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Razieh Rafieijahed

Projet de recherche :

Understanding the Structure and attributes of boreal old-growth forests of Quebec (Canada) using airborne LiDAR

The old-growth forests contain a variety of structures and compositions, including diverse deadwood, large trees, and complex structures. These forests can serve as biodiversity hot spots and provide crucial ecosystem services that are scarce or absent in younger or managed stands. In recent years, the concept of old-growth forests has attracted the attention of the scientific community, managers, and even popular culture. Despite their unique characteristics between different biomes, few large-scale and spatially explicit information describing their attributes, e.g., forest age or keystone habitats such as deadwood and habitat trees (i.e., tree bearing tree-related microhabitats), are available. Forests in this biome typically have low tree species diversity, with many species present both at the start and end of forest succession. This apparent homogeneity complexifies the mapping of old-growth forest attributes. The Quebec government adopted a forest ecosystem management approach in 2013, intending to minimize the disparities between managed and natural forests. This process facilitates estimating the required evolution of forest management practices to meet the standards of ecosystem management. Therefore, identifying key old-growth forest attributes will help forest biodiversity and sustainable forest management. Our project has aimed to develop new tools to identify the boreal old-growth forest attributes using remote sensing data, and in particular airborne LiDAR data. Its objective is in line with two CFR (Centre for Forest Research) axes: Axis 2 – Populations and communities ecology, and conservation biology, and Axis 3 – Functioning and dynamics of forest ecosystems. This project will indeed contribute to better areas of high conservation values for biodiversity, while also helping to understand how natural disturbances shape the spatial heterogeneity of old-growth forests in North America. My integration into the CEF will allow me to make a significant contribution to these axes, which in return will gain in impact through CFR's large network of researchers and recognized dissemination capacities. Sharing this research work within the CFR community will also facilitate the development of new collaborations with its members, helping the project reach a new scale.