Modeling Complex Forest Ecology in a Parallel Computing Infrastructure

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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 ... continued below

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Mayes, John August 2003.

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This thesis is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 353 times , with 8 in the last month . More information about this thesis can be viewed below.

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  • Mayes, John

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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.

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  • August 2003

Added to The UNT Digital Library

  • Feb. 15, 2008, 2:52 p.m.

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  • Dec. 11, 2008, 5:12 p.m.

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Mayes, John. Modeling Complex Forest Ecology in a Parallel Computing Infrastructure, thesis, August 2003; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc4305/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .