The Computational Ecology Lab’s Mission is to develop engaging, cutting-edge open science. We engage in thought-provoking collaborative research projects on different aspects of community assembly, organisation and stability. Our research collaborations encompass experts from many differents disciplines in different research labs across the globe. We aim at making our research as open as possible not only by sharing our results on open fora such as international scientific conferences and published papers, but also by openly sharing the code produced in each of our projects, which you can find in this website.
We want to produce high quality research in an uncompromising and highly transparent manner.
We believe in an open, inclusive, and encouraging scientific environment emerging from a free and respectful exchange of ideas from all our members.
As a researcher you are expected to develop your knowledge and skills, make incremental progress on your projects, and contribute to the running of the lab. There are no specific “set hours” for the lab, but generally I expect people to be around from 10-4:30. We benefit from a flexible schedule to accomodate caregiver responsibilities, personal fitness, etc. You are expected to attend 1:1, subgroup, and group meetings. The lab is very flexible with rescheduling, just send a message ahead of time and we can likely accomodate it.
Every week, each lab member has a one-on-one meeting with me to talk about current progress, issues, etc. To make the most of these meetings I request that you make an agenda and send it to me in advance of our meeting. In addition, my door is always open, and my mentality is that I work for my students and staff.
As transparency and openness are key values to the lab, sharing our information both within the lab and externally to the scientific community is a top priority. Lab members always make their data, materials, processing details available to the public through deposition to various public repositories. Lab code is made accessible through GitHub. We also deposit our code and data on public repositories as requested by the journals that publish our research. Examples of these platforms are:
As a scientist, it should be a pleasure to keep up with current literature. At the computational ecology lab we encourage the pursuit of knowledge in general, regardless of whether it is “useful” to your project. As such, science become a lifestyle, in the sense of ever wanting to learn and discover more things, rather than a target activity in which everything is only seem from the perspective of finishing a project or completing an assignment. We believe should dedicate a few hours each week to scanning and reading new preprints and journal articles. This activity helps increase one’s breadth of knowledge.
I like to take an active role in the preparation of all our manuscripts and love to help people clarify their writing for fellowships and job applications. Many learners are often afraid to show PIs anything other than finished work. This is a mistake! I expect a draft to be very rough and a starting point to grow from. If you think it’s time to start a paper, let’s get in a room (or a zoom) and start hammering out an outline!
Panels for figures should be as scripted as possible. Generally, as we write, I prefer that you embed the figures in the document and share a folder with the raw files (images, Keynote files, illustrator files, etc). Figure legends should be extremely comprehensive and include all the information needed to fully understand all the information in the figures without any reference to the text.
I believe that conversations about positions in author order should occur early in a project. Communicate with me and I will help navigate these conversations with collaborator labs. I err on having more authors on a paper: everyone with a meaningful contribution must be included.
Sharing results openly and swiftly are keys to 21st century science communication. The real end goal of any research is to get the work out there for others to build on, not to publish in journals. We share openly at conferences, but recognize the role of publication as a more permanent and accessible form of communication. In publishing our work, we welcome peer review, but most importantly, we also maintain our own high scientific standards by posting preprints when we judge them to be ready for sharing.
We benefit from feedback on our manuscripts, most often in the form of journal organized peer review, and we are enthusiastic about offering our feedback to others to help improve their manuscripts.
For our lab, we are motivated by the ability to potentially improve:
the clarity of how the scientific results are communicated
the contrast between what is supported by results and what is speculative
the speed and transparency of the publication process
These values represent a change of focus from some traditional ideas of peer review that center on gatekeeping (“does this paper belong in nature?”). We want to write reviews that are constructive, empathetic, and respectful - and we think that this can be done in a way that enhances the rigour of the manuscript.
Peer review is an important training opportunity for lab members in scientific thinking and writing.
On the other side of the coin, How do we react to our reviews? We try to put ourselves in the shoes of the review. We assume the best intentions and adopt a default state that this offers us an opportunity to clarify the communication of our science.
My mentorship philosophy is simple: I treat all my students as my peers and scientific collaborators. I am enthusiastic about sharing knowledge and I believe that the most effective way of doing science is to engage in constant scientific discussions. I aim at all times at providing the most conducive and fertile grounds for the scientific development of all my students and postdocs.
Talk about your work openly. Share early. A key component to information transparency is getting it out there. People should present their work at conferences as they are great ways to communicate our results and get other people excited about our work. Conferences are important to build your network as well as your science communication skills. I think everyone should attend 1-2 conferences a year.
We strive to give clear presentations that explain our scientific results to new audiences. We know that delivering a good presentation is hard work. Below we outline advice for structuring and delivering presentations, focused primarily on external audiences, noting modifications for internal audiences below. When planning a new presentation consider first:
1) Who is your audience?
(graduate students from your program, specialists in your field at a conference, people evaluating you for a job/fellowship, etc)
2) What question does your presentation answer?
(is the answer a key data take away, a clear next step you want to take, a shift in how we approach a problem, etc)
The key to delivering a good presentation is to structure it clearly around a single and straigthforward main message. We want to make sure that we are delivering our main question (occasionally questions) in a way that the audience can understand and appreciate.
A good presentation is NOT about showing off or overwhelming folks with data or results, it is about transmitting the main message as clearly and easy to understand as possible.
When structuring your presentations consider the following:
If you are struggling with how your work fits this framework, ask for help and we will talk about ways to structure your presentation. It is important to note that sometimes in science, especially if we are being ambitious, the HOW section can be about to how you are not able to answer the question, yet! That is ok! You should still relate your results to the barrier you identified and provide context to the broader question you are asking. This is an opportunity to point the way forward with a strong WHERE section. Amongst the most commonly encountered issues is that too much time spent on the details of HOW and not enough on WHY/WHAT. Defining the scope of the question and the key barriers to answering it takes a lot of practice to get right. Another problem observed frequently is that the scope of the WHY/background section is often not right for the actual question the presentation seeks to answer: people tend to give generic background that is not actually relevant to the question they are addressing. In building a presentation around WHY/WHAT/HOW/WHERE, your presentation should develop a coherent narrative arc. This should naturally orient the audience as to what the stakes are for the field or what contrast you are trying to draw to previous work. This structure basic structure is expanded for longer talks as well. In a longer talk, there is usually a single broad narrative arc with sections of the talk that connect to each other. Ideally the talk flows so that each segment connects to the next with a WHY/WHAT/HOW/WHERE->WHY… structure.
Once again, we know that delivering a good presentation is hard work. Therefore, practice, feedback, iteration are key to deliverying good presentations. In practicing, you will receive advice from many people - be grateful. It is wonderful to get feedback. But, don’t listen to all of it (even the advice on this page!). Pay special attention to those who say they didn’t understand parts of your talk - this is the most valuable feedback: use it to refine and clarify your message.
An overarching philosophy of mine is “Minimize text on slides”. Avoid walls of text bullet points and especially reading walls of text. The main text on a slide should be a single Title sentence at the top of the slide. This should be different for every slide and be a single sentence using simple and active language. You should be able to read the titles of the slides only and have a pretty good understanding of the talk.
Be nice and don’t get stressed if someone misinterprets the talk (that is an opportunity to clarify for next time). Try not to be defensive in answers. It’s hard work! Start by rephrasing the question.
We’re all growing, we’re all trying to live up to our core values, and essential to this is an emphasis on feedback. I am always open to feedback on how the lab and I can function better as long as it is respectful.
The tips and guidance provided above has been greatly inspired by the Fraser Lab: