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Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)-vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982-2010) data found that for OPEN ACCESSRemote Sens. 2013, 5 6514 MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

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The United Nations and Intergovernmental Panel on Climate Change deem many regions of southern Africa as vulnerable landscapes due to changing climatic regimes, ecological conditions, and low adaptive capacity. Typically in highly vulnerable regions, multiple livelihood strategies are employed to enable sustainable development. In Botswana, livelihood strategies have diversified over time to include tourism and other non-agricultural activities. While such diversification and development have been studied, little is known about how locals perceive livelihood risks. This article analyzes perceptions of risk through a risk hazards framework. During the summer of 2010, 330 surveys were completed within seven villages in northern Botswana and the Caprivi Strip of Namibia. During the survey respondents were asked to list the biggest threats/challenges to their livelihoods. Responses were grouped into categories of risk according to the capital assets on which livelihoods depend: natural, physical, financial, human, and social. A risk mapping procedure was utilized, for which indices of severity, incidence, and risk were calculated. It is hypothesized that people’s perception of risk is directly dependent on environmental conditions and employment status of the household. Results indicate that problems related to natural and financial assets are the greatest source of risk to livelihoods. Furthermore, flood, drought, and other measures of climate variability are perceived as influential, typically negatively, to livelihood strategies