Description: Abstract ID: 11526 PosterID: A0020 We are focused on determining the total concentrations of the anthropogenic radionuclides 239Pu, 240Pu, 237Np, and 137Cs in depth profiles from 2010 Atlantic GEOTRACES sections. Data from the equatorial region (A11) compared to GEOSECS data indicate water column inventories of 137Cs have increased over the last 40 years, while those of Pu are variable. By comparison, Pu and 237Np water column inventories are similar to regional soil core inventories, whereas 137Cs inventories are significantly higher, further suggesting continued supply of 137Cs to the open ocean. Water column 240Pu/239Pu inventory ratios are indicative of global fallout (~0.18). Deviations of the water column 237Np/239Pu inventory ratio from the average global fallout value (~0.48) can be used to estimate Pu-particulate fluxes, which are comparable to sediment trap data and may be used to assess scavenging at different locations along the cruise track. Data from mid and high latitude regions (A02) will be compare them to GEOSECS data; inventories and ratios will be used to identify additional contaminant sources, as water mass tracers, and to elucidate important processes such as scavenging and remineralization.

Description: Heme is the iron-containing prosthetic group of hemoproteins, and is thus required for photosynthesis, respiration and nitrate reduction in marine phytoplankton. Here we report concentrations of heme b in Southern Ocean phytoplankton and contrast our findings with those in coastal species. The concentration of particulate heme b (pmol l-1) observed at the end of the exponential growth phase was related to the concentration of dissolved iron in the culture media. Small Southern Ocean phytoplankton species (〈6 μm in diameter) had heme b quotas 〈1 μmol mol-1 carbon, the lowest yet reported for marine phytoplankton. Heme b was also depleted in these species with respect to chlorophyll a. We calculated the amount of carbon accumulated per mole of heme b per second in our cultures (heme growth efficiency, HGE) and found that small Southern Ocean species can maintain growth rates, even while heme b content is reduced. Small Southern Ocean phytoplankton can thus produce more particulate carbon than larger Southern Ocean or small coastal species at equivalent iron concentrations. Combining primary productivity and heme b concentrations reported for the open ocean, we found that HGE in natural populations was within the range of our laboratory culture results. HGE was also observed to be higher at open ocean stations characterized by low iron concentrations. Our results suggest that low heme b quotas do not necessarily result in reduced growth and that marine phytoplankton can optimize iron use by manipulating the intracellular hemoprotein pool

Description: With the common goal of more accurately and consistently quantifying ambient concentrations of free metal ions and natural organic ligands in aquatic ecosystems, researchers from 15 laboratories that routinely analyze trace metal speciation participated in an intercomparison of statistical methods used to model their most common type of experimental dataset, the complexometric titration. All were asked to apply statistical techniques that they were familiar with to model synthetic titration data that are typical of those obtained by applying state-of-the-art electrochemical methods - anodic stripping voltammetry (ASV) and competitive ligand equilibration-adsorptive cathodic stripping voltammetry (CLE-ACSV) - to the analysis of natural waters. Herein, we compare their estimates for parameters describing the natural ligands, examine the accuracy of inferred ambient free metal ion concentrations ([Mf]), and evaluate the influence of the various methods and assumptions used on these results.The ASV-type titrations were designed to test each participant's ability to correctly describe the natural ligands present in a sample when provided with data free of measurement error, i.e., random noise. For the three virtual samples containing just one natural ligand, all participants were able to correctly identify the number of ligand classes present and accurately estimate their parameters. For the four samples containing two or three ligand classes, a few participants detected too few or too many classes and consequently reported inaccurate 'measurements' of ambient [Mf]. Since the problematic results arose from human error rather than any specific method of analyzing the data, we recommend that analysts should make a practice of using one's parameter estimates to generate simulated (back-calculated) titration curves for comparison to the original data. The root-mean-squared relative error between the fitted observations and the simulated curves should be comparable to the expected precision of the analytical method and upon visual inspection the distribution of residuals should not be skewed.Modeling the synthetic, CLE-ACSV-type titration dataset, which comprises 5 titration curves generated at different analytical windows or levels of competing ligand added to the virtual sample, proved to be more challenging due to the random measurement error that was incorporated. Comparison of the submitted results was complicated by the participants' differing interpretations of their task. Most adopted the provided 'true' instrumental sensitivity in modeling the CLE-ACSV curves, but several estimated sensitivities using internal calibration, exactly as is required for actual samples. Since most fitted sensitivities were biased low, systematic error in inferred ambient [Mf] and in estimated weak ligand (L2) concentrations resulted.The main distinction between the mathematical approaches taken by participants lies in the functional form of the speciation model equations, with their implicit definition of independent and dependent or manipulated variables. In 'direct modeling', the dependent variable is the measured [Mf] (or I p) and the total metal concentration ([M]T) is considered independent. In other, much more widely used methods of analyzing titration data - classical linearization, best known as van den Berg/Ružić, and isotherm fitting by nonlinear regression, best known as the Langmuir or Gerringa methods - [Mf] is defined as independent and the dependent variable calculated from both [M]T and [Mf]. Close inspection of the biases and variability in the estimates of ligand parameters and in predictions of ambient [Mf] revealed that the best results were obtained by the direct approach. Linear regression of transformed data yielded the largest bias and greatest variability, while non-linear isotherm fitting generated results with mean bias comparable to direct modeling, but also with greater variability.Participants that performed a unified analysis of ACSV titration curves at multiple detection windows for a sample improved their results regardless of the basic mathematical approach taken. Overall, the three most accurate sets of results were obtained using direct modeling of the unified multiwindow dataset, while the single most accurate set of results also included simultaneous calibration. We therefore recommend that where sample volume and time permit, titration experiments for all natural water samples be designed to include two or more detection windows, especially for coastal and estuarine waters. It is vital that more practical experimental designs for multi-window titrations be developed.Finally, while all mathematical approaches proved to be adequate for some datasets, matrix-based equilibrium models proved to be most naturally suited for the most challenging cases encountered in this work, i.e., experiments where the added ligand in ACSV became titrated. The ProMCC program (Omanović et al., this issue) as well as the Excel Add-in based KINETEQL Multiwindow Solver spreadsheet (Hudson, 2014) have this capability and have been made available for public use as a result of this intercomparison exercise.

