Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink

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Overview

This book fills the need for quantitative modeling in the field of ecotoxicology recognized for decades. It discusses the role of modeling and simulation in environmental toxicology, and describes toxicological processes from the level of the individual organism to populations and ecosystems. Mathematical functions and simulations are presented using Matlab and Simulink programming languages. Chapters cover principles and practices in simulation modeling; stochastic modeling; modeling ecotoxicology; parameter estimation; model validation; as well as designing and analyzing simulation experiments.

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Product Details

  • ISBN-13: 9781439855171
  • Publisher: Taylor & Francis
  • Publication date: 9/14/2011
  • Pages: 270
  • Product dimensions: 7.20 (w) x 10.10 (h) x 1.00 (d)

Meet the Author

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.

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Table of Contents

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.

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