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2015
Semeniuk, DM, Bundy RM, Payne CD, Barbeau KA, Maldonado MT.  2015.  Acquisition of organically complexed copper by marine phytoplankton and bacteria in the northeast subarctic Pacific Ocean. Marine Chemistry. 173:222-233.   10.1016/j.marchem.2015.01.005   AbstractWebsite

Copper (Cu) is an essential micronutrient for marine phytoplankton, but can cause toxicity at elevated intracellular concentrations. The majority of Cu (>99.9%) in oceanic surface waters is bound to strong organic ligands, presumably produced by prokaryotes to detoxify Cu. Although laboratory studies have demonstrated that organically complexed Cu may be bioavailable to marine eukaryotic phytoplankton, the bioavailability of Cu organic complexes to indigenous marine phytoplankton has not been examined in detail. Using the carrier free radioisotope Cu-67 at an iron limited station in the northeast subarctic Pacific Ocean, we performed size fractionated short-term Cu uptake assays with three Cu(II)-chelates, and Cu-67 bound to the strong in situ ligands, with or without additions of weak Cu(I) ligands. Estimates of the maximum supply of inorganic Cu (Cu') to the cell surface of eukaryotic phytoplankton were unable to account for the observed Cu uptake rates from the in situ ligands and two of the three added Cu(II)-chelates. Addition of 10 nM weak organic Cu(I) ligands enhanced uptake of Cu bound to the in situ ligands. Thus, Cu within the in situ and strong artificial Cu(II) organic ligands was accessible to the phytoplankton community via various possible Cu uptake strategies, including; cell surface enzymatically mediated reduction of Cu(II) to Cu(I), the substrate of the high-affinity Cu transport system in eukaryotes; or ligand exchange between weak Cu-binding ligands and the cellular Cu transporters. During a 14-hour uptake assay, particulate Cu concentrations reached a plateau in most treatments. Losses were observed in some treatments, especially in the small size fractions (<5 mu m), corresponding with faster initial Cu uptake rates. This may indicate that Cu cycling is rapid between particulate and dissolved phases due to cellular efflux or remineralization by micrograzers. The acquisition of Cu from the strong in situ ligands puts into question the historic role attributed to Cu binding ligands in decreasing Cu bioavailability. (C) 2015 Elsevier B.V. All rights reserved.

Pizeta, I, Sander SG, Hudson RJM, Omanovic D, Baars O, Barbeau KA, Buck KN, Bundy RM, Carrasco G, Croot PL, Garnier C, Gerringa LJA, Gledhill M, Hirose K, Kondo Y, Laglera LM, Nuester J, Rijkenberg MJA, Takeda S, Twining BS, Wells M.  2015.  Interpretation of complexometric titration data: An intercomparison of methods for estimating models of trace metal complexation by natural organic ligands. Marine Chemistry. 173:3-24.   10.1016/j.marchem.2015.03.006   AbstractWebsite

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 (]M-f]), 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 [M-f]. 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 [M-f] and in estimated weak ligand (L-2) 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 [M-f] (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/Ruzic and isotherm fitting by nonlinear regression, best known as the langmuir or Gerringa methods - [M-f] is defined as independent and the dependent variable calculated from both [M](T) and [M-f]. Close inspection of the biases and variability in the estimates of ligand parameters and in predictions of ambient [M-f] 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 (Omanovic 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. (C) 2015 The Authors. Published by Elsevier B.V.

2014
Bundy, RM, Biller DV, Buck KN, Bruland KW, Barbeau KA.  2014.  Distinct pools of dissolved iron-binding ligands in the surface and benthic boundary layer of the California Current. Limnology and Oceanography. 59:769-787.   10.4319/lo.2014.59.3.0769   AbstractWebsite

