This five day workshop will explore statistical analysis of assemblage and multi-variable environmental data that arise in a diverse spectrum of environmental and biological science research, such as environmental impact assessments, basic studies of community ecology, monitoring of biodiversity and analysis of water quality indices.
The focus of the workshop is learning how to use an advanced software tool, the PERMANOVA+ add-on package for PRIMER v6. The PRIMER (Plymouth Routines In Multivariate Ecological Research) package is a worldwide standard software tool used for analysis of aquatic assemblages and, increasingly, terrestrial, paleontological, microbial, and genetic data, and for model output in eco-toxicology, epidemiology, and sociology.
The PERMANOVA+ add-on package enhances the capability of PRIMER to allow the analysis of multivariate data in response to more complex experimental designs and sampling structures, using semi-parametric partitioning on the basis of a resemblance measure of choice and with rigorous inferences obtained using permutation methods. PERMANOVA+ allows the development of more formal models, tests, and predictions (and associated relevant graphics) for multivariate (or univariate) ecological (and other) systems that are over-parameterised (i.e., have too many variables) or that demonstrate substantial non-normality.
Who should attend
This is an advanced workshop, but is not intended primarily for statisticians: the course is for practicing ecologists, biologists, microbiologists, geneticists, and environmental scientists. Participants should already have a working knowledge of basic multivariate techniques commonly used in ecology, such as cluster analysis and PCA or MDS ordination. Those experienced in standard analysis of variance models in univariate statistics will also find many parallels in this multivariate course. It is ideally suited to those who have some experience of the base PRIMER package and are seeking to extend their work to handle higher-way designs and regression models, but there are no formal pre-requisites – simply the motivation to learn an up-to-date tool in handling complex multivariate data.
Lab sessions will use real literature case studies analyzed with PRIMER v6 and PERMANOVA+, but participants are encouraged to bring their own data, as there will be entire day at the end of the week to seek help from the lecturer in tackling specific data problems using these tools. The emphasis throughout the course is on practical application and interpretation.
For more information visit: http://www.rwaa.us/PERMANOVA.htm
