NEOLab is the Numerical Ecosystems and Oceanography Laboratory run by Frédéric Maps at Université Laval, Québec City (Canada).
Our lab's focused on the study of the marine environment through the use of numerical methods. We study (some) physical and (many) biological processes as well as the resulting/emerging bio-physical interactions. The use of numerical models and algorithmic approaches forms the common thread of our research.
Frederic Maps is an oceanographer who was formed as a multidisciplinary environmental scientist, and our group of students and early career scientists shares this common interdisciplinary interest.
NEOLab is an academic research laboratory where (under)graduate students can quench their thirst for answers, mainly by asking more questions...
We develop interdisciplinary research projects led by several Canadian and international collaborators from academia and governmental institutions, within which students can fully develop their own path.
Our ultimate goal is to contribute together to the common edification of scientific knowledge about the state and functioning of the rapidly changing Northern marine ecosystems. We also aim at fostering the transfer of information and development of solution based on cutting-edge observational and experimental science.
Our research projects span several orders of complexity, from physiological processes that operate within the individual organisms to properties of complex trophic networks that emerge in response to the environment.
All of them have in common the need to better understand how the articulation of several mechanisms together allows natural systems to respond to their variable environment. We think that numerical approaches (models and algorithms) can be very useful to identify and quantify the crucial components producing theses complex responses.
The major subjects of research that are currently pursued in NEOLab are:
- Biogeochemistry of northern seas
- Trophic networks dynamics
- Trait-based approaches to plankton ecology
- Integration of individual organisms images and machine learning approaches
- Community-based development of modelling tools for Arctic peoples
