Ariane Roberge
Université de Montréal
Ph.D. candidate
Supervisor: Etienne Laliberté
Erik Veneklaas, University of Western Australia
Start: 2023-09-01
Personal page
Ph.D. candidate
Supervisor: Etienne Laliberté
Erik Veneklaas, University of Western Australia
Start: 2023-09-01
Personal page
Project
Aerial eco-phenotyping : Characterization of tree fitness in response to water useThe acceleration of climate change is a reality we are facing, with increasingly serious consequences for biodiversity. In this context, assisted migration, a conservation strategy aimed at artificially expanding the range of individuals, can help plant and animal species adapt to environmental change. To understand how different species can benefit from this conservation method, it is important to characterize their adaptive value in changing environmental contexts. Some plant species, such as those more tolerant of periods of drought or frost, may be particularly well suited to assisted migration. However, characterizing the adaptive value of long-lived species can be a time-consuming and costly process, highlighting the need to develop more time-efficient methods to achieve this (Laughlin et al., 2020). It is with this in mind that this research project becomes relevant. It aims to develop remote sensing approaches using drones to characterize the effects of water use on the adaptive value of trees, particularly in terms of their growth and survival. In ecophysiology, the processes influencing tree phenology are well documented. However, the majority of studies on this topic focus on leaf emergence (Polgar & Primack, 2011; Zohner et al., 2020), and few on senescence (Moon et al., 2022; Zani et al., 2020). Yet this process is just as important, not least because it determines the end of the growing season and enables nutrients to be recycled (Estiarte & Peñuelas, 2015). What environmental mechanisms influence the onset of senescence? How can we explain inter- and intraspecific variations? The first part of the study will explore these questions, the answers to which currently remain uncertain. The Kunming-Montreal Agreement, adopted as part of the 15th Conference of the Parties (COP15) to the United Nations Convention on Biological Diversity, has as its second target to undertake the restoration of at least 30% of degraded natural environments by 2030 (Convention on Biological Diversity & United Nations Environment Programme, 2022). In this context, it becomes all the more relevant to study the possibilities of assisted migration in order to ensure the long-term success of restored environments. My doctoral research will therefore focus on the study of water stress in vegetation under restoration conditions, in order to better understand how the adaptive value of planted trees is affected under such conditions. For the implementation of assisted migration, it will be necessary to test the performance of a variety of genotypes from different climatic regions, to determine which respond best to this stress. By addressing these themes, this research will make it possible to: • develop and validate remote sensing methods for more efficient phenotyping in plant ecology; • understand how water use influences tree performance and survival; • contribute to the development of effective restoration and assisted migration strategies. In summary, this project aims to fill important gaps in our understanding of the adaptive value of trees in the face of water stress, by developing innovative drone-based remote sensing methods. These methods will not only accelerate the phenotyping of plant species, but also provide essential data to guide ecological restoration and assisted migration strategies in a climate change context.
