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Data Analysis in Vegetation Ecology, 3rd Edition
The 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis. The book succinctly illustrates the various paths leading to high quality data suitable for pattern recognition, pattern testing, static and dynamic modelling and model testing including spatial and temporal aspects of ecosystems. Step-by-step introductions using small examples lead to more demanding approaches illustrated by real world examples aimed at explaining interpretations. All data sets and examples described in the book are available online and are written using the freely available statistical package R. This book will be of particular value ...
A Changing World
Modern landscape research uses a panoply of techniques to further our understanding of our changing world, including mathematics, statistics and advanced simulation techniques to combine empirical observations with known theories. This book identifies emerging fields and new challenges that are discussed within the framework of the ‘driving forces’ of Landscape Development. the book addresses all of the ‘hot topics’ in this important area of study and emphasizes major contemporary trends in these fields.
Long-Memory Processes
Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.
Vegetation Description and Data Analysis
Vegetation Description and Data Analysis: A PracticalApproach, Second Edition is a fully revised and up-datededition of this key text. The book takes account of recent advancesin the field whilst retaining the original reader-friendly approachto the coverage of vegetation description and multivariate analysisin the context of vegetation data and plant ecology. Since the publication of the hugely popular first edition therehave been significant developments in computer hardware andsoftware, new key journals have been established in the field andscope and application of vegetation description and analysis hasbecome a truly global field. This new edition includes fullcoverage of new development...
Biomonitoring: General and Applied Aspects on Regional and Global Scales
This volume contains a selection of 14 articles dealing with different aspects of biomonitoring and their relation to questions of global change. The first part concerns general aspects of biomonitoring. The second part gives examples of applied biomonitoring in Germany and Switzerland (changes in species composition, phenologies, vegetation restoration, changes in soil conditions, and heavy metal concentrations). The third part deals with climate-related monitoring studies of arctic-alpine and temperate regions of the Northern Hemisphere (mountain peaks and timberline ecotones of the Alps, spread of exotic evergreen broad-leaved plants, phytomass and carbon balance in Svalbard).
Wildlife Review
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The Greater Plains
This collection of essays represents an attempt to move beyond degradation and exploitation as the defining ecological narratives of the Great Plains by examining the region through the interrelated themes of water, grasses, animals, and energy.
Mires and Man
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