Functional Trait Space Analyses in R


23-25 September 2024

To foster international participation, this course will be held online


Course overview

In trait-based ecology, functional trait spaces are key tools to explore the diversity of organismal form and function across the tree of life. Such tools are particularly useful to summarize the main specialization axes that underpin species adaptations to the environment. During the last ten years, functional trait space analyses have become increasingly common, resulting in a wide landscape of R resources to deal with such analyses. This course provides a theoretical and practical overview of such a landscape by combining theoretical and hands-on sessions in R.

Target Audience and assumed background

The course is aimed at PhD students and postdocs with an interest in functional traits, functional diversity and multivariate analyses linking traits to other ecological dimensions. Previous basic experience with R is strongly recommended and will ease the progress of the practicals . Slides and scripts will be shared integrally and explained in detail.

Learning outcomes

By the end of this course, participants will be able to:

•    Have an overview of the theory and methods behind trait space analyses
•    Build and interpret functional trait spaces
•    Link trait spaces to other ecological dimensions
•    Plot and export the results of these analyses


Session content

Daily schedule:
14:00 - 18:00 (Berlin time): live lectures and introduction to / review of the practicals


Monday – Theory/Practice from 14:00 to 18:00

A journey towards functional trait spaces
The need for functional trait spaces
Exploring the main trait data sources available online
Trait spectra and trait spaces:
Standardized Major Axis Regression (SMA)
Principles and comparison with other linear models
Application in R with the smatr R package
Principal Component Analysis (PCA)
Doing PCA ‘by hand’
Application in R
Q&A session

Tuesday – Theory/Practice from 14:00 to 18:00

- Kernel density-based methods
- Univariate and multivariate kernel density estimates
- Kernel density-based dissimilarity
- Kernel density across levels of biological organization
- Kernel density-based functional diversity indices
- The TPD R package
- Application in R (Practice)
- Q&A session

Wednesday – Theory/Practice from 14:00 to 18:00

- Presenting R packages for functional trait space analyses
- Convex-hulls vs. kernel-density estimates
- Choosing the proper trait space dimensionality
- Correlate spaces
- Mapping functional trait spaces
- The funspace R package (Practice)
- Including intraspecific trait variability in functional trait spaces
- Wrap up + Q&A

COst overview


Package 1




430 €










Cancellation Policy:


> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.


Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.