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Annual boom-bust cycles of polar phytoplankton biomass revealed by space-based lidar

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Polar plankton communities are among the most productive, seasonally dynamic and rapidly changing ecosystems in the global ocean. However, persistent cloud cover, periods of constant night and prevailing low solar… Click to show full abstract

Polar plankton communities are among the most productive, seasonally dynamic and rapidly changing ecosystems in the global ocean. However, persistent cloud cover, periods of constant night and prevailing low solar elevations in polar regions severely limit traditional passive satellite ocean colour measurements and leave vast areas unobserved for many consecutive months each year. Consequently, our understanding of the annual cycles of polar plankton and their interannual variations is incomplete. Here we use space-borne lidar observations to overcome the limitations of historical passive sensors and report a decade of uninterrupted polar phytoplankton biomass cycles. We find that polar phytoplankton dynamics are categorized by ‘boom–bust’ cycles resulting from slight imbalances in plankton predator–prey equilibria. The observed seasonal-to-interannual variations in biomass are predicted by mathematically modelled rates of change in phytoplankton division. Furthermore, we find that changes in ice cover dominated variability in Antarctic phytoplankton stocks over the past decade, whereas ecological processes were the predominant drivers of change in the Arctic. We conclude that subtle and environmentally driven imbalances in polar food webs underlie annual phytoplankton boom–bust cycles, which vary interannually at each pole. Phytoplankton productivity is high in the polar oceans. Lidar observations from 2006–2015 reveal that phytoplankton biomass was characterized by annual cycles influenced by sea-ice extent in the Antarctic and ecological processes in the Arctic.

Keywords: polar phytoplankton; phytoplankton biomass; biomass; bust cycles; boom bust; phytoplankton

Journal Title: Nature Geoscience
Year Published: 2017

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