Portrait of Étienne Laliberté

Étienne Laliberté

Associate Academic Member
Etienne.laliberte@mila.quebec
Full Professor, Université de Montréal, Department of Biological Sciences
Research Topics
Computer Vision
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Biography

Etienne Laliberté is a full professor in the Department of Biological Sciences at Université de Montréal, a member of the Institut de recherche en biologie végétale (IRBV), and the Canada Research Chair in Plant Functional Biodiversity. He also heads the Canadian Airborne Biodiversity Observatory (CABO).

Laliberté’s current research focuses on the development of new approaches for vegetation monitoring (plant biodiversity and carbon) based on high-resolution remote sensing using drones and computer vision. He is particularly interested in applications of this technology that can help mitigate biodiversity loss and climate change, and that can have a rapid and widespread impact

Current Students

Carol Altimas
Master's Research - Université de Montréal
Co-supervisor :
Tegan Maharaj
carol.altimas@mila.quebec
Hugo Baudchon
PhD - Université de Montréal
Principal supervisor :
Chris Pal
hugo.baudchon@mila.quebec
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LinkedIn
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Antoine Caron-Guay
Independent visiting researcher - Université de Montréal
antoine.caron-guay@mila.quebec
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Sabrina Demers-Thibeault
Independent visiting researcher - Université de Montréal
sabrina.demers-thibeault@mila.quebec
Simon-Olivier Duguay
Master's Research - Université de Montréal
simon-olivier.duguay2@mila.quebec
Github
Arthur Ouaknine
Postdoctorate - McGill University
Principal supervisor :
David Rolnick
arthur.ouaknine@mila.quebec
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Paula Uzcategui-Leon
Master's Research - Université de Montréal
paula.uzcategui-leon@mila.quebec
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LinkedIn

Publications

Evolutionary history explains foliar spectral differences between arbuscular and ectomycorrhizal plant species
Johanna R. Jantzen
Étienne Laliberté
Alexis Carteron
Rosalie Beauchamp‐Rioux
Florence Blanchard
Anna L. Crofts
Alizée Girard
Paul W. Hacker
Juliana Pardo
Anna K. Schweiger
Sabrina Demers‐Thibeault
Nicholas C. Coops
Margaret Kalácska
Mark Vellend
Anne Bruneau
Leaf spectra are integrated foliar phenotypes that capture a range of traits and can provide insight into ecological processes. Leaf traits,… (see more) and therefore leaf spectra, may reflect belowground processes such as mycorrhizal associations. However, evidence for the relationship between leaf traits and mycorrhizal association is mixed, and few studies account for shared evolutionary history. We conduct partial least squares discriminant analysis to assess the ability of spectra to predict mycorrhizal type. We model the evolution of leaf spectra for 92 vascular plant species and use phylogenetic comparative methods to assess differences in spectral properties between arbuscular mycorrhizal and ectomycorrhizal plant species. Partial least squares discriminant analysis classified spectra by mycorrhizal type with 90% (arbuscular) and 85% (ectomycorrhizal) accuracy. Univariate models of principal components identified multiple spectral optima corresponding with mycorrhizal type due to the close relationship between mycorrhizal type and phylogeny. Importantly, we found that spectra of arbuscular mycorrhizal and ectomycorrhizal species do not statistically differ from each other after accounting for phylogeny. While mycorrhizal type can be predicted from spectra, enabling the use of spectra to identify belowground traits using remote sensing, this is due to evolutionary history and not because of fundamental differences in leaf spectra due to mycorrhizal type.
2023-03-23
New Phytologist (published)
doi.org