Understanding Land Management and Desertification in the South African Kalahari with Local Knowledge and Perspectives
AuthorKong, Taryn M.
AdvisorOrr, Barron J.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
EmbargoRelease after 30-Jun-2013
AbstractDesertification, or land degradation in drylands, is a serious environmental problem in South Africa with tremendous socio-economic consequences. Land users' perspectives on land management practices and knowledge about their rangelands have been poorly represented in the discourse of land degradation in South Africa. We addressed this knowledge gap by examining three participatory methods to capture local knowledge and perspectives, as well as the relation between knowledge, attitude and practice status relative to three land management actions done by livestock farmers in the South African Kalahari. Photo elicitation captured a greater level of detail and new information compared to semi-structured interviews alone, while enhancing researchers' understanding of farmers' knowledge and perception in multiple ways. The photovoice group discussions led to farmers' engagement in reflective dialogues, which facilitated mutual learning among the farmers. We found that a high level of knowledge and positive attitude alone did not always result in actual full scale practice. Situational factors such as limited financial resources, inadequate farm infrastructure, farm size, and land tenure were given by farmers as constraints or challenges to their land management. We further examined how effective local knowledge and remotely sensed data were in assessing the veld condition in the Kalahari Duneveld. The farmers' assessment of veld condition corresponded to field measured grass, shrub and bare ground cover. The three vegetation metrics calculated from remotely sensed images (i.e., Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and the tasseled cap greenness) all correlated poorly to the measured vegetation cover because of the excess spectral noise caused by the high iron oxide content in the Kalahari sand. Local perspectives and knowledge have potential to augment traditional ground-based rangeland assessment and contribute in the combat against desertification by offering a more holistic view of land management.
Degree ProgramGraduate College