JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for BES-MIRE Archives


BES-MIRE Archives

BES-MIRE Archives


BES-MIRE@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

BES-MIRE Home

BES-MIRE Home

BES-MIRE  December 2016

BES-MIRE December 2016

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

'Advances in Spatial Analysis of Multivariate Ecological Data' - Pierre Legendre

From:

Oliver Hooker <[log in to unmask]>

Reply-To:

Oliver Hooker <[log in to unmask]>

Date:

Wed, 14 Dec 2016 16:04:51 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (111 lines)

“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. 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 [log in to unmask]
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 [log in to unmask]

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 MULTIVAIRAITE 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.	INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (May 2017) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

9.	GEOMETRIC MORPHOMETRICS USING R (June) #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.	BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/

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

13.	ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

14.	APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017)
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

15.	GENETIC DATA ANALYSIS USING R (October TBC) #GDAR
16.     INTRODUCTION TO BIOINFORMATICS USING LINUX (October TBC) #IBUL
17.	LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November TBC)#LNDG
18.	PHYLOGENETIC DATA ANALYSIS USING R (November TBC) #PHYL
19.	INTRODUCTION TO METHODS FOR REMOTE SENSING (December 2017 TBC) #IRMS
20.	ADVANCING IN STATISTICAL MODELLING USING R (December 2017 TBC) #ADVR
21.     INTRODUCTION TO PYTHON FOR BIOLOGISTS (December 2017 TBC) #IPYB
22.     DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017TBC) #DVMP

23.     ANIMAL MOVEMENT ECOLOGY USING R (TBC) #ANME
24.     INTRODUCTION TO MIXED MODELS USING R (TBC) #IMMR
25.     STRUCTURAL EQUATION MODELLING USING R (TBC) #SEMR
26.     TIMESERIES MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS (TBC) TSME#

email [log in to unmask] for details
visit www.prstatistics.com 
TWITTER @PRstatistics 
TWITTER @DrOliverHooker
Facebook www.facebook.com/prstatistics/

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

April 2024
March 2024
February 2024
December 2023
November 2023
August 2023
July 2023
June 2023
May 2023
March 2023
February 2023
January 2023
December 2022
October 2022
September 2022
August 2022
April 2022
March 2022
February 2022
November 2021
July 2021
April 2021
September 2020
June 2020
May 2020
February 2020
September 2019
July 2019
October 2018
September 2018
August 2018
June 2018
May 2018
April 2018
February 2018
January 2018
November 2017
August 2017
June 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
March 2016
February 2016
January 2016
October 2015
September 2015
April 2015
March 2015
February 2015
January 2015
December 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
March 2014
February 2014
January 2014
May 2013
February 2013
November 2012
October 2012
June 2012
May 2012
March 2012
January 2012
September 2011
May 2011
February 2011
December 2010
September 2010
August 2010
July 2010
June 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
August 2009
July 2009
May 2009
April 2009
March 2009
February 2009
January 2009
October 2008
September 2008
August 2008
June 2008
April 2008
March 2008
February 2008
January 2008
November 2007
October 2007
September 2007
August 2007
July 2007
May 2007
April 2007
February 2007
January 2007
November 2006
September 2006
June 2006
May 2006
April 2006
March 2006
January 2006
November 2005
October 2005
September 2005
May 2005
March 2005
December 2004
October 2004
September 2004
August 2004
July 2004
May 2004
April 2004
February 2004
January 2004
December 2003
November 2003
October 2003
September 2003
July 2003
June 2003
May 2003
April 2003
March 2003
February 2003
January 2003
December 2002
October 2002
September 2002
August 2002
May 2002
April 2002
March 2002
February 2002
January 2002
November 2001
October 2001
September 2001
August 2001
July 2001
May 2001
April 2001
March 2001
February 2001
January 2001
December 2000
November 2000
October 2000
September 2000
August 2000
July 2000
June 2000
May 2000
April 2000
March 2000
February 2000
January 2000
December 1999
November 1999
September 1999
August 1999
July 1999
June 1999
May 1999
April 1999
March 1999
February 1999


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

For help and support help@jisc.ac.uk

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager