A gravity model and network analysis of household food sharing in Zambia
Authorvon Gnechten, Rachel
Jackson, Nicole D
AffiliationUniv Arizona, Sch Geog & Dev
MetadataShow full item record
PublisherIOP PUBLISHING LTD
CitationVon Gnechten, R., Wang, J., Konar, M., Baylis, K., Anderson, P., Giroux, S., ... & Evans, T. (2020). A gravity model and network analysis of household food sharing in Zambia. Environmental Research Letters, 15(11), 115010.
JournalENVIRONMENTAL RESEARCH LETTERS
Rights©2020 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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AbstractFood sharing is an important part of smallholder food systems and can help households to buffer food security shocks. Household food sharing is the smallest scale food exchange system, yet we do not understand how it compares with food exchange networks at other spatial scales. To this end, we collect information on bilateral household food sharing in two villages in Zambia with approximately 50 households each. We observed seasonal fluctuations for the density of the food sharing. To our knowledge, we are the first to show that the gravity model of trade is applicable to household food sharing. Additionally, sharing networks exhibit the same statistical properties as food exchanges in other locations and at different spatial scales. Specifically, maize exchanges (in mass) follow the Gamma distribution and the relationship between household mass flux and connectivity follows a power law distribution. This work sheds light on household food sharing in rainfed agricultural systems and suggests common underlying mechanisms of food exchange systems across spatial scales and geographies.
NoteOpen access journal
VersionFinal published version
SponsorsNational Science Foundation
Except where otherwise noted, this item's license is described as ©2020 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.