Artificial oxygen fluxes measured by the eddy correlation method using stirring-sensitive oxygen microsensor and oxygen optodes in a flume experiment

In the last decade, the aquatic eddy correlation (EC) technique has proven to be a powerful approach for non-invasive measurements of oxygen fluxes across the sediment water interface. Fundamental to the EC approach is the correlation of turbulent velocity and oxygen concentration fluctuations measured with high frequencies in the same sampling volume. Oxygen concentrations are commonly measured with fast responding electrochemical microsensors. However, due to their own oxygen consumption, electrochemical microsensors are sensitive to changes of the diffusive boundary layer surrounding the probe and thus to changes in the ambient flow velocity. The so-called stirring sensitivity of microsensors constitutes an inherent correlation of flow velocity and oxygen sensing and thus an artificial flux which can confound the benthic flux determination. To assess the artificial flux we measured the correlation between the turbulent flow velocity and the signal of oxygen microsensors in a sealed annular flume without any oxygen sinks and sources. Experiments revealed significant correlations, even for sensors designed to have low stirring sensitivities of ~0.7%. The artificial fluxes depended on ambient flow conditions and, counter intuitively, increased at higher velocities because of the nonlinear contribution of turbulent velocity fluctuations. The measured artificial fluxes ranged from 2 - 70 mmol m**-2 d**-1 for weak and very strong turbulent flow, respectively. Further, the stirring sensitivity depended on the sensor orientation towards the flow. Optical microsensors (optodes) that should not exhibit a stirring sensitivity were tested in parallel and did not show any significant correlation between O2 signals and turbulent flow. In conclusion, EC data obtained with electrochemical sensors can be affected by artificial flux and we recommend using optical microsensors in future EC-studies. Flume experiments were conducted in February 2013 at the Institute for Environmental Sciences, University of Koblenz-Landau Landau. Experiments were performed in a closed oval-shaped acrylic glass flume with cross-sectional width of 4 cm and height of 10 cm and total length of 54 cm. The fluid flow was induced by a propeller driven by a motor and mean flow velocities of up to 20 cm s-1 were generated by applying voltages between 0 V and 4 V DC. The flume was completely sealed with an acrylic glass cover. Oxygen sensors were inserted through rubber seal fittings and allowed positioning the sensors with inclinations to the main flow direction of ~60°, ~95° and ~135°. A Clark type electrochemical O2 microsensor with a low stirring sensitivity (0.7%) was tested and a fast-responding needle-type O2 optode (PyroScience GmbH, Germany) was used as reference as optodes should not be stirring sensitive. Instantaneous three-dimensional flow velocities were measured at 7.4 Hz using stereoscopic particle image velocimetry (PIV). The velocity at the sensor tip was extracted. The correlation of the fluctuating O2 sensor signals and the fluctuating velocities was quantified with a cross-correlation analysis. A significant cross-correlation is equivalent to a significant artificial flux. For a total of 18 experiments the flow velocity was adjusted between 1.7 and 19.2 cm s**-1, and 3 different orientations of the electrochemical sensor were tested with inclination angles of ~60°, ~95° and ~135° with respect to the main flow direction. In experiments 16-18, wavelike flow was induced, whereas in all other experiments the motor was driven by constant voltages. In 7 experiments, O2 was additionally measured by optodes. Although performed simultaneously with the electrochemical sensor, optode measurements are listed as separate experiments (denoted by the attached 'op' in the filename), because the velocity time series was extracted at the optode tip, located at a different position in the flume.

Metadata und statistic analysis of archael and bacterial sequences originating from sediments of the Håkon Mosby mud volcano (Z1-Z3, all habitats)

