The objectives of the proposed research are (1) to develop a systematic, computerized procedure to detect the structural patterns in the grassland landscape of Jasper Ridge, California, based primarily on the 2-Dimensional Net Function Interpolation Theory; (2) to construct and validate a hierarchically structured, spatially explicit, stochastic simulation model of pattern-process dynamics, based mainly on data from the Jasper Ridge grassland ecosystem. The model will take into consideration processes involving small-scale/high frequency, middle-scale/low frequency, and large-scale/very low frequency phenomena. Stochasticity in each process will have to be incorporated. Large-scale phenomena may include weather fluctuations (e.g., precipitation, temperature), wind/water erosion, prolonged drought, and irregularly timed, fires. Small- scale phenomena, on the other hand, may involve physical environmental patchiness and activities of mound-building animals such as gophers and ants. Overall, the model will incorporate demographics of small-scaled disturbances in grasslands, monitor the temporal changes of patches, and trace aging and extinction of the patches at various scales. The spatially explicit, multiple-scale pattern induction model takes a bottom-up approach, deriving landscape-level dynamics of the grassland from that of hierarchically decomposable lower levels. The computational demand in spatial and temporal statistical analyses of patterns, and the sensitivity anaLysis and Monte Carlo simulation of the model, will make desirable and imperative the use of the parallel capabilities of the supercomputer facilities. The completion of the proposed study will add substantially to understanding of the role of naturally occurring disturbances at various scales in creating the pattern-process dynamics, provide a modeling framework for further comparative investigation on different types o grassland ecosystems, serve as a strong basis for comparing grasslands with forests, and exemplify the significance of supercomputer facilities in enhancing ecological understanding.
