A critical look at the calculation of the binding characteristics and concentration of iron complexing ligands in seawater with suggested improvements

Abstract

Environmental context. The low concentration of iron in the oceans limits growth of phytoplankton. Dissolved organic molecules, called ligands, naturally present in seawater, bind iron thereby increasing its solubility and, consequently, its availability for biological uptake by phytoplankton. The characteristics of these ligands are determined indirectly with various mathematical solutions; we critically evaluate the underlying method and calculations used in these determinations.Abstract. The determination of the thermodynamic characteristics of organic Fe binding ligands, total ligand concentration ([L t ]) and conditional binding constant (K 0 ), by means of titration of natural ligands with Fe in the presence of an added known competing ligand, is an indirect method. The analysis of the titration data including the determination of the sensitivity (S) and underlying model of ligand exchange is discussed and subjected to a critical evaluation of its underlying assumptions. Large datasets collected during the International Polar Year, were used to quantify the error propagation along the determination procedure. A new and easy to handle non-linear model written in R to calculate the ligand characteristics is used. The quality of the results strongly depends on the amount of titration points or Fe additions in a titration. At least four titration points per distinguished ligand group, together with a minimum of four titration points where the ligands are saturated, are necessary to obtain statistically reliable estimates of S, K 0 and [L t ]. As a result estimating the individual concentration of two ligands, although perhaps present, might not always be justified.

An Intercomparison of Dissolved Iron Speciation at the Bermuda Atlantic Time-series Study (BATS) Site: Results from GEOTRACES Crossover Station A

“…In the November 2011 titration data, curvature evident in the Scatchard plots was consistent with the presence of more than one ligand class (Rue and Bruland, 1995;Buck et al, 2012). The difficulty in quantifying a second ligand class in the Gerringa et al (2014) non-linear interpretation of the 2011 data may in part reflect insufficient titration points in the interpretation limiting the degrees of freedom available to calculate the additional parameters required of two ligand classes with statistical certainty, regardless of whether the additional ligand class is present (Hudson et al, 2003;Wu and Jin, 2009;Gerringa et al, 2014).…”

“…Determining two ligand classes, as seen in the November 2011 titration dataset, was more challenging and resulted in poorer agreement between the interpretation approaches, especially for the second (weaker) ligand class (Figure 5). In particular, while the average ligand concentrations and conditional stability constants resulting from the two interpretation techniques approached each other, the The Gerringa et al (2014) approach is mathematically robust, requiring at least twelve titration points to determine two ligand classes with confidence-four for each ligand class and four for the linear section of the titration curve to determine sensitivity . The combined linearization approach applied to the November 2011 dataset was not limited by this data structure, as this more traditional technique does not incorporate error calculations in the determination of speciation parameters.…”

“…In the Gerringa et al (2014) paper, the authors evaluated the influence of numbers of titration points on derived standard deviations for the speciation parameters (see Figure 5 in Gerringa et al, 2014). In that case, the focus was on determining a single ligand class.…”

“…The Gerringa et al (2014) non-linear interpretation approach reported predominantly a single ligand class as the best fit to the November 2011 titration data (data not shown). Allowing the determination of two ligand classes from these titration data using this approach resulted in large standard deviations for the results (Figures 4A,B).…”

“…The interpretation techniques used to obtain ligand concentrations and conditional stability constants from the titration data generated by CLEAdCSV are diverse as well, and several new techniques have emerged recently (Sander et al, 2011;Laglera et al, 2013;Gerringa et al, 2014;Omanović et al, 2015). At this time, there are no established reference samples for DFe speciation, and intercomparison activities are a useful alternative for assessing how these different CLE-AdCSV approaches compare.…”