Scaling and Uncertainty Analysis in Ecology (eBook, PDF)
Methods and Applications
Redaktion: Wu, Jianguo; Loucks, Orie L.; Li, Harbin; Jones, K. Bruce
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Presenting the current state of the art in scaling and uncertainty in ecology, Wu et al's Scaling and Uncertainty Analysis in Ecology is the first book of its kind - explicitly considering uncertainty and error analysis as an integral part of scaling.Primarily, the book draws together a series of important case studies to provide a comprehensive review and synthesis of the most recent concepts, theories and methods in scaling and uncertainty analysis. It compares current definitions and ideas concerning scale within a coherent framework, and examines two key scaling approaches: similarity-base...
Presenting the current state of the art in scaling and uncertainty in ecology, Wu et al's Scaling and Uncertainty Analysis in Ecology is the first book of its kind - explicitly considering uncertainty and error analysis as an integral part of scaling.
Primarily, the book draws together a series of important case studies to provide a comprehensive review and synthesis of the most recent concepts, theories and methods in scaling and uncertainty analysis. It compares current definitions and ideas concerning scale within a coherent framework, and examines two key scaling approaches: similarity-based scaling, which is rooted in the idea of similitude or self-similarity; and dynamic model-based scaling, which emphasizes processes and mechanisms.
With case studies focusing on issues ranging from population to ecosystem processes; from biodiversity to landscape patterns; and from basic research to multidisciplinary management and policy-making, the book will appeal to both researchers and practitioners working on landscape issues. It will also provide a valuable resource for graduate students and professional trainees in ecology, environmental policy, resource management and global change science.
Primarily, the book draws together a series of important case studies to provide a comprehensive review and synthesis of the most recent concepts, theories and methods in scaling and uncertainty analysis. It compares current definitions and ideas concerning scale within a coherent framework, and examines two key scaling approaches: similarity-based scaling, which is rooted in the idea of similitude or self-similarity; and dynamic model-based scaling, which emphasizes processes and mechanisms.
With case studies focusing on issues ranging from population to ecosystem processes; from biodiversity to landscape patterns; and from basic research to multidisciplinary management and policy-making, the book will appeal to both researchers and practitioners working on landscape issues. It will also provide a valuable resource for graduate students and professional trainees in ecology, environmental policy, resource management and global change science.
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