Data Analysis in Vegetation Ecology
(Sprache: Englisch)
The first edition of Data Analysis in Vegetation Ecology provided an accessible and thorough resource for evaluating plant ecology data, based on the author's extensive experience of research and analysis in this field. Now, the Second Edition expands on...
Leider schon ausverkauft
versandkostenfrei
Buch
49.99 €
24 DeutschlandCard Punkte
sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
Produktdetails
Produktinformationen zu „Data Analysis in Vegetation Ecology “
Klappentext zu „Data Analysis in Vegetation Ecology “
The first edition of Data Analysis in Vegetation Ecology provided an accessible and thorough resource for evaluating plant ecology data, based on the author's extensive experience of research and analysis in this field. Now, the Second Edition expands on this by not only describing how to analyse data, but also enabling readers to follow the step-by-step case studies themselves using the freely available statistical package R.The addition of R in this new edition has allowed coverage of additional methods for classification and ordination, and also logistic regression, GLMs, GAMs, regression trees as well as multinomial regression to simulate vegetation types. A package of statistical functions, specifically written for the book, covers topics not found elsewhere, such as analysis and plot routines for handling synoptic tables. All data sets presented in the book are now also part of the R package 'dave', which is freely available online at the R Archive webpage.
The book and data analysis tools combined provide a complete and comprehensive guide to carrying out data analysis students, researchers and practitioners in vegetation science and plant ecology.
Summary:
A completely revised and updated edition of this popular introduction to data analysis in vegetation ecology
Now includes practical examples using the freely available statistical package 'R'
Written by a world renowned expert in the field
Complex concepts and operations are explained using clear illustrations and case studies relating to real world phenomena
Highlights both the potential and limitations of the methods used, and the final interpretations
Gives suggestions on the use of the most widely used statistical software in vegetation ecology and how to start analysing data
Praise for the first edition: "This book will be a valuable addition to the shelves of early postgraduate candidates and postdoctoral researchers. Through the excellent background material and use of real world
... mehr
examples, Wildi has taken the fear out of trying to understand these much needed data analysis techniques in vegetation ecology." Austral Ecology
... weniger
Inhaltsverzeichnis zu „Data Analysis in Vegetation Ecology “
Preface to the second edition xiPreface to the first edition xvList of figures xixList of tables xxvAbout the companion website xxvii1 Introduction 12 Patterns in vegetation ecology 52.1 Pattern recognition 52.2 Interpretation of patterns 92.3 Sampling for pattern recognition 122.3.1 Getting a sample 122.3.2 Organizing the data 142.4 Pattern recognition in R 173 Transformation 233.1 Data types 233.2 Scalar transformation and the species enigma 263.3 Vector transformation 303.4 Example: Transformation of plant cover data 334 Multivariate comparison 374.1 Resemblance in multivariate space 374.2 Geometric approach 384.3 Contingency measures 434.4 Product moments 454.5 The resemblance matrix 484.6 Assessing the quality of classifications 505 Classification 535.1 Group structures 535.2 Linkage clustering 565.3 Average linkage clustering 595.4 Minimum-variance clustering 615.5 Forming groups 635.6 Silhouette plot and fuzzy representation 666 Ordination 716.1 Why ordination? 716.2 Principal component analysis 756.3 Principal coordinates analysis 826.4 Correspondence analysis 866.5 Heuristic ordination 896.5.1 The horseshoe or arch effect 896.5.2 Flexible shortest path adjustment 916.5.3 Nonmetric multidimensional scaling 936.5.4 Detrended correspondence analysis 956.6 How to interpret ordinations 966.7 Ranking by orthogonal components 1006.7.1 RANK method 1006.7.2 A sampling design based on RANK (example) 1047 Ecological patterns 1097.1 Pattern and ecological response 1097.2 Evaluating groups 1117.2.1 Variance testing 1117.2.2 Variance ranking 1157.2.3 Ranking by indicator values 1177.2.4 Contingency tables 1207.3 Correlating spaces 1247.3.1 The Mantel test 1247.3.2 Correlograms 1277.3.3 More trends: 'Schlaenggli' data revisited 1307.4 Multivariate linear models 1347.4.1 Constrained ordination 1347.4.2 Nonparametric multiple analysis of variance 1417.5 Synoptic vegetation tables 1467.5.1 The aim of ordering tables 1467.5.2 Steps involved in sorting tables 1477.5.3 Example:
... mehr
ordering Ellenberg's data 1518 Static predictive modelling 1558.1 Predictive or explanatory? 1558.2 Evaluating environmental predictors 1568.3 Generalized linear models 1598.4 Generalized additive models 1648.5 Classification and regression trees 1668.6 Building scenarios 1698.7 Modelling vegetation types 1718.8 Expected wetland vegetation (example) 1769 Vegetation change in time 1859.1 Coping with time 1859.2 Temporal autocorrelation 1869.3 Rate of change and trend 1889.4 Markov models 1929.5 Space-for-time substitution 1999.5.1 Principle and method 1999.5.2 The Swiss National Park succession (example) 2039.6 Dynamics in pollen diagrams (example) 20710 Dynamic modelling 21310.1 Simulating time processes 21410.2 Simulating space processes 22210.3 Processes in the Swiss National Park 22310.3.1 The temporal model 22310.3.2 The spatial model 22811 Large data sets: wetland patterns 23311.1 Large data sets differ 23311.2 Phytosociology revisited 23511.3 Suppressing outliers 23911.4 Replacing species with new attributes 24111.5 Large synoptic tables? 24512 Swiss forests: a case study 25512.1 Aim of the study 25512.2 Structure of the data set 25612.3 Selected questions 25812.3.1 Is the similarity pattern discrete or continuous? 25812.3.2 Is there a scale effect from plot size? 26212.3.3 Does the vegetation pattern reflect environmental conditions? 26612.3.4 Is tree species distribution man-made? 27012.3.5 Is the tree species pattern expected to change? 27612.4 Conclusions 278Bibliography 281Appendix A Functions in package dave 293Appendix B Data sets used 295Index 297
... weniger
Autoren-Porträt von Otto Wildi
Otto Wildi is from the WSL Swiss Federal Institute for Forest, Snow and Landscape Research, Birmensdorf, Switzerland.
Bibliographische Angaben
- Autor: Otto Wildi
- 2013, 2. Aufl., 330 Seiten, mit Abbildungen, Maße: 14,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Wiley & Sons
- ISBN-10: 1118384032
- ISBN-13: 9781118384039
- Erscheinungsdatum: 10.05.2013
Sprache:
Englisch
Rezension zu „Data Analysis in Vegetation Ecology “
"This primer would make an ideal course text for postgraduate or upper‐level undergraduate students, and introduces all the key concepts and research questions currently driving the field." ("F""rontiers of biogeography", 5 February 2013)
Kommentar zu "Data Analysis in Vegetation Ecology"
0 Gebrauchte Artikel zu „Data Analysis in Vegetation Ecology“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Data Analysis in Vegetation Ecology".
Kommentar verfassen