Leveraging spatial sciences to measure household food security across communities in a semiarid African savanna

Authors: Andrea E Gaughan*, University of Louisville, Forrest Stevens, University of Louisville, Narcisa Pricope, University of North Carolina, Wilmington, Jonathan Salerno, Colorado State University, Joel Hartter, University of Colorado, Lin Cassidy, Independent Researcher, Michael Drake, University of Colorado, Ariel Weaver, University of Louisville, Kolarik Nick, University of Louisville, Steele Olsen, University of North Carolina, Wilmington , Amelia Bradshaw, University of North Carolina, Wilmington
Topics: Human-Environment Geography, Global Change, Spatial Analysis & Modeling
Keywords: livelihoods, vulnerability, food security, remote sensing, data fusion, savanna, drylands, Southern Africa
Session Type: Paper
Day: 4/6/2019
Start / End Time: 5:00 PM / 6:40 PM
Room: Governor's Room, Omni, East
Presentation File: No File Uploaded


Environmental variability and change impacts rural livelihoods in a myriad of well-documented ways. The degree of exposure depends on reliance of land-based activities including agriculture, grazing, and natural resource gathering activities. That level of exposure is compounded by the role of governance and management shaping landscape dynamics across different geographic scales. Our research quantifies spatial and temporal aspects of that intersection with household vulnerability as measured by food security, and as it is mediated by access to various livelihood capitals. We use a generalized model of household vulnerability, organized under a socio-ecological systems framework, and operationalize it using a combination of remotely-sensed data merged with data from 721 household surveys. Surveys were done across Namibia, Botswana and Zambia for communities centrally located within the Kavango-Zambezi Transfrontier Conservation Area of southern Africa. Using this model we show how estimates of vegetation structure, composition, and dynamics from different resource sheds may link to variation in food security at the household level, after taking into account household-, community-, and country-level factors that may mediate food insecurities. We discuss the strength and directional pathways between model components and associated indicators to illustrate our ability to operationalize the different components of the model. We also discuss the implications of this conceptual framing as it relates to remotely-sensed and other biophysical data across various scales, and their incorporation into coupled human-environment research. We also address potential interventions that might affect household food security in this region in the future.

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