Presence-absence species/sample matrix for the measured sections at the area of Maghara, North Sinai, Egypt

As age-diagnostic fossils are rare in the Middle to Upper Jurassic sedimentary succession of Gebel Maghara, North Sinai, Egypt, and in order to ensure maximal stratigraphic resolution, chronostratigraphic boundaries were determined based on quantitative biostratigraphy. A data matrix comprising 231 macrofaunal taxa in 93 samples from four sections has been processed with the Unitary Association (UA) Method. This led to construction of a sequence of 29 UAs (maximal sets of actually or virtually coexisting taxa), which have been grouped into 14 laterally reproducible association zones. The UA method allowed an in-depth analysis of the stratigraphically conflicting taxa, enabled the biostratigraphic subdivision of the studied interval, and also provided stratigraphic correlation among the measured sections and with the Tethyan ammonite zones.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.

Benthic isopod species in the Ross Sea and their distribution in the Southern Ocean

In this study isopod species of the Ross Sea were investigated. Literature until May 2008 was checked to provide an overview of all known and described species in the Ross Sea. This species checklist was then enlarged through material of the 19th Italica expedition in 2004. During this expedition for the first time a small mesh net (500 µm) was used. Nine thousand four hundred and eighty one isopod specimens were collected during this expedition. Through this material the number of isopod species in the Ross Sea increased from 42 to 117 species, which belong to 20 families and 49 genera. Fifty-six percentage of the isopods species collected during the Italica expedition are new to science. The zoogeography of the 117 species was investigated. A non-transformed binary presence-absence data matrix was constructed using the Bray-Curtis coefficient. The results were displayed in a cluster analysis and by nonmetric multidimensional scaling (MDS). This paper gives a first insight into the occurrence and distribution of the isopod species of the Ross Sea.

Oxygen content and paleoproductivity from surface sediment samples Y69-86 to PLDS-004G

Quantitative estimation of surface ocean productivity and bottom water oxygen concentration with benthic foraminifera was attempted using 70 samples from equatorial and North Pacific surface sediments. These samples come from a well defined depth range in the ocean, between 2200 and 3200 m, so that depth related factors do not interfere with the estimation. Samples were selected so that foraminifera were well preserved in the sediments and temperature and salinity were nearly uniform (T = 1.5° C; S = 34.6 per mil). The sample set was also assembled so as to minimize the correlation often seen between surface ocean productivity and bottom water oxygen values (r**2 = 0.23 for prediction purposes in this case). This procedure reduced the chances of spurious results due to correlations between the environmental variables. The samples encompass a range of productivities from about 25 to >300 gC m**-2 yr**-1, and a bottom water oxygen range from 1.8 to 3.5 ml/L. Benthic foraminiferal assemblages were quantified using the >62 µm fraction of the sediments and 46 taxon categories. MANOVA multivariate regression was used to project the faunal matrix onto the two environmental dimensions using published values for productivity and bottom water oxygen to calibrate this operation. The success of this regression was measured with the multivariate r? which was 0.98 for the productivity dimension and 0.96 for the oxygen dimension. These high coefficients indicate that both environmental variables are strongly imbedded in the faunal data matrix. Analysis of the beta regression coefficients shows that the environmental signals are carried by groups of taxa which are consistent with previous work characterizing benthic foraminiferal responses to productivity and bottom water oxygen. The results of this study suggest that benthic foraminiferal assemblages can be used for quantitative reconstruction of surface ocean productivity and bottom water oxygen concentrations if suitable surface sediment calibration data sets are developed and appropriate means for detecting no-analog samples are found.

(Table 2) Trace element composition of seleceted clast and matrix materials from ODP Site 125-786

Shipboard examination of volcanic and sedimentary strata at Site 786 suggested that at least four types of breccias are present: flow-top breccias, associated with cooling and breakup on the upper surface of lava flows; autobreccias, formed by in-situ alteration at the base of flows; fault-gouge breccias; and true sedimentary breccias derived from weathering and erosion of underlying flows. It is virtually impossible to assess the origin of breccia matrix by textural and mineralogical analyses alone. However, it is fundamental for our understanding of breccia provenance to determine the source component of the matrix material. Whether the matrix is uniquely clastderived can be determined by geochemical fingerprinting. Trace elements that are immobile during weathering and alteration do not change their relative abundances. A contribution to the matrix from any source with an immobile trace element signature different from that of the clasts would appear as a perturbation of the trace element signature of the matrix. Trace element analysis of bulk samples from clasts and matrix material in individual breccia units was undertaken in a fashion similar to that used by Brimhall and Dietrich (1987, doi:10.1016/0016-7037(87)90070-6) in analyzing soil provenance: (1) to help distinguish between sedimentary and volcanic breccias, (2) to determine the degree of mixing and depth of erosion in sedimentary breccias, and (3) to analyze the local provenance of the individual breccia components (matrix and clasts). The following elements were analyzed by X-ray fluorescence (XRF): Rb, Sr, Ba, U, Zr, Cu, Zn, Ti, Cr, and V. Of these elements, Zr and Ti probably exhibit truly immobile behavior (Humphris and Thompson, 1978, doi:10.1016/0016-7037(78)90222-3 ). The remaining elements are useful as a reference for the extent of compositional change during the formation of matrix material (Brimhall and Dietrich, 1987, doi:10.1016/0016-7037(87)90070-6).

Mean dynamic topography and oceanographic parameters estimated from an inverse model and satellite geodesy, with link to model result in one single NetCDF file (392 MB), including the inverse data error covariance

Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.