Kirjahaku

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.

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.

Whether discussing habitat placement for the northern spotted owl or black-tailed prairie dog or strategies for controlling exotic pests, this book explains how capturing ecological relationships across a landscape with pragmatic optimization models can be applied to real world problems. Using linear programming, Hof and Bevers show how it is possible for the researcher to include many thousands of choice variables and many thousands of constraints and still be quite confident of being able to solve the problem in hand with widely available software. The authors' emphasis is to preserve optimality and explore how much ecosystem function can be captured, stressing the solvability of large problems such as those in real world case studies.