Course: Ecological Niche Models in R Where: Berlin
When: 20-24 May 2019 Instructors: Dr. Sara Varela (Museum für Naturkunde, Berlin, Germany) Dr. A. Márcia Barbosa (CIBIO/InBIO - Universidade de Évora) Course website: https://www.physalia-courses.org/courses-workshops/course45/ COURSE OVERVIEW Ecological niche models (ENMs) are a fundamental tool for working in global change biology. Predicting species distributions is key for designing conservation and management plans that remain effective in the long run. Further, combining population genetics with maps of the species potential ranges in the past (e.g. during the last glacial maximum), allows researchers to unveil the role of cyclic global climatic changes on population dynamics. ENMs use data on species occurrences (both past or present) along with climatic layers, to extract the climatic conditions where the species have been sampled, and map species potential range dynamics through time. ENMs have been widely used and discussed in the recent literature. Data and biases in the data, climatic layers and climatic models, and most of all, the models itself. How to test our map predictions and what those map predictions really mean was hotly debated in the last 10 years. In this course, we are going to teach you how to use R to program ecological niche models (ENMs), models that aim to map the distribution of species based on its climatic requirements. Day by day, we will cover all the different steps of making an ENM and we will talk and discuss about their drawbacks (see below). TARGETED AUDIENCE & ASSUMED BACKGROUND This workshop is aimed at postgraduate students and researchers who are interested in using ENMs in their research. Experience in using R is not mandatory, but desirable. We will use R and RStudio in the lessons. TEACHING FORMAT The workshop is delivered over ten half-day sessions (see the detailed curriculum below). Each session consists of a combination of lectures and practical exercises, with breaks at the organisers’ discretion. There will also be time for students to discuss their own problems and data. Program Day 1. 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. Day 2. 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. Day 3. 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. Day 4. 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). Day 5. 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. For any questions, please feel free to contact us at: i...@physalia-courses.org Best regards, Carlo
