Sunday, 5 October 2008: 3:25 PM
George R. Brown Convention Center, 320F
Mima mounds and vernal pools dominated the pre-cultivation landscape in California's eastern San Joaquin Valley, though the origin of these unusual features has long been debated. Here we use a new approach to examine whether burrowing organisms such as pocket gophers maintain and possibly create the mounds by preferentially translocating soils towards mound centers as an adaptive response to high water tables. We use high-resolution topographic data to develop a spatial data set of Mima mounds, which we analyze to try to infer the underlying processes of formation. An airborne LIDAR (Light Detection and Ranging) survey was conducted on a 25km2 region of Mima mounds near Merced, California. The survey extends across a series of river terraces which span 4 million years in age and, as a result of soil formation processes and clay/hardpan development, systematically vary in hydrologic condition. We hypothesize that gopher sediment transport will change in response to varying soil saturation and that these changes will be perceptible in the land surface profiles. We evaluate the differences in mound form and distribution to test this hypothesis.
Initial analysis indicates that there are a minimum of 100,000 mounds within the survey region. Two approaches for automated object (mound) detection, a fuzzy membership function and a local maxima technique, were compared, in terms of detection accuracy and computational efficiency. Mound size, location, slope, and curvature values were assembled and compared between different-aged geologic formations and hillslope positions in order to test whether patterns conform to predicted changes in biological processes. Applying a linear biogenic sediment transport law to a mass balance model enabled us to use curvature values to estimate landscape-wide rates of erosion and deposition. From this, the rates of biologic upbuilding that would be required for burrowing animals to build or maintain the mounds can be estimated.