This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – GMT – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email firstname.lastname@example.org for full details or to discuss how we can accommodate you).
This course introduces the participants to the main concepts and methods of trait-based ecology. While traits have been used in ecology for a long time, an approach explicitly based on traits has been increasingly introduced to almost all aspects of ecological research in the last two decades. In particular, since the early 2000s, methodological developments have really flourished, up to a point that it is hard to keep track of such developments. In this course, we will combine lectures providing an overview of the main principles and methods of trait-based ecology with practices using the statistical software R, so that participants will acquire a knowledge of available R packages and customized functions, and how to use them in the context of trait-based analyses. The course will span methods taking both species-level and community-level perspectives that can be applied to a large variety of organisms. Additional practical aspects that will be covered include the choice of the “right” traits for a given study, what to consider when using trait data from data bases, and how to design and optimize your own trait sampling campaign. The course is largely based on the book recently published by Cambridge University Press “Handbook of Trait-Based Ecology: From Theory to R Tools” and the accompanying R material. The book is not required for course participation.
Master and PhD students, as well as post docs and established researchers new to the topic, who are at the start of their own trajectory in trait-based ecological research.
Time zone – GMT
Availability – 30 places
Duration – 8 days (4 hours per day, one day per week, for 8 weeks)
Contact hours – Approx. 32 hours
ECT’s – Equal to 3 ECT’s
Language – English
The course will consist in 1 teaching block per week, for 8 weeks. Each block will consist of approximately 3.5 hours of interactive live online sessions (at xx:xx GMT time), which will include theoretical lectures, discussion, and demonstrations of R code of selected packages and functions and approximately 4 hours of practical’s that each participant will do on their own schedule / time zone, based on annotated self-explanatory R scripts. The instructor will be available for questions and help during Western European working hours and a bit beyond that, depending on the participants’ time zones. Data sets and R codes for practicals will be provided, so that participants can repeat and extend the methods demonstrated during the lectures, at their own convenience.
A basic knowledge of uni- and multivariate statistical analyses is assumed (correlation, simple regression models, unconstrained and constrained ordination, e.g. PCA, RDA). Without such knowledge the course can probably be followed for most parts, but the practicals will be much less efficient for the student.
Participants should have basic experience in working with the R statistical environment, preferably in connection with the R studio interface. They should be familiar with importing data to R, installing and loading packages, and basic plot functions.
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more firstname.lastname@example.org
Introduction, definitions, response and effect, functional groups, trade-offs, Gower distance.
People’s trait game
Community Weighted Mean (CWM) and Functional Diversity (FD)
CWM & FD
Response traits and environmental filtering
Basics of null-models
Intraspecific trait variability
Trait overlap (trova), Trait variance, CWM flex anova
Conservatism, Phylogenetic diversity, PICs
Response & Effect traits
Selection/Complementarity, Lautaret, multitrophic
Missing traits, databases, sampling traits
Databases extraction, sampling game, data imputation