Forest Landscape Dynamics: a Semi-Markov Modeling Approach

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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 ... continued below

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ix, 138 leaves : ill.

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Ablan, Magdiel August 1997.

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  • Ablan, Magdiel

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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 methods and procedures developed in this study.

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ix, 138 leaves : ill.

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  • August 1997

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  • March 26, 2014, 9:30 a.m.

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  • Sept. 4, 2014, 8:10 a.m.

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Ablan, Magdiel. Forest Landscape Dynamics: a Semi-Markov Modeling Approach, dissertation, August 1997; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc278908/: accessed June 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .