Research
IDS2: Hydrologic & Nutrient Controls - Southern Africa
NASA Project Number: NNG04GM71G
Hank Shugart, D'Odorico, Macko, Okin
This award is part of the KALAHARI TRANSECT - AFRICA Project.
Understanding and modeling the response of complex ecosystems to change is recognized as a problem that requires understanding of change at multiple scales and involving multiple potential significant and causal phenomena. In this project, we will use EOS remote sensing, in situ measurements, and modeling in a multi-scale and modeling approach focused on assessing the feedback and stability of interactions in the complex savanna ecosystems found along a unique aridity gradient in Zambia, Botswana, Namibia, and the Republic of South Africa. The gradient, known as the Kalahari Transect (KT), follows a north-south decline in mean annual rainfall from ~1600 mm/yr to ~250 mm/yr, all on a fairly homogeneous sand formation. Results from our previous IDS and SAFARI 2000 activities in the region have revealed that although the coarse-scale (100s of km) pattern of vegetation cover for the KT savanna is determined by mean annual rainfall and nutrient availability, the small-scale (1- to 100 m) pattern of vegetation structure is highly organized by internal system processes, which operate at local scales. To understand and predict how savanna vegetation dynamics respond to alterations in climate or land-use forcings, it is necessary to observe, characterize and model interactions over these disparate scales. We will address this research goal by conducting a focused field campaign that will support the continued development and application of process-based modeling combined with remotely sensed data. A major goal of the proposed research is to understand how sub-pixel scale local variability is expressed in data from EOS sensors (esp. MODIS, ASTER,MISR) and, in turn, how these sensors may be used to provide synoptic regional-scale information about sub-pixel structure and processes. Thus, we will employ linked field observation, modeling analysis, and remote sensing observations over a set of core sites on which we will anchor our regional parameterizations and models.
