Spatial Phylogenetics and the Bayesian Phylogenetic Mixed Model (PMM) (BPMM01)
Learn spatial phylogenetics and Bayesian phylogenetic mixed models in R. Practical online training in phylogenetic modelling and comparative workflows.
Duration: 3 Days, 6 hours per day
Next Date: September 22-24, 2026
Format: Live Online Format
UK (GMT+1) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.
£350Registration Fee
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- Overview
- Instructors
- Schedule
Course Description
In this three-day course, we introduce the theoretical foundations and practical implementation of spatial phylogenetics and the Bayesian Phylogenetic Mixed Model (PMM) using R, with a particular emphasis on its application to spatially explicit ecological and evolutionary data. PMMs provide a powerful framework to incorporate shared evolutionary history into hierarchical models, allowing researchers to properly account for non-independence among species and improve ecological inference.
We begin by introducing the essential concepts of the phylogenetic comparative method and spatial phylogenetics, including how phylogenies and geographic data can be combined to describe patterns of biodiversity and evolutionary structure across space (Day 1). We then devote the remainder of the course to understanding, implementing, and interpreting Bayesian PMMs. Participants will learn how to specify phylogenetic covariance structures, integrate them into mixed modelling frameworks, and interpret the resulting parameters (Day 2). Finally, we focus on practical applications, including model fitting, diagnostics, and the projection of PMM results into spatial contexts, highlighting when and why incorporating phylogenetic information improves model performance (Day 3).
What You’ll Learn
During the course will cover the following:
- Understand the principles of spatial phylogenetics and phylogenetic comparative methods in ecological research.
- Build and interpret Bayesian phylogenetic mixed models (BPMMs) using R.
- Analyse phylogenetic signal and evolutionary relationships within spatial ecological datasets.
- Apply Bayesian workflows for modelling species traits, distributions, and evolutionary patterns.
- Evaluate model performance, convergence, and uncertainty in Bayesian phylogenetic analyses.
- Develop reproducible workflows for spatial phylogenetic analysis and comparative modelling in R.
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 aimed at ecologists and evolutionary biologists who wish to integrate phylogenetic information into spatial analyses and modelling frameworks. It is particularly suited for researchers interested in biodiversity patterns, macroecology, macroevolution, community ecology, and conservation.
The course is also relevant for researchers working with species trait data, comparative analyses, and spatial biodiversity datasets where phylogenetic relationships need to be accounted for statistically. Participants will gain practical experience applying Bayesian phylogenetic mixed models using modern R workflows.
It is suitable for postgraduate students, researchers, academics, and professional scientists working in ecology, evolution, conservation biology, biogeography, and related environmental sciences.
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. Ignacio Morales-Castilla
Ignacio is a biogeographer and macroecologist whose research focuses on the spatial and temporal distribution of biodiversity. His work integrates ecological, evolutionary, and biogeographical perspectives to better understand how species assemble into communities and how biodiversity patterns emerge across scales. His research program aims to: (1) disentangle the relative roles of evolution and ecology as drivers of community structure, (2) investigate how different aspects of species’ niches are evolutionarily conserved, and (3) improve models of biotic interactions and species distributions by incorporating phylogenetic, functional, and geographic information.
Education & Career
• PhD in Ecology from the University of Alcalá (Universidad de Alcalá), Alcalá de Henares, Spain.
• Affiliated with the the GloCEE – Global Change Ecology and Evolution Group, in the Department of Life Sciences at the Universidad de Alcalá, Alcalá de Henares, Spain, where hue is a is currently a Beatriz Galindo Fellow.
Research Focus
Ignacio’s work centres on:
• Disentangling ecological and evolutionary processes that shape community structure
• Niche evolution and the degree of evolutionary conservatism across traits and taxa
• Integrating phylogenetic and functional data into species distribution models
• Advancing models of biotic interactions and biodiversity under global change
Current Projects
• Developing integrative models of species distributions that account for evolutionary history and functional traits
• Exploring the role of evolutionary constraints in shaping biodiversity patterns across large spatial and temporal scales
• Assessing biodiversity responses to global change by linking ecology, evolution, and biogeography
Professional Consultancy & Teaching
Ignacio contributes expertise in macroecology, biodiversity modelling, and biogeography to interdisciplinary projects. He trains students and researchers in phylogenetic and functional approaches to ecology, and is engaged in advancing reproducible, open science practices within biodiversity research.
Links
• ResearchGate
• ORCID
• University Profile
• Personal Site
• GitHub
Session 1 – 02:00:00 –
- Introduction to phylogenetics and spatial phylogenetics: concepts and applications
- The phylogenetic comparative method
- The phylogenetic signal
Break – 01:00:00
Session 2 – 02:00:00 –
- Linking phylogenies and geography: why it matters
- Common metrics: Phylogenetic diversity (PD), Mean pairwise distance (MPD), Mean nearest taxon distance (MNTD)
- Phylogenetic turnover and beta diversity
Break – 01:00:00
Session 3 – 02:00:00 –
- Mapping and visualising phylogenetic structure across space
- Implementing spatial phylogenetic analyses in R
Session 4 – 02:00:00
- Why incorporate phylogenies into statistical models?
- The rationale for phylogenetic covariance in ecological data
Break – 01:00:00
Session 5 – 02:00:00
- Introduction to the Bayesian Phylogenetic Mixed Model
- Model structure: fixed effects, random effects, phylogenetic random effects
- Understanding evolutionary signal in model residuals
Break – 01:00:00
Session 6 – 02:00:00
- Evolutionary signal in model coefficients
- Linking PMMs with familiar GLMM frameworks
- Introduction to implementation in R (e.g. brms, rstan)
- Interpreting model outputs and phylogenetic effects
Session 7 – 02:00:00
- Practical implementation of PMMs in R
- Specifying phylogenetic covariance structures
- Model fitting, diagnostics, and convergence
Break – 01:00:00
Session 8 – 02:00:00
- Interpreting phylogenetic variance components
- Comparing models with and without phylogeny
- Projecting model posterior distributions into geographic space
Break – 01:00:00
Session 9 – 02:00:00
- Visualising spatial patterns from PMMs
- When and why phylogenetic information improves models
- Limitations and common pitfalls
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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