The fate and behavior of metals in the soil environment is innately coupled with the process of aqueous complexation. This fact is particularly true in the rhizosphere; the volume of soil that is directly impacted by plant roots and the myriad of microorganisms that therein reside. Plant roots and microbes are known to exude a variety of organic compounds, most commonly the low-molecular-mass organic acid anions. Many of these substances display a capacity to complex, and in some cases chelate metal cations. It has been established that nutrient deficiencies, such as for P and Fe, and elevated soil phytotoxin concentrations, such as for Al, can stimulate the root and microbial production of a select group of organic acid anions. Presumably, the deficiency or toxicity effect triggers a biochemical response within the organism which results in increased exudation. In turn, the cocktail of organic acid anions in the rhizosphere solution facilitates the dissolution and enhanced solubility of both metals and ligands. In the case of Fe, the direct chelation of Fe(III), and solubilization of sparingly soluble Fe(III) precipitates, results in the mobilization of Fe(III) to the root surface, where it is reduced to Fe(II) by ferric reductase, released from the chelate, and absorbed. Similarly, the chelation of Al monomers by root exudates generates soluble Al-organic complexes; however, these complexes are not absorbed, mitigating the phytotoxic effects of Al. The organic anion-enhanced bioavailability of P is realized via a less direct mechanism. Phosphorus, which in its bioavailable form occurs as the orthophosphate oxyanion, commonly exists in soils in metal (e.g., Al, Fe(III), and Ca) phosphates and in the chemisorbed phase on metal (e.g., Al and Fe(III)) oxyhydroxides. Orthophosphate is released to the soil solution by the organic ligand-enhanced dissolution of metal phosphates (chelation effect), or by displacement from surface functional groups (ligand exchange with organic anions). The description and prediction of the various organic ligand-affected processes in the soil environment is facilitated by employing any one of several computer codes that perform ion association model computations (geochemical models). Implicit to the model predictions are the robustness and accuracy of the accompanying thermodynamic database. Unfortunately, many of the more popular geochemical models are deficient relative to database robustness, particularly in their consideration of metal-organic ligand interactions. However, this need not be the case, as metal-organic ligand complexation chemistry is general well-described. More problematic, however, are the metal-organic ligand species and their associated formation constants that may be selected for incorporation into data files and compilations. The normal mechanism for quantifying the aqueous speciation of metal-organic ligand systems (e.g., potentiometric titrations) does not provide a mechanistic characterization of species formation. Instead, these data are employed to establish a chemical model: a series of chemical reactions and associated formation constants. For example, the reported chemical models for Al-citrate and Fe(III)-citrate speciation range in complexity from those consisting of a small number of monomeric species, to elaborate models containing combinations of mono- and polymeric species. The fact that titration data interpretations and the developed chemical models differ is not in itself problematic. While mechanistically the predicted effect of an organic ligand on metal speciation will be model-specific, the net effect (the mass distribution of a metal between free and complexed forms) may be accurate, irrespective of the chemical model employed. However, compilers of geochemical model databases and reference literature do not always recognize the uniqueness of a particular chemical model, opting instead to select species from several chemical models for inclusion into a single database. Such a practice results in thermodynamic compilations that, when used, are incapable of effecting an accurate prediction of metal complexation chemistry. To guard against such erroneous predictions, thermodynamic compilations must be critically evaluated; a process that must also