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...

This is the first book of its kind explicitly considering uncertainty and error analysis as an integral part of scaling. 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 includes case studies illustrating how scaling and uncertainty analysis are being conducted in ecology and environmental science.