To understand the impact of the melting of late summer Arctic brash ice on the surface waters of the Chukchi Sea, we collected sea-ice samples during 2021. Floating sea ice was collected by a wire mesh pallet cage from the side of the R/V Mirai. We measured physical and biogeochemical parameters such as salinity, oxygen stable isotopic ratios, turbidity, and concentrations of chlorophyll-a and nutrients. The samples of brash ice were multiyear ice based on satellite back-trajectory analysis. Comparison of nutrient concentrations in brash ice with those of seawater samples from the temperature minimum layer similar to the water in the sea ice originated suggested that the characteristics of the brash ice were greatly affected by biogeochemical processes such as remineralization. The extremely high turbidity and concentrations of chlorophyll-a observed in the brown/green ice samples reflected the impact of sediment as well as the influence of biological activities. The N:P ratios were less than 1 because of the high phosphate concentrations, even though the ammonium concentrations were high. We hypothesized that this low N:P ratio reflected the combined effects of the accumulation of nutrients due to remineralization in the biofilm and differences of remineralization rate and adsorption features of nitrogen and phosphorus. Based on the high nitrate and ammonium concentrations in the sea-ice samples, we postulated a marked impact of sea-ice meltwater on the nitrogen cycle in the nitrate-depleted surface waters of the Chukchi Sea during late summer. We estimated that meltwater nitrogen could support 0.3%–2.6% of primary production in the northern Chukchi Sea. Our results suggest that high-turbidity ice will play an important role as a source of nutrients to the ocean during melting of sea ice, and understanding its distribution, amount, and geochemical characteristics is vital.
Knowledge on the phenology and distribution of phytoplankton taxonomic groups (PTGs) represent valuable information when studying marine ecosystem, especially in the Arctic Ocean where rapid warming has drastic effects on sea-ice dynamics, which affect the marine food web. Taxonomic groups of phytoplankton can be discriminated based on their pigment signatures, which, in turn, impact their absorption spectra, given that different pigments have different absorption windows in the visible. Using concurrent measurements of phytoplankton diagnostic pigments and absorption spectra (aph) collected in the Bering and Chukchi Seas, a novel and direct approach was designed for simultaneously estimating the biomass concentrations of several PTGs (Ci) as well as their specific absorption coefficient. The chemotaxonomic tool CHEMTAX was applied to twelve diagnostic pigments measured by high-performance liquid chromatography (HPLC). Their results revealed that the phytoplankton community composition was made of nine groups, from which six dominant were identified: diatoms, dinoflagellates, c3-flagellate, haptophytes type 7, two types of prasinophytes. Out of 117 samples, twenty pairs of Ci derived by CHEMTAX and measured aph were randomly selected and used in a linear unmixing model to extract the specific absorption spectral of each group. This step was repeated 1000 times to provide the mean specific absorption of a given phytoplankton group. These specific absorption spectra were used to reconstruct total aph, which was consistent with the measured aph (R2 from 0.8 to 0.95) at all visible wavelengths (400-700 nm). The derived specific absorption spectra were further used with the measured aph(λ) at ten Moderate Resolution Imaging Spectroradiometer (MODIS) wavebands in a linear unmixing model to test the ability to retrieve the concentrations of PTGs from satellite remote sensing. A comparison between estimated and measured Ci showed that the approach used in this study performed best when retrieving five groups (i.e., dinoflagellates, c3-flagellate, haptophytes, two types of prasinophytes) from the nine initially identified using CHEMTAX with a mean absolute percentage error (MAPE) <35%, except for diatoms with a MAPE value of about 45%. Our approach provides a practical basis for estimation of PTGs using aph(λ) derived from satellite observations and field measurements.
Phytoplankton are composed of diverse taxonomical groups, which are manifested as distinct morphology, size and pigment composition. These characteristics, modulated by their physiological state, impact their light absorption and scattering, allowing them to be detected with ocean color satellite radiometry. There is a growing volume of literature describing satellite algorithms to retrieve information on phytoplankton composition in the ocean. This synthesis provides a review of current methods and a simplified comparison of approaches. The aim is to provide an easily comprehensible resource for non-algorithm developers, who desire to use these products, thereby raising the level of awareness and use of these products and reducing the boundary of expert knowledge needed to make a pragmatic selection of output products with confidence. The satellite input and output products, their associated validation metrics, as well as assumptions, strengths and limitations of the various algorithm types are described, providing a framework for algorithm organization to assist users and inspire new aspects of algorithm development capable of exploiting the higher spectral, spatial and temporal resolutions from the next generation of ocean color satellites.
Abstract. Recent ocean warming and subsequent sea ice decline resulting from climate change could affect the northward shift of the ecosystem structure in the Chukchi Sea and Bering Sea shelf region. The size structure of phytoplankton communities provides an index of trophic levels that is crucial to understanding the mechanisms underlying such ecosystem changes and their implications for the future. This study proposes a new ocean color algorithm for deriving this characteristic by using the region's optical properties. The size derivation model (SDM) estimates the phytoplankton size index FL on the basis of size-fractionated chlorophyll-a (chl-a) using the light absorption coefficient of phytoplankton, aph(λ), and the backscattering coefficient of suspended particles including algae, bbp(λ). FL was defined as the ratio of algal biomass attributed to cells larger than 5 μm to the total. It was expressed by a multiple regression model using the aph(λ) ratio, aph(488)/aph(555), which varies with phytoplankton pigment composition, and the spectral slope of bbp(λ), γ, which is an index of the mean suspended particle size. A validation study demonstrated that the SDM successfully derived an FL value of 69 % within an error range of ± 20 % for unknown data. The spatial distributions of FL for the cold August of 2006 and the warm August of 2007 were compared to examine application of the SDM to satellite remote sensing. The results suggested that phytoplankton size was responsive to changes in sea surface temperature. Further analysis of satellite-derived FL values and other environmental factors can advance our understanding of ecosystem structure changes in the shelf region of the Chukchi and Bering Seas.
Abstract. We analysed mooring and ship-based hydrographic and biogeochemical data obtained from a Hope Valley biological hotspot in the southern Chukchi Sea. The moorings were deployed from 16 July 2012 to 19 July 2014, and data were captured during spring and fall blooms with high chlorophyll a concentrations. Turbidity increased and dissolved oxygen decreased in the bottom water at the mooring site before the fall bloom, suggesting an accumulation of particulate organic matter and its decomposition (nutrient regeneration) at the bottom. This event may have been a trigger for the fall bloom at this site. The bloom was maintained for 1 month in 2012 and for 2 months in 2013. The maintenance mechanism for the fall bloom was also studied by hydrographic and biogeochemical surveys in late summer to fall 2012 and 2013. Nutrient-rich water from the Bering Sea supplied nutrients to Hope Valley, although a reduction in nutrients may have occurred in 2012 by mixing of lower-nutrient water that would have remained on the Chukchi Sea shelf during the spring and fall blooms. In addition, nutrient regeneration at the bottom of Hope Valley could have increased nutrient concentrations and explained 60 % of its nutrient content in fall 2012. The high nutrient content with the dome-like structure of the bottom water may have maintained the high primary productivity at this site during the fall bloom. Primary productivity was 0.3 in September 2012 and 1.6 g C m−2 d−1 in September 2013. The lower productivity in 2012 was related to strong stratification caused by the high fraction of surface sea ice meltwater.
