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    • April 1998
    • 9780231106375
  • 320 Pages
  • 48 illus

  • Paperback
  • $47.00
  • / £32.50

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    • April 1998
    • 9780231106368
  • 320 Pages
  • 48 illus

  • Hardcover
  • $130.00
  • / £89.50

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Spatial Optimization for Managed Ecosystems

John Hof and Michael Bevers

Spatial optimization is a methodology used to maximize or minimize a management objective, given the limited area, finite resources, and spatial relationships in an ecosystem. Optimization approaches can be used to evaluate a great variety of options and allow tradeoff analyses that might be impossible with other methods.

This book presents ideas and methods for directly optimizing the spatial layout of the landscape features in which an ecosystem functions. The problems Hof and Bevers address are complex, and the book relies heavily on mathematical presentations; the ideas are explained in a tutorial fashion that allows readers to grasp the general principals even if they skip the math. The first of four parts treats static spatial relationships that reflect the importance of shape, size, and proximity within an ecosystem. Part 2 considers spatial autocorrelation in a chance-constrained modeling framework. Part 3 discusses dynamic spatial changes within modeled ecosystems, and the final section focuses on diversity and sustainability. Although most discussion concerns wildlife habitat issues, the authors also include chapters on recreation, timber management, water runoff, and pest management.

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.

Ferret Releases
Net Population Growth Rate
Ferret Dispersal
Spatial Definition
Ferret Reintroduction in South Dakota
The Spatial Optimization Model
The Black-Footed Ferret: A Case Study
Discussion
The Modeling Approach
Sustainability of Species Richness
The Logistic Distribution
Transformations
Declining Monotonicity of Natural Logarithm
Results
Allocation Over Time and Space
Results
Continuous Choice Variables
Results
The Problem
An Example
The Model
A Cellular Model of Wildlife Population Growth and Dispersal
Methods
Dynamic Movement
Row-Total Variance Reduction
An Example
Post--Optimization Calculations
Simulation Versus Optimization
An Adaptive Management Context
Synthesis
A New Definition for a Regulated Forest
Single-Species Emphasis
Accounting for Mortality
Sensitivity to Planning Horizon Length
Sensitivity to Minimum Harvest Age
Model Reduction
Linear Approximation of Objective Functions
A Coastal Douglas-fir Case Study
Objective Functions
Wildlife Habitat Fragmentation Effects
Edge Effects
A Cellular Model of Wildlife Habitat Spatial Relationships
Static Spatial Relationships
A Final Introductory Note
Solvability of Nonlinear Programs
Solvability of (0--1) Integer Programs
Methods
Organization
Viewpoint
Introduction
The Problem
Pragmatic Approaches to Handling Risk and Uncertainty
Discussion
Results
The Problem
An Example
Rectangles
Circles
Optimization
Chance Maximization
Spatial Autocorrelation
Connectivity
Theory
A Geometric Wildlife Model with Spatial Autocorrelation and Habitat Connectivity
Discussion
Results
The Problem
An Example
A Cellular Timber Model with Spatial Autocorrelation
Approximation of the CDF
Total Probability Chance-Maximizing Programming
Joint Probability Chance-Maximizing Programming
MAXMIN Chance-Maximizing Programming
Chance-Maximizing Programs
Total Probability Chance Constraint
Joint Probability Chance Constraint
Individual Chance Constraints
Chance-Constrained Programming
Spatial Autocorrelation
Discussion
Results
The Problem
An Example
A Spatial Recreation Allocation Model
The Case of More Than One Proposed Site
The Travel Cost Model
Spatial Supply--Demand Equilibrium: A Recreation Example
Discussion
Results
An Example
Spatial Effects
A Geometric Model of Wildlife Habitat Spatial Relationships
Discussion
Results
The Problem
An Example
Wildlife Habitat Size Thresholds
Results
A Steady-State Example
Determining the Optimal Steady State
Species Richness Objective Functions
Diversity and Sustainability
Discussion
Results
Two Examples
The Spatial Optimization Approach
A Nested-Schedule Model of Stormflow
Discussion
Results
The Problem
An Example
The Model
A Cellular Model of Pest Management
Model Results
Ferret Carrying Capacity

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.

About the Author

John Hof is a project leader, and Michael Bevers is a research scientist at the USDA Forest Service's Rocky Mountain Research Station in Fort Collins, Colorado.