|
Résumé :
|
This book presents a comprehensive and up-to-date review and synthesis of concepts, theories, methods and case studies in scaling and uncertainty analysis in ecology and related fields. Various definitions and ideas concerning scale are compared and contrasted in a coherent framework, and two general scaling approaches, similarity-based scaling that is rooted in the idea of similitude or self-similarity and dynamic model-based scaling that emphasizes processes and mechanisms, are discussed. The book is the first of its kind to explicitly consider uncertainty and error analysis as an integral part of scaling. The series of case studies included illustrate how scaling and uncertainty analysis are being conducted in ecology and environmental science, from population to ecosystem processes, from biodiversity to landscape patterns, and from basic research to multidisciplinary management and policy-making issues. While the theme of this book focuses primarily on spatial scaling, several chapters deal as well with aspects of temporal scaling. Although it is not intended to be a handbook of scaling recipes, the book provides both examples and a set of guidelines for scaling across heterogeneous ecological systems. Overall, this book will help readers gain a fuller understanding of the state-of-the-science of scale issues.
|
