Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDMPR)
Analyse entire ecological communities with hierarchical models and joint species distribution modelling in R.
Duration: 20 Hours
Format: Recorded ‘on-demand’ Format
£450Registration Fee
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- Overview
- Instructors
- Schedule
Course Description
Hierarchical Modelling of Species Communities (HMSC) represents one of the most powerful and flexible approaches for analysing multi-species ecological data. Moving beyond single-species models, HMSC enables you to jointly model species distributions, account for environmental drivers, incorporate species traits and phylogenies, and uncover patterns of species co-occurrence and community assembly.
This course provides a practical, applied introduction to Joint Species Distribution Modelling (JSDMs) using the HMSC framework in R. You will learn how to build, fit, interpret, and validate hierarchical community models using real ecological datasets.
Through a combination of theory and hands-on coding, you will develop the skills needed to move from traditional species distribution modelling to fully integrated community-level analysis, producing deeper ecological insight and more robust predictions.
HMSC allows you to relate species occurrences or abundances to environmental covariates, traits, phylogeny, and spatial or temporal structure within a unified framework
What You’ll Learn
- Principles of Joint Species Distribution Modelling (JSDMs) and HMSC
- Structuring multi-species datasets (environmental, traits, phylogeny)
- Building hierarchical models for community data in R
- Incorporating spatial and temporal structure into models
- Understanding species co-occurrence and residual associations
- Evaluating model performance, convergence, and predictive power
- Interpreting outputs at both species and community levels
- Linking results to ecological theory (e.g. niche theory, community assembly)
Course Format
Flexible Learning Structure
Learn through a carefully structured mix of lecture recordings and guided exercises that you can pause, revisit, and complete at your own pace—ideal for busy professionals or those balancing multiple commitments.
Access Anytime, Anywhere
All course content is available on-demand, making it accessible across all time zones without the need to attend live sessions or adjust your schedule.
Independent Exploration with Support
Engage deeply with course topics through self-directed study, with the option to reach out to instructors via email for clarification or deeper discussion.
Comprehensive Learning Resources
Gain full access to the same high-quality materials provided in live sessions, including code, datasets, and presentation slides—all available to download and keep. Please note recordings can only be streamed.
Work With Your Own Data, On Your Terms
Apply what you learn directly to your own data projects as you go, allowing for a personalized and immediately practical learning experience.
Continued Guidance and Resource Access
Receive 30 days of post-enrolment email support and unrestricted access to all session recordings for 60 days, so you can review and reinforce your learning as needed.
Who Should Attend / Intended Audiences
This course is designed for ecologists working with community or multi-species data, as well as researchers currently using species distribution models (SDMs) who are looking to advance to joint species distribution models (JSDMs). It is particularly suitable for PhD students and postdoctoral researchers in ecology, biodiversity, or conservation science, alongside quantitative ecologists and data analysts working with hierarchical models. It will also benefit anyone interested in gaining a deeper understanding of species interactions and community dynamics.
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. Bastien Parisy
Bastien is a community ecologist with a particular interest in understanding how the assemblages of interactions between plants and their associated organisms are changing with environmental changes. After earning his PhD at the University of Helsinki, Bastien is now working as a postdoctoral researcher at the same institution.Education & Career
- Postdoctoral researcher (2024-2027) at University of Helsinki, Finland
- PhD in wildlife Biology (2019-2024), University of Helsinki, Finland
- Master in ecosystems modelling (2018-2019), University Paul Sabatier-Toulouse, France
- Master in plant ecology (2016-2018), University Paul Sabatier-Toulouse, France
- Bachelor in biology of organisms, populations and ecosystems (2013-2016), University Paul Sabatier-Toulouse, France
Research FocusDuring my PhD, I began to unravel the mechanisms underlying plant–soil microbe interactions in the Arctic region and now I further explore how such changes in interactions may impact ecosystems processes. During my past and ongoing projects, I combined intensive fieldwork and experimental approaches with topical statistical analyses such as bipartite networks analyses and joint species distribution models, and in particular HMSC.
Teaching & SkillsBastien has extensive experience in teaching subjects such as community ecology, eDNA metabarcoding, plant-soil microbes interactions and multivariate statistical methods in R.
Links
Theoretical background behind HMSC (what HMSC is and what HMSC is not)
Session 1 – 02:30:00 – Theoretical background behind HMSC framework
- Quick introduction of myself and previous experience with HMSC.
- History and conceptual framework behind HMSC (i.e, community ecology conceptual framework)
- Global structure of HMSC and what questions and hypotheses it can answers
Session 2 – 02:30:00 – Data formatting and preparation for HMSC
- Presentation package, and data preparation (based on published but also participant’s data)
- Preparing the HMSC model (Formulating the hypotheses into the model)
How to fit and assess quality
Session 3 – 02:30:00 – Fitting HMSC models
- Participant fitting their HMSC model (from their own data) and troubleshooting
Session 4 – 02:30:00 – Assessing model fit
- How HMSC fitting procedure works; Presentation of MCMC and Bayesians statistic behind it
Outputs and their interpretation
Session 5 – 02:30:00 – Understanding and interpreting HMSC output
- HMSC outputs and their ecological interpretation
- Cross validation procedure
Session 6 – 02:30:00 – Producing HMSC output
- Assessing quality of participants’ models
- Producing HMSC outputs (HMSC based and ggplots functions).
- What are the key parameters to assess the quality of the fit
Beyond this introductory course
Session 7 – 02:30:00 – Reporting key information of HMSC model in a manuscript
- Reporting key information into a manuscript.
- Introduction of Hmsc-gpu and other application HMSC not presented here (i.e, spatial predictions)
Session 8 – 02:30:00 – Troubleshooting and solutions
- Most common troubles with HMSC outputs and their solutions
- Troubleshooting of participants models, output, fitting and everything.
- Questions and Answers
Testimonials
PR Stats 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 PR Stats 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
PR Stats provided excellent training in stable isotope analysis through the SIMMPR course, which was incredibly valuable for my research. I was fortunate to attend the course through a generous fee waiver, which directly supported my work and enabled me to develop skills that contributed to my recent publication on reservoir food webs in Sri Lanka. I’m very grateful for the opportunity and support, and would highly recommend their courses to others working in ecological research.
Subodha Silva
Aquatic Ecology Researcher
Courses attended
SIMMPR
Testimonials
PR Stats has become an invaluable part of developing my skills in advanced statistical and spatial analysis. Through training in areas such as Bayesian statistics and Species Distribution Modelling, I’ve gained both practical expertise and exposure to leading experts in the field. The impact on my research has been significant with at least four of my published papers have been directly influenced by PR Stats courses. My most recent work benefitted from modelling advice on sample design and model accuracy evaluation and can be seen here.
Carlos P.E. Bedson
Quantitative Spatial Ecology, Ecology and Environment Research Centre, Manchester Metropolitan University, United Kingdom
Courses attended
ADVR08, ENMR03, BMIN02, ISBD01, BADA01, SDMB06
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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