Foot and mouth disease (FMD) is a highly contagious viral infection that affects all Artiodactyls (cloven-hoofed) species. The United States has been free of FMD since 1929, and the entire population of cloven-hoofed species is therefore susceptible to FMD virus infection. In the face of an outbreak, it is crucial that appropriate control measures be applied rapidly to control the disease. However, in most cases decisions on mitigation strategies must be made with little current or empirical data and in the context of political, economic and social pressures. Disease spread models can be used to evaluate the design of optimal control strategies, for policy formulation, for gap analysis and to develop and refine research agendas when disease is not present. This research project is designed to investigate the potential role of wildlife (deer) in the transmission and spread of FMD in an extensive livestock management system in southern Texas. The spread of FMD was simulated in white tailed deer populations using a Geographic Automata model. Past research has focused primarily on modeling the spread of FMD in livestock populations. There has been limited research into the potential role of wildlife in the spread and maintenance of FMD, specifically in the United States and using a spatial modeling approach. The study area is a nine-county area located in southern Texas, bordering Mexico. It is a region of concern for the introduction of foreign animal diseases, particularly through the movement of wild and feral animal species. It is both a strategic location and is generally representative of the many similar eco-climatic regions throughout the world. It is an ideal model landscape to simulate FMD incursions. In this research project, the potential spread of FMD is simulated based on various spatial estimates of white tailed deer distribution, various estimates of critical model parameters (such as the latent and infectious periods), seasonal population variability and in the face of potential pre-emptive mitigation strategies. Significant differences in the predicted spread were found for each group of simulations. The decision-support system developed in the studies described in this dissertation provide decision-makers and those designing and implementing disease response and control policy with information on the potential spread of a foreign animal disease incursion with a likely wildlife reservoir. Use of such a decision-support system would enhance the disease incursion preparedness and response capacity of the United States.

In this thesis, we investigate methods by which discrete event network diffusion simulators may execute without the restriction of lockstep or near lockstep synchronicity. We develop a discrete event simulator that allows free clock drift between threads, develop a differential equations model to approximate communication cost of such a simulator, and propose an algorithm by which we leverage information gathered in the natural course of simulation to redistribute agents to parallel threads such that the burden of communication is lowered during future replicates.

The search for alternative energy sources has increased interests in forest biomass. During the last few years, the sever infestation of the Mountain Pine Beetle (MPB) within the Interior BC forests has led to huge volumes of dead wood that exceed the capacity of the lumber industry. One way to make the most value of the surplus wood is to use it as the feedstock for bioenergy. The forest biomass can be supplied through conventional (roadside residuals), full-tree chipping, or satellite yard systems. This thesis presents the development of a simulation model of supply logistics of forest biomass and its application to a case of supplying MPB-killed biomass from Quesnel Timber Supply Area (one of the most infested areas in the Interior BC) to a potential 300 MW power plant adjacent to the city of Quesnel. The model has the ability of providing estimates of quantity, delivery cost, and moisture content of biomass which are critical in feasibility study of any bioenergy project. The results obtained from simulation model showed a delivery cost of C$45 per oven dry tonne of wood chips to the power plant. The results also revealed that the feedstock recovered from roadside residues in one year meets about 30% of the annual demand of the power plant. Potential increase in the Allowable Annual Cut (AAC) for Quesnel TSA increases the quantity of biomass supplied from roadside residuals. However, as long as the biomass is supplied only through conventional harvesting, increasing the AAC even by 40% does not provide enough feedstock to meet the annual demand of the plant. Using the simulation modeling, this research has the benefit of considering the logistics of forest biomass supply as an integrated and interacting system as well as providing different critical parameters over time. The model also has the potential of considering dynamic and random behavior of the logistics system of supplying forest biomass. The model can be modified and applied to similar cases of conventional forest biomass supply. It also can be extended to other harvesting systems including satellite yard and whole-tree chipping.

No description available.

