Understanding Diatoms’ Past and Future Biogeochemical Role in High‐Latitude Seas

Abstract

Because cold‐water diatoms’ baseline elemental density (BED) is substantially higher than temperate diatoms, previous polar studies may have underestimated diatoms’ contribution to elemental standing stocks, contribution to particulate organic carbon (POC) export and incorrectly modeled their susceptibility to future warming. We apply cold‐water diatom allometry to Arctic field samples and derive diatom growth rates ranging from 0.01–0.68 day−1, versus unrealistically high rates estimated using temperate diatom allometry. Reanalysis of published Southern Ocean data (Antarctic Environment and Southern Ocean Process Study and European Iron Fertilization Experiment) shows that diatom POC was significantly underestimated and diatoms could have accounted for a majority of POC export. However, during some field programs (Kerguelen Plateau), temperate allometry properly accounted for diatom biomass. We also predict that warming sea surface temperature may alter high‐latitude diatom BED, suggesting that even if abundances do not change with warming, the reduced diatom BED will likely lower the trophic‐transfer efficiency and their total carbon flow to consumers.

Seasonal Dynamics of Primary Production in the Southeastern Bering Sea Assessed Using Continuous Temporal and Vertical Dissolved Oxygen and Chlorophyll‐a Measurements

“…Such shifts in species composition influence community phytoplankton growth rates since the functional growth response to temperature in diatoms are almost three times that of dinoflagellates (Kremer et al., 2017). Cold water diatoms may respond even faster to enhanced temperature (Krause & Lomas, 2020). Smaller phytoplankton cells generally flourish in warmer and more stratified, low‐nutrient waters (Irwin et al., 2006).…”

Reporting of methods for automated devices: A systematic review and recommendation for studies using FlowCam for phytoplankton

“…As an example, Lomas et al (2019) and Krause and Lomas (2020) both used the FlowCam automated biovolume (cylinder) measure to represent biovolume of mixed diatom samples when proposing and validating a new method for calculating cold‐water diatom elemental density, an important measure used to reflect diatom standing stocks and carbon flux, and for predicting the influences of climate change. Lomas et al (2019) present the new cold‐water diatom allometry calculation based on FlowCam biovolume (cylinder) outputs, while Krause and Lomas (2020) test the calculation on additional FlowCam biovolume (cylinder) outputs and then also compare these findings to those of several prior studies (not using FlowCam) that relied on existing temperate diatom allometry calculations, concluding that the new method is different (with diatom contributions significantly increased) but superior. We have shown (in Case Study 3) that this FlowCam output is calculated incorrectly and produces either over‐ or under‐estimates of biovolume depending on diatom orientation.…”

“…We have shown (in Case Study 3) that this FlowCam output is calculated incorrectly and produces either over‐ or under‐estimates of biovolume depending on diatom orientation. Lomas et al (2019) do not describe any FlowCam image sorting, while Krause and Lomas (2020) specifically state that images were manually sorted to exclude empty frustules, but do not mention cell orientation. Lomas et al (2019) state that their FlowCam biovolume (cylinder) estimates compared favorably to manual microscopic quantification (no data are provided), but we know that this measure is incorrect, especially for unsorted cell orientations.…”

“…These examples clearly highlight that due to the complexities of calculating measures based on two-dimensional images, automated outputs can exhibit marked errors. Given this finding, the veracity of the 10 studies that used FlowCam geodesic length, geodesic width or biovolume (cylinder) outputs is brought into question, especially where those findings were compared to previous data collected using traditional manual microscopy techniques (Krause and Lomas 2020). It is vital that researchers carefully consider which automated outputs they make use of and take the time to check that they accurately represent the features they are estimating for their specific cells.…”

Sinking Diatom Assemblages as a Key Driver for Deep Carbon and Silicon Export in the Scotia Sea (Southern Ocean)

“…Due to their high sinking rates, diatoms have the capacity to transfer organic carbon (OC) and biogenic silicon (bioSi) from the productive surface layer to the deep ocean. As a result, diatoms are widely identified as the most relevant phytoplankton group for unraveling SO organic carbon cycling (Bathmann et al, 1991;Smetacek et al, 2012;Krause and Lomas, 2020). To fully understand diatom-driven export, and hence how carbon and silicon are sequestered, it is also critical to consider diatom ecological traits.…”