David Grenier-Héon

PhD Student

Centre for Forest Research (CEF), Université du Québec à Montréal (UQAM), Environment and Climate Change Canada (ECCC)

Alain Paquette (director, UQAM), Dominic Cyr (co-director, ECCC), Daniel Kneeshaw (co-director, UQAM)

grenier_heon.david@courrier.uqam.ca mail_outline

Interests and Expertise

Forest/urban/ecosystem ecology, allometric scaling, data analysis, LiDAR and remote sensing, ecological complexity

Short description of Project

Title : “Adapting cities to climate change: A revisited allometry-based approach to predict urban forests functions and services with remote sensing techniques” In the current context of global change, the unprecedented rates of urbanization raise serious concerns about the persistence of human well-being. The biophysical characteristics of cities exacerbate the climate change-induced stresses on urban human populations such as more frequent heat waves and increased air pollution. Adapting cities to climate change has thus become imperative for maintaining human well-being and reduce their impact on the environment. Urban forests (UF) are now identified as key elements to achieve that goal given the wide range of ecosystem services they provide (carbon sequestration, micro-climate cooling, etc.). Nonetheless, climate change and urbanization might also compromise UFs capacity to maintain its core function from which service provision depends. Future management strategies must not only aim at fostering UFs services but also ensuring their long-term sustainability. Currently, Canada does not have precise and robust tools to quantify how management, urban patterns and climate change impact the functioning and service provision of UFs at individual to ecosystem scale. Given the lack of proper mathematical tools, the assessment of UF services is mostly based on individual tree allometric equations derived from natural forests or data from the United States, which potentially incorporate substantial biases in Canadian urban environments. Focusing on Montreal and its main tree species, the core goals of this project are 1) develop adapted allometric models quantifying tree traits associated with key UF services in Canada (e.g. C sequestration and stocking, microclimate cooling, removal of air pollutants, etc.); 2) estimate the respective influences of species and site conditions on tree allometries; and 3) upscale and expand the allometry method to assess the state and energetic efficiency of the UF at the ecosystem level. This will be achieved by using cutting-edge remote sensing techniques and applying concepts borrowed from biophysics and complexity science to the study of the UF functions.

Short description of internship with partner

This project is conducted with the collaboration of Jakarto, a company from Montreal specializing into applying artificial intelligence and mobile LiDAR techniques to the 3D cartography of urban environments. As collaborators, Jakarto will provide data and expertise that will enable the processing of a large amount of point clouds which will certainly benefit the robustness and precision of the allometric models developed within the framework of this project.

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