Using household survey data to identify large-scale food security patterns across Uganda
To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and povert...
| Autores principales: | , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Public Library of Science
2018
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/98923 |
| _version_ | 1855526338118549504 |
|---|---|
| author | Wichern, Jannike Heerwaarden, Joost van Bruin, S. de Descheemaeker, Katrien K. Asten, Piet J.A. van Giller, Kenneth E. Wijk, Mark T. van |
| author_browse | Asten, Piet J.A. van Bruin, S. de Descheemaeker, Katrien K. Giller, Kenneth E. Heerwaarden, Joost van Wichern, Jannike Wijk, Mark T. van |
| author_facet | Wichern, Jannike Heerwaarden, Joost van Bruin, S. de Descheemaeker, Katrien K. Asten, Piet J.A. van Giller, Kenneth E. Wijk, Mark T. van |
| author_sort | Wichern, Jannike |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and poverty are driven largely by processes at the household level. At present, it is unclear if and how household level information can contribute to the spatial prediction of such welfare indicators or to what extent local variability is ignored by current mapping efforts. A combination of geo-referenced household level information with spatially continuous information is an underused approach to quantify local and large-scale variation, while it can provide a direct estimate of the variability of welfare indicators at the most relevant scale. We applied a stepwise regression kriging procedure to translate point information to spatially explicit patterns and create country-wide predictions with associated uncertainty estimates for indicators on food availability and related livelihood activities using household survey data from Uganda. With few exceptions, predictions of the indicators were weak, highlighting the difficulty in capturing variability at larger scale. Household explanatory variables identified little additional variation compared to environmental explanatory variables alone. Spatial predictability was strongest for indicators whose distribution was determined by environmental gradients. In contrast, indicators of crops that were more ubiquitously present across agroecological zones showed large local variation, which often overruled large-scale patterns.
Our procedure adds to existing approaches that often only show large-scale patterns by revealing that local variation in welfare is large. Interventions that aim to target the poor must recognise that diversity in livelihood activities for income generation within any given area often overrides the variability of livelihood activities between distant regions in the country. |
| format | Journal Article |
| id | CGSpace98923 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Public Library of Science |
| publisherStr | Public Library of Science |
| record_format | dspace |
| spelling | CGSpace989232024-05-23T19:41:36Z Using household survey data to identify large-scale food security patterns across Uganda Wichern, Jannike Heerwaarden, Joost van Bruin, S. de Descheemaeker, Katrien K. Asten, Piet J.A. van Giller, Kenneth E. Wijk, Mark T. van food security data households surveys To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and poverty are driven largely by processes at the household level. At present, it is unclear if and how household level information can contribute to the spatial prediction of such welfare indicators or to what extent local variability is ignored by current mapping efforts. A combination of geo-referenced household level information with spatially continuous information is an underused approach to quantify local and large-scale variation, while it can provide a direct estimate of the variability of welfare indicators at the most relevant scale. We applied a stepwise regression kriging procedure to translate point information to spatially explicit patterns and create country-wide predictions with associated uncertainty estimates for indicators on food availability and related livelihood activities using household survey data from Uganda. With few exceptions, predictions of the indicators were weak, highlighting the difficulty in capturing variability at larger scale. Household explanatory variables identified little additional variation compared to environmental explanatory variables alone. Spatial predictability was strongest for indicators whose distribution was determined by environmental gradients. In contrast, indicators of crops that were more ubiquitously present across agroecological zones showed large local variation, which often overruled large-scale patterns. Our procedure adds to existing approaches that often only show large-scale patterns by revealing that local variation in welfare is large. Interventions that aim to target the poor must recognise that diversity in livelihood activities for income generation within any given area often overrides the variability of livelihood activities between distant regions in the country. 2018-12-13 2019-01-02T12:09:29Z 2019-01-02T12:09:29Z Journal Article https://hdl.handle.net/10568/98923 en Open Access Public Library of Science Wichern, J., Heerwaarden, J. Van, Bruin, S. De, Descheemaeker, K., Asten, P.J.A. Van, Giller, K.E. and Wijk, M.T. Van. 2018. Using household survey data to identify large-scale food security patterns across Uganda. PLoS ONE 13(12): e0208714 |
| spellingShingle | food security data households surveys Wichern, Jannike Heerwaarden, Joost van Bruin, S. de Descheemaeker, Katrien K. Asten, Piet J.A. van Giller, Kenneth E. Wijk, Mark T. van Using household survey data to identify large-scale food security patterns across Uganda |
| title | Using household survey data to identify large-scale food security patterns across Uganda |
| title_full | Using household survey data to identify large-scale food security patterns across Uganda |
| title_fullStr | Using household survey data to identify large-scale food security patterns across Uganda |
| title_full_unstemmed | Using household survey data to identify large-scale food security patterns across Uganda |
| title_short | Using household survey data to identify large-scale food security patterns across Uganda |
| title_sort | using household survey data to identify large scale food security patterns across uganda |
| topic | food security data households surveys |
| url | https://hdl.handle.net/10568/98923 |
| work_keys_str_mv | AT wichernjannike usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT heerwaardenjoostvan usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT bruinsde usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT descheemaekerkatrienk usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT astenpietjavan usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT gillerkennethe usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda AT wijkmarktvan usinghouseholdsurveydatatoidentifylargescalefoodsecuritypatternsacrossuganda |