Monday - Classes from 9:30 to 17:30
Occurrence data: how to load your own data and how to import data from open access databases (such as GBIF or paleobioDB). We will discuss here the different potential biases on the input data and how to address them.
Tuesday - Classes from 9:30 to 17:30
Climatic layers: types of climatic models (interpolations vs. mechanistic models, or worldclim vs. AOGCMs). How to use R as a GIS, how to extract climatic data from your occurrence points, etc.
Wednesday - Classes from 9:30 to 17:30
Ecological Niche Models: types of models (distance models, regressions, classification and regression trees, maxent). We will learn about the different R packages to run those models, and their main differences.
Thursday - Classes from 9:30 to 17:30
Program flow. Programming loops for working with large lists of species, models and climatic scenarios. When working in global change biology we need to automatize our scripts to make predictions over hundreds of species, trying several ENMs, and projecting the ENMs over different climatic scenarios (e.g. present and several future predictions).
Friday - Classes from 9:30 to 17:30
Student exercises. Students will present their case study (we encourage students to think about a hypothesis that they would like to test during this course in advance), their initial goals, the problems that they faced, and how they manage to solve them.