4.7 Article

How Are Under Ice Phytoplankton Related to Sea Ice in the Southern Ocean?

期刊

GEOPHYSICAL RESEARCH LETTERS
卷 48, 期 21, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021GL095051

关键词

phytoplankton; sea ice; southern ocean; productivity; ICESat-2; Argo

资金

  1. ICESat-2 science project office
  2. National Science Foundation, Division of Polar Programs [NSF PLR -1,425,989, OPP-1936222]
  3. National Environmental Research Council [NE/T010622/1]
  4. NASA [80NSSC20K0970]
  5. International Argo Program
  6. NOAA programs

向作者/读者索取更多资源

This study investigated the relationship between Southern Ocean sea ice and under-ice phytoplankton characteristics using a distributional approach. The results showed significant correlations between Argo float data and freeboard variance, lead fraction, and mixed layer depth, indicating that sea ice dynamics play a key role in modulating the amount of light available to phytoplankton. The study highlights the importance of diagnostic models and field studies to further understand the processes influencing under-ice phytoplankton in the Southern Ocean.
Little is known about Southern Ocean under-ice phytoplankton, despite their suspected potential-ice and stratification conditions permitting-to produce blooms. We use a distributional approach to ask how Southern Ocean sea ice and under-ice phytoplankton characteristics are related, circumventing the dearth of co-located ice and phytoplankton data. We leverage all available Argo float profiles, together with freeboard (height of sea ice above sea level) and lead (ice fractures yielding open water) data from ICESat-2, to describe co-variations over time. We calculate moments of the probability distributions of maximum chlorophyll, particulate backscatter, the depths of these maxima, freeboard, and ice thickness. Argo moments correlate significantly with freeboard variance, lead fraction, and mixed layer depth, implying that sea ice dynamics drive plankton by modulating how much light they receive. We discuss ecological implications in the context of data limitations and advocate for diagnostic models and field studies to test additional processes influencing under-ice phytoplankton.

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