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Author Gardener, Mark., author
Title Community ecology : analytical methods using R and Excel / Mark Gardener
Imprint Exeter [United Kingdom] : Pelagic Publishing, [2014]
©2014
book jacket
Descript 1 online resource (x, 556 pages) : illustrations (some color)
text rdacontent
computer rdamedia
online resource rdacarrier
Series Data in the wild series
Data in the wild series
Note Includes bibliographical references (pages 542-546) and index
Starting to look at communities -- Software tools for community ecology -- Recording your data -- Beginning data exploration: using software tools -- Exploring data: choosing your analytical method -- Exploring data: getting insights -- Diversity: species richness -- Diversity: indices -- Diversity: comparing -- Diversity: sampling scale -- Rank abundance or dominance models -- Similarity and cluster analysis -- Association analysis: identifying communities -- Ordination
About the author; Acknowledgements; Software used; Support material; Reader feedback; Publish with Pelagic Publishing; Contents; Introduction; What you will learn in this book; How this book is arranged; Support files; 1. Starting to look at communities; 1.1 A scientific approach; 1.2 The topics of community ecology; 1.3 Getting data -- using a spreadsheet; 1.4 Aims and hypotheses; 1.5 Summary; 2. Software tools for community ecology; 2.1 Excel; 2.2 Other spreadsheets; 2.3 The R program; 2.4 Summary; 2.5 Exercises; 3. Recording your data; 3.1 Biological data; 3.2 Arranging your data; 3.3 Summary
3.4 Exercises4. Beginning data exploration:using software tools; 4.1 Beginning to use R; 4.2 Manipulating data in a spreadsheet; 4.3 Getting data from Excel into R; 4.4 Summary; 4.5 Exercises; 5. Exploring data: choosing your analytical method; 5.1 Categories of study; 5.2 How 'classic' hypothesis testing can be used in community studies; 5.3 Analytical methods for community studies; 5.4 Summary; 5.5 Exercises; 6. Exploring data: getting insights; 6.1 Error checking; 6.2 Adding extra information; 6.3 Getting an overview of your data; 6.4 Summary; 6.5 Exercises; 7. Diversity: species richness
7.1 Comparing species richness 7.2 Correlating species richness over time or against an environmental variable; 7.3 Species richness and sampling effort; 7.4 Summary; 7.5 Exercises; 8. Diversity: indices; 8.1 Simpson's index; 8.2 Shannon index; 8.3 Other diversity indices; 8.4 Summary; 8.5 Exercises; 9. Diversity: comparing; 9.1 Graphical comparison of diversity profiles; 9.2 A test for differences in diversity based on the t-test; 9.3 Graphical summary of the t-test for Shannon and Simpson indices; 9.4 Bootstrap comparisons for unreplicated samples; 9.5 Comparisons using replicated samples
9.6 Summary 9.7 Exercises; 10. Diversity: sampling scale; 10.1 Calculating beta diversity; 10.2 Additive diversity partitioning; 10.3 Hierarchical partitioning; 10.4 Group dispersion; 10.5 Permutation methods; 10.6 Overlap and similarity; 10.7 Beta diversity using alternative dissimilarity measures; 10.8 Beta diversity compared to other variables; 10.9 Summary; 10.10 Exercises; 11. Rank abundance or dominance models; 11.1 Dominance models; 11.2 Fisher's log-series; 11.3 Preston's log normal model; 11.4 Summary; 11.5 Exercises; 12. Similarity and cluster analysis
12.1 Similarity and dissimilarity 12.2 Cluster analysis; 12.3 Summary; 12.4 Exercises; 13. Association analysis: identifying communities; 13.1 Area approach to identifying communities; 13.2 Transect approach to identifying communities; 13.3 Using alternative dissimilarity measures for identifying communities; 13.4 Indicator species; 13.5 Summary; 13.6 Exercises; 14. Ordination; 14.1 Methods of ordination; 14.2 Indirect gradient analysis; 14.3 Direct gradient analysis; 14.4 Using ordination results; 14.5 Summary; 14.6 Exercises; Appendices; Appendix 1: Answers to exercises
Appendix 2 Custom R commands in this book
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Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force. UkOxU
Online resource; title from e-book title screen (EBL platform, viewed May 25, 2016)
Academic
Subject Microsoft Excel (Computer file)
Microsoft Excel (Computer file) fast (OCoLC)fst01366659
NATURE / Ecology bisacsh
Biotic communities -- Research -- Methodology
Electronic spreadsheets -- Computer programs
R (Computer program language) -- Statistical methods
MATHEMATICS -- Applied. bisacsh
MATHEMATICS -- Probability & Statistics -- General. bisacsh
Biotic communities -- Research -- Methodology. fast (OCoLC)fst00832846
Electronic spreadsheets -- Computer programs. fast (OCoLC)fst00907465
MATHEMATICS / Probability & Statistics / General bisacsh
Probability & statistics bicssc
Excel bicssc
Probability & statistics
Electronic books
Ecological science, the Biosphere
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