Geometric Morphometrics Using R (GMMR01)External

Activity Overview

Type: Capacity building and training
, Type: Course
Start Date: June 5, 2017
End Date: June 9, 2017
Venue: Millport, Scotland
Website: Official website
E-mail: oliverhooker [at]

The field of geometric morphometrics (GM) is concerned with the quantification and analysis of patterns of shape variation, and its covariation with other variables. Over the past several decades these approaches have become a mainstay in the field of ecology, evolutionary biology, and anthropology, and a panoply of analytical tools for addressing specific biological hypotheses concerning shape have been developed. The goal of this is to provide participants with a working knowledge of the theory of geometric morphometrics, as well as practical training in the application of these methods.

This course contains both theoretical and practical sessions. These sessions focus on the generation of shape variables from primary landmark data, the statistical treatment of shape variation with respect to biological hypotheses, and the visualization of patterns of shape variation and of the shapes themselves for interpretation of statistical findings, using the R language for statistical programming. While practice datasets will be available, it is strongly recommended that participants come with their own datasets.
The course programme is as follows:

Sunday 5th Meet at Millport field centre at approximately 18:30.

Monday 6th – Classes from 09:00 to 18:001:
1: Morphometrics: History, Introduction and Data Types
2: Review of matrix algebra and multivariate statistics
3: Superimposition
4: Software demonstration and lab practicum

Tuesday 7th – Classes from 09:00 to 18:00
1: Shape spaces, shape variables, PCA
2: GPA with semi-landmarks
3: Shape covariation
4: Software demonstration and lab practicum

Wednesday 8th – Classes from 09:00 to 18:00
1: Phylogenetic shape variation
2: Group Differences & Trajectory Analysis
3: Allometry
4: Software demonstration and lab practicum

Thursday 9th – Classes from 09:00 to 18:00
1: Assymetry
2: Missing Data
3: Integration and Modularity
4: Disparity
5: Software demonstration and lab practicum

Friday 10th – Classes from 09:00 to 16:00
1: Future Directions
2: Lab Pacticum
3: Student Presentations