“Advances in Spatial Analysis of Multivariate Ecological Data: Theory and Practice” http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivari... This course is being delivered by Prof. Pierre Legendre who is a leading expert in numerical ecology and author of the book titled ‘Numerical ecology’ This course will run from 3rd – 7th April at Margam Discovery Centre, Wales. The course will describe recent methods (concepts and R tools) that can be used to analyse spatial patterns in community ecology and is highly applicable to people studying distribution and composition of marine mammals and sea birds communities. The umbrella concept of the course is beta diversity, which is the spatial variation of communities. These methods are applicable to all types of communities (bacteria, plants, animals) sampled along transects, regular grids or irregularly distributed sites. The new methods, collectively referred to as spatial eigen-function analysis, are grounded into techniques commonly used by community ecologists, which will be described first: simple ordination (PCA, CA, PCoA), multivariate regression and canonical analysis, permutation tests. The choice of dissimilarities that are appropriate for community composition data will also be discussed. The focal question is to determine how much of the community variation (beta diversity) is due to environmental sorting and to community-based processes, including neutral processes. Recently developed methods to partition beta diversity in different ways will be presented. Extensions will be made to temporal and space-time data. Course content is as follows Day 1 • Introduction to data analysis. • Ordination in reduced space: principal component analysis (PCA), correspondence analysis (CA), principal coordinate analysis (PCoA). • Transformation of species abundance data tables prior to linear analyses. Day 2 • Measures of similarity and distance, especially for community composition data. • Multiple linear regression. R-square, adjusted R-square, AIC, tests of significance. • Polynomial regression. • Partial regression and variation partitioning. Day 3 • Statistical testing by permutation. • Canonical redundancy analysis (RDA) and canonical correspondence analysis (CCA). Multivariate analysis of variance by canonical analysis. • Forward selection of environmental variables in RDA. Day 4 • Origin of spatial structures. • Beta diversity partitioning and LCBD indices • Replacement and richness difference components of beta diversity. Day 5 • Spatial modelling: Multi-scale modelling of the spatial structure of ecological communities: dbMEM, generalized MEM, and AEM methods. • Community surveys through space and time: testing the space-time interaction in repeated surveys. • Additional module depending on time – Is the Mantel test useful for spatial analysis in ecology and genetics? Please email any inquiries to oliverhooker@prstatistics.com or visit our website www.prstatistics.com or to book online http://prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-... Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhooker@prstatistics.com 1. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January 2017) #MBMV http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abund... 2. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB http://www.prstatistics.com/course/advanced-python-biologists-apyb01/ 3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R (February 2017) #SIMM http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm... 4. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/ 5. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April 2017) #MVSP http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivari... 6. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biol... 7. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-a... 8. ECOLOGICAL AND EVOLUTIONARY BIOGEOGRAPHY USING R (May 2017) #EEBR 9. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/ 10. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecologic... 11. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME) 12. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biolog... 13. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-... 14. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (July 2017 TBC) #SEMR 15. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01... 16. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL 17. GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR 18. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017 TBC) #LNDG 19. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (November 2017) #ABME http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epi... 20. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS 21. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB 22. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017) #DVMP http://www.prstatistics.com/course/data-visualisation-and-manipulation-using... 23. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR 24. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-mod... 25. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL -- Oliver Hooker PhD. PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/