Portrait of Étienne Laliberté

Étienne Laliberté

Associate Academic Member
Full Professor, Université de Montréal, Department of Biological Sciences
Research Topics
Computer Vision
Website
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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

Altimas Carol
Master's Research - Université de Montréal
Co-supervisor :
Tegan Maharaj
Antoine Caron-Guay
Independent visiting researcher - Université de Montréal
Github
Sabrina Demers-Thibeault
Independent visiting researcher - Université de Montréal
Arthur Ouaknine
Postdoctorate - McGill University
Principal supervisor :
David Rolnick
Website
Github
Google Scholar

Publications

Early Detection of an Invasive Alien Plant (Phragmites australis) Using Unoccupied Aerial Vehicles and Artificial Intelligence
Antoine Caron-Guay
Mickaël Germain
Étienne Laliberté
The combination of unoccupied aerial vehicles (UAVs) and artificial intelligence to map vegetation represents a promising new approach to im… (see more)prove the detection of invasive alien plant species (IAPS). The high spatial resolution achievable with UAVs and recent innovations in computer vision, especially with convolutional neural networks, suggest that early detection of IAPS could be possible, thus facilitating their management. In this study, we evaluated the suitability of this approach for mapping the location of common reed (Phragmites australis subsp. australis) within a national park located in southern Quebec, Canada. We collected data on six distinct dates during the growing season, covering environments with different levels of reed invasion. Overall, model performance was high for the different dates and zones, especially for recall (mean of 0.89). The results showed an increase in performance, reaching a peak following the appearance of the inflorescence in September (highest F1-score at 0.98). Furthermore, a decrease in spatial resolution negatively affected recall (18% decrease between a spatial resolution of 0.15 cm pixel−1 and 1.50 cm pixel−1) but did not have a strong impact on precision (2% decrease). Despite challenges associated with common reed mapping in a post-treatment monitoring context, the use of UAVs and deep learning shows great potential for IAPS detection when supported by a suitable dataset. Our results show that, from an operational point of view, this approach could be an effective tool for speeding up the work of biologists in the field and ensuring better management of IAPS.
2024-06-06
bioRxiv (preprint)
doi.org
Arbuscular and ectomycorrhizal tree seedling growth is inhibited by competition from neighboring roots and associated fungal hyphae
V. Parasquive
Jacques Brisson
Étienne Laliberté
P. L. Chagnon
2024-05-28
Plant and Soil (published)
doi.org
Coordination among leaf and fine-root traits along a strong natural soil fertility gradient
Xavier Guilbeault-Mayers
Hans Lambers
Étienne Laliberté
2024-05-18
Plant and Soil (published)
doi.org
Foliar spectra accurately distinguish most temperate tree species and show strong phylogenetic signal
Florence Blanchard
Anne Bruneau
Étienne Laliberté
2024-04-20
American-Eurasian journal of botany (published)
doi.org
Coordination among leaf and fine root traits across a strong natural soil fertility gradient
Xavier Guilbeault-Mayers
Hans Lambers
Étienne Laliberté
2023-11-05
bioRxiv (preprint)
doi.org
Root phosphatase activity is coordinated with the root conservation gradient across a phosphorus gradient in a lowland tropical forest
Xavier Guilbeault-Mayers
Étienne Laliberté
Soil phosphorus (P) is a growth-limiting nutrient in tropical ecosystems, driving diverse P-acquisition strategies among plants. Particularl… (see more)y, mining for inorganic P through phosphomonoesterase (PME) activity is essential, given the substantial proportion of organic P in soils. Yet the relationship between PME activity and other P-acquisition root traits remains unclear. We measured root PME activity and commonly-measured root traits, including root diameter, specific root length (SRL), root tissue density (RTD), and nitrogen concentration ([N]) in 18 co-occurring trees across soils with varying P availability to better understand trees response to P supply. Root [N] and RTD were inversely related, and that axis was related to soil P supply. Indeed, both traits correlated positively and negatively to PME activity, which responded strongly to P supply. Conversely, root diameter was inversely related to SRL, but this axis was not related to P supply. Suggesting that limiting similarity influenced variation along the diameter-SRL axis, explaining high local trait diversity. Meanwhile, environmental filtering tended to impact trait values along the root [N]-RTD axis. Overall, P availability indicator traits like PME activity and root hairs only tended to be associated with these axes, highlighting limitations of these axes in describing convergent adaptations at local sites.
2023-10-31
bioRxiv (preprint)
doi.org
Study Beekeeping potential data and development of a decision support system involving a web mapping platform
Philippe Doyon
Mickaël Germain
Guy Armel Fotso Kamga
Étienne Laliberté
Yacine Bouroubi
Madeleine Chagnon
The role of a decision support system is to gather, synthesize and present information in order to make informed decisions. In this project,… (see more) a mapping platform and a decision support system are proposed to present beekeeping data in Quebec. A complete review of the data and factors influencing honey production must first be carried out. The decision support system will be designed according to the nature of the data and access to available technologies. Continuous and real-time data management must be configured to make data interoperable. Multi-dimensional data loading tools will need to be configured to display data and analyses in a dashboard. Beekeepers will be able to optimize or move their hives according to their interpretation of the results displayed in the decision support system.
2023-07-16
IEEE International Geoscience and Remote Sensing Symposium (published)
doi.org