The search for alternative energy sources has increased interests in forest biomass. During the last few years, the sever infestation of the Mountain Pine Beetle (MPB) within the Interior BC forests has led to huge volumes of dead wood that exceed the capacity of the lumber industry. One way to make the most value of the surplus wood is to use it as the feedstock for bioenergy. The forest biomass can be supplied through conventional (roadside residuals), full-tree chipping, or satellite yard systems. This thesis presents the development of a simulation model of supply logistics of forest biomass and its application to a case of supplying MPB-killed biomass from Quesnel Timber Supply Area (one of the most infested areas in the Interior BC) to a potential 300 MW power plant adjacent to the city of Quesnel. The model has the ability of providing estimates of quantity, delivery cost, and moisture content of biomass which are critical in feasibility study of any bioenergy project. The results obtained from simulation model showed a delivery cost of C$45 per oven dry tonne of wood chips to the power plant. The results also revealed that the feedstock recovered from roadside residues in one year meets about 30% of the annual demand of the power plant. Potential increase in the Allowable Annual Cut (AAC) for Quesnel TSA increases the quantity of biomass supplied from roadside residuals. However, as long as the biomass is supplied only through conventional harvesting, increasing the AAC even by 40% does not provide enough feedstock to meet the annual demand of the plant. Using the simulation modeling, this research has the benefit of considering the logistics of forest biomass supply as an integrated and interacting system as well as providing different critical parameters over time. The model also has the potential of considering dynamic and random behavior of the logistics system of supplying forest biomass. The model can be modified and applied to similar cases of conventional forest biomass supply. It also can be extended to other harvesting systems including satellite yard and whole-tree chipping.

The search for alternative energy sources has increased interests in forest biomass. During the last few years, the sever infestation of the Mountain Pine Beetle (MPB) within the Interior BC forests has led to huge volumes of dead wood that exceed the capacity of the lumber industry. One way to make the most value of the surplus wood is to use it as the feedstock for bioenergy. The forest biomass can be supplied through conventional (roadside residuals), full-tree chipping, or satellite yard systems. This thesis presents the development of a simulation model of supply logistics of forest biomass and its application to a case of supplying MPB-killed biomass from Quesnel Timber Supply Area (one of the most infested areas in the Interior BC) to a potential 300 MW power plant adjacent to the city of Quesnel. The model has the ability of providing estimates of quantity, delivery cost, and moisture content of biomass which are critical in feasibility study of any bioenergy project. The results obtained from simulation model showed a delivery cost of C$45 per oven dry tonne of wood chips to the power plant. The results also revealed that the feedstock recovered from roadside residues in one year meets about 30% of the annual demand of the power plant. Potential increase in the Allowable Annual Cut (AAC) for Quesnel TSA increases the quantity of biomass supplied from roadside residuals. However, as long as the biomass is supplied only through conventional harvesting, increasing the AAC even by 40% does not provide enough feedstock to meet the annual demand of the plant. Using the simulation modeling, this research has the benefit of considering the logistics of forest biomass supply as an integrated and interacting system as well as providing different critical parameters over time. The model also has the potential of considering dynamic and random behavior of the logistics system of supplying forest biomass. The model can be modified and applied to similar cases of conventional forest biomass supply. It also can be extended to other harvesting systems including satellite yard and whole-tree chipping. / Forestry, Faculty of / Graduate

