Week 01 — Introductions

1 Session A: Introductions

1.1 Session Objectives

  • Short class to introduce ourselves

  • Get familiarized with course objectives

2 Session B: Papers and introduction to code

2.1 Part 1: Paper discussion (~60 minutes of the class)

2.1.1 Preparation:

We will have a short discussion of two papers. Get in groups of four, each group will then read a paper and present it to the other team.

Group a: Tredennick et al. (2021) This is a paper that some of you have read. But I think all of you should read it to be successful in this class.

Group b: Zuur, Ieno, and Elphick (2010) if you have already read Tredennick et al. (2021), this is the one you should read.

2.1.2 Deliverable:

You will give a short lecture ~25 to 30 minutes on the most important aspects of your paper to the other group. YOU ARE THE EXPERTS, so make sure you can answer questions from your “students”. You can use slides, but you don’t have to. You will self-govern your group. Each member can present, just two, or have a single person present.

You will have ~10 minutes at the beginning of class to ask questions and make a plan

2.2 Part 2: Github and R

Make sure you have downloaded the following:

  • Program R

  • RStudio

  • Know basics of R and RStudio: https://moctezumaii.github.io/SNR610/installation_instructions.html

  • RStudio

  • Create a Github account

  • Apply for GitHub Education

  • Join the course repository (you will be invited, accept the invite)

  • Confirm Codespaces access (we will provide guidance; Codespaces may be enabled by GitHub Education or by the organization)

2.3 Part 3: Look for papers

Please send me any and all papers that you find interesting, would be interested in my taking into account for the course!

You should start looking for the paper you want to lead the discussion on!

Other tasks to come

These are tasks that will come when we start the “collaborative section of the course”

  • Join the course repository (you will be invited, accept the invite 😄

  • Confirm Codespaces access (I will provide guidance)

References

Tredennick, Andrew T., Giles Hooker, Stephen P. Ellner, and Peter B. Adler. 2021. “A Practical Guide to Selecting Models for Exploration, Inference, and Prediction in Ecology.” Ecology 102 (6): e03336. https://doi.org/10.1002/ecy.3336.
Zuur, Alain F., Elena N. Ieno, and Chris S. Elphick. 2010. “A Protocol for Data Exploration to Avoid Common Statistical Problems.” Methods in Ecology and Evolution 1 (1): 3–14. https://doi.org/10.1111/j.2041-210X.2009.00001.x.