Species Distribution Modelling with Bayesian Statistics (SDMB08) – Applications for Marine Mammal Research
Species Distribution Modelling with Bayesian Statistics (SDMB08)<https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb08/?utm_source=chatgpt.com> Delivered by Dr Márcia Barbosa, a biogeographer and macroecologist with extensive experience in species distribution modelling, GIS and ecological modelling, with a particular focus on open, transparent and reproducible analytical workflows. Learn how to build, evaluate and interpret species distribution models using Bayesian Additive Regression Trees (BART) in R, providing a flexible Bayesian approach for investigating relationships between marine mammal occurrence and environmental conditions. Species distribution modelling has particularly strong applications in marine mammal ecology and conservation, where researchers frequently need to understand how cetacean and pinniped distributions relate to environmental conditions, identify suitable habitat, investigate spatial patterns of occurrence, and predict distributions across large or incompletely surveyed marine environments. What you'll gain * An understanding of species distribution and ecological niche modelling * An introduction to Bayesian Additive Regression Trees (BART) * Practical experience fitting Bayesian distribution models in R * Working with species occurrence and environmental/climatic variables * Selecting appropriate spatial resolution and geographic extent * Computing and fine-tuning BART models to predict geographic distributions * Interpreting posterior predictions, credible intervals and uncertainty * Evaluating and cross-validating models * Quantifying environmental variable importance * Selecting relevant environmental predictors * Producing partial dependence plots and maps * Developing reproducible workflows that can be adapted to participants' own species and datasets Course format * 3-day live, instructor-led online course * 12 hours of training * Lectures combined with hands-on practical exercises in R * Complete worked example from data preparation through to model interpretation * Annotated R scripts that can be adapted to participants' own species * Opportunity to discuss participants' own data * Code, datasets and presentation materials provided * All sessions recorded * 30 days of recording access and post-course email support Who is this course for? * Marine mammal ecologists * Cetacean and pinniped researchers * Marine conservation scientists * Marine spatial ecologists * Researchers studying species distributions and habitat use * Researchers investigating relationships between marine mammals and their environment * Researchers working with marine mammal occurrence or survey datasets * Researchers involved in habitat suitability, conservation or spatial management * Postgraduate students and early-career researchers Participants should already be familiar with the concept of species distribution models (SDMs) or ecological niche models (ENMs) and have some basic experience using R. No previous knowledge of Bayesian statistics is required. Why take this course? Understanding the spatial distribution of marine mammals is central to many questions in marine ecology, conservation and management. Distribution models can be used to investigate how occurrence relates to environmental conditions, identify areas of suitable habitat, explore geographic patterns and support evidence-based spatial conservation. For marine mammal researchers, potential environmental predictors may include variables such as sea-surface temperature, depth, bathymetry, productivity and other oceanographic or climatic conditions. Modelling these relationships can help reveal the environmental characteristics associated with observed distributions and how habitat suitability varies geographically. Bayesian Additive Regression Trees provide a flexible approach for modelling complex species–environment relationships while allowing uncertainty in predictions to be quantified. This is particularly valuable when interpreting distribution maps and identifying areas where model predictions are more or less certain. The course goes beyond simply generating maps. Participants learn how to make decisions about spatial extent and resolution, cross-validate models, assess predictive performance, examine variable importance, interpret credible intervals and explore partial responses to environmental predictors. Whether you're studying cetaceans, pinnipeds, habitat use, distribution, environmental drivers, marine spatial ecology or conservation, this course provides a practical Bayesian framework for analysing and predicting species distributions. Course dates 6–8 October 2026 14:00–18:00 UK time 12 hours | Live online | £385 Learn more & enrol PR Stats – Species Distribution Modelling with Bayesian Statistics (SDMB08)<https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb08/?utm_source=chatgpt.com> Questions? 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