Due to the COVID-19 outbreak, this course will be held online
This course will encompass the theory and practice of species distributions models (SDM) and ecological niche models (ENM), spanning the underlying concepts, methods, and applications. We will address the caveats and challenges of these models, and see how to make the most of their strengths while avoiding their most common pitfalls. Participants will build and validate models based on species occurrence data of their choice, and learn how to apply these models to a variety of purposes.
The course is aimed at students, researchers and practitioners at any career stage with an interest in building and applying species distribution and/or ecological niche models in a reproducible and automated way. Participants should be accustomed to working with computers, have a good internet connection, and preferably a webcam, as the live online sessions are intended to be highly interactive. Previous basic experience with R is strongly desirable, though not strictly mandatory if you’re a fast learner. All R scripts will be provided and explained in detail.
By the end of this course, participants will be able to:
- Know the basic theory and concepts behind SDM and ENM
- Design, build and evaluate SDM and ENM using automated R scripts
- Understand the strengths and limitations of SDM and ENM for different purposes
- Use SDM and ENM to describe, predict and project species distributions in space and time
15:30 - 18:30 (Berlin time): live lectures and introduction to / review of the practicals
4 additional hours: self-guided practicals using annotated R scripts, with live e-mail support from 09:00 to 23:00 (Berlin time)
Monday – Lectures from 15:30 to 18:30 + 4 hours practicals
- [PRE-COURSE] Self-guided introduction / refresher on base R language
- Underlying theory in SDM and ENM: geographic distributions and ecological niches
- Differences between SDM and ENM
- Types of niches and types of models
- Data for building SDM and ENM: species occurrence records and predictor variables
- Identifying and addressing data quality issues
- Practical: data gathering, cleaning and formatting
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.