Organized sessions

2. Complexity matters: subjectivity as practice in contemporary biology

Leroux, E., Mélançon, V., Banville, F., Brémaud, J., Robitaille, F., & Gholamhosseini, M. (2023, March 16-17)
33rd Biology Symposium of the University of Montreal, Montreal, Qc, Canada
event

I was part of the student committee in charge of organizing the 33rd symposium of the department of biological sciences of the University of Montreal. This event aims to promote students’ research in the department and dedicates its annual theme to key contemporary scientifical and societal questions. We invited keynote speakers and organized a round table on the issues of subjectivity and complexity in science. We also organized a fully vegetarian buffet for more than 200 ravenous participants with waste minimization in mind. Picture credit: Tanya Strydom.

1. Space Oddity: Thinking about ecological networks across space

Dansereau, G., Banville, F., & Strydom, T. (2022, August 14-19)
ESA & CSEE Joint Meeting (Inspire session), Montreal, Qc, Canada
event, inspire session, Space Oddity

Contributed talks

8. Quoi, quand et où manger ? À la découverte des interactions trophiques entre contraintes et incertitudes

Banville, F., Gravel, D., & Poisot, T. (2024, March 21-22)
34th Biology Symposium of the University of Montreal, Montreal, Qc, Canada
event, slides

7. Quoi, quand et où manger ? À la découverte des interactions trophiques entre contraintes et incertitudes

Banville, F., Gravel, D., & Poisot, T. (2024, February 19-21)
2024 QCBS Symposium, Montreal, Qc, Canada
event, slides

6. Comment les réseaux de prédateurs et de proies sont-ils structurés dans les milieux naturels?

Banville, F., Gravel, D., & Poisot, T. (2023, May 8-12)
90e congrès de l’ACFAS, Montreal, Qc, Canada
event, slides, video

5. What constrains food webs? A maximum entropy model for predicting their structure with minimal biases

Banville, F., Gravel, D., & Poisot, T. (2022, August 14-19)
2022 Annual Meeting of the Ecological Society of America (ESA), Montreal, Qc, Canada
event, slides

4. Food webs of maximum entropy: A story of ecology and stochasticity

Banville, F., Gravel, D., & Poisot, T. (2022, March 25)
32nd Biology Symposium of the University of Montreal, Montreal, Qc, Canada
event, slides

3. Predicting networks of species interactions

Banville, F., Gravel, D., & Poisot, T. (2020, October 22)
IVADO Digital October 2020, virtual
event, slides, video

2. How to estimate network structure without interaction data

Banville, F., MacDonald, A., Gravel, D., & Poisot, T. (2020, February 19)
Extreme Climate Events Symposium 2020, Toronto, On, Canada
event, slides

1. How to estimate network structure without data

Banville, F., MacDonald, A., Gravel, D., & Poisot, T. (2019, December 18-20)
10th Annual QCBS Symposium, Montreal, Qc, Canada
event, slides

That was my first scientific talk! I presented our framework to predict food-web structure across space using simple food-web models and data on species richness, without using species interactions data. Since then, our framework greatly evolved, going from mechanistic ecological models to maximum entropy. I remember listening to Les Antipodes (the new album of Les Cowboys Fringants) on loop (and quite loudly to the detriment of my eardrums) as a stress coping mechanism before presenting.

Lightning talks

4. Interactions entre espèces : une histoire d’écologie et de hasard

Banville, F., Gravel, D., & Poisot, T. (2022, March 29)
My IVADO research project in 180 seconds, Montreal, Qc, Canada
event, slides, video

A fascinating predator-prey food web flourishes in the Lion King universe, where insects were opportunistically incorporated into a lion’s diet after a drastic change in its lifestyle. Could this exceptional interaction have been anticipated? To document feeding interactions across large spatial and temporal scales, we often need to rely on statistical models, which are more powerful when the structure of the entire food web is known beforehand. The principle of maximum entropy can help us reconstruct the emerging structure of food webs by finding the most complex network configuration given prior ecological information about that system.

3. Predicting food webs across space: First estimates of food-web structure derived from species richness

Banville, F., Gravel, D., & Poisot, T. (2021, October 28)
IVADO Digital October 2021, virtual
event, video

2. Trophic-METE: A parsimonious theory of food-web structure

Banville, F., Gravel, D. & Poisot, T. (2020, December 14-16)
11th Annual QCBS Symposium, virtual
event, slides

1. Analyzing species interaction networks in Julia

Banville, F., Vissault, S., Bélisle, Z., Hoebeke, L., Stock, M., Szefer, P., & Poisot, T. (2020, July 29-31)
Juliacon 2020, virtual
event, slides, video
Mangal.jl, EcologicalNetworks.jl, EcologicalNetworksPlots.jl

JuliaCon 2020 was supposed to take place in Lisbon (Portugal), but that was before a global pandemic would occur. I ended up presenting virtually three packages built by the Poisot Lab (`Mangal.jl`, `EcologicalNetworks.jl` and `EcologicalNetworksPlots.jl`) to analyze and visualize species interaction networks in Julia. I’m still dreaming about Lisbon’s beaches to this day.

Posters

2. Given limited knowledge, what can we say about a food web’s properties?

Banville, F., Gravel, D. & Poisot, T. (2021, December 8-10)
12th Annual QCBS Symposium, virtual
event, poster

1. Trophic-METE: A parsimonious theory of food-web structure

Banville, F., Gravel, D. & Poisot, T. (2020, December 14-16)
11th Annual QCBS Symposium, virtual
event, poster

The structure of food webs can be derived using known ecological information such as the total numbers of species, interactions, and individuals, as well as the network’s area and total energy transfer. These variables constrain the space of feasible networks by narrowing down the number of plausible configurations. Although the project of building a maximum entropy theory of food-web structure based on these five variables is still a work in progress, we were able to develop a robust framework to predict food-web structure based solely on the total numbers of species and interactions.