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Estimation of Antarctic land-fast sea ice algal biomass and snow thickness from under-ice radiance spectra in two contrasting areas

Citation

Wongpan, P and Meiners, KM and Langhorne, PJ and Heil, P and Smith, IJ and Leonard, GH and Massom, RA and Clementson, LA and Haskell, TG, Estimation of Antarctic land-fast sea ice algal biomass and snow thickness from under-ice radiance spectra in two contrasting areas, Journal of Geophysical Research: Oceans, 123, (3) pp. 1907-1923. ISSN 2169-9275 (2018) [Refereed Article]


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Copyright Statement

Copyright 2018 American Geophysical Union

DOI: doi:10.1002/2017JC013711

Abstract

Fast ice is an important component of Antarctic coastal marine ecosystems, providing a prolific habitat for ice algal communities. This work examines the relationships between normalized difference indices (NDI) calculated from under‐ice radiance measurements and sea ice algal biomass and snow thickness for Antarctic fast ice. While this technique has been calibrated to assess biomass in Arctic fast ice and pack ice, as well as Antarctic pack ice, relationships are currently lacking for Antarctic fast ice characterized by bottom ice algae communities with high algal biomass. We analyze measurements along transects at two contrasting Antarctic fast ice sites in terms of platelet ice presence: near and distant from an ice shelf, i.e., in McMurdo Sound and off Davis Station, respectively. Snow and ice thickness, and ice salinity and temperature measurements support our paired in situ optical and biological measurements. Analyses show that NDI wavelength pairs near the first chlorophyll a (chl a) absorption peak (≈440 nm) explain up to 70% of the total variability in algal biomass. Eighty‐eight percent of snow thickness variability is explained using an NDI with a wavelength pair of 648 and 567 nm. Accounting for pigment packaging effects by including the ratio of chl a‐specific absorption coefficients improved the NDI‐based algal biomass estimation only slightly. Our new observation‐based algorithms can be used to estimate Antarctic fast ice algal biomass and snow thickness noninvasively, for example, by using moored sensors (time series) or mapping their spatial distributions using underwater vehicles.

Item Details

Item Type:Refereed Article
Keywords:Antarctic, landfast sea ice, primary production, snow thickness
Research Division:Earth Sciences
Research Group:Physical Geography and Environmental Geoscience
Research Field:Glaciology
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Physical Sciences
UTAS Author:Meiners, KM (Dr Klaus Meiners)
UTAS Author:Heil, P (Dr Petra Heil)
UTAS Author:Massom, RA (Dr Robert Massom)
ID Code:129186
Year Published:2018
Web of Science® Times Cited:2
Deposited By:CRC-Antarctic Climate & Ecosystems
Deposited On:2018-11-14
Last Modified:2018-12-13
Downloads:72 View Download Statistics

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