Daniel G Brown George P Malanson Michigan State University University of Iowa The research will assess the possible relations between pattern and process by using a spatially explicit simulation model that produces spatial patterns which will be compared to patterns recorded by Landsat imagery. The work will allow testing of the effects of different positive feedback strength, seed rain, and environmental gradient on the abundance of tree species at an ecotone. A sample of 30 to 40 rectangular hillslopes will be identified for this purpose in Glacier National Park. The patterns observed on the landscape and simulated in the model runs will be quantified using common metrics of landscape pattern. Further a hybrid metric will be generated which best describes the dominant variation among the sampled units. A model to predict the observed metrics will be fit from the simulation parameterizations. The outcome will be a deeper understanding of the basic ecology of ecotones through a stronger conceptualization between pattern and process. The work is also germane to the notion of ecotones as indicators of the impacts of climate change.
