[MARMAM] Advances in Spatial Analysis of Multivariate Ecological Data - Pierre Legendre - STATS COURSE
oliverhooker at prstatistics.com
Tue Jan 10 05:07:32 PST 2017
“Advances in Spatial Analysis of Multivariate Ecological Data: Theory
This course is being delivered by Prof. Pierre Legendre who is a leading
expert in numerical ecology and author of the book titled ‘Numerical
This course will run from 3rd – 7th April at Margam Discovery Centre,
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
• 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
• Measures of similarity and distance, especially for community
• Multiple linear regression. R-square, adjusted R-square, AIC, tests
• Polynomial regression.
• Partial regression and variation partitioning.
• 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.
• Origin of spatial structures.
• Beta diversity partitioning and LCBD indices
• Replacement and richness difference components of beta diversity.
• 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 at prstatistics.com
or visit our website www.prstatistics.com
or to book online
Please feel free to distribute this material anywhere you feel is
Upcoming courses - email for details oliverhooker at prstatistics.com
1. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January
2. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017) #SIMM
4. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
5. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
6. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB
7. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
8. ECOLOGICAL AND EVOLUTIONARY BIOGEOGRAPHY USING R (May 2017) #EEBR
9. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
10. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
11. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)
12. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
13. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
14. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY
BIOLOGISTS (July 2017 TBC) #SEMR
15. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
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
19. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017) #ABME
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)
23. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR
24. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM
25. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL
Oliver Hooker PhD.
128 Brunswick Street
+44 (0) 7966500340
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