Organic dissolved iron (dFe)-binding ligands were measured by competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-ACSV) at multiple analytical windows (side reaction coefficient of salicylaldoxime, alpha(Fe(SA)2) = 30, 60, and 100) in surface and benthic boundary layer (BBL) samples along the central California coast during spring and summer. The weakest ligands were detected in the BBL at the lowest analytical window with average log K-FeL,Fe'(cond) = 10.2 +/- 0.4 in the summer and 10.8 +/- 0.2 in the spring. Between 3% and 18% of the dFe complexation in the BBL was accounted for by HS, which were measured separately in samples by ACSV and may indicate a source of dFe-binding ligands from San Francisco Bay. The strongest ligands were found in nearshore spring surface waters at the highest analytical window with average log K-FeL,Fe'(cond) = 11.9 +/- 0.3, and the concentrations of these ligands declined rapidly offshore. The ligand pools in the surface and BBL waters were distinct from each other based on principal components analysis, with variances in the BBL ligand pool explained by sample location, and variance in surface waters explained by water mass. The use of multiple analytical window analysis elucidated several distinct iron-binding ligand pools, each with unique distributions in the central California Current system.

2013
Bundy, RM, Barbeau KA, Buck KN.  2013.  Sources of strong copper-binding ligands in Antarctic Peninsula surface waters. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 90:134-146.   10.1016/j.dsr2.2012.07.023   AbstractWebsite

Copper-binding organic ligands were measured during austral winter in surface waters around the Antarctic Peninsula using competitive ligand exchange-adsorptive cathodic stripping voltammetry with multiple analytical windows. Samples were collected from four distinct water masses including the Antarctic Circumpolar Current, Southern Antarctic Circumpolar Current Front, Bransfield Strait, and the shelf region of the Antarctic Peninsula. Strong copper-binding organic ligands were detected in each water mass. The strongest copper-binding ligands were detected at the highest competition strength in the Antarctic Circumpolar Current, with an average conditional stability constant of logK(CuL,Cu2+)(cond) = 16.00 +/- 0.82. The weakest ligands were found at the lowest competition strength in the shelf region with logK(CuL,Cu2+)(cond) = 12.68 +/- 0.48. No ligands with stability constants less than logK(CuL,Cu2+)(cond) = 13.5 were detected in the Antarctic Circumpolar Current at any competition strength, suggesting a shelf source of weaker copper-binding ligands. Free, hydrated copper ion concentrations, the biologically available form of dissolved copper, were less than 10(-14) M in all samples, approaching levels that may be limiting for some types of inducible iron acquisition. (C) 2012 Elsevier Ltd. All rights reserved.

2010
Buck, KN, Selph KE, Barbeau KA.  2010.  Iron-binding ligand production and copper speciation in an incubation experiment of Antarctic Peninsula shelf waters from the Bransfield Strait, Southern Ocean. Marine Chemistry. 122:148-159.   10.1016/j.marchem.2010.06.002   AbstractWebsite

The evolution of dissolved iron (Fe) and copper (Cu) speciation was followed through a simulated spring bloom event in a 15-day incubation experiment of natural seawater collected during austral winter from high macronutrient high Fe waters of Bransfield Strait in the Southern Ocean. The incubation experiment included unamended bottles as well as Fe additions using the stable isotope of Fe, Fe-57. as inorganic ((FeCl3)-Fe-57) and organic (Fe-57-aerobactin, Fe-57-desferrioxamine B) amendments. Exposure to summer light conditions resulted in substantial growth for all treatments, mimicking the initiation of a spring bloom. The addition of Fe resulted in a 30% increase in phytoplankton biomass over unamended controls by day 15, indicating that the unamended waters became Fe limited despite initially elevated dissolved Fe concentrations. Dissolved Cu and Cu speciation remained largely unchanged for all treatments of the incubation, with Cu speciation dominated by exceedingly strong Cu-binding ligands (log K-CuL1.Cu2+(Cond) similar to 16) and low resultant Cu2+ concentrations (10(-16.3 +/- 0.3) mol L-1). In only the unamended light bottles, strong Fe-binding ligands were produced over the course of the experiment. The observed production of strong Fe-binding ligands in the control bottles that became Fe-limited supports the important role of biologically produced siderophore-type natural ligands in the marine Fe cycle. (C) 2010 Elsevier B.V. All rights reserved.