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The goal of my dissertation was to describe the dynamics of a group of Houston toads located at the Griffith League Ranch (GLR), Bastrop County, Texas. My research included using statistical modeling to predict activity and abundance, mark-recapture techniques to estimate survivorship, and simulation modeling to explore the impacts of the difference in age at first reproduction and to project the future dynamics of the population at the GLR. From 2001 – 2005, 225 individual Houston toads (199 M : 26 F) were captured using two methods: breeding pond surveys and drift fences. Houston toads were neither caught equally among capture methods, nor across years. Toad activity was mostly confined within their breeding season, and activity was not continuous. A logistic regression indicated activity depended on time of year, mean precipitation, mean minimum daily temperature, and mean percent lunation as well as two-way interactions with moon-phase and other variables. Abundance depended on time of year, current precipitation, minimum temperature, and two-way interactions between time of year and the other two variables. Twenty-one of the 199 males (10.5%) and no females were recaptured among years. The probability of male survival was estimated using program MARK. Eight of 16 candidate models were supported and all but one contained precipitation as a covariate, indicating precipitation is important for Houston toad survival. Survivorship estimates varied from 0.1 to 0.41. The sex ratio was significantly male-biased. The odds of catching females in traps were 3.5 greater than capturing females in a pond, while the odds of capturing males in a trap were 0.28 compared to ponds. Results from a simulation model indicated the sex ratio is biased because of the difference in maturation times between males and females, coupled with high juvenile mortality. Results from an individual-based, spatially-explicit, stochastic simulation model, indicated a relatively low probability (~ 0.013) of B. houstonensis going extinct at the GLR within the next 10 years. Emergent properties of the model were similar to results observed in the field or reported in the literature. The model also identified that dispersal of Houston toads should be a future research priority.

Today, the threat to humanity survival, economic crisis, financial crisis, global warming, ecological extinction, greenhouse effect ... etc., are gradually grow by both detail and dynamic complexity process. Most current humanity facing problems is because human can¡¦t handle the gradually growing complexity system problems on our environment. The main purpose of this research is to explore the causal feedback diagram model translation into stock flow diagram model, and to discover key transfer principle from current system dynamics and fundamental components. This will improve dynamic system accuracy and validity. According to model transformation design, this research is to provide a model based architecture, on simulating actual causal feedback diagram module with Maria 2 Plus provided function. Maria is the first Chinese language interface for the system dynamics simulation software. Through Software development tools transfer model and natural language operation interface to user easy use on causal feedback diagram and stock flow diagram model rapid creation. This will also decrease the learning cycle and will increase model creation speed and validity.

Assessment of vegetation productivity on rangelands is needed to assist in timely decision making with regard to management of the livestock enterprise as well as to protect the natural resource. Characterization of the vegetation resource over large landscapes can be time consuming, expensive and almost impossible to do on a near real-time basis. The overarching goal of this study was to examine available technologies for implementing near real-time systems to monitor forage biomass available to livestock on a given landscape. The primary objectives were to examine the ability of the Climate Prediction Center Morphing Product (CMORPH) and Next Generation Weather Radar (NEXRAD) rainfall products to detect and estimate rainfall at semi-arid sites in West Texas, to verify the ability of a simulation model (PHYGROW) to predict herbaceous biomass at selected sites (patches) in a semi-arid landscape using NEXRAD rainfall, and to examine the feasibility of using cokriging for integrating simulation model output and satellite greenness imagery (NDVI) for producing landscape maps of forage biomass in Mongolia’s Gobi region. The comparison of the NEXRAD and CMORPH rainfall products to gage collected rainfall revealed that NEXRAD outperformed the CMORPH rainfall with lower estimation bias, lower variability, and higher estimation efficiency. When NEXRAD was used as a driving variable in PHYGROW simulations that were calibrated using gage measured rainfall, model performance for estimating forage biomass was generally poor when compared to biomass measurements at the sites. However, when model simulations were calibrated using NEXRAD rainfall, performance in estimating biomass was substantially better. A suggested reason for the improved performance was that calibration with NEXRAD adjusted the model for the general over or underestimation of rainfall by the NEXRAD product. In the Gobi region of Mongolia, the PHYGROW model performed well in predicting forage biomass except for overestimations in the Forest Steppe zone. Cross-validation revealed that cokriging of PHYGROW output with NDVI as a covariate performed well during the majority of the growing season. Cokriging of simulation model output and NDVI appears to hold promise for producing landscape maps of forage biomass as part of near real-time forage monitoring systems.