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AC

Anna Crofts

Student Speaker | Étudiant.e
To date, Québec’s forests have experienced major transformations as a result of human activities and ongoing anthropogenic pressures promise to further alter forest biodiversity patterns. Contemporary forests grow on lands with variable histories of land-use (e.g., timing and intensity of logging) and long-lasting legacies of land-use may modify forest response to changing climatic conditions. Identifying patterns in forest communities along spatial climatic gradients, across different logging histories, is a crucial first step for predicting how these forests will respond to future global change. While ecological questions are often examined via field-based methods, due to their labor-intensive nature and associated logistical limitations, they are restricted in spatial and temporal coverage. Hyperspectral imaging, a new remote-sensing approach, promises rapid biodiversity assessment across large spatial extents that can potentially fill the temporal and spatial gaps associated with field-based approaches. However, to date, we are limited in our ability to interpret hyperspectral data without corresponding field-based data. Here, I will present the conceptual framework for applying hyperspectral imagery to forest biodiversity assessment in south-eastern Québec. Specifically, I will outline my proposal to examine the relationship between hyperspectral data and field-based biodiversity metrics (e.g., taxonomic and functional diversity and composition) and, subsequently, to apply hyperspectral data to examine the effects of logging history and climate (e.g., elevation) on forest diversity and composition at Parc national du Mont Mégantic. To contextualize predicted trends, I will present preliminary findings on how field-based taxonomic diversity and composition vary across the two gradients of interest.