When it comes to designing a statistical model, a lot of uncertainty comes to mind. In December, BIOS2 will offer a workshop which will give you some helpful strategies for fitting and understanding your regression models. Led by Dr Andrew MacDonald, the workshop will happen during 3h in two days on December 12 and 14, 2023, with lots of time for questions and discussions of your own work. This workshop should be accessible to any graduate student, though prior experience in R is helpful. The workshop will be in English, with support in French.
To register, fill out the form linked at the end of this page by December 9th, 2023.
What’s zero? When and how to center a variable?
What are the units? Scaling a variable and why you should do it.
What does it mean? Making predictions.
Does it depend? Fitting and visualizing interactions.
What do you expect? Simulating datasets.
The secret weapon: fitting the same model multiple times.
When: 13h EST, Tuesday 12 Dec and Thursday 14 Dec, 2023.
Duration: 3h each day (total of 6 hours)
Where: Online - information to be sent one day before the workshop
Registration deadline: December 9th, 2023
Machine Learning is not a black box (unless we want to!). If you ever wondered what the results of a species distribution model actually mean, BIOS² is here to help you! On October 6, 2023, at 1pm – 3pm EDT, Professor Timothée Poisot will host a short and very participatory workshop on how to interpret machine learning models applied to SDMs.
In this workshop, participants will build a simple model to predict the distribution of the raccoon in the South of Québec based on observations. Rather than focus on “what is the prediction?”, we will ask questions about “why”. Specifically, by mixing the presentation of the results with mini group discussions, we will question how the model works, when it is acceptable to apply our best judgment and ignore some performance metrics, and how we can think about interpretable machine learning to improve model transparency. Attendees will get access to all the code and data at the end of the workshop.
The workshop will be hosted virtually, and information about access will be sent out to registered participants one day before the event.
The BIOS² training program offers an Introductory workshop to Python for R users. The workshop will be presented on May 15 and 16, 2023 by Vincent Beauregard, data specialist at Biodiversité Québec.
The course aims to provide the basics of Python and to familiarize participants with the tools and libraries relevant to computational ecology. Sessions will build on participants’ prior knowledge of the R language to facilitate learning. Topics will include data manipulation with Pandas, data visualization with Matplotlib, and data analysis with Numpy and Scipy. Students will also learn how to break their code into functions and work with classes in Python.
Vincent Beauregard is a technical coordinator, and a specialist in infrastructure, biodiversity data interfaces and spatial data from remote sensing at Biodiversité Québec. He is interested in the automation of data processing schemes.
What: Introductory workshop to Python When: May 15 and 16, 2023 @ 1 pm – 4 pm (your time here) Where: Online and at Université Laval Language: English (bilingual Q&A and discussion) Fees: free – offered only for participants of the Advanced Field School in Computational Ecology. Registration deadline: May 11, 2023 Registration link: https://forms.office.com/r/kWvCrdpbus
The BIOS² and Hydro-Québec have partnered up to offer a workshop on environmental impact assessment on May 4, 2023 at 1 pm EDT. This workshop is free and open to all and is part of the training offered to BIOS² fellows.
This session will be a guided tour of Hydro-Québec’s perspective on biologists’ involvement in major hydroelectric projects. The main milestones of the environmental impact assessment process will be illustrated using multiple examples of projects that favoured biodiversity and were inspired by the field of applied ecology.
This workshop is the first activity of a series that will be done in collaboration with Hydro-Québec. In the fall, BIOS2 will be organizing a working group whose objective will be to propose solutions for better integration of ecological knowledge and biodiversity data into Hydro-Quebec’s environmental impact studies. The working group will be carried out in consultation with relevant stakeholders and in collaboration with biologists working at Hydro-Quebec. Trainees who are interested in participating in this working group are strongly encouraged to attend the proposed workshop on May 4.
About the trainers
Alexandre Beauchemin has been working for Hydro-Québec since 2004. He studied biology at McGill University and obtained his Master’s degree in Environmental Sciences from Université du Québec à Montréal. Amélie Drolet studied wildlife biology at McGill University and obtained her Master’s degree in Biology from Université Laval. After graduating she worked for several years in consulting before joining Hydro-Québec in 2021.
What: Environmental Impact Assessment workshop When: May 4, 2023 – 1pm – 3:30pm EDT (your time here) Where: Online Language: English (bilingual Q&A and discussion) Fees: free (places are limited). Registration deadline: May 3, 2023 Registration link: https://forms.office.com/r/MpYunysQLw
BIOS² is proposing a series of two workshops on Indigenous Awareness and Collaborative Research in an indigenous context. These trainings aim to provide an understanding of the historical context that has shaped the relationship between Indigenous and non-Indigenous people in Canada, in order to develop an environment of respect and collaboration. The workshops will be offered online by Catherine-Alexandra Gagnon (Érébia) on April 18th and 19th (2023).
As a great start to 2023, BIOS² will present an Introduction to Programming workshop on January 17 and 19, 2023 to introduce new BIOS2 Fellows and everyone else interested to the basics of computer programming, working with data and the skills needed to be productive in collaborative research projects.