Bring Bayesian precision to marine mammal habitat modelling.
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/
Marine mammal research often involves sparse data, imperfect detection, and complex oceanographic drivers. The Species Distribution Modelling with Bayesian Statistics (SDMB07) course provides the tools to meet these challenges with greater rigour and transparency. This three-day live online workshop introduces Bayesian workflows and BART-based SDMs designed to improve prediction accuracy while clearly quantifying uncertainty — essential for evidence-based decisions in marine environments.
Why this course is valuable for marine mammal researchers
Marine ecosystems are dynamic, data-limited and often difficult to survey. Bayesian methods help incorporate uncertainty, account for variability and produce predictions that are more defensible in management and conservation contexts. Whether you work with aerial surveys, telemetry, acoustic detections or opportunistic sightings, Bayesian SDMs can strengthen your ecological interpretation and spatial decision-making.
What you will learn
How to use Bayesian Additive Regression Trees (BART) to model species distributions with strong predictive performance and robust uncertainty outputs.
How to generate spatial projections with credible intervals and uncertainty surfaces, supporting transparent assessments in marine spatial planning and conservation.
How to conduct full Bayesian workflows in R, including data preparation, predictor selection, model fitting and interpretation of posterior estimates.
Practical, hands-on R scripts and exercises you can adapt directly to your marine mammal datasets.
Who should attend
Marine mammal ecologists and conservation scientists working with distribution, habitat-use or movement data.
Researchers using telemetry, passive acoustic monitoring, shipboard surveys, or environmental DNA to map presence and suitability.
Practitioners engaged in protected-area design, offshore development assessments, impact studies or climate-change vulnerability analyses.
Anyone with prior SDM experience who wants to integrate Bayesian approaches for more rigorous inference and uncertainty handling.
Course format
Live online instruction across three intensive days.
Four hours of training per day, combining teaching, coding and interpretation.
Accessible internationally, with recordings available afterward for review.
Outcome
By the end of the course, you will be equipped to build and evaluate Bayesian SDMs that better reflect the realities of marine mammal data, enabling more confident and defensible ecological conclusions.