Description: The deposition of atmospheric dust into the ocean has varied considerably over geological time1, 2. Because some of the trace metals contained in dust are essential plant nutrients which can limit phytoplankton growth in parts of the ocean, it has been suggested that variations in dust supply to the surface ocean might influence primary production3, 4. Whereas the role of trace metal availability in photosynthetic carbon fixation has received considerable attention, its effect on biogenic calcification is virtually unknown. The production of both particulate organic carbon and calcium carbonate (CaCO3) drives the ocean's biological carbon pump. The ratio of particulate organic carbon to CaCO3 export, the so-called rain ratio, is one of the factors determining CO2 sequestration in the deep ocean. Here we investigate the influence of the essential trace metals iron and zinc on the prominent CaCO3-producing microalga Emiliania huxleyi. We show that whereas at low iron concentrations growth and calcification are equally reduced, low zinc concentrations result in a de-coupling of the two processes. Despite the reduced growth rate of zinc-limited cells, CaCO3 production rates per cell remain unaffected, thus leading to highly calcified cells. These results suggest that changes in dust deposition can affect biogenic calcification in oceanic regions characterized by trace metal limitation, with possible consequences for CO2 partitioning between the atmosphere and the ocean.

Description: During the Polarstern (PS94) expedition, summer 2015, part of the international GEOTRACES program, sources and sinks of dissolved (D) Cd, Co, Cu, Fe, Mn, Ni and Zn were studied in the central Arctic Ocean. In the Polar Surface Water in which the TransPolar Drift (TPD) is situated, salinity and δ18O derived fractions indicated a distinct riverine source for silicate DCo, DCu, DFe, DMn and DNi. Linear relationships between DMn and the meteoric fraction depended on source distance, likely due to Mn-precipitation during transport. In the upper 50 m of the Makarov Basin, outside the TPD core, DCo, DMn, DNi, DCd and DCu were enriched by Pacific waters, whereas DFe seemed diluted. DCo, DFe, DMn and DZn were relatively high in the Barents Sea and led to enrichment of Atlantic water flowing into the Nansen Basin. Deep concentrations of all metals were significantly lower in the Makarov Basin compared to the Nansen and Amundsen, the Eurasian, Basins. The Gakkel ridge hydrothermal input and higher continental slope convection are explanations for higher metal concentrations in the Eurasian Basins. Although scavenging rates are lower in the Makarov Basin compared to the Eurasian Basins, the residence time is longer and therefore scavenging can decrease the dissolved concentrations with time. This study provides a baseline to assess future change, and additionally identifies processes driving trace metal distributions. Our results underline the importance of fluvial input as well as shelf sources and internal cycling, notably scavenging, for the distribution of bio-active metals in the Arctic Ocean.

Description: Dissolved neodymium (Nd) isotopes (expressed as εNd) have been widely used as a water mass tracer to reconstruct paleo ocean circulation. However, the marine geochemical cycle of Nd is not well understood. Unclear input mechanisms, scarcity of available data, and observed decoupling between dissolved εNd and Nd concentration patterns ([Nd]) are only a few of the unresolved issues. The latter is often referred to as the Nd paradox (e.g. [1]). Here we revisit this paradox with an unprecedented data set on particulate Nd isotope and concentration data from five stations along the Dutch GEOTRACES transect GA02 in the western North and equatorial Atlantic Ocean (cruises 64PE319 and 64PE321 from April to July 2010).