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Titlebook: Scaling and Uncertainty Analysis in Ecology; Methods and Applicat JIANGUO WU,K. BRUCE JONES,ORIE L. LOUCKS Book 20061st edition Springer Sc

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书目名称Scaling and Uncertainty Analysis in Ecology
副标题Methods and Applicat
编辑JIANGUO WU,K. BRUCE JONES,ORIE L. LOUCKS
视频video
概述The first book to consider uncertainty analysis as integral part of scaling, to examine relations between scaling and uncertainty analysis methods.Presents reviews and syntheses of theories and method
图书封面Titlebook: Scaling and Uncertainty Analysis in Ecology; Methods and Applicat JIANGUO WU,K. BRUCE JONES,ORIE L. LOUCKS Book 20061st edition Springer Sc
描述.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..
出版日期Book 20061st edition
关键词biodiversity; development; ecology; ecosystem; ecosystem processes; environment
版次1
doihttps://doi.org/10.1007/1-4020-4663-4
isbn_softcover978-1-4020-4664-3
isbn_ebook978-1-4020-4663-6
copyrightSpringer Science+Business Media B.V. 2006
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978-1-4020-4664-3Springer Science+Business Media B.V. 2006
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ate variables and whose dependence on the uncertain parameters is expressed as a matrix form. A key property of this class of Lyapunov functions is that they allow one to formulate robustness conditions in terms of convex optimizations, by adopting the SMR of matrix forms introduced in Chapter 1 and
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