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ONLINE COURSE – Species distribution modelling with Bayesian statistics in R (SDMB01) This course will be delivered live

9 November 2020 - 13 November 2020

£500.00 – £1684.00

This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak.

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 – Western European Time +1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@psstatistics.com for full details or to discuss how we can accommodate you).

Please feel free to email oliverhooker@prstatistics.com with any questions, full course detials below.

Course Overview:

Bayesian Additive Regression Trees (BART) are a powerful machine learning technique with very promising potential applications in ecology and biogeography in general, and in species distribution modelling (SDM) in particular. Unlike most other SDM methods, BART models can generally provide a well-balanced performance regarding both main aspects of predictive accuracy, namely discrimination (i.e. distinguishing presence from absence localities) and calibration (i.e., having predicted probabilities reflect the species’ gradual occurrence frequencies). BART can generate accurate predictions without overfitting to noise or to particular cases in the data. As it is a cutting-edge technique in this field, BART is not yet routinely included in SDM workflows or in ensemble modelling packages. This course will include 1) an introduction or refresher on the essentials of the R language; 2) an introduction or refresher on species distribution modelling; 3) an overview of SDM methods of different complexity, including regression-based and machine-learning (both Bayesian and non-Bayesian) methods; 4) SDM building and block cross-validation focused on different aspects of model performance, including discrimination, classification, and calibration or reliability. We will use R packages ’embarcadero’, ‘fuzzySim’ and ‘modEvA’ to see how BART can perform well when all these aspects are equally important, as well as to identify relevant predictors, map prediction uncertainty, plot partial dependence curves with credible intervals, and map relative favourability regarding combined or individual predictors. Students will apply all these techniques to their own species distribution data, or to example data that will be provided during the course.

Intended Audience

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.

Venue – Delivered remotely

Time zone – GMT+1 (British daylight saving time

Availability – 20 places

Duration – 5 days

Contact hours – Approx. 35 hours

ECT’s – Equal to 3 ECT’s

Language – English

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 oliverhooker@prstatistics.com. 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.


Dr. Marcia Barbosa



Teaching Format
Course Programme


9 November 2020
13 November 2020
£500.00 – £1684.00


Delivered remotely (United Kingdom)
Western European Time, United Kingdom + Google Map


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