Shock (economics) Agriculture Greenhouse gas Environmental science Livestock business

Keywords

Settore AGR/02 - Agronomia e Coltivazioni Erbacee, Climate change; Crowd-sourced data; Feed availability; Greenhouse gas emissions; Herd size; Panel survey data; Pastoralism;, Animal Science and Zoology, Agronomy and Crop Science

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    Powered byBIP!BIP!
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
moresidebar

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.