DNA extraction was carried out as described on the MICROBIS project pages (http://icomm.mbl.edu/microbis ) using a commercially available extraction kit. We amplified the hypervariable regions V4-V6 of archaeal and bacterial 16S rRNA genes using PCR and several sets of forward and reverse primers (http://vamps.mbl.edu/resources/primers.php). Massively parallel tag sequencing of the PCR products was carried out on a 454 Life Sciences GS FLX sequencer at Marine Biological Laboratory, Woods Hole, MA, following the same experimental conditions for all samples. Sequence reads were submitted to a rigorous quality control procedure based on mothur v30 (doi:10.1128/AEM.01541-09) including denoising of the flow grams using an algorithm based on PyroNoise (doi:10.1038/nmeth.1361), removal of PCR errors and a chimera check using uchime (doi:10.1093/bioinformatics/btr381). The reads were taxonomically assigned according to the SILVA taxonomy (SSURef v119, 07-2014; doi:10.1093/nar/gks1219) implemented in mothur and clustered at 98% ribosomal RNA gene V4-V6 sequence identity. V4-V6 amplicon sequence abundance tables were standardized to account for unequal sampling effort using 1000 (Archaea) and 2300 (Bacteria) randomly chosen sequences without replacement using mothur and then used to calculate inverse Simpson diversity indices and Chao1 richness (doi:10.2307/4615964). Bray-Curtis dissimilarities (doi:10.2307/1942268) between all samples were calculated and used for 2-dimensional non metric multidimensional scaling (NMDS) ordinations with 20 random starts (doi:10.1007/BF02289694). Stress values below 0.2 indicated that the multidimensional dataset was well represented by the 2D ordination. NMDS ordinations were compared and tested using Procrustes correlation analysis (doi:10.1007/BF02291478). All analyses were carried out with the R statistical environment and the packages vegan (available at: http://cran.r-project.org/package=vegan), labdsv (available at: http://cran.r-project.org/package=labdsv), as well as with custom R scripts. Operational taxonomic units at 98% sequence identity (OTU0.03) that occurred only once in the whole dataset were termed absolute single sequence OTUs (SSOabs; doi:10.1038/ismej.2011.132). OTU0.03 sequences that occurred only once in at least one sample, but may occur more often in other samples were termed relative single sequence OTUs (SSOrel). SSOrel are particularly interesting for community ecology, since they comprise rare organisms that might become abundant when conditions change.16S rRNA amplicons and metagenomic reads have been stored in the sequence read archive under SRA project accession number SRP042162.

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Chemical composition of phillipsites from Core AKO26-35

Behavior of rare earth elements (REE) was examined in oceanic phillipsites collected from four horizons of eupelagic clay in the Southwest Basin of the Pacific Ocean. REE concentrations were determined in >50 ?m size fraction phillipsite samples by the ICP-MS method. Composition of separate phillipsite aggregates was studied by electron microprobe and secondary ion mass-spectrometry. Rare earth elements in phillipsite samples are related to admixture of ferrocalcium hydroxophosphates. Analysis of separate phillipsite aggregates reveals low (<0.1-18.1 ppm) REE(III) concentrations. Ce concentration varies between 2.7 and 140 ppm. The correlation analysis shows that REE(III) present in admixture of iron oxyhydroxides in separate phillipsite aggregates. Based on the REE(III) concentration in iron oxyhydroxides we can identify two generations of phillipsite aggregates. Massive rounded aggregates (phillipsite I) are depleted in REE, while pseudorhombic (phillipsite II) aggregates are enriched in REE and marked by a positive Ce anomaly. Oceanic phillipsites do not accumulate REE or inherit the REE signature of volcaniclastic material and oceanic deep water. Hence, REE distribution in phillipsites does not depend on sedimentation rate and composition of host sediments.

Composition of surface layer bottom sediments from the Kem' River estuary, White Sea

Based on grain-size, mineralogical and chemical analyses of samples collected in cruises of R/V Ekolog (Institute of Northern Water Problems, Karelian Research Centre of RAS, Petrozavodsk) in 2001 and 2003 regularities of chemical element distribution in surface layer bottom sediments of the Kem' River Estuary in the White Sea were studied. For some toxic elements labile and refractory forms were determined. Correlation analysis was carried out and ratios Me/Al were calculated as proxies of terrigenous contribution. Distribution of such elements as Fe, Mn, Zn, Cr, Ti was revealed to be influenced by natural factors, mainly by grain size composition of bottom sediments. These metals have a tendency for accumulation in fine-grained sediments with elevated organic carbon contents. Distribution of Ni is different from one of Fe, Mn, Zn, Cr, Ti. An assumption was made that these distinctions were caused by anthropogenic influence.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

(Table 1) Polychlorinated biphenyl (PCB) and PCB metabolite concentrations in ringed seals (Phoca hispida) from Svalbard and the Baltic Sea

