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dc.contributor.authorMeiners, K. M.
dc.contributor.authorArndt, S.
dc.contributor.authorBestley, S.
dc.contributor.authorKrumpen, T.
dc.contributor.authorRicker, R.
dc.contributor.authorMilnes, M.
dc.contributor.authorNewbery, K.
dc.contributor.authorFreier, U.
dc.contributor.authorJarman, S.
dc.contributor.authorKing, R.
dc.contributor.authorProud, R.
dc.contributor.authorKawaguchi, S.
dc.contributor.authorMeyer, B.
dc.date.accessioned2018-01-30T00:31:46Z
dc.date.available2018-01-30T00:31:46Z
dc.date.issued2017-07-29
dc.identifier.citationMeiners , K M , Arndt , S , Bestley , S , Krumpen , T , Ricker , R , Milnes , M , Newbery , K , Freier , U , Jarman , S , King , R , Proud , R , Kawaguchi , S & Meyer , B 2017 , ' Antarctic pack-ice algal distribution : floe-scale spatial variability and predictability from physical parameters ' , Geophysical Research Letters , vol. 44 , no. 14 , pp. 7382-7390 . https://doi.org/10.1002/2017GL074346en
dc.identifier.issn1944-8007
dc.identifier.otherPURE: 250569526
dc.identifier.otherPURE UUID: bb98c792-b156-47c8-85b0-01c8863ddf64
dc.identifier.otherBibtex: urn:57d61ee960f8414003f6155995804046
dc.identifier.otherScopus: 85026463552
dc.identifier.otherORCID: /0000-0002-8647-5562/work/35710928
dc.identifier.otherWOS: 000407790500033
dc.identifier.urihttps://hdl.handle.net/10023/12630
dc.descriptionThis study was supported by the PACES (Polar Regions and Coasts in a changing Earth System) program (Topic 1, WP 5) of the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, the Helmholtz Virtual Institute „PolarTime“ (VH-VI-500: Biological timing in a changing marine environment — clocks and rhythms in polar pelagic organisms), the Helmholtz Alliance “Remote Sensing and Earth System Dynamics” (HA-310); and by the Australian Government through i) Australian Antarctic Science projects (4073, 4298), ii) the Cooperative Research Centres Programme through the Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC), and iii) the Antarctic Gateway Partnership special research initiative through the Australian Research Council. All data used in this study are available through the Australian Antarctic Data Centre as well as PANGAEA (doi.pangaea.de/10.1594/PANGAEA.870706).en
dc.description.abstractAntarctic pack ice serves as habitat for microalgae which contribute to Southern Ocean primary production and serve as important food source for pelagic herbivores. Ice algal biomass is highly patchy, and remains severely undersampled by classical methods such as spatially restricted ice-coring surveys. Here we provide an unprecedented view of ice algal biomass distribution, mapped (as chlorophyll-a) in a 100m-by-100m area of a Weddell Sea pack-ice floe, using under-ice irradiance measurements taken with an instrumented Remotely Operated Vehicle. We identified significant correlations (p <0.001) between algal biomass and concomitant in situ surface measurements of snow depth, ice thickness and estimated sea-ice freeboard levels using a statistical model. The model's explanatory power (r2 = 0.30) indicates that these parameters alone may provide a first basis for spatial prediction of ice algal biomass, but parameterisation of additional determinants is needed to inform more robust upscaling efforts.
dc.language.isoeng
dc.relation.ispartofGeophysical Research Lettersen
dc.rights© 2017, Commonwealth of Australia. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at onlinelibrary.wiley.com / https://doi.org/10.1002/2017GL074346en
dc.subjectSea-ice propertiesen
dc.subjectSnowen
dc.subjectFreeboarden
dc.subjectChlorophyll-aen
dc.subjectIce algaeen
dc.subjectBiomassen
dc.subjectGE Environmental Sciencesen
dc.subjectQH301 Biologyen
dc.subjectDASen
dc.subject.lccGEen
dc.subject.lccQH301en
dc.titleAntarctic pack-ice algal distribution : floe-scale spatial variability and predictability from physical parametersen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Pelagic Ecology Research Groupen
dc.identifier.doihttps://doi.org/10.1002/2017GL074346
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-01-29
dc.identifier.urlhttp://onlinelibrary.wiley.com/doi/10.1002/2017GL074346/full#footer-support-infoen


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