EURO-BASIN Training Workshop on
Introduction to statistical modelling tools,
for habitat models development
AZTI-Tecnalia, Pasaia, 26-28 October 2011
Admission and selection process: Priority to WP3, WP5 and WP7 (open to all basin
participants and North America participants). Maximum 15 participants. No fees but
expenses covered by participants.
Lecturers: B. Planque, J. Fernandes, I. Galparsoro, G. Chust, L. Ibaibarriaga
Data: Assistants can bring their own data for practice.
Software: It would be advisable that workshop participants have the following software
installed before the workshop:
R (http://cran.r-project.org/bin/windows/base/ )
WEKA (http://www.cs.waikato.ac.nz/ml/weka/ )
BIOMAPPER (http://www2.unil.ch/biomapper/products.html)
QUANTUM GIS (http://www.qgis.org/)
Check-in: AZTI Reception at 9am on 26th Oct. See Google Map
Agenda:
Day one (Wednesday, 26 October):
09:00-09:30 Welcome
09:30-10:00 Data Management and Integration within EURO-BASIN (J. Felden)
10:00-11:00 Overview of statistical methods for habitat modelling (L. Ibaibarriaga)
Coffee break
11:30-13:00 A brief introduction to GIS tools (I. Galparsoro)
Lunch
14:30-15:00 Short introduction to R (L. Ibaibarriaga)
15:00-17:00 Modelling the spatial distribution of fish: some key concepts and an
application. Part 1 (B. Planque)
Day two (Thursday, 27 October):
09:00-11:00 Modelling the spatial distribution of fish: some key concepts and an
application. Part 2 (B. Planque)
Coffee break
11:30-13:00 Model Validation, performance measures, models comparison and Weka
(open source software for data mining). Part 1 (J. Fernandes)
Lunch
14:30-17:00 Model Validation, performance measures, models comparison and Weka
(open source software for data mining). Part 2 (J. Fernandes)
Day three (Friday, 28 October):
09:00-11:00 An example of a self contained package, BIOMAPPER (I. Galparsoro)
Coffee break
11:30-13:00 Habitat modelling at community level (G. Chust):
Lunch
14:30-06:00 Community Ecology with R (G. Chust)
16:00-17:00 Open session: questions and working with own data