[MARMAM] Advances in Spatial Analysis of Multivariate Ecological Data - Pierre Legendre - STATS COURSE

Tue Jan 10 05:07:32 PST 2017

“Advances in Spatial Analysis of Multivariate Ecological Data: Theory 
and Practice”

http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/

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 at prstatistics.com

or visit our website www.prstatistics.com

or to book online 
http://prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice/

Please feel free to distribute this material anywhere you feel is 
suitable

Upcoming courses - email for details oliverhooker at 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-abundance-data-using-r-mbmv01/

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-simm03/

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-multivariate-ecological-data-theory-and-practice-mvsp02/

6.	INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/

7.	ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/

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-ecological-data-using-r-mase01/

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-biologists-bigb02/

13.	SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

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-epidemiologists-abme03/

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-python-dvmp01/

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-modelling-using-r-ibhm02/

25.	PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL

-- 
Oliver Hooker PhD.
PR statistics

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128 Brunswick Street
Glasgow
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www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/