Sea ice bio-optical measurements
Samples were stranded in Antarctic for greater than 12 months but were stored always below -80C. Pigment signatures (HPLC) do not show any signs of degradation. And data quality is ok. However, sampling location x = 70m, y = 64m sampled on 23/11/2015 should be excluded from any further analyses due...
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Australian Ocean Data Network
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| Online Access: | https://researchdata.ands.org.au/sea-ice-bio-optical-measurements/993031 https://data.aad.gov.au/metadata/records/AAS_4298_Davis2015_Sea_Ice_Bio_Optics https://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4298_Davis2015_Sea_Ice_Bio_Optics http://data.aad.gov.au/eds/4553/download https://secure3.aad.gov.au/proms/public/projects/report_project_public.cfm?project_no=AAS_4298 |
| Summary: | Samples were stranded in Antarctic for greater than 12 months but were stored always below -80C. Pigment signatures (HPLC) do not show any signs of degradation. And data quality is ok. However, sampling location x = 70m, y = 64m sampled on 23/11/2015 should be excluded from any further analyses due to unrealistic data in sea ice interior sections. csv copies of some of the spreadsheets have been made, and are available in the download file. Field-based sampling: As part of Australian Antarctic Science project # 4298, a total number of 44 sea ice sites were sampled for bio-optical measurements along 4 transects on land-fast sea ice off Davis Station (Antarctica) during November – December 2015. Measurements included simultaneous hyperspectral down-welling (ice surface) irradiance (triplicate) and under-ice radiance (triplicate) measurements (320 – 900 nm, 3.3 nm resolution) with a TriOS ACC and Trios ARC radiometer, respectively. The radiance measurements were conducted with the TriOS ARC radiometer mounted onto an L-shaped arm (for deployment details see Melbourne-Thomas et al. 2015). Subsequently, snow thickness was measured with a ruler and an ice core was collected directly above the radiometer location. Sea-ice freeboard (tape measure) and ice thickness (ice core length) were also recorded. Ice cores (9 cm internal diameter) were cut into sections, and these were melted in the dark at +4 degrees C, filtered onto GFF filters and then used to measure ice algal pigment content (using High Performance Liquid Chromatography (HPLC) and spectral ice algal absorption coefficients (ap, ad, aph) for entire vertical profiles or for the lower-most 0.1 m of ice cores. The location of the sampling grid had its origin (x=0, y=0) at GPS position: -68.568904, 77.945439. Transects (128m – 512 m in length) started at x=60, x=70, x=80 and x=90 m and were sampled at y-positions of 0m, 0.5m, 1m, 2m, 4m, 8m, 16m, 32m, 64m, 128m, (256m, and 512m) on 19/11/2015, 23/11/2015, 29/11/2015 and 02/12/2015, respectively. Analysis of ice algal chlorophyll a concentration: For pigment analysis, 0.25 to 1.0 litres of melted ice core subsamples were passed through 25 mm diameter glass-fiber (Whatman GF/F) filters. The filters were then frozen and stored below −80 degrees C prior to analysis using HPLC. Samples were extracted over 15 to 18 hours in acetone before analysis by HPLC using a modified C8 column and binary gradient system with an elevated column temperature [Van Heukelem and Thomas, 2001]. Pigments were identified by retention time and absorption spectra from a photo-diode array (PDA) detector, and concentrations were determined from commercial and international standards (Sigma; DHI, Denmark). Analysis of particulate (algal and non-algal) absorption: The optical density (OD) spectra of the particulate material on these filters (see section above) were measured over the 350 to 750 nm spectral range in 0.9 nm increments, using a Cintra 404 UV/VIS dual-beam spectrophotometer equipped with an integrating sphere. The pigments on the sample filter were then extracted using the method of Kishino et al. [1985]'s method to determine the OD of the non-algal particles in a second scan. The OD due to ice algae was then obtained by calculating the difference between the optical density of the total particulate and non-algal fractions. The OD measurements were converted to absorption spectra using blank filter measurements, and by first normalizing the scans to zero at 750 nm and then correcting for the path length amplification using the coefficients of Mitchell [1990]. A detailed description of the method is given in Clementson et al. [2001], and followed SeaWiFS protocols [Muller et al., 2003]. An exponential function was fitted to all spectra of non-algal particulate material: ad(λ) = ad(350 nm) exp[−S(λ − 350 nm)] + b, (1) where ad(λ) is the residual absorption coefficient over the wavelength (λ) range 350 to 750 nm of the particles after methanol extraction, also referred to as absorption of detritus [m−1] although this may include absorption of non-extractable pigments and heterotrophic protists. A non-linear least-squares technique was used to fit Equation 1 to the untransformed data, where S and b are empirically-determined constants. The inclusion of an offset b allows for any baseline correction. In some samples, pigment extraction was incomplete, leaving small residual peaks in detritus spectra at the principal chlorophyll absorption bands. To avoid distorting the fitted detritus spectra, data at these wavelengths were omitted when all spectra were fitted. Total particulate spectra were smoothed using a running box-car filter with 10 nm width, and the fitted detritus spectra were subtracted to yield the ice algae spectra. Subtracting fitted detritus spectra minimized any artifacts due to incomplete extraction of pigments. The resulting ice algae spectra were base-corrected by subtracting absorption at 750 nm to obtain aph(λ). The following parameters were then determined: ap(λ) = absorption coefficient of particles [m−1]; aph(λ) = absorption coefficient of ice algae [m−1] calculated as the difference between ap(λ) and ad(λ). Literature cited: Clementson, L. A., J. S. Parslow, A. R. Turnbull, D. C. McKenzie, and C. E. Rathbone (2001), Optical properties of waters in the Australasian sector of the Southern Ocean, Journal of Geophysical Research: Oceans, 106(C12), 31,611–31,625, doi:10.1029/2000jc000359. Kishino, M., M. Takahashi, N. Okami, and S. Ichimura (1985), Estimation of the spectral absorption-coefficients of phytoplankton in the sea, Bulletin of Marine Science, 37(2), 634–642.Melbourne-Thomas, J., K. Meiners, C. Mundy, C. Schallenberg, K. Tattersall, and G. Dieckmann (2015), Algorithms to estimate Antarctic sea ice algal biomass from under-ice irradiance spectra at regional scales, Marine Ecology Progress Series, 536, 107–121, doi:10.3354/meps11396. Mitchell, B. G. (1990), Algorithms for determining the absorption coefficient for aquatic particulates using the quantitative filter technique, Orlando’90, 1302, 137–148, doi:10.1117/12.21440. Müller, J. L., R. R. Bidigare, C. Trees, W. M. Balch, and J. Dore (2003), Ocean Optics Protocols for Satellite Ocean Colour Sensor Validation, Revision 5, Volume V: Biogeochemical and Bio-Optical Measurements and Data, NASA Tech. Memo. Van Heukelem, L., and C. S. Thomas (2001), Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments, Journal of Chromatography A, 910(1), 31–49, doi:10.1016/s0378-4347(00)00603-4. The main objective for the collection of this dataset was to develop algorithms to estimate ice algal biomass from hyperspectral under-ice radiance measurements. |
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