Wirewalker data collected during the 2020 Southern California red tide
Data files
Jul 25, 2023 version files 7.58 MB
Abstract
Harmful algal blooms (HABs) are globally increasing economic, health, and ecosystem threats. In spite of the relatively frequent occurrence of HABs, the mechanisms responsible for their initiation and exceptional abundance remain imperfectly understood. A 50-year-old hypothesis posits that dense dinoflagellate blooms derive from motility: swimming upward during the day to photosynthesize and downward at night to access the deep nutrient pool. This allows dinoflagellates to outgrow their nonmotile competitors. We tested this hypothesis using in situ data from an autonomous, ocean-wave-powered vertical profiling system. We showed that the dinoflagellate Lingulodinium polyedra’s vertical migration led to depletion of the deep nitrate pool during a 2020 red tide HAB event. Downward migration began at dusk, with the maximum migration depth determined by local nitrate concentrations. Losses of nitrate at depth were balanced by proportional increases in phytoplankton chlorophyll concentrations and suspended particle load, conclusively linking vertical migration to the access and assimilation of deep nitrate in the ocean environment. Vertical migration during the red tide created distinctly anomalous biogeochemical conditions compared to 70 years of climatological data, demonstrating the capacity of these events to temporarily reshape the coastal ocean’s ecosystem and biogeochemistry. Advances in the understanding of the physiological, behavioral, and metabolic dynamics of HAB-forming organisms from cutting-edge observational techniques will improve our ability to forecast HABs and mitigate their consequences in the future.
Methods
This dataset was acquired by a moored ocean-wave-powered Wirewalker (WW) profiler. The WW was equipped with a conductivity-temperature-depth (CTD) sensor (RBR Concerto), nitrate sensor (SUNA V2), Chl-a fluorescence and optical backscatter sensor (SBE ECOPuck), and irradiance sensor (SBE OCR-504). Over the three-week period from April 29, 2020 to May 21, 2020, The final gridded WW data had 1 m vertical resolution and ~15 min temporal resolution. Detailed data processing steps can be found in Zheng et al., PNAS, 2023.
Usage notes
Matlab is suggested to open the data file.