Summary: | The Arctic Ocean is currently experiencing major and abrupt changes in its atmospheric and oceanic compartments due to climate change. The first emerging ecological consequences to the loss of sea ice are undeniable, such as increasing annual primary production (PP) globally in the Arctic Ocean. However, in some areas, studies suggest a decrease in productivity in response to a local intensification of the vertical stratification of the upper water column. The response of phytoplankton communities to climate change remains complex and difficult to predict, with potential dramatic impacts extending through all trophic levels of marine ecosystems. The primary objective of this thesis explores this fundamental question, with a particular emphasis on biogeography, phenology (i.e., the study of annual recurring biological cycles) and productivity of Arctic phytoplankton communities. More specifically, this study is based on two complementary research approaches: (1) the compilation and analysis of historical databases covering the vertical and spatial distribution, productivity and ecology of Arctic phytoplankton, and (2) the use of remote sensing data describing the biogeography, phenology and ongoing changes in Arctic phytoplankton communities. Based on a unique compilation of vertical profiles of chlorophyll a (chl a; i.e., 5206 stations), we documented the spatio-temporal variability of the vertical distribution of phytoplankton and the range of productivity regimes (from oligotrophic to eutrophic regions) across the Arctic Ocean. An empirical model has also been developed to predict the vertical distribution of chl a based on surface chl a values depending on season and the province of the Arctic Ocean. The benefits of this model allow us to improve satellite-derived PP estimates and improve our understanding of the ecology and phenology of phytoplankton communities. Particular attention has been focused on the mechanisms of formation and maintenance of subsurface chlorophyll maximum (SCM) and their contribution ...
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