ONLINE COURSE – Multivariate Analysis Of Ecological Communities Using R With The VEGAN package (VGNR04) This course will be delivered live
12 September 2022 - 16 September 2022£480.00
Monday, September 12th, 2022
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 – Eastern European Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
About This Course
This 5-day course will cover R concepts, methods, and tools that can be used to analyze community ecology data. The course will review data processing techniques relevant to multivariate data sets. We will cover diversity indices, distance measures and distance-based multivariate methods, clustering, classification and ordination techniques using the R package VEGAN. We will use real-world empirical data sets to motivate analyses, such as describing patterns along gradients of environ-mental or anthropogenic disturbances, quantifying the effects of continuous and discrete predictors. We will emphasise visualisation and reproducible workflows as well as good programming practices. The modules will consist of introductory lectures, guided computer coding, and participant exercises. The course is intended for intermediate users of R who are interested in community ecology, particularly in the areas of terrestrial and wetland ecology, microbial ecology, and natural resource management. You are strongly encouraged to use your own data sets (they should be clean and already structured, see the document: “recommendation if you participate with your data”.
Any researchers (PhD and MSc students, post-docs, primary investigators) and environmental professionals who are interested in implementing best practices and state-of-the-art methods for modelling species’ distributions or ecological niches, with applications to biogeography, spatial ecology, biodiversity conservation and related disciplines.
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
The course will be divided into theoretical lectures to introduce and explain key concepts and theories, and practices with workshop sessions on R.
~2 modules per day, each module consists of ~1h30/2h lecture + coding, break, ~1h30/2h exercises + summary/discussion.
The schedule can be slightly modified according to the interest of the participants.
The course will take place online.
All the sessions will be video recorded and made available immediately on a private video hosting website as soon as possible after each 2hr session.
Assumed quantitative knowledge
We will assume that you are familiar with basic statistical concepts, linear models, and statistical tests (the equivalent of an undergraduate introductory statistics course will be sufficient to follow the course).
Assumed computer background
To take full advantage of this course, minimal prior experience with R is required. Participants should be familiar with basic R syntax and commands, know how to write code in the RStudio console and script editor, load data from files (txt, xls, csv).
Equipment and software requirements
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 firstname.lastname@example.org. 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.
Monday 12th – Classes from 10:00 – 17:00
• Module 1: Introduction to community data analysis, basics of programming in R
• Module 2: Diversity analysis, species-abundance distributions
Tuesday 13th – Classes from 10:00 – 17:00
• Module 3: Distance and transformation measures
• Module 4: Clustering and classification analysis
Wednesday 14th – Classes from 10:00 – 17:00
• Module 5: Unconstrained ordinations: Principal Component Analysis
• Module 6: Other unconstrained ordinations
Thursday 15th – Classes from 10:00 – 17:00
• Module 7: Constrained ordinations: RDA and other canonical analysis
• Module 8: Statistical tests for multivariate data and variation partitioning
Friday 16th – Classes from 10:00 – 17:00
• Module 9: Overview of Spatial analysis, and recent Hierarchical Modeling of Species Communities (HMSC) methods
• Modules 10: Special topics and discussion, analyzing participants’ data.
Dr. Antoine Becker-Scarpitta
Works at – University of Helsink
Teaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
Antoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay, and from the Natural History Museum of Paris, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology, plant ecology and evolution, linear and multivariate statistics assisted on R.