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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.

Bundy, RM, Jiang M, Carter M, Barbeau KA.  2016.  Iron-binding ligands in the southern California Current System: Mechanistic studies. Frontiers in Marine Science. 3:27.   10.3389/fmars.2016.00027   Abstract

The distributions of dissolved iron and organic iron-binding ligands were examined in water column profiles and deckboard incubation experiments in the southern California Current System (sCCS) along a transition from coastal to semi-oligotrophic waters. Analysis of the iron-binding ligand pool by competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-ACSV) using multiple analytical windows (MAWs) revealed three classes of iron-binding ligands present throughout the water column (L1-L3), whose distributions closely matched those of dissolved iron and nitrate. Despite significant biogeochemical gradients, ligand profiles were similar between stations, with surface minima in strong ligands (L1 and L2), and relatively constant concentrations of weaker ligands (L3) down to 500 m. A phytoplankton grow-out incubation, initiated from an iron-limited water mass, showed dynamic temporal cycling of iron-binding ligands. A biological iron model was able to capture the patterns of the strong ligands in the grow-out incubation relatively well with only the microbial community as a biological source. An experiment focused on remineralization of particulate organic matter showed production of both strong and weak iron-binding ligands by the heterotrophic community, supporting a mechanism for in-situ production of both strong and weak iron-binding ligands in the subsurface water column. Photochemical experiments showed a variable influence of sunlight on the degradation of natural iron-binding ligands, providing some evidence to explain differences in surface ligand concentrations between stations. Patterns in ligand distributions between profiles and in the incubation experiments were primarily related to macronutrient concentrations, suggesting microbial remineralization processes might dominate on longer time-scales over short-term changes associated with photochemistry or phytoplankton growth.

Bundy, RM, Abdulla HAN, Hatcher PG, Biller DV, Buck KN, Barbeau KA.  2015.  Iron-binding ligands and humic substances in the San Francisco Bay estuary and estuarine-influenced shelf regions of coastal California. Marine Chemistry. 173:183-194.   10.1016/j.marchem.2014.11.005   AbstractWebsite

Dissolved iron (dFe) and organic dFe-binding ligands were determined in San Francisco Bay, California by competitive ligand exchange adsorptive cathodic stripping voltammetry (CLE-ACSV) along a salinity gradient from the freshwater endmember of the Sacramento River (salinity <2) to the mouth of the estuary (salinity >26). A range of dFe-binding ligand classes was simultaneously determined using multiple analytical window analysis, involving titrations with multiple concentrations of the added ligand,salicylaldoxime. The highest dFe and ligand concentrations were determined in the low salinity end of the estuary, with dFe equal to 131.5 nmol L-1 and strong ligand (log K-Fel, Fe'(cond) >= 12.0) concentrations equal to 139.5 nmol L-1. The weakest ligands (log K-Fel, Fe'(cond) < 10.0) were always in excess of dFe in low salinity waters, but were rapidly flocculated within the estuary and were not detected at salinities greater than 7. The strongest ligands (log K-Fel, Fe'(cond) > 11.0) were tightly coupled to dFe throughout the estuary, with average excess ligand concentrations ([L]-[dFe]) equal to 0.5 nmol L-1. Humic-like substances analyzed via both CLE-ACSV and proton nuclear magnetic resonance in several samples were found to be a significant portion of the dFe-binding ligand pool in San Francisco Bay, with concentrations ranging from 559.5 mu g L-1 to 67.5 mu g L-1 in the lowest and highest salinity samples, respectively. DFe-binding ligands and humic-like substances were also found in benthic boundary layer samples taken from the shelf near the mouths of San Francisco Bay and Eel River, suggesting estuaries are an important source of dFe-binding ligands to California coastal shelf waters. (C) 2014 Elsevier B.V. All rights reserved.

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Hopkinson, BM, Mitchell G, Reynolds RA, Wang H, Selph KE, Measures CI, Hewes CD, Holm-Hansen O, Barbeau KA.  2007.  Iron limitation across chlorophyll gradients in the southern Drake Passage: Phytoplankton responses to iron addition and photosynthetic indicators of iron stress. Limnology and Oceanography. 52:2540-2554.   10.4319/lo.2007.52.6.2540   AbstractWebsite

Processes influencing phytoplankton bloom development in the southern Drake Passage were studied using shipboard iron-enrichment incubations conducted across a surface chlorophyll gradient near the Antarctic Peninsula, in a region of water mass mixing. Iron incubation assays showed that Antarctic Circumpolar Current (ACC) waters were severely iron limited, while shelf waters with high ambient iron concentrations (1-2 nmol L-1) were iron replete, demonstrating that mixing of the two water masses is a plausible mechanism for generation of the high phytoplankton biomass observed downstream of the Antarctic Peninsula. In downstream high-chlorophyll mixed waters, phytoplankton growth rates were also iron limited, although responses to iron addition were generally more moderate as compared to ACC waters. Synthesizing results from all experiments, significant correlations were found between the initial measurements of Photosystem II (PSII) parameters (F-v: F-m, sigma(PSII), and p) and the subsequent responses of these waters to iron addition. These correlations indicate that PSII parameters can be used to assess the degree of iron stress experienced in these waters and likely in other regions where photoinhibition and nitrogen stress are not confounding factors.

