Multivariate Analysis of Ecological Communities Using VEGAN
Analyse ecological community data in R using VEGAN. Learn ordination, clustering, and multivariate statistics with real datasets.
Duration: 5 Days, 7 hours per day
Next Date: December 8-12, 2025
Format: Live Online Format
UK (GMT) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.
£485Registration Fee
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5.0
from 200+ reviews
- Overview
- Instructors
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Course Description
This 5-day course provides a comprehensive introduction to analysing ecological community data using R, with a focus on the VEGAN package. Designed for intermediate R users, the course blends foundational theory with practical, hands-on sessions that will help you apply multivariate methods to real-world ecological datasets.
Throughout the course, we will work with empirical datasets from a range of ecological fields including terrestrial and wetland ecology, microbial ecology, natural resource management, evolution, and palaeoecology. Analyses will focus on detecting patterns along environmental or anthropogenic gradients and quantifying relationships with continuous and categorical predictors.
During the workshops, you will follow guided coding exercises using your own data or real-world datasets. Activities include analyzing patterns related to environmental or human impacts and assessing effects of various predictors. Topics include ecology (terrestrial, wetland, microbial), evolution, palaeoecology, and natural resource management.
Recordings will be made available the same day for those who can’t attend live. We can also provide access to last year’s recordings in advance if that would be helpful.
You are highly encouraged to use your data, contact us beforehand if you need assistance in cleaning and structuring your data (see our guidelines: “Recommendations if participating with your data”). We offer full support in helping you apply the methods to your own data, including: Refining your research question; Choosing suitable transformations and analyses; Interpreting and presenting your results.
Whether you’re working in ecological research, conservation, or natural resource management, this course will give you the tools to conduct robust multivariate analyses and build reproducible, high-quality analytical workflows in R.
What You’ll Learn
You will learn how to process and analyse complex multivariate data typical in community ecology, covering topics such as:
- Diversity indices and community metrics.
- Data transformation and distance measures.
- Clustering and classification techniques.
- Hypothesis testing using canonical ordinations.
- Ordination methods, both unconstrained and constrained (e.g., PCA, NMDS, RDA, CCA) .
- Reproducible workflows and best practices in R programming.
Course Format
Interactive Learning Format
Each day features a well-balanced combination of lectures and hands-on practical exercises, with dedicated time for discussing participants’ own data, time permitting.
Global Accessibility
All live sessions are recorded and made available on the same day, ensuring accessibility for participants across different time zones.
Collaborative Discussions
Open discussion sessions provide an opportunity for participants to explore specific research questions and engage with instructors and peers.
Comprehensive Course Materials
All code, datasets, and presentation slides used during the course will be shared with participants by the instructor.
Personalized Data Engagement
Participants are encouraged to bring their own data for discussion and practical application during the course.
Post-Course Support
Participants will receive continued support via email for 30 days following the course, along with on-demand access to session recordings for the same period.
Who Should Attend / Intended Audiences
This course is ideal for researchers—including PhD and MSc students, postdoctoral researchers, and principal investigators—as well as environmental professionals interested in applying best practices and state-of-the-art methods for modelling species distributions and ecological niches. Applications span a variety of fields such as biogeography, spatial ecology, biodiversity conservation, and related disciplines.
Participants should have a basic understanding of statistical concepts, including linear models and statistical tests—roughly equivalent to an undergraduate introductory statistics course.
To make the most of the course, some prior experience with R is required. You should be comfortable with basic R syntax and commands, using the RStudio console and script editor and importing data from common file formats (e.g., .txt, .xls, .csv)
Equipment and Software requirements
A laptop or desktop computer with a functioning installation of R and RStudio is required. Both R and RStudio are free, open-source programs compatible with Windows, macOS, and Linux systems.
A working webcam is recommended to support interactive elements of the course. We encourage participants to keep their cameras on during live Zoom sessions to foster a more engaging and collaborative environment.
While not essential, using a large monitor—or ideally a dual-monitor setup—can significantly enhance your learning experience by allowing you to view course materials and work in R simultaneously.
All necessary R packages will be introduced and installed during the workshop. A comprehensive list of required packages will also be shared with participants ahead of the course to allow for optional pre-installation.
Dr. Antoine Becker-Scarpitta
Antoine is a community and forest ecologist currently working as a researcher at the French Agricultural Research and International Cooperation Organization (CIRAD), which is dedicated to supporting sustainable development in tropical and Mediterranean regions.
Antoine earned his PhD in Biology/Ecology from the University of Sherbrooke (Canada). He has held postdoctoral research positions at the University of Helsinki (Finland) and the Institute of Botany at the Czech Academy of Sciences (Czech Republic).
Education & Career
- PhD in Biology/Ecology, University of Sherbrooke, Canada
- BSc in Conservation Biology, University of Paris‑Sud‑Orsay
- Postdoctoral research at University of Helsinki and the Institute of Botany, Czech Academy of Sciences
- International consultant
Research Focus
His research focuses on the temporal dynamics of biodiversity and restoration ecology, with a particular interest in forest ecosystems and Arctic vegetation. His work combines field surveys and advanced modelling to unravel ecological changes over time, especially along environmental gradients.
Current Projects
- ReMiNat (2024–2028) – Restauration of Natural Ecosystems, from field diagnosis to restoration planning. Collaboration with La Réunion National Park and The University of La Réunion. ~4.2M euro.
- GIROFLEE (2023-2025) – Innovative management of forest resources for sustainable energy. In collaboration with ONF (French National Office Administration), Département de La Réunion. ~1.8 M euro
- FEADER (2024-2027) – Ecological restoration and monitoring of natural communities of Reunion Island. CIRAD.
Professional Consultancy
Antoine has provided scientific expertise to organisations such as the FAO, various universities, ARES (Belgium), and the European Science Foundation. Topics covered include community ecology, multivariate statistical analysis, ecological inventory strategy, sustainable resource management, and ecological restoration.
Teaching & Skills
Antoine has extensive experience in teaching subjects such as community ecology, botany, evolutionary biology, ecological restoration and linear and multivariate statistical methods in R.
Links
Session 1 – 01:50:00 – Introduction to community data analysis, basics of programming in R
Break – 00:10:00
Session 2 – 01:50:00 – Diversity analysis, species-abundance distributions
Break – 01:00:00
Practical – 02:00:00 / 03:00:00 – Practical
Session 3 – 01:50:00 – Distance and transformation measures
Break – 00:10:00
Session 4 – 01:50:00 – Clustering and classification analysis
Break – 01:00:00
Practical – 02:00:00 / 03:00:00 – Practical
Practical – 02:00:00 – Practical (session for the Americas (Western time zones)
Session 5 – 01:30:00 – Unconstrained ordinations: Principal Component Analysis
Break – 00:10:00
Session 6 – 01:30:00 – Other unconstrained ordinations
Break – 01:00:00
Practical – 02:00:00 / 03:00:00 – Practical
Session 7 – 01:30:00 – Constrained ordinations: RDA and other canonical analysis
Break – 00:10:00
Session 8 – 01:30:00 – Statistical tests for multivariate data and variation partitioning
Break – 01:00:00
Practical – 02:00:00 / 03:00:00 – Practical
Session 9 – 01:30:00 – Overview of Spatial analysis, and recent Hierarchical Modeling of Species Communities (HMSC) methods
Break – 00:10:00
Session 10 – 01:30:00 – Special topics and discussion, analyzing participants’ data.
Break – 01:00:00
Practical – 02:00:00 / 03:00:00 – Practical
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Frequently asked questions
Everything you need to know about the product and billing.
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
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