Diatom abundance in surface sediments of the Southern Ocean


Autoria(s): Esper, Oliver; Gersonde, Rainer
Cobertura

MEDIAN LATITUDE: -57.934039 * MEDIAN LONGITUDE: -72.114875 * SOUTH-BOUND LATITUDE: -74.415300 * WEST-BOUND LONGITUDE: -179.009600 * NORTH-BOUND LATITUDE: -37.158300 * EAST-BOUND LONGITUDE: 25.212600 * DATE/TIME START: 2000-02-17T20:49:00 * DATE/TIME END: 2010-01-20T11:20:00 * MINIMUM DEPTH, sediment/rock: 0 m * MAXIMUM DEPTH, sediment/rock: 0 m

Data(s)

06/02/2014

Resumo

Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.

Formato

text/tab-separated-values, 4480 data points

Identificador

https://doi.pangaea.de/10.1594/PANGAEA.828674

doi:10.1594/PANGAEA.828674

Idioma(s)

en

Publicador

PANGAEA

Relação

Esper, Oliver; Gersonde, Rainer (2014): Quaternary surface water temperature estimations: New diatom transfer functions for the Southern Ocean. Palaeogeography, Palaeoclimatology, Palaeoecology, 414, 1-19, doi:10.1016/j.palaeo.2014.08.008

Direitos

Access constraints: access rights needed

Fonte

Supplement to: Esper, Oliver; Gersonde, Rainer (2014): New tools for the reconstruction of Pleistocene Antarctic sea ice. Palaeogeography, Palaeoclimatology, Palaeoecology, 399, 260-283, doi:10.1016/j.palaeo.2014.01.019

Palavras-Chave #Actinocyclus actinochilus; Actinocyclus curvatulus; Alveus marinus; Amundsen Sea; ANT-XX/2; ANT-XXII/4; ANT-XXIII/4; ANT-XXVI/2; Asteromphalus hookeri; Asteromphalus hyalinus; Asteromphalus parvulus; AWI_Paleo; Azpeitia tabularis var. tabularis; Azpeitia tabularis var egregius; Central South Atlantic; Chaetoceros spp.; Corethron pennatum; Counting, diatoms; CTD/Rosette; CTD-RO; DEPTH, sediment/rock; DFG-Schwerpunktprogramm 1158 - Antarktisforschung; DFG-SPP1158; Diatoms; Diatoms indeterminata; Elevation of event; Eucampia antarctica; Event label; Fragilariopsis curta; Fragilariopsis cylindrus; Fragilariopsis doliolus; Fragilariopsis kerguelensis; Fragilariopsis obliquecostata; Fragilariopsis rhombica; Fragilariopsis ritscheri; Fragilariopsis separanda; Fragilariopsis sublinearis; Fragilariopsis vanheurckii; GC; GeoB6403-4; GeoB6404-3; GeoB6405-8; GeoB6406-1; GeoB6407-2; GeoB6409-2; GeoB6410-1; GeoB6411-4; GeoB6416-2; GeoB6419-1; GeoB6420-2; Giant box corer; GKG; Gravity corer; Hemidiscus cuneiformis; Indian Ocean; Latitude of event; Longitude of event; M46/4; Meteor (1986); MIC; MiniCorer; MUC; MultiCorer; Nathaniel B. Palmer; Navicula directa; NBP98-02; NBP98-02-3MC2; NBP98-02-4MC1; NBP98-02-5MC2; Nitzschia bicapitata; Nitzschia kolaczeckii; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; Polarstern; Porosira pseudodenticulata; PS63/024-1; PS63/026-2; PS63/027-2; PS63/028-2; PS63/033-5; PS63/035-2; PS63/037-4; PS63/039-3; PS63/041-2; PS63/042-4; PS63/043-2; PS63/047-2; PS63/064-6; PS63/071-1; PS63/078-1; PS63/083-2; PS63/095-3; PS63/126-3; PS63/130-2; PS63/136-2; PS63/141-2; PS63/143-2; PS63/146-1; PS63/149-2; PS63 06AQ200211_2; PS67; PS67/182-2; PS67/185-1; PS67/197-4; PS67/205-4; PS67/206-3; PS67/219-3; PS67/224-3; PS69; PS69/269-1; PS69/272-3; PS69/275-2; PS69/283-5; PS69/288-1; PS69/297-1; PS75/034-1; PS75/049-1; PS75/051-2; PS75/053-1; PS75/055-1; PS75/062-1; PS75/064-2; PS75/065-2; PS75/067-2; PS75/069-2; PS75/070-1; PS75/072-3; PS75/074-1; PS75/076-1; PS75/080-2; PS75/082-2; PS75/084-1; PS75/085-2; PS75/086-1; PS75/087-2; PS75/088-3; PS75/089-6; PS75/090-6; PS75/091-6; PS75/092-1; PS75/094-3; PS75/095-6; PS75/097-5; PS75/098-6; PS75 BIPOMAC; Pseudo-nitzschia turgiduloides; Rhizosolenia antennata forma antennata; Rhizosolenia antennata forma semispina; Rhizosolenia bergonii; Rhizosolenia sp.; Rhizosolenia spp.; Riiser-Larsen Sea; Roperia tesselata; South Atlantic Ocean; South-East Pacific; South Pacific Ocean; Stellarima microtrias; Stellarima stellaris; Thalassionema nitzschioides forma 1; Thalassionema nitzschioides var. capitulata; Thalassionema nitzschioides var. lanceolata; Thalassionema nitzschioides var. parva; Thalassionema spp.; Thalassiosira antarctica; Thalassiosira eccentrica; Thalassiosira gracilis var. expecta; Thalassiosira gracilis var. gracilis; Thalassiosira gravida; Thalassiosira lentiginosa; Thalassiosira lineata; Thalassiosira oestrupii; Thalassiosira oliverana; Thalassiosira spp.; Thalassiosira symmetrica; Thalassiosira trifulta; Thalassiosira tumida; Thalassiothrix antarctica/longissima group; Weddell Sea
Tipo

Dataset