Return of the "age of dinoflagellates" in Monterey Bay: Drivers of dinoflagellate dominance examined using automated imaging flow cytometry and long-term time series analysis

LIMNOLOGY AND OCEANOGRAPHY(2020)

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摘要
Phytoplankton biomass in Monterey Bay, California is typically dominated by diatoms, but it shifted to dinoflagellates twice in the past 18 years (2004-2007, 2017-2018), which was associated with increased harmful algal blooms. Located within the central California Current System (CCS), Monterey Bay is strongly influenced by cycles of upwelling-favorable winds and their relaxation or reversal. Both dinoflagellate-dominated periods were linked to a negative North Pacific Gyre Oscillation (NPGO) and increased river discharge, but each had a different relationship with upwelling. To examine the connection between large-scale and local forcings underlying floristic shifts in the phytoplankton assemblage, an Imaging FlowCytobot (IFCB) was deployed within the Monterey Bay upwelling shadow for a full year. A machine learning classifier differentiating IFCB images of the phytoplankton assemblage was developed. Despite anomalously strong upwelling in 2018, dinoflagellates comprised 57% of the annual phytoplankton-specific biomass. During upwelling, dinoflagellates appear to have accumulated at convergent fronts, while during relaxation these frontal populations were transported to the nearshore where they seeded local blooms. Frequent upwelling-relaxation cycles and local wind anomalies generated an unusually retentive circulation pattern in the upwelling shadow, producing a warm and stratified bloom incubator. Thus, local features and forcings (upwelling shadow, winds, river discharge) modified the effects of regional- and basin-scale oceanographic variability (regional upwelling, NPGO), altering local phytoplankton patterns. As North Pacific decadal variability and CCS upwelling intensity increase under climate warming, dinoflagellates may become more common in some CCS regions, due to the enhancement or mitigation of large-scale trends by local forcings.
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