Analysis of Multivariate Data from Ecology and Environmental Science, using PRIMER v6
Institute of Biology (Room U99), University of Southern Denmark, Odense
16th May – 20th May 2011
Provisional programme
Monday
09:00-09:30 Arrival and Introduction
09:30-11:00 Lecture: Measures of resemblance (similarity/dissimilarity/distance) in multivariate structure for
assemblage & environmental data, including pre-treatment options (standardisation, transformation,
normalisation) and the effects of different coefficient choices
11:00-11:15 Coffee break
11:15-12:30 Lecture: Hierarchical clustering of samples (CLUSTER), including a global test for the presence of
multivariate structure in a priori unstructured biotic or environmental samples, using similarity
profiles (the SIMPROF test)
12:30-13:00 Demo: Introduction to PRIMER v6 routines
13:00-14:00 Lunch break
14:00-15:00 Practical: Similarity options, CLUSTER and SIMPROF
15:00-16:00 Lecture: Ordination (of environmental data) by Principal Components Analysis (PCA)
16:00-16:15 Coffee break
16:15-18:00 Practical: Ordination by PCA, and own data. (Throughout, participants may take the opportunity
during lab sessions to work on their own data as well as - or instead of - the supplied examples.*)
Tuesday
09:00-10:00 Lecture: Ordination (of assemblage data) by non-metric Multi-Dimensional Scaling (MDS)
10:00-11:00 Practical: Ordination by MDS
11:00-11:15 Coffee break
11:15-12:15 Lecture: Multivariate testing for differences between groups of samples (1-way ANOSIM)
12:15-13:00 Practical: 1-way ANOSIM
13:00-14:00 Lunch break
14:00-14:45 Lecture: ANOSIM tests for 2-way designs
14:45-15:30 Practical: 2-way ANOSIM
15:30-16:00 Lecture: Determining variables which discriminate groups of samples (1- and 2-way similarity
percentages, SIMPER)
16:00-16:15 Coffee break
16:15-18:00 Practical: 1- and 2-way SIMPER, and own data
Wednesday
09:00-10:00 Lecture: Linking potential environmental drivers to an observed assemblage pattern, via the matching
of multivariate structures (the BEST procedure)
10:00-11:00 Practical: Draftsman plots, PCA and BEST
11:00-11:15 Coffee break
11:15-11:40 Lecture: Linkage trees – a further technique for ‘explaining’ assemblage patterns by environmental
variables (LINKTREE, a ‘classification and regression tree’ approach)
11:40-12:00 Practical: Linking to environmental variables (LINKTREE)
12:00-13:00 Lecture: Comparison of multivariate patterns 1: Global hypothesis tests of no agreement between two
resemblance matrices (RELATE), comparing assemblage (or environmental) structure with linear or
cyclic models in space and time
13:00-14:00 Lunch break
14:00-15:15 Practical: RELATE and model matrices
15:15-15:30 Lecture: Comparison of multivariate patterns 2: Test of no evidence for a biota-environment link,
allowing for the selection effects in finding an optimum match (the global BEST test)
15:30-16:00 Lecture: Comparison of multivariate patterns 3: Testing in a 2-way layout (ANOSIM) with no
replication
16:00-16:15 Coffee break
16:15-18:00 Practical: Global BEST test and 2-way ANOSIM with no replication, and own data
Thursday
09:00-10:00 Lecture: Diversity measures (DIVERSE) and comments on sampling properties and multivariate
treatment of multiple indices. Dominance plots and tests for differences between sets of curves
(DOMDIS), particle-size distributions etc
10:00-11:00 Practical: DIVERSE, dominance plots and testing sets of curves (DOMDIS)
11:00-11:15 Coffee break
11:15-12:30 Lecture: Taxonomic (or phylogenetic) diversity and distinctness for quantitative data, or simple
species lists, as valid biodiversity measures (DIVERSE) over broad spatial and temporal scales;
sampling properties and testing structures (TAXDTEST)
12:30-13:00 Practical: DIVERSE and TAXDTEST
13:00-14:00 Lunch break
14:00-14:45 Lecture: Comparison of multivariate patterns 4: Stepwise form of the BEST routine, e.g. for finding
species subsets determining overall assemblage pattern
14:45-16:00 Practical: BEST for species selection
16:00-16:15 Coffee break
16:15-17:15 Demo of PERMANOVA+ add-on to PRIMER
17:15-18:00 Practical: Own data
Friday
09:00-10:00 Lecture: Comparison of multivariate patterns 5: Second-stage analysis (2STAGE) to compare
taxonomic levels and transformation or coefficient choices; also for a possible testing framework in
some repeated measures designs
10:00-11:00 Practical: 2STAGE
11:00-11:15 Coffee break
11:15-12:15 Lecture: Further options in PRIMER v6 (EM algorithm for estimating missing environmental data;
direct SIMPROF tests; modifying Bray-Curtis for denuded samples; dispersion weighting to
downweight counts from clumped species; dissimilarity measures based on taxonomic distinctness)
12:15-13:00 Practical: Further tests & resemblance measures (SIMPROF, Dispersion weighting, Zero-adjusted
Bray-Curtis, 2STAGE for similarities)
13:00-14:00 Lunch break
14:00-17:30 Practical: Main all-afternoon lab session on analysing own data using PRIMER v6
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* Participants are encouraged to bring some of their own multivariate data. These should be in numeric, rectangular arrays, with
variables (e.g. species) as rows, samples as columns, or vice-versa, in an Excel spreadsheet or text file. Non-numeric sets of
information (factors) on each sample are placed below (or to the side of) this table, separated by a blank row (or blank column).
There is also a 3-column format (sample label, variable label, non-zero entry) suitable for very large arrays.