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ISDM01

Integrated Species Distribution Modelling (ISDM01)

Learn Integrated Species Distribution Modelling (ISDM) in R. Explore joint species distributions, environmental drivers and ecological community patterns.

  • Duration: 3 Days, 4 hours per day
  • Next Date: February 23-25, 2027
  • Format: Live Online Format
TIME ZONE

UK (GMT+0) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.

£300Registration Fee

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Course Description

This course is aimed towards researchers that want to analyse complementary species distribution information using integrated species distribution models, particularly for when each of the data sets is known to suffer from low sample size, high sampling effort or restricted spatio-temporal or environmental coverage.

Species distribution models (SDMs) are practical tools for quantifying a species’ environmental niche and predicting a species’ range. However, SDMs are constrained by the extent and quality of species occurrence data: systematically collected data may be sparse and cover only parts of the species range, whereas opportunistic data may extensively cover the species range but suffer from sampling biases that further bias the estimates for the species response to environment. Integrating complementary species data types in single SDM can alleviate the data deficiency and sampling biases but requires more ecological thinking and technical understanding compared with a conventional SDM that is fitted with a single data type.

Here, we will cover comprehensively cover integrated SDMs: joint likelihood structure, flexible covariate and covariance structures, random effects and different data types. We will focus on active learning through hands-on programming exercises.

We will use publicly available data sets to demonstrate model training and predictions and use freely available and open-source R packages. The expected outcome of the course is a solid foundation in applying integrated SDMs.

What You’ll Learn

  • Different observation models and associated likelihood structures in an SDM
  • Covariates and covariance to account for differences between data types
  • Random effects
  • Validation of integrated SDMs
  • Use and benefits of different data types
  • Hierarchical Bayesian inference for integrated SDMs
  • INLAbru package in R for building integrated SDMs

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 intended for academics and postgraduate students working on projects involving the species distribution modelling, as well as applied researchers and analysts in public, private, or third-sector organizations. Users should have a basic understanding of statistical concepts such as regression, and some experience with data analysis and manipulation including the ability to import and export data, manipulate data frames, fit basic statistical models, and generate exploratory and diagnostic plots. Knowledge in core concepts (environmental niche, different data types) in SDMs is beneficial. Although the language used will be R, and familiarity with R will help, an understanding of similar programming languages (e.g. python) will also be beneficial.

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.

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.

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.

All necessary R packages will be introduced and installed during the workshop.

Download R Download RStudio Download Zoom

Prof. Luca Börger

Prof. Luca Börger

Luca is an ecologist working at the interface of movement ecology, population biology, and biodiversity conservation. His research focuses on understanding the mechanistic processes — including movement, traits, demography, and species interactions — that shape ecological dynamics and responses to environmental change. He applies and develops statistical, mathematical, and simulation-based approaches to link individual behaviour with population- and community-level processes, with the aim of improving predictions of biodiversity change and informing sustainable policy. His work spans a wide range of taxa, from invertebrates and vertebrates to plants, and is strongly interdisciplinary, involving collaborations with mathematicians, statisticians, engineers, conservationists, and policymakers.

Luca is Chair in Ecology and Biodiversity in the Department of Biosciences at Swansea University, co-Director of the Centre for Biomathematics, and Chair/Secretary of the British Ecological Society’s Movement Ecology Special Interest Group. Before his academic career, he trained and worked as a professional freelance musician specialising in the French horn.

 

Education & Career
• PhD in Zoology, University of Cambridge (with visiting research at Imperial College London, Silwood Park)
• MSc in Biology, University of Pisa
• Postdoctoral fellowships in Canada (University of Guelph) and France (CNRS & INRA)
• Associate Professor, Swansea University (2013–2017)
• Professor and Chair in Ecology and Biodiversity, Swansea University (2017–present)

 

Research Focus
Luca’s research is question-driven, bridging behavioural, population, and community ecology in both theoretical and applied contexts. He leads the Biodiversity Dynamics and Movement Ecology Lab (BioMove), part of the Swansea Laboratory for Animal Movement (SLAM). His work integrates ecological data with advanced modelling to address challenges in conservation, management, and environmental policy across Europe, Africa, North America, Brazil, and Australia.

 

Current Projects
• Movement ecology of large vertebrates (e.g., red deer, sea turtles, adders)
• Trait-based approaches to predicting biodiversity responses to environmental change
• Impacts of invasive species on native communities (e.g., wallabies on the Isle of Man)
• Development of quantitative tools for analysing high-resolution movement data
• Interdisciplinary collaborations linking ecology with mathematics, statistics, and engineering

 

Professional Consultancy
Luca collaborates with conservation agencies, NGOs, and government organisations to provide ecological expertise on biodiversity monitoring, spatial management, and policy design. He also advises interdisciplinary teams on study design, quantitative methods, and movement data analysis.

