Spatial Optimization for Managed Ecosystems - John Hof

. .

Résumé :
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.

Biographie:
John Hof and Michael Bevers

Sommaire:
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 Continuous Choice Variables The Problem An Example The Model A Cellular Model of Wildlife Population Growth and Dispersal Methods Dynamic Movement Row-Total Variance Reduction 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 Organization Viewpoint Introduction Pragmatic Approaches to Handling Risk and Uncertainty Rectangles Circles Optimization Chance Maximization Spatial Autocorrelation Connectivity Theory A Geometric Wildlife Model with Spatial Autocorrelation and Habitat Connectivity 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 A Spatial Recreation Allocation Model The Case of More Than One Proposed Site The Travel Cost Model Spatial Supply--Demand Equilibrium: A Recreation Example Spatial Effects A Geometric Model of Wildlife Habitat Spatial Relationships Wildlife Habitat Size Thresholds A Steady-State Example Determining the Optimal Steady State Species Richness Objective Functions Diversity and Sustainability Two Examples The Spatial Optimization Approach A Nested-Schedule Model of Stormflow A Cellular Model of Pest Management Model Results Ferret Carrying Capacity