*Take your species-distribution modelling skills into the Bayesian realm!* *Species Distribution Modelling With Bayesian Statistics (SDMB07)*
*ONLY 3 PLACES LEFT! Registration deadline - 13th January 2026* https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb07/ Join our intensive *three-day live online workshop*: *Species Distribution Modelling With Bayesian Statistics (SDMB07)*. If you have working knowledge of species distribution modelling and R and want to deepen your ability to handle uncertainty, interpret predictions and apply advanced Bayesian workflows, this course is for you. *What you will learn* - How to apply the Bayesian method Bayesian Additive Regression Trees (BART) in R for species distribution models, exploiting its strengths in prediction accuracy and uncertainty surfaces. - How to conduct full Bayesian workflows: data preparation, variable/ predictor selection, model fitting, mapping credible intervals and local prediction uncertainty. - How to handle model interpretation and diagnostics in a Bayesian context: posterior summaries, credible intervals, uncertainty surfaces and model robustness. - Hands-on R coding sessions including annotated scripts you can adapt for your own species of interest. *Who should attend* - Researchers, ecologists, conservation scientists, and spatial-modelling practitioners with previous experience in species distribution modelling and R. - Anyone who wants to move beyond standard SDM frameworks into Bayesian methods that provide richer inference, improved uncertainty estimation, and more robust predictive performance. - Practitioners working in ecology, biogeography, conservation planning or any applied field that requires spatial predictions with quantified uncertainty. *Format & logistics* - Live online format — you can participate from anywhere with internet access. - Three full days of training, each day with four hours of interactive instruction and practical exercises. - Sessions will be recorded and available afterward — making it easier to follow up or catch up across time-zones. *Why this course stands out* - It introduces the state-of-the-art Bayesian modelling technique BART, which recent research shows provides strong performance in species distribution modelling. - Focus on uncertainty quantification: rather than a point-prediction only approach, the course equips you to map credible intervals and interpret confidence in predictions. - Hands-on, applicable: you leave the course with code and workflows that you can adapt directly to your species modelling projects. *How to register / next steps* Visit the PR Stats website for full details, upcoming dates and registration. Early registration is recommended as places are limited. If you have any questions about suitability, schedule, or prerequired experience, contact the course organisers. https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb07/ Email [email protected] with any questions -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