Polychlorinated biphenyls (PCBs) may induce activity of hepatic enzymes, mainly Phase I monooxygenases and conjugating Phase II enzymes, that catalyze the metabolism of PCBs leading to formation of metabolites and to potential adverse health effects. The present study investigates the concentration and pattern of PCBs, the induction of hepatic phase I and II enzymes, and the formation of hydroxy (OH) and methylsulfonyl (CH3SO2=MeSO2) PCB metabolites in two ringed seal (Phoca hispida) populations, which are contrasted by the degree of contamination exposure, that is, highly contaminated Baltic Sea (n = 31) and less contaminated Svalbard (n = 21). Phase I enzymes were measured as ethoxyresorufin-O-deethylation (EROD), benzyloxyresorufin-O-dealkylation (BROD), methoxyresorufin-O-demethylation (MROD), and pentoxyresorufin-O-dealkylation (PROD) activities, and phase II enzymes were measured as uridine diphosphophate glucuronosyl transferase (UDPGT) and glutathione-S-transferase (GST). Geographical comparison, multivariate, and correlation analysis indicated that sum-PCB had a positive impact on Phase I enzyme and GST activities leading to biotransformation of group III (vicinal ortho-meta-H atoms and <=1 ortho-chlorine (Cl)) and IV PCBs (vicinal meta-para-H atoms and <=2 ortho-Cl). The potential precursors for the main OH-PCBs detected in plasma in the Baltic seals were group III PCBs. MeSO2-PCBs detected in liver were mainly products of group IV PCB metabolism. Both CYP1A- and CYP2B-like enzymes are suggested to be involved in the PCB biotransformation in ringed seals.

(Table T2) Remanent anomaly and Koenigsberger ratio of ODP holes

Magnetic field strength and magnetic susceptibility were logged with the geological high-resolution magnetic tool (GHMT) at three of the holes drilled during Ocean Drilling Program Leg 178 to the west of the Antarctic Peninsula. Polarity stratigraphies derived from the GHMT logs bear close resemblance to the polarities determined from core paleomagnetism at two of the holes and were used for magnetostratigraphic dating, especially in intervals where no core was recovered. Polarity is determined in the following way. First, the susceptibility log is used to determine the induced magnetization of the sediment. Then the background field, the field of the metal drill pipe, and the field anomaly of the sediment's induced magnetization are removed from the measured total field to leave the downhole anomaly of the sediment's remanent magnetization. The sign (positive or negative) of this anomaly gave a good polarity stratigraphy for Holes 1095B and 1096C, which are located in sediment drifts. A further step, correlation analysis, is based on the fact that in an interval of normal polarity sediment the remanent anomaly will correlate with the induced anomaly, whereas in reversed polarity sediment they will anticorrelate. The magnetite-rich, fine-grained sediments found in the two holes drilled into the sediment drift have a ratio of remanent to induced magnetization (the Koenigsberger ratio) of ~1. In contrast, the coarser-grained diamict sediments on the shelf have a Koenigsberger ratio of ~0.2, and extracting the remanent part of the downhole anomaly is much more difficult. By the comparison of core and log results, we can assess the viability of the GHMT polarities in detail, what proportion of the overprint in the cores is imparted by the coring process, and whether any paleointensity information is extractable from the GHMT logs.

Benthic foraminifera in Southwest Indian Ocean surface sediments

The distribution of deep-sea benthonic foraminifera in core top samples from the southwest Indian Ocean is examined. Principal component analysis reveals two major assemblages. One assemblages between 3600 and 4800-m water depth is dominated by Episominella umbonifera and is associated with cold (Theta = -0.3 to 0.8°C), low salinity (34.66 to 34.72 * 10**-3) Antarctic Bottom Water in the Crozet Basin, in fracture zones, and on the flanks of the Southwest Indian Ridge. A second assemblage, dominated by Planulina wuellerstorfi, Globocassidulina subglobasa, Astrononion echolsi and Pullenia bulloides, is between 1600 and 3800 m on the Crozet Plateau, Madagascar Ridge, Central Indian Ridge, and Southwest Indian Ridge and is associated with relatively warm (Theta = 0.8 to 2.6°C), high salinity (34.72 to 34.76 * 10**-3) North Atlantic Deep Water. The third principal component divides the P. wuellerstorfi assemblage into two subgroups. One is dominated by Epistominella exigua, P. bulloides, P. wuellerstorfi, and A. echolsi and a second is dominated by G. subglobosa. The distribution of the E. umbonifera assemblage and previous hydrographic studies suggest that AABW flows as a western boundary contour current in the Crozet Basin and penetrates fracture zones in the Southwest Indian Ridge between 55 and 57°E and near 66°E as it travels northward into the Madagascar and Mascarene basins. The faunal-water mass associations from the southeast Indian Ocean are compared; the most notable faunal difference is the absence of Uvigerina as a dominant taxon in the southwest Indian Ocean. A comparison of dissolved oxygen and Uvigerina data shows that oxygen is not a major influence upon the distribution of Uvigerina. A correlation analysis of the faunal data and water depth, potential temperature, in situ temperature, salinity, dissolved oxygen, and 1 - Omega, an index of calcium carbonate undersaturation, was carried out to determine the relationships between fauna and hydrography. The second principal component has a significant positive correlation at the 99.9% level with temperature and negative correlations with water depth and 1 - Omega. A general faunal-water mass correlation exists, but it is not possible to determine which variable controls the faunal distributions.