PRIMER / PERMANOVA Essentials

PRIMER-e is pleased to announce a hybrid course (offered in person and online) in Multivariate Analysis for Ecology & Other Sciences to be held over one week at the Graduate School of Oceanography, Bay Campus, University of Rhode Island, USA.

This 5-day course will cover the essentials – a suite of core non-parametric methods implemented in PRIMER software, as well as several key semi-parametric methods encapsulated in PERMANOVA+. Sessions will run daily, Monday to Friday, from 8:30 am to 5:30 pm on each day. Online participants will be joining the course live in the USA Eastern Daylight Time (EDT, UTC –4 hrs).

Each day will include a mixture of lectures and computer lab sessions to implement the new methods and techniques learned on example datasets. Participants will have the opportunity to discuss and analyse their own data in consultation with the presenter. Those who register to attend in person are expected to bring their own laptop to the venue. A free fully functional (but time-limited) licence of our latest software, PRIMER 8 with PERMANOVA+, will be made available to registered participants for trial use during the course. At the completion of the course, participants will receive an offer for a special discount on software subscriptions. (Note that PRIMER is a Windows-only product, so Macs need to run in Windows emulation.) This course will cater both to those who are new to multivariate analysis and to those who are familiar with PRIMER methods but would like a refresher regarding the latest techniques and approaches. This course is designed for scientists and research practitioners; it will emphasise the achievement of a conceptual understanding of multivariate methods, with demonstrations of how to implement these methods in the software and interpret results. No prior background in statistics is required.

OUTLINE of TOPICS

The topics covered in this course shall include:

• Properties of multivariate data (summary statistics, shade plots, histograms, draftsman plots, etc.);
• Pre-treatment options (transformations, normalization, standardization, & dispersion weighting);
• Measures of resemblance: distance, similarity and dissimilarity (Euclidean, Bray-Curtis, Jaccard, Sorensen, etc.);
• Cluster analysis (CLUSTER), including tests for significant structure within clusters (SIMPROF) to permit non-arbitrary classifications of samples or variables (species);
• Ordination via projection: principal components analysis (PCA); principal coordinate analysis (PCO);
• Ordination to preserve inter-sample relationships via non-metric, metric or threshold metric multi-dimensional scaling (MDS, mMDS, tmMDS);
• Relating biotic to abiotic data, including tests of association between resemblance matrices (RELATE), and finding optimal subsets of environmental (or other) variables that generate a ‘best’ match to patterns among samples based on species variables (BEST - BIOENV);
• Non-parametric permutation test for differences among a priori groups of samples (analysis of similarities (ANOSIM), and ordination of bootstrap averages;
• Finding important variables (SIMPER and BEST – BVSTEP);
• Diversity measures (DIVERSE); Taxonomic distinctness; Taxonomic resemblance
• Partitioning variation; tests for centroid differences among groups (PERMANOVA), including one-way and two-way cases, tests of interactions, constructing a priori contrasts and pairwise tests. Accounting for heterogeneity of dispersions.
• Tests for homogeneity of multivariate dispersions and comparisons of beta diversity (PERMDISP);
• Complex multi-factor experimental designs, identifying fixed and random factors that are nested or crossed with one another (PERMANOVA);
• Multivariate control charts for detecting unusual observations in space or time (e.g., monitoring).
• Fitting multivariate response data (e.g., species) to continuous predictor variables (e.g., environmental), including model selection (DISTLM) and visualising fitted variation using dissimilarity-based redundancy analysis (dbRDA);
• Graphical tools for effective presentation of results, including matrix displays and a variety of plot types, animations of ordinations captured to video files, centroid plots, bubble plots and multi-variable segmented bubble plots.

VENUE

All sessions will be held live online and in person at Graduate School of Oceanography, Bay Campus, University of Rhode Island, 215 South Ferry Road, Narragansett, USA. Online participants will join the course via Google Meet. For further local information or if you have questions regarding logistics at the venue, please contact the local host: Kristy Lewis (kristy.lewis@uri.edu). For information regarding registration or any other course-related matters, contact the PRIMER-e admin team directly (tel: +64-9-869-2230, email: primer@primer-e.com).

COURSE FEES

The course fee includes all course materials, and - for in-person participants - coffee/tea and snacks during breaks, lunch, free Wi‑Fi, and a temporary licence key to use PRIMER 8 with PERMANOVA+ software (fully functional, for the duration of the course), but not accommodation, other meals, or the separate cost to purchase an annual subscription to the software (offered at discounted prices for workshop participants, see below).

The prices to register (in $USD) are:

All prices are in US dollars ($USD). Note that GST will be applied for New Zealand residents.

DISCOUNTED SOFTWARE PRICES FOR COURSE PARTICIPANTS

We are pleased to offer all course participants (attending online or in person) a special discounted price of 10% off our standard base prices to purchase an annual subscription for PRIMER 8 software. Details regarding this discount offer will be provided to participants at the end of the course.

ABOUT THE PRESENTER

Marti J. Anderson is the Director of PRIMER-e (Quest Research Limited), a Fellow of the Royal Society of New Zealand and Distinguished Professor Emerita in the New Zealand Institute for Advanced Study (NZIAS) at Massey University in Auckland. Her core research is in community ecology, biodiversity, multivariate analysis, experimental design and resampling methods, with a special focus on developing novel statistical methods for ecology. She has developed all of the statistical methods in PERMANOVA+ and especially enjoys engaging in the dynamic interactions with students, academics and professionals that have become a trademark of the PRIMER/PERMANOVA+ international courses, shedding new light on multivariate data.