1 Overview

This open text book provides a short introduction to Ecological Forecasting for advanced undergraduate students. It was developed for the 3rd year Quantitative Biology course (BIO3019S) offered by the Biological Sciences Department at the University of Cape Town. A brief introduction to the course in general can be found here.

1.1 General

This book provides a very brief introduction to the framework for Ecological Forecasting. As a course it is taught over two weeks, so this really is a minimalist introduction. The focus is on providing a broad overview of the general framework and motivation for ecological forecasting, but doesn’t delve too deeply into the more gory theoretical and statistical details. Ecological Forecasting is used as a framework to highlight various themes and principles that are increasingly important for quantitative biologists - understanding how we inform or make decisions; managing data; working reproducibly; propagating, understanding and reducing uncertainty, etc.

Not all of this is fun and exciting, but it is important for quantitative biologists to know. Hopefully by the end of the module you’ll see the value in it all - both for you as an individual and for science and society in general.

The core outcomes/concepts you’ll come away with:

  • To be able to situate the role of models and the importance of forecasting in science and ecological decision making
  • Familiarity with the concepts and understand the need for Open, Reproducible Science
  • Familiarity with The Data Life Cycle
  • Familiarity with the value and flexibility of Bayesian statistical methods
  • Some familiarity with sources of uncertainty and the need to characterize, propagate, analyze, reduce and present uncertainties when forecasting


1.2 Information for the BIO3019S class of 2025

Lectures

Lectures will be held live in BIO LT in the HW Pearson Building 12:00 - 12:45 from 4 - 15th August.


Practicals

There is only one practical exercise for this module (see section 12), which will be run 2-5PM on Tuesday the 12th August. You will need to spend half an hour setting up the required software on your laptops before Monday the 11th August!!! See instructions below.

Your report on the practical will be due on Tuesday, 19th August - You will be evaluated on how well you completed the Github task during the practical and your answers to a short set of questions about the analyses. Answering the questions shouldn’t take more than half an hour.

You need to install and set up RStudio and Github and test your setup. You can find the step-by-step instructions in section 11. This may be a bit tedious, but there’s no other option really. I’ve done my best to make it as painless as possible. It should take you about half an hour if all goes well… (less if you have R and RStudio installed already, but please make sure they are the latest versions!).

PLEASE DO THE SETUP BEFORE WE MEET!!! I will check in on Monday the 11th August to see if people are having issues, but don’t expect my help if you haven’t tried by yourself first. Trust me, I will be able to tell…


Readings and Discussions

  • You are expected to read M. C. Dietze et al. (2018) for Tuesday the 12th August. You can download it here. You will need to answer a few questions beforehand on this Google Form.


1.3 Preparation

The following 4 minute video will give you a glossy overview of what most of this module is about:


1.4 A bit about the author

I’m an ecologist who has become more quantitative through time, but has little formal training in quantitative methods (i.e. I’ve learnt by doing over the past 20 years). As such, I still make elementary mistakes. In fact, the entry requirements for this course are beyond my formal training, so you may have much to teach me! If you spot any errors, confusion or contradictions, please let me know and I’ll get back to you and/or update the course notes accordingly. Hopefully by the end of the course you can suggest changes directly using pull requests to the GitHub repository for the course notes.


1.5 Acknowledgements and further reading:

The following resources were instrumental in pulling this material together and are worth spending time exploring. Sources are cited throughout the course notes, so check out the references at the end of each section and the end of the course notes for more.


All code, images, etc can be found here. Only images and other materials that were made available online under a non-restrictive license (Creative Commons, etc) or for which I have express permission have been used. Sources are attributed throughout. Content without attribution is my own and shared under the license below. If there are any errors or any content you find concerning with regard to licensing, or that you find offensive, please get in touch. Any feedback, positive or negative, is welcome!


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

References

Dietze, Michael C, Andrew Fox, Lindsay M Beck-Johnson, Julio L Betancourt, Mevin B Hooten, Catherine S Jarnevich, Timothy H Keitt, et al. 2018. “Iterative near-term ecological forecasting: Needs, opportunities, and challenges.” Proceedings of the National Academy of Sciences of the United States of America 115 (7): 1424–32. https://doi.org/10.1073/pnas.1710231115.