Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink

Introduction Theories Underlying Predictive Models Reasons for Modeling and Simulation What Does It Take To Be a Modeler? Why Models Fail: A Cautionary Note Principles of Modeling and Simulation Systems Modeling Simulation Introduction to Matlab and Simulink MATLAB Simulink Exercises Introduction to Stochastic Modeling Introduction to Probability Distributions Example Probability Distributions Discrete-State Markov Processes Monte Carlo Simulation Exercises Modeling Ecotoxicology of Individuals Toxic Effects on Individuals Exercises Modeling Ecotoxicology of Populations, Communities, and Ecosystems Effects of Toxicants on Aggregated Populations Effects of Toxicants on Age-Structured Populations Effects of Toxicants on Communities Effects of Toxicants on Ecosystems Exercises Parameter Estimation Linear Regression Nonlinear Regression Comparison between Linear and Nonlinear Regressions Exercises Designing Simulation Experiments Factorial Designs Response Surface Designs Exercises Analysis of Simulation Experiments Simulation Output Analysis Stability Analysis Sensitivity Analysis Response Surface Methodology Exercises Model Validation Validation and Reasons for Modeling and Simulation Testing Hypotheses Statistical Techniques Some MATLAB Methods Exercises A Model to Predict the Effects of Insecticides on Avian Populations Problem Definition Model Development Model Implementation Data Requirements Model Validation Design Simulation Experiments Analyze Results of Simulation Experiments Case Study: Predicting Health Risk to Bottlenose Dolphins from Exposure to Oil Spill Toxicants Problem Definition Model Development Model Implementation Data Requirements Model Validation Design of Simulation Experiments Analyze Results of Simulation Experiments Presentation and Implementation of Results Case Study: Simulating the Effects of Temperature Plumes on the Uptake of Mercury in Daphnia Problem Definition Model Development Model Implementation Data Requirements Model Validation Design of Simulation Experiments Analyze Results of Simulation Experiments Presentation and Implementation of Results Index.