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Multivariate Analysis for Ecologists: Step-by-Step

Order Online or Fax/Mail Order Form

Multivariate Analysis for Ecologists: Step-by-Step is a book by
Dr. JeriLynn E Peck that answers your questions:

What are multivariate data?

How should I prepare my data?

Which analysis tools should I use?

What do they do?

Do they have weaknesses?

How do I interpret the output?

This richly illustrated second edition, published by MjM Software Design 2016, will help you answer those questions by providing a step-by-step process for approaching your multivariate community data analysis project. Simple explanations and diagrams explain the tools, recipes walk you though the process using the PC-ORD software, and guidance is given on everything from ensuring sampling independence to when to rotate an ordination. Each technique has sections on:

what it's good for
what it actually does
what it means
what you need in order to run it
what you get in the output
what you should know about its strengths and weaknesses
how to run it in PC-ORD v.7
when you should use it

Contents
Preface		i
Why Multivariate?		1
The 10-Step Process		5
Step 1. Getting yourself ready		8
1. Embracing statistics		8
2. Articulating goals		16
Analysis objectives		17
Step 2. Getting your data ready		19
3. Meeting matrices		19
4. Starting in *PC-ORD*		22
5. Inputting and screening your data		27
Entering your data		27
Importing your data		27
From a spreadsheet		27
From a database		31
Screening your data		32
Screening with Summary		32
Screening with Species Lists		33
Step 3. Structuring your data		34
6. Sampling sufficiently		34
Is N enough?		34
Species Area Curves (SPA)		34
7. Structuring your matrices		36
Restructuring with Modify Data		36
Step 4. Exploring and preparing your data		39
8. What have you actually measured?		39
Sparsity (zeros)		40
Checking sparsity with Summary		41
Checking sparsity with Profile		41
Reducing sparsity with Delete Columns		41
Non-zero values		41
Response comparability		43
Standardizing with General Relativization		44
Standardizing with Relativization by Maximum		45
9. How variable are your data?		46
Heterogeneity		46
Checking sparsity with SUMMARY		46
Checking sparsity with PROFILE		48
Reducing sparsity with Functional Diversity		48
Outliers		51
Checking for outliers with Summary		51
Checking for outliers with Outlier Analysis		51
Checking for outliers with Profile		51
Checking for outliers with Boxplots		52
Response distributions		52
Checking for normality with Distributions		52
Checking for normality with Boxplots		53
Step 5. Selecting the tools		54
10. Distance measures		54
Euclidean Distance		55
Chi-square Distance		57
City-block Distance (e.g., S�rensen)		58
11. Model form		60
Hypothesizing relationships		60
Exploring relationships with Scatterplot		60
12. Analysis tools		62
13. What is ordination?		64
Step 6. Modifying your data		68
14. Meeting parametric assumptions		68
Transforming to a Power		68
Transforming to the Logarithmic		69
Transforming to Arcsinesquareroot		69
To Multiply or add a constant		69
15. Reweighting responses		70
Checking influence with Dominance Curves		70
Adjusting influence with Relativizations		70
Step 7a: Guiding pattern (guided ordination)		73
16. WA: Weighted averaging		73
How to run it		75
17. Polar (Bray-Curtis) ordination		77
How to run it		79
18. CCA: Canonical correspondence analysis		81
How to run it		88
19. RDA: Redundancy analysis		91
How to run it		95
20. FSO: Fuzzy set ordination		97
How to run it		100
21. Interpreting guided ordinations		102
Step 7b: Seeking pattern (free ordination)		104
22. PCA: Principal components analysis		104
How to run it		109
23. NMS: Nonmetric multidimensional scaling		112
How to run it		117
Choosing dimensionality using the stress test		118
Verifying the final solution		119
NMS Scores		121
24. Interpreting free ordinations		124
Step 7c: Looking for groups (classification)		126
25. Cluster analysis		126
How to run it		130
Two-way cluster		131
26. TWINSPAN		135
How to run it		136
Step 7d: Testing among groups		137
27. MRPP: Multi-response permutation procedure		137
28. PerMANOVA: Distance-based MANOVA		141
How to run it		144
29. SumF		147
How to run it		148
30. ISA: Indicator species analysis		150
How to run it		153
Blocked indicator species analysis		153
Step 7e: Assessing associations		154
31. Mantel test		154
How to run it		156
Partial Mantel test		156
32. FCA: Fourth corner analysis		157
How to run it		160
Step 8: Confirming your results		161
Step 9: Using interpretive tools		163
33. Finding your story		163
Interpreting ordination diagrams		163
Simple scatterplot		164
Overlay Main Matrix		165
Overlay Second Matrix		167
Joint plots		168
Convex hulls and centroids		169
% of variance		170
Successional vectors		170
Ordered Main Matrix		173
Step 10: Presenting your story		175
34. Communicating your message		175
Presenting Summaries		175
Presenting Graphics		175
Rotating and reflecting ordinations		177
Drawing outlines on ordered tables		179
*Appendix A: Other PC-ORD* Tools**		180
Appendix B: Matrix Algebra Unplugged		181
Appendix C: How to Report		183
Appendix D: Further Reading		186
Appendix E: Available Supplements		187
Appendix F: Acronyms & Symbols		188
Index		189

Contents