1st Edition

Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink

By Kenneth R. Dixon Copyright 2012
    270 Pages 167 B/W Illustrations
    by CRC Press

    270 Pages 167 B/W Illustrations
    by CRC Press

    Exploring roles critical to environmental toxicology, Modeling and Simulation in Ecotoxicology with Applications in MATLAB® and Simulink® covers the steps in modeling and simulation from problem conception to validation and simulation analysis. Using the MATLAB and Simulink programming languages, the book presents examples of mathematical functions and simulations, with special emphasis on how to develop mathematical models and run computer simulations of ecotoxicological processes.

    Designed for students and professionals with little or no experience in modeling, the book includes:

    • General principles of modeling and simulation and an introduction to MATLAB and Simulink
    • Stochastic modeling where variability and uncertainty are acknowledged by making parameters random variables
    • Toxicological processes from the level of the individual organism, with worked examples of process models in either MATLAB or Simulink
    • Toxicological processes at the level of populations, communities, and ecosystems
    • Parameter estimation using least squares regression methods
    • The design of simulation experiments similar to the experimental design applied to laboratory or field experiments
    • Methods of postsimulation analysis, including stability analysis and sensitivity analysis
    • Different levels of model validation and how they are related to the modeling purpose

    The book also provides three individual case studies. The first involves a model developed to assess the relative risk of mortality following exposure to insecticides in different avian species. The second explores the role of diving behavior on the inhalation and distribution of oil spill naphthalene in bottlenose dolphins. The final case study looks at the dynamics of mercury in Daphnia that are exposed to simulated thermal plumes from a hypothetical power plant cooling system.

    Presented in a rigorous yet accessible style, the methodology is versatile enough to be readily applicable not only to environmental toxicology but a range of other biological fields.

    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.


    Biography

    Dr. Kenneth R. Dixon’s current research interests include developing and applying computer simulation models to predict the movement of toxic chemicals in the environment and their effects on human and wildlife populations. He also studies the spatial distribution of toxicants and effects at ecosystem, landscape, and regional scales by integrating models with geographic information systems. Current research projects include developing food-chain models to predict the uptake and effects of pesticides, perchlorate, and explosives; developing spatial models of the spread of infectious diseases; and a mathematical programming model of the effects of pollutants on optimal feeding strategies. Dr. Dixon has taught courses in modeling, geographic information systems, ecosystems analysis, biometry, and wildlife management.