Savanna ecosystems are geographically extensive and both ecologically and economically important; they therefore require monitoring over large spatial extents. There are, in particular, large areas within southern Africa savanna ecosystems that lack consistent geospatial data on vegetation morphological properties, which is a prerequisite for biodiversity conservation and sustainable management of ecological resources. Given the challenges involved in distinguishing and mapping savanna vegetation assemblages using remote sensing, the objective of this study was to develop a vegetation morphology map for the largest protected area in Africa, the central Kalahari. Six vegetation morphology classes were developed and sample training/validation pixels were selected for each class by analyzing extensive in situ data on vegetation structural and functional properties, in combination with existing ancillary data and coarse scale land cover products. The classification feature set consisted of annual and intra annual matrices derived from 14 years of satellite-derived vegetation indices images, and final classification was achieved using an ensemble tree based classifier. All vegetation morphology classes were mapped with high accuracy and the overall classification accuracy was 91.9%. Besides filling the geospatial data gap for the central Kalahari area, this vegetation morphology map is expected to serve as a critical input to ecological studies focusing on habitat use by wildlife and the efficacy of game fencing, as well as contributing to sustainable ecosystem management in the central Kalahari.

Texas savanna experienced substantial woody plant encroachment during the past several decades, resulting in habitat fragmentation and species loss. A detailed map of woody plant abundance and distribution in this area is critically needed for management purpose. This study endeavors to map the fractional woody cover of Texas savanna at Landsat scale (30 m) in an affordable way. The top of atmosphere reflectance, thermal bands, and NDVI layer of Web-Enabled Landsat Data (WELD) of 2012 were used as predictors, together with mean annual precipitation. Classification and Regression Trees (CART) were calibrated against training data of a whole range of fractional woody cover, which were derived from 1-m resolution digital orthophotos of 2012. Validation indicates a reasonable pixel level accuracy of the result fractional woody cover map, with a R-squared value of 0.45. Moreover, the result map clearly depicts the distribution of woody plants across the study area, as reflected by the orthophotos. Furthermore, this new map proves an improvement over the existing Landsat Vegetation Continuous Fields (VCF) tree cover product. The method developed here, combining remote sensing and statistical techniques, can contribute to savanna management through revealing the abundance and distribution of woody plants.

Current and future impacts of climate change include increasing variability in a number of biophysical processes, such as temperature, precipitation, and flooding. The Intergovernmental Panel on Climate Change (IPCC) has suggested that Southern Africa is particularly vulnerable to the anticipated impacts from global climate change and that social and ecological systems in the region will be disrupted and likely transformed in future decades. This article engages with current research within geography and cognate disciplines on the possibilities for responsive livelihoods within socio-ecological systems experiencing biophysical change. The paper draws from an ongoing research project that is evaluating perceptions of environmental change, specifically of precipitation and flooding dynamics, in order to understand social responses. We report on the findings from qualitative interviewing conducted in 2010 and 2011 in the communities of Etsha 1, Etsha 6, and Etsha 13 within the Okavango Delta of Botswana. While flooding and precipitation patterns have been dynamic and spatially differentiated, some livelihood systems have proven rigid in their capacity to enable adaptive responses. We assert this demonstrates the need for detailed research on livelihood dynamics to support adjustments to biophysical variability within socio-ecological systems experiencing change.

Landscape changes and the processes driving them have been a critical component in both research and management efforts of savanna systems. These dynamics impact human populations, wildlife, carbon storage, and general spatio-temporal dynamism in response to both anthropomorphic and climatic shifts. Both biophysical and human agents of change can be identified by isolating their respective spatial, temporal, and organizational contingencies. However, we argue here that a significant portion of savanna research has either considered humans as exogenous (e.g., via enacting regional or broader policies) or somewhat spatio-temporally removed from the system (e.g., as in many protected areas with limited current human habitation). Examples from African savanna research and particularly those systems of southern Africa are thus reviewed and used to model a stylized or prototypical savanna system and contingencies. Such an approach allows for a richer socio-temporal integration of theories and data on past biophysical and human histories to facilitate an improved framework for understanding savanna systems and their complex contingencies as socio-ecological landscapes.