From the Chapman & Hall Microbiology Series this unique resource offers specific experimental and practical applications of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to test whether the models provide a good representation of the system. The book also encourages further development and application of modeling to burgeoning problems associated with microbial ecology, such as the pollution and destruction of pesticides and herbicides.
From the Chapman & Hall Microbiology Series this unique resource offers specific experimental and practical applications of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to test whether the models provide a good representation of the system. The book also encourages further development and application of modeling to burgeoning problems associated with microbial ecology, such as the pollution and destruction of pesticides and herbicides.
1. What is Happening to Microbial Ecology?.- 1. Introduction.- 2. Analytical Methods.- 3. Kinetic Aspects.- 4. Principles of Kinetic Modeling.- 5. Progress in Statistical Methods.- 6. Conclusions.- 2. Modeling Microbial Processes: An Overview of Statistical Considerations.- 1. Introduction.- 2. Model Identification versus Discrimination.- 3. The Least-Squares Criterion.- 4. Model Identification.- 5. Model Discrimination.- 6. Optimal Experiments for Parameter Estimation.- 7. Concluding Remarks.- References.- 3. Analysis of Repeated Measures Data Using Nonlinear Models.- 1. Introduction.- 2. The Model.- 3. Parameter Estimation.- 4. Comparing the Treatments.- 5. Constructing Confidence Bands for the Models.- 6. Example 1: Growing Cookies.- 7. Example 2: Cumulative Radioactive CO2 Production.- 8. Summary.- References.- 4. The Monod Model and Its Alternatives.- 1. Jacques Monod: His Life and Work.- 2. The Monod Model and Its Derivations.- 3. Limitation of the Hyperbolic Model.- 4. The Blackman (1905) Model and the Best (1955) Model.- 5. Still More Complication: The Phosphotransferase System.- 6. Still More Complications: The Kinetic Contribution of Porins and Passage through the Outer Membrane.- 7. The Experimental Measurement of Glucose Consumption.- 8. Selection of a Mutant Growing More Avidly at Low Glucose Concentrations.- 9. The Data Fitting: The Role of Models.- 10. The Statistical Fitting.- 11. Diffusion Limitation and Effect of Multiple Layers.- 12. The Effect of the Variation of the Surface Area to Volume during the Cell Cycle.- 13. Grave Omissions.- 14. Conclusions.- References.- 5. Using Transport Model Interpretations of Tracer Tests to Study Microbial Processes in Groundwater.- 1. Introduction.- 2. The Groundwater Environment.- 3. Measuring Microbial Processes in an Aquifer.- 4. Tracer-Test Technology.- 5. Transport-Process Models.- 6. Assessing Methane Oxidation.- 7. Assessing Denitrification.- 8. Future Applications and Limitations.- References.- 6. Modeling of Pesticide Biodegradation in Soil Daniel R. Shelton, Michael A. Doherty, Timothy B. Parkin, and.- 1. Introduction.- 2. Modeling.- 3. More Elaborate Models.- 4. Effect of Microbial Numbers.- 5. Role of Sorption.- 6. Summary.- References.- 7. Modeling Nitrogen Transformation in Soil.- 1. Introduction.- 2. Using Models to Calculate Data.- 3. Using Models to Understand N Cycle Transformations and Their Regulation.- 4. Using Models to Make Predictions about N Cycling.- 5. Summary.- References.- 8. Construction and Analysis of Static, Structured Models of Nitrogen Cycling in Coastal Ecosystems.- 1. Introduction.- 2. Methods.- 3. Model Development.- 4. Analysis Results and Interpretation.- 5. Conclusions and Subsequent Directions.- References.- 9. A Modeling Approach to Elucidating the Distribution and Rates of Microbially Catalyzed Redox Reactions in Anoxic Groundwater.- 1. Introduction.- 2. Use of H2 Concentrations to Predict Terminal Electron-Accepting Processes in Anoxic Groundwater.- 3. Estimating Rates of Microbial Processes with Geochemical Modeling.- 4. Conclusions.- References.- 10. From the Ground Up: The Development and Demonstrated Utility of the Ruminai Ecosystem Model.- 1. Introduction.- 2. Balance Models of Rumen Digestion.- 3. Dynamic Models of Ruminant Digestion.- 4. Early Dynamic Models.- 5. Current Dynamic Models.- References.- 11. Mathematical Models of Bacterial Chemotaxis.- 1. Introduction.- 2. Population Balance Models.- 3. Cellular Dynamics Simulation.- 4. Comparison of Modeling Approaches.- 5. Application to Multiple Stimuli.- 6. Concluding Remarks.-References.
