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Modeling Complex Forest Ecology in a Parallel Computing Infrastructure

Description: Effective stewardship of forest ecosystems make it imperative to measure, monitor, and predict the dynamic changes of forest ecology. Measuring and monitoring provides us a picture of a forest's current state and the necessary data to formulate models for prediction. However, societal and natural events alter the course of a forest's development. A simulation environment that takes into account these events will facilitate forest management. In this thesis, we describe an efficient parallel implementation of a land cover use model, Mosaic, and discuss the development efforts to incorporate spatial interaction and succession dynamics into the model. To evaluate the performance of our implementation, an extensive set of simulation experiments was carried out using a dataset representing the H.J. Andrews Forest in the Oregon Cascades. Results indicate that a significant reduction in the simulation execution time of our parallel model can be achieved as compared to uni-processor simulations.
Date: August 2003
Creator: Mayes, John
Partner: UNT Libraries

Forest Landscape Dynamics: a Semi-Markov Modeling Approach

Description: A transition model (MOSAIC) is used to describe forest dynamics at the landscape scale. The model uses a semi-Markov framework by considering transition probabilities and Erlang distributed holding times in each transition. Parameters for the transition model are derived from a gap model (ZELIG). This procedure ensures conceptual consistency of the landscape model with the fine scale ecological detail represented by the forest gap model. Spatial heterogeneity in the transition model is driven by maps of terrain with characteristics contained in a Geographic Information System (GIS) database. The results of the transition model simulations, percent cover forest type maps, are exported to grid-maps in the GIS. These cover type maps can be classified and used to describe forest dynamics using landscape statistics metrics. The linkage model-GIS enhances the transition model spatial analytical capabilities. A parameterization algorithm was developed that takes as input gap model tracer files which contain the percent occupation of each cover type through time. As output, the algorithm produces a file that contains the parameter values needed for MOSAIC for each one of the possible transitions. Parameters for the holding time distribution were found by calculating an empirical estimate of the cumulative probability function and using a non-linear least squares method to fit this estimate to an Erlang distribution. The algorithm provided good initial estimates of the transitions parameters that can be refined with few additional simulations. A method for deriving classification criteria to designate cover types is presented. The method uses cluster analysis to detect the number and type of forest classes and Classification and Regression Tree (CART) analysis to explain the forest classes in term of stand attributes. This method provided a precise and objective approach for forest cover type definition and classification. The H. J. Andrews forest in Oregon was used to demonstrate the ...
Date: August 1997
Creator: Ablan, Magdiel
Partner: UNT Libraries