This online course helps you to tackle common challenges that arise with any kind of spatial coordinate data in biology. Knowledge of the tools introduced in this workshop is essential when presenting spatial biological data (e.g. a map of sampling sites) in presentations or publications. More specifically you will be introduced to strategies to deal with the non-independence of spatial data points also known as spatial autocorrelation. Further the course addresses challenges arising in global analyses from the simple fact that the earth is round. You will also touch upon some of the globally available environmental predictors often applied in spatial analyses and their potential challenges. To run this course you should have basic knowledge of the R programming language and more specifically with spatial operations in R. We therefore encourage you to run the basic spatial R course (SBDI-03) first. We also encourage you to bring your own data and questions, and if possible run this course together in a small group – this will make the exercises more fun and comprehensible.
Contact: Matthias Obst (matthias.obst@marine.gu.se)
Creator: Gothenburg Global Biodiversity Center (GGBC)
Time effort: 4-6 hours
Course level: PhD level (motivated Master’s students welcome)
Recommended background: Basic R knowledge required
Link to module: https://github.com/biodiversitydata-se/workshops/tree/master/advanced_spatial_r