Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas

Phytoplankton blooms provide biomass to the marine trophic web, contribute to the carbon removal from the atmosphere and can be deadly when associated with harmful species. This points to the need to understand the phenology of the blooms in the Barents, Norwegian, and North seas. We use satellite chlorophyll-a from 2000 to 2020 to assess robust climatological and the interannual trends of spring and summer blooms onset, peak day, duration and intensity. Further, we also correlate the interannual variability of the blooms with mixed layer depth (MLD), sea surface temperature (SST), wind speed and suspended particulate matter (SPM) retrieved from models and remote sensing. The climatological spring blooms start on March 10th and end on June 19th. The climatological summer blooms begin on July 13th and end on September 17th. In the Barents Sea, years of shallower mixed layer (ML) driven by both calm waters and higher freshwaters input keeps the phytoplankton in the euphotic zone, causing the spring bloom to start earlier and reach higher biomass but end sooner due to the lack of nutrients upwelling from the deep. In the Norwegian Sea, a correlation between SST and the spring blooms is found. Here, warmer waters are correlated to earlier and stronger blooms in most regions but with later and weaker blooms in the eastern Norwegian Sea. In the North Sea, years of shallower ML reduces the phytoplankton sinking below the euphotic zone and limits the SPM increase from the bed shear stress, creating an ideal environment of stratified and clear waters to develop stronger spring blooms. Last, the summer blooms onset, peak day and duration have been rapidly delaying at a rate of 1.25-day year–1, but with inconclusive causes based on the parameters assessed in this study.

Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans

While forecasts of atmospheric variables, and to a lesser degree ocean circulation, are relatively common, the forecast of biogeochemical conditions is still in its infancy. Using a dynamical ocean biogeochemical forecast forced by seasonal forecasts of atmospheric and physical ocean variables, we produce seasonal predictions of chlorophyll concentration at the global scale. Results show significant Anomaly Correlation Coefficients (ACCs) for the majority of regions (11 out of the 12 regions for the 1-month lead forecast). Root mean square errors are smaller (<0.05 µg chlorophyll (chl) L−1) in the Equatorial regions compared to the higher latitudes (range from 0.05 up to 0.13 µg chl L−1). The forecast for all regions except three (North Atlantic, South Pacific and North Indian) are within the Semi-Interquartile Range of the satellite chlorophyll concentration (Suomi-National Polar-orbiting Partnership (NPP), 27.9%). This suggests the potential for skillful global biogeochemical forecasts on seasonal timescales of chlorophyll, primary production and harmful algal blooms that could support fisheries management and other applications.

The Effect of Cold and Warm Anomalies on Phytoplankton Pigment Composition in Waters off the Northern Baja California Peninsula (México): 2007–2016

In this study, we report the response of phytoplankton community composition to cold and warm interannual events affecting the waters off the Baja California Peninsula from 2007 to 2016 based on data obtained from a single marine station (31.75° N/116.96° W). Included variables were satellite chlorophyll a, sea surface temperature (MODIS/Aqua), upwelling intensity, and field data (phytoplankton pigments, inorganic nutrients, light penetration). Phytoplankton pigments were determined by high performance liquid chromatography, and CHEMTAX software was used to determine the relative contributions of the main taxonomic groups to chlorophyll a. Our results confirm the decrease in phytoplankton biomass due to the influence of the recent Pacific Warm Anomaly (2014) and El Niño 2015–2016. However, this decrease was especially marked at the surface. When data from the entire water column was considered, this decrease was not significant, because at the subsurface Chla did not decrease as much. Nevertheless, significant changes in community composition occurred in the entire water column with Cyanobacteria (including Prochlorococcus) and Prymnesiophytes being dominant at the surface, while Chlorophytes and Prasinophytes made a strong contribution at the subsurface. Analysis of the spatial distribution of SST and satellite chlorophyll a made it possible to infer the spatial extension of these anomalies at a regional scale.