Simulation of Ecological and Environmental Models

About this book

Given the importance of interdisciplinary work in sustainability, Simulation of Ecological and Environmental Models introduces the theory and practice of modeling and simulation as applied in a variety of disciplines that deal with earth systems, the environment, ecology, and human-nature interactions. Based on the author's many years of teaching graduate and undergraduate students in the United States, Spain, and Latin America, Simulation of Ecological and Environmental Models shows how to implement simulations and analyze the results using an open-source software platform.

Learn How to Use a Broad Range of Environmental Models

Simulation of Ecological and Environmental Models is organized into three parts to allow greater flexibility using the material in various countries and types of curricula. The first part provides a tutorial-style mathematical review and a gentle introduction to the basics of R software. The second part explains the fundamentals of modeling methodology through one-dimensional models. After a review of matrix algebra, the third part progresses to multidimensional models, focusing on structured populations, communities, and ecosystems. The final chapters show how simple models are hooked together to generate more comprehensive models.

Build from Fundamental Concepts to Problem Solving

Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions let students grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seem, an open-source R package developed by the author, which lets students quickly produce simulations and explore the effects of changing conditions in the model. Simulation of Ecological and Environmental Models is a comprehensive, unified presentation of ecological and environmental models. It describes the mathematical fundamentals to analyze models and the methodology to simulate them, with a focus on understanding environmental change-a key element of environmental management and problem solving.

Contents

Part I Introduction, Mathematical Review, and Software Fundamentals

Introduction
Modeling and Simulation
Process-Based Dynamic Models
Applications of Environmental Modeling
Modeling Methodology
Book Organization
Simulation Platforms
Computer Session
Supplementary Reading

Review of Basic Mathematical Concepts and Introduction to R
Variables
Functions
Derivatives and Optimization
Integrals and Area
Ordinary Differential Equations
Functions of Several Variables
Random Variables and Distributions
Random Variables and Moments
Some Important Random Variables
Covariance and Correlation
Computer Session

Part II One-Dimensional Models and Fundamentals of Modeling Methodology

Exponential Model
Fundamentals
Units
Population Dynamics
Chemical Fate
Model Terms
Review of Simple Linear Regression
Model Calibration: Parameter Estimation
Nonlinear Regression
Computer Session

Model Simulation
Concepts of Computer Simulation Based on Ordinary Differential Equations
Euler Method
Fourth-Order Runge–Kutta Method
Random Number Generation
Stochastic Simulation
Computer Session
Seem Functions Explained

Model Evaluation
Testing the Numerical Method and the Code
Graphical Evaluation
Testing the Model
Testing the Parameter Values: Sensitivity Analysis
Computer Session
Seem Functions Explained

Nonlinear Models
Populations: Logistic Growth
Fate of Chemicals: Michaelis–Menten–Monod
Monod Kinetics
Computer Session
Seem Functions Explained

Stability and Disturbances
Stability
Disturbances
Variability and Stress
Sudden and Impulsive Disturbances
Computer Session
Seem Functions Explained

Sensitivity Analysis, Response Surfaces, and Scenarios
Multiparameter Sensitivity Analysis
Response Surface and Scenarios
Computer Session
Seem Functions Explained

Part III Multidimensional Models: Structured Populations, Communities, and Ecosystems

Linear Dynamical Systems
Matrices
Dimensions of a Matrix
Vectors
Square Matrices
Matrix Operations
Solving Systems of Linear Algebraic Equations
Eigenvalues and Eigenvectors
Linear Dynamical Systems: Constant Coefficients
Computer Session: Matrix Algebra

Structured Population Models
Types of Structure
Methods of Model Structure
Projection Matrices
Extensions
Continuous Time Stage Structured Model
Delay-Differential Equations
Computer Session
Seem Functions Explained

Ecotoxicological Modeling
Bioavailability
Bioaccumulation
Effects: Lethal and Sublethal
Including Food Pathways
Compartment Models
Bioaccumulation: Two-Compartment Model
Bioaccumulation: Multicompartment
Bioaccumulation: Varying Exposure
Population Effects
Risk Assessment
Computer Session
Seem Functions Explained

Community Dynamics
Two-State System Concepts
Two Species: Simple Interactions
Cycles in Two-Species Consumer–Resource Interactions
Two Species: Disturbances
Two Species: Structured Populations
More Than Two Species, But Not Too Many
Computer Session
Seem Functions Explained

Ecosystems: Nutrients and Energy
Nutrient Cycles
Closed Cycles
Open Cycles
Nutrient Cycle Examples
Nutrient Cycle Example: Aquatic Ecosystems
Global Biogeochemical Cycles
Primary Productivity
Secondary and Tertiary Productivity
Computer Session
Seem Functions Explained

Aquatic Ecosystems
Environmental Drivers
Solar Radiation
Light as a Function of Depth
Dissolved Oxygen and Primary Productivity
River Eutrophication
Computer Session
Seem Functions Explained

Terrestrial Ecosystems: Soils, Plants, and Water
Weather Generators
Evapotranspiration
Soil Water Dynamics
Soil Water Balance
Infiltration and Runoff
Computer Session
Seem Functions Explained

Terrestrial Ecosystems: Vegetation Dynamics
Individual-Based Approach
Growth Equation
Allometric Relationships
Diameter Ordinary Differential Equation
Environmental Conditions
Estimation of G_max
Sunlight
Soil Moisture
Temperature
Nutrients
Tree Population Demography
Model Responses
Deterministic and Lumped Model
Markovian Models
Computer Session
Seem Functions Explained

Bibliography

Index

Customer Reviews

Biography

Miguel F. Acevedo has 38 years of academic experience, the last 20 of these as faculty member of the University of North Texas (UNT). His career has been interdisciplinary, especially at the interface of science and engineering. He obtained his Ph.D. in biophysics from the University of California Berkeley and master degrees in electrical engineering and computer science from Berkeley and the University of Texas at Austin, respectively. Prior to UNT, he was at the Universidad de Los Andes in Merida, Venezuela, where he taught for 18 years. He has served on the Science Advisory Board of the U.S. Environmental Protection Agency and on many review panels of the U.S. National Science Foundation. He has received numerous research grants and written many journal articles, book chapters, and proceedings articles. UNT has recognized him with the Regent's Professor rank, the Citation for Distinguished Service to International Education, and the Regent's Faculty Lectureship. For more information, see Dr. Acevedo's page at UNT.