 

Teaching & Skills
• Teaches ecological data analysis in R (undergraduate and postgraduate)
• Delivers international workshops on movement ecology and statistical ecology
• Experienced in supervising interdisciplinary PhD and MRes projects
• Strong advocate of open science, reproducibility, and cross-disciplinary training

 

Links
• University Profile
• Google Scholar
• Research Gate

Prof. Garrett M. Street

Prof. Garrett M. Street

Garrett is a quantitative ecologist working at the interface of habitat selection, animal movement, and landscape ecology. His research focuses on how fine-scale behavioral processes—such as thermoregulation, foraging, and habitat preference—shape broad-scale patterns in species distribution, abundance, and population dynamics. He utilizes a range of methods including statistical and simulation modeling, biotelemetry, geographic information systems (GIS), and laboratory microcosms to explore ecological processes from both theoretical and empirical perspectives. His recent work further examines animal fitness and body condition under energetic constraints, behavioral influences on habitat selection and species distribution, and the role of animal movement in the global carbon budget.

Garrett earned his PhD in Integrative Biology from the University of Guelph (supervised by Dr. John Fryxell), following a Master’s degree in Population & Conservation Biology from Texas State University (under Dr. Floyd “Butch” Weckerly). He then completed postdoctoral research at the University of Minnesota with Drs. John Fieberg and James Forester. In August 2015, he joined the Department of Wildlife, Fisheries, and Aquaculture at Mississippi State University, where he co-founded the Quantitative Ecology and Spatial Technologies (QuEST) Laboratory.

 

Education & Career
• PhD in Integrative Biology, University of Guelph
• M.Sc. in Population & Conservation Biology, Texas State University
• Postdoctoral Researcher, University of Minnesota
• Associate Professor, Department of Wildlife, Fisheries & Aquaculture, Mississippi State University (since 2015)

 

Research Focus
Garrett’s work centers on elucidating how micro-scale behavioral and physiological processes translate into macro-scale ecological patterns. He is particularly interested in the energetics of movement and foraging, habitat selection dynamics, and ecological forecasting across climatic and spatial gradients. His lab, QuEST, combines cutting-edge quantitative tools and empirical data to address key questions in movement ecology and ecosystem health across diverse taxa and landscapes.

 

Current Projects
• Energetic constraints on animal movement and body condition
• Behavioral drivers of habitat preference and species distribution
• Modeling animal movement across spatiotemporal and bioclimatic gradients
• Exploring wildlife contributions to carbon fluxes in ecosystems
• Feral swine and white-tailed deer behavior in managed landscapes, moose habitat selection, and avian population dynamics

 

Teaching & Skills
• Delivers courses in wildlife biostatistics, landscape ecology, GIS applications, and movement ecology
• Expert in applying statistical modeling, telemetry data, GIS, and simulation approaches to movement ecology
• Experienced in training students and professionals in quantitative ecological methods

 

Links
• University Profile
• Research Gate

Session 1 – 04:00:00 – A statistical model with two likelihoods, one for presence-absence and presence-only data each. Introducing observation models and associated likelihoods. Hierarchical Bayesian inference and INLAbru. Validating models. Theory and a practice.

Break – 00:30:00

Session 2 – 02:00:00 – Practical: Fitting SDMs for data types separately and jointly.

Session 3 – 02:00:00 – Spatio-temporal random effects and data type specific predictors. Graphical presentation of the model structure.

Break – 00:30:00

Session 4 – 02:00:00 – Practical: Assigning spatio-temporal random effects in a joint SDM.

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?

Yes — administrator access is recommended, as you may need to install software during the course. If you don’t have admin rights, please contact us before the course begins and we’ll provide a list of software to install manually.

I’m attending the course live — will I also get access to the session recordings?

Yes. All participants will receive access to the recordings for 30 days after the course ends.

I can’t attend every live session — can I join some sessions live and catch up on others later?

Absolutely. You’re welcome to join the live sessions you can and use the recordings for those you miss. We do encourage attending live if possible, as it gives you the chance to ask questions and interact with the instructor. You’re also welcome to send questions by email after the sessions.

I’m in a different time zone and plan to follow the course via recordings. When will these be available?

We aim to upload recordings on the same day, but occasionally they may be available the following day.

I can’t attend live — how can I ask questions?

You can email the instructor with any questions. For more complex topics, we’re happy to arrange a short Zoom call at a time that works for both of you.

Will I receive a certificate?

Yes. All participants receive a digital certificate of attendance, which includes the course title, number of hours, course dates, and the instructor’s name.

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?

Yes — administrator access is recommended, as you may need to install software during the course. If you don’t have admin rights, please contact us before the course begins and we’ll provide a list of software to install manually.

I’m attending the course live — will I also get access to the session recordings?

Yes. All participants will receive access to the recordings for 30 days after the course ends.

I can’t attend every live session — can I join some sessions live and catch up on others later?

Absolutely. You’re welcome to join the live sessions you can and use the recordings for those you miss. We do encourage attending live if possible, as it gives you the chance to ask questions and interact with the instructor. You’re also welcome to send questions by email after the sessions.

I’m in a different time zone and plan to follow the course via recordings. When will these be available?

We aim to upload recordings on the same day, but occasionally they may be available the following day.

I can’t attend live — how can I ask questions?

You can email the instructor with any questions. For more complex topics, we’re happy to arrange a short Zoom call at a time that works for both of you.

Will I receive a certificate?

Yes. All participants receive a digital certificate of attendance, which includes the course title, number of hours, course dates, and the instructor’s name.

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ISDM10 ONLINE
ISDM10 ONLINE
£ 300.00
Unlimited
£300.00
23rd February 2027 - 27th February 2027
Delivered remotely (United Kingdom), Western European Time Zone, United Kingdom
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