Hopkinson, BM, Barbeau KA.  2008.  Interactive influences of iron and light limitation on phytoplankton at subsurface chlorophyll maxima in the eastern North Pacific. Limnology and Oceanography. 53:1303-1318.   10.4319/lo.2008.53.4.1303   AbstractWebsite

The roles of iron and light as limiting and colimiting factors for phytoplankton growth in subsurface chlorophyll maxima (SCMs) were investigated in mesotrophic to oligotrophic waters of the Southern California Bight and the eastern tropical North Pacific using microcosm manipulation experiments. Phytoplankton responses indicative of iron-light colimitation were found at several SCMs underlying macronutrient-limited surface waters in the eastern Pacific. Iron additions led to a shift in the size and taxonomic structure of the phytoplankton community, where large diatoms dominated what was formerly a diverse community of relatively small phytoplankton. The strongest and most ubiquitous responses of diatoms to iron addition were found under elevated light conditions, indicating that iron availability may have the greatest potential to affect SCM phytoplankton communities when light levels increase rapidly, such as during eddy events or with strong internal waves. The results show that iron influences phytoplankton community structure at SCMs, which would have consequences for nutrient cycling and carbon export within the lower euphotic zone.

Hopkinson, BM, Barbeau KA.  2012.  Iron transporters in marine prokaryotic genomes and metagenomes. Environmental Microbiology. 14:114-128.   10.1111/j.1462-2920.2011.02539.x   AbstractWebsite

In the pelagic environment, iron is a scarce but essential micronutrient. The iron acquisition capabilities of selected marine bacteria have been investigated, but the recent proliferation of marine prokaryotic genomes and metagenomes offers a more comprehensive picture of microbial iron uptake pathways in the ocean. Searching these data sets, we were able to identify uptake mechanisms for Fe3+, Fe2+ and iron chelates (e.g. siderophore and haem iron complexes). Transport of iron chelates is accomplished by TonB-dependent transporters (TBDTs). After clustering the TBDTs from marine prokaryotic genomes, we identified TBDT clusters for the transport of hydroxamate and catecholate siderophore iron complexes and haem using gene neighbourhood analysis and co-clustering of TBDTs of known function. The genomes also contained two classes of siderophore biosynthesis genes: NRPS (non-ribosomal peptide synthase) genes and NIS (NRPS Independent Siderophore) genes. The most common iron transporters, in both the genomes and metagenomes, were Fe3+ ABC transporters. Iron uptake-related TBDTs and siderophore biosynthesis genes were less common in pelagic marine metagenomes relative to the genomic data set, in part because Pelagibacter ubique and Prochlorococcus species, which almost entirely lacked these Fe uptake systems, dominate the metagenomes. Our results are largely consistent with current knowledge of iron speciation in the ocean, but suggest that in certain niches the ability to acquire siderophores and/or haem iron chelates is beneficial.

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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.

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Semeniuk, DM, Taylor RL, Bundy RM, Johnson WK, Cullen JT, Robert M, Barbeau KA, Maldonado MT.  2016.  Iron-copper interactions in iron-limited phytoplankton in the northeast subarctic Pacific Ocean. Limnology and Oceanography. 61:279-297.   10.1002/lno.10210   AbstractWebsite

In August 2010, iron (Fe) and Fe and copper (Cu) addition incubation experiments were conducted at two low Fe stations (P20 and P26) along Line P, off the western coast of British Columbia, to investigate Cu physiology in Fe- and Fe-light co-limited phytoplankton. Chlorophyll a concentrations ([Chl a]), maximum variable fluorescence yield (F-v/F-m), and Fe uptake rates by the Cu-dependent high-affinity Fe transport system (HAFeTS) were measured. Additions of Fe resulted in an increase in [Chl a] and F-v/F-m at both stations compared with the controls, regardless of light availability, and confirmed that the phytoplankton communities were Fe-limited. Uptake of Fe by the HAFeTS in both incubations increased with the addition of Fe, and likely reflects luxury Fe uptake and storage. While the in situ inorganic Cu concentrations were similar to those that can induce Cu-limitation in laboratory cultures, increasing Cu availability had no effect on biomass accumulation during both incubations, regardless of Fe availability or light regime. At P26, additions of 1 nmol L-1 CuSO4 resulted in a short-term increase in F-v/F-m of the phytoplankton community, and an increase in Fe uptake rates by large phytoplankton (>5 mu m), but only when light was not limiting. These data confirm a complex interaction between light, Fe and Cu physiology in indigenous phytoplankton communities, and suggest that these interactions may be both spatially heterogeneous and different for different phytoplankton size classes.