Principle goals: to use data mining techniques to understand how variables drive ecosystem functioning and a qualitative study to determine which of a variety of data mining techniques best replicates observed ecosystem processes.
The functioning of an ecosystem depends on a variety of drivers. One of the best places to examine these parameters is the Andes-to-Amazon slope , where a gradient of ecosystems can be found, from high elevation grassland and montane rain forest to lowland rain forest, distinguished by differences in climate (related to altitude), and soil. This project involves conducting a numerical analysis of real data from databases governing ecosystem properties. Data available include Digital Elevation Models (DEMs), slope, biomass, soil CO2 efflux, tree growth and tree species diversity; the forest ecosystem data are derived from specific sites (plots) at 10 different elevations, ranging from 3000 m to 220 m above sea level. Weather data are available for 4 of these sites. Before any analysis can happen these data need to be integrated to make one coherent set.