1. What is Happening to Microbial Ecology?.- 1. Introduction.- 2. Analytical Methods.- 3. Kinetic Aspects.- 4. Principles of Kinetic Modeling.- 5. Progress in Statistical Methods.- 6. Conclusions.- 2. Modeling Microbial Processes: An Overview of Statistical Considerations.- 1. Introduction.- 2. Model Identification versus Discrimination.- 3. The Least-Squares Criterion.- 4. Model Identification.- 5. Model Discrimination.- 6. Optimal Experiments for Parameter Estimation.- 7. Concluding Remarks.- References.- 3. Analysis of Repeated Measures Data Using Nonlinear Models.- 1. Introduction.- 2. The Model.- 3. Parameter Estimation.- 4. Comparing the Treatments.- 5. Constructing Confidence Bands for the Models.- 6. Example 1: Growing Cookies.- 7. Example 2: Cumulative Radioactive CO2 Production.- 8. Summary.- References.- 4. The Monod Model and Its Alternatives.- 1. Jacques Monod: His Life and Work.- 2. The Monod Model and Its Derivations.- 3. Limitation of the Hyperbolic Model.- 4. The Blackman (1905) Model and the Best (1955) Model.- 5. Still More Complication: The Phosphotransferase System.- 6. Still More Complications: The Kinetic Contribution of Porins and Passage through the Outer Membrane.- 7. The Experimental Measurement of Glucose Consumption.- 8. Selection of a Mutant Growing More Avidly at Low Glucose Concentrations.- 9. The Data Fitting: The Role of Models.- 10. The Statistical Fitting.- 11. Diffusion Limitation and Effect of Multiple Layers.- 12. The Effect of the Variation of the Surface Area to Volume during the Cell Cycle.- 13. Grave Omissions.- 14. Conclusions.- References.- 5. Using Transport Model Interpretations of Tracer Tests to Study Microbial Processes in Groundwater.- 1. Introduction.- 2. The Groundwater Environment.- 3. Measuring Microbial Processes in an Aquifer.- 4. Tracer-Test Technology.- 5. Transport-Process Models.- 6. Assessing Methane Oxidation.- 7. Assessing Denitrification.- 8. Future Applications and Limitations.- References.- 6. Modeling of Pesticide Biodegradation in Soil Daniel R. Shelton, Michael A. Doherty, Timothy B. Parkin, and.- 1. Introduction.- 2. Modeling.- 3. More Elaborate Models.- 4. Effect of Microbial Numbers.- 5. Role of Sorption.- 6. Summary.- References.- 7. Modeling Nitrogen Transformation in Soil.- 1. Introduction.- 2. Using Models to Calculate Data.- 3. Using Models to Understand N Cycle Transformations and Their Regulation.- 4. Using Models to Make Predictions about N Cycling.- 5. Summary.- References.- 8. Construction and Analysis of Static, Structured Models of Nitrogen Cycling in Coastal Ecosystems.- 1. Introduction.- 2. Methods.- 3. Model Development.- 4. Analysis Results and Interpretation.- 5. Conclusions and Subsequent Directions.- References.- 9. A Modeling Approach to Elucidating the Distribution and Rates of Microbially Catalyzed Redox Reactions in Anoxic Groundwater.- 1. Introduction.- 2. Use of H2 Concentrations to Predict Terminal Electron-Accepting Processes in Anoxic Groundwater.- 3. Estimating Rates of Microbial Processes with Geochemical Modeling.- 4. Conclusions.- References.- 10. From the Ground Up: The Development and Demonstrated Utility of the Ruminai Ecosystem Model.- 1. Introduction.- 2. Balance Models of Rumen Digestion.- 3. Dynamic Models of Ruminant Digestion.- 4. Early Dynamic Models.- 5. Current Dynamic Models.- References.- 11. Mathematical Models of Bacterial Chemotaxis.- 1. Introduction.- 2. Population Balance Models.- 3. Cellular Dynamics Simulation.- 4. Comparison of Modeling Approaches.- 5. Application to Multiple Stimuli.- 6. Concluding Remarks.-References.
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