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During the International Botanical Congress in Edinburgh, 1964, Mrs. I. M. WEISBACH-JUNK of The Hague discussed a plan for preparation by her publishing company (Dr. W. Junk B.V.) of an international Handbook of Vegetation Science. She proposed a series that should give a comprehensive survey of the varied directions within this science, and their achievements to date as well as their objectives for the future. The challenge of such an enterprise, and its evident value for the further development of vegetation research, induced the undersigned after some consideration to accept the offer of the honorable but also burdensome task of General Editor. The decision was encouraged by a well formulated and detailed outline for the Handbook worked out by the Dutch phytosociolo gists J. J. BARKMAN and V. WESTHOFF. A circle of scholars from numerous countries was invited by the Dr. Junk Publishing Com pany to The Hague in January 1966 to draw up a list of editors and contributors for the parts of the Handbook. The outline and list have served since for the organization of the Handbook, with no need for major change. The different burdens of editors and authors have compelled quite different timings for completion of the individual sections.
A detailed introduction to the methods used by ecologists--classification and ordination--to clarify and interpret large, unwieldy masses of multivariate field data. Permits ecologists to understand, not just mechanically use, pre-packaged programs for multivariate analysis. Demonstrates these techniques using artificial data simple enough for every analytical step to be understood.
Eddy V AN DER MAAREL This volume is the first of two volumes covering the Sym computer programmes for the rapid clustering and ordina posium 'Advances in vegetation science', which was held at tion of very large sets of reI eves and for (subsequent) table Nijmegen, The Netherlands, from 15-19 May 1979. This rearrangement (this volume as well as the book Data symposium was organized on behalf of the Working Group Processing in Phytosociology contain various new pro for Data-Processing of the International Society for Vege grams). What we do not have is a manual in which the tation Science. After this group held its final meeting two apparently successful methods are compared and applied years earlier it decided to continue its activities, but within a to some data-sets. H. Lieth, editor-in-chief of a new Junk wider scope. Most members of the Group felt that the series 'Tasks for vegetation science' already suggested to original aim, i. e. the introduction of data-processing and produce such a manual in this series. multivariate methods for use in the systematic description The present volume contains the texts of the lectures and of plant communities, was more or less fulfilled. The book most of the poster demonstrations of the first three sessions Data -Processing in Phytosociology, largely based on papers of the Symposium, dealing with classification and ordina in Vegetatio, edited by E. van der Maarel, L. Orloci & S.
A large part of ecological research depends on use of two ap proaches to synthesizing information about natural communities: classification of communities (or samples representing these) into groups, and ordination (or arrangement) of samples in relation to environmental variables. A book published in 1973, 'Ordination and Classification of Communities,' sought to provide, through contributions by an international panel of authors, a coherent treatise on these methods. The book appeared then as Volume 5 of the Handbook of Vegetation Science, for which R. TuxEN is general editor. The desire to make this work more widely available in a less expensive form is one of the reasons for this second edition separating the articles on ordinction and on classification into two volumes. The other reason is the rapid advancement of understanding in the area of indirect ordination-mathematical techniques that seek to use measurements of samples from natural communities to produce arrangements that reveal environmental relationships of these communities. Such is the rate of change in this area that the last chapter on ordination in the first edition is already, 4 or 5 years after it was written, out of date; and new techniques of indirect ordination that could only be mentioned as possibilities in the first edition are becoming prominent in the field. In preparing the second edition the chapter on evaluation of ordinations has been rewritten, a new chapter on recent developments in continuous multivariate techniques has been included, and references to recent work have been added to other chapters.
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Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
A full description of computer-based methods of analysis used to define and solve ecological problems. Multivariate techniques permit summary of complex sets of data and allow investigation of many problems which cannot be tackled experimentally because of practical restraints.
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/.
One of the most important contributions in the field of plant ecology during the twentieth century, this definitive survey established the geographical limits, species compositions, and as much as possible of the environmental relations of the communities composing the vegetation of Wisconsin.
This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis. This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/).