Distribution of iodide and iodate in the Atlantic sector of the southern ocean during austral summer

The biogeochemistry of iodine in the waters of the Atlantic sector of the Southern Ocean was investigated during the Polarstern cruise ANTXXIV-3 ZERO&DRAKE. The speciation and distribution of iodine (iodate and iodide) in seawater was examined across gradients of iron concentrations and phytoplankton abundance, ranging from an open ocean region along the Zero Meridian to the Weddell Sea and Drake Passage. Iodine cycling in high latitudes differs from that in low latitudes due to differences in the plankton community composition and the physicochemical characteristics. Iodate concentrations ranged between 400 and 450 nmol L(-1) from the surface to the bottom. Surface concentrations of iodide (17 to over 60 nmol L(-1)) were about an order of magnitude higher than below the pycnocline. The peak values of iodide lay nearly always within the euphotic zone and showed a weak, positive correlation with nitrite concentrations in the upper 200 m. In all vertical profiles a pronounced sub-surface maximum in iodide appears between 50 and 200 m depth indicating an iodide drawdown at the near surface. Iodide distribution in the Weddell Sea showed elevated levels in Weddell Sea Bottom Water (WSBW) indicating slow oxidation kinetics and the potential for iodide as a tracer of WSBW formation. (C) 2011 Elsevier Ltd. All rights reserved

The fate of added iron during a mesoscale fertilisation experiment in the polar Southern Ocean

The first Southern Ocean Iron RElease Experiment (SOIREE) was performed during February 1999 in Antarctic waters south of Australia (61°S, 140°E), in order to verify whether iron supply controls the magnitude of phytoplankton production in this high nutrient low chlorophyll (HNLC) region. This paper describes iron distributions in the upper ocean during our 13-day site occupation, and presents a pelagic iron budget to account for the observed losses of dissolved and total iron from waters of the fertilised patch. Iron concentrations were measured underway during daily transects through the patch and in vertical profiles of the 65-m mixed layer. High internal consistency was noted between data obtained using contrasting sampling and analytical techniques. A pre-infusion survey confirmed the extremely low ambient dissolved (0.1 nM) and total (0.4 nM) iron concentrations. The initial enrichment elevated the dissolved iron concentration to 2.7 nM. Thereafter, dissolved iron was rapidly depleted inside the patch to 0.2–0.3 nM, necessitating three re-infusions.A distinct biological response was observed in iron-fertilised waters, relative to outside the patch, unequivocally confirming that iron limits phytoplankton growth rates and biomass at this site in summer. Our budget describing the fate of the added iron demonstrates that horizontal dispersion of fertilised waters (resulting in a quadrupling of the areal extent of the patch) and abiotic particle scavenging accounted for most of the decreases in iron concentrations inside the patch (31–58% and 12–49% of added iron, respectively). The magnitude of these loss processes altered towards the end of SOIREE, and on days 12–13 dissolved (1.1 nM) and total (2.3 nM) iron concentrations remained elevated compared to surrounding waters. At this time, the biogenic iron pool (0.1 nM) accounted for only 1–2% of the total added iron. Large pennate diatoms (>20 m) and autotrophic flagellates (2–20 m) were the dominant algal groups in the patch, taking up the added iron and representing 13% and 39% of the biogenic iron pool, respectively. Iron regeneration by grazers was tightly coupled to uptake by phytoplankton and bacteria, indicating that biological Fe cycling within the bloom was self-sustaining. A concurrent increase in the concentration of iron-binding ligands on days 11–12 probably retained dissolved iron within the mixed layer. Ocean colour satellite images in late March suggest that the bloom was still actively growing 42 days after the onset of SOIREE, and hence by inference that sufficient iron was maintained in the patch for this period to meet algal requirements. This raises fundamental questions regarding the biogeochemical cycling of iron in the Southern Ocean and, in particular, how bioavailable iron was retained in surface waters and/or within the biota to sustain algal growth

Shipboard analytical intercomparison of dissolved iron in surface waters along a north-south transect of the tropical Atlantic Ocean

A shipboard analytical intercomparison of dissolved (<0.2 m) iron in the surface waters of the Atlantic Ocean was undertaken during October 2000. A single underway surface (1–2 m) seawater sampling and filtration protocol was used, in order to minimise differences from possible sample contamination. Over 200 samples (1/h) were collected over 12 days and analysed immediately using four different analytical methods, based on three variants of flow injection with luminol chemiluminescence (FI–CL) and cathodic stripping voltammetry (CSV). Dissolved iron concentrations varied between 0.02 and 1.61 nM during the intercomparison. On average, CSV [Electroanalysis 12 (2000) 565] measured 0.08 nM higher iron concentrations than one FI–CL method [Anal. Chim. Acta 361 (1998) 189], which measured 0.13 nM higher iron values than the other two [Anal. Chem. 65 (1993) 1524; Anal. Chim. Acta 377 (1998) 113]. Statistical analyses (paired two-tailed t-test) showed that each analytical method gave significantly different dissolved iron concentrations at the 95% confidence interval. These data however, represent a significant improvement over earlier intercomparison exercises for iron. The data have been evaluated with respect to accuracy and overall inter-laboratory replicate precision, which was generally better than the 95% confidence intervals reported for the NASS Certified Reference Materials. Systematic differences between analytical methods were probably due to the extraction of different physico-chemical forms of iron during preconcentration, either on the micro-column resin (in the FI methods) or with competing ligand equilibration (in the CSV method). Small systematic concentration differences may also have resulted from protocols used for quantification of the analytical blank and instrument calibration

Synoptic transects on the distribution of trace elements (Hg, Pb, Cd, Cu, Ni, Zn, Co, Mn, Fe, and Al) in surface waters of the Northern- and Southern East Atlantic

Surface seawater samples were taken in the framework of the GEOTRACES program on “POLARSTERN” expedition ANT XXIII/1 in the Eastern Atlantic in 2005 to study the distribution of the trace elements Hg (mercury), Pb (lead), Cd (cadmium), Cu (copper), Ni (nickel), Zn (zinc), Co (cobalt), Mn (manganese), Fe (iron), and Al (aluminium). With the exception of Hg, results were compared to earlier datasets from 1989 to 1990. The particulate fraction averaged over the transect was calculated to be 49% for Cd, 23% for Mn and 50% for Fe indicating a release of these TEI's (trace elements and their isotopes) from a leachable SPM fraction in the stored and acidified samples. Total Pb concentrations ranged between 5 and 20 pmol kg− 1 in 2005 with highest values in the ITCZ (intertropical convergence zone). In 1989 Pb concentrations were twice as high in the region of the ITCZ, while by a factor of 10–15 higher values were obtained in the North Atlantic. Total Cd and Co are dominated, by different seasonal upwelling regimes (Equatorial upwelling, Guinea Dome, Angola Dome). Total Cu, Ni, Fe, Mn and Al show nearly identical concentrations in 1990 and 2005. For total manganese and aluminium strong maxima (3–4 nmol kg− 1 and 55 nmol kg− 1 respectively) are observed between 23°N and 0°, while the Fe maximum (6–9 nmol kg− 1) is located at 7°N. Total Hg concentrations ranged between 0.5 and 4.5 pmol kg− 1

Interpretation of complexometric titration data: an intercomparison of methods for estimating models of trace metal complexation by natural organic ligands

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 Ip) 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/Ruži?, 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 (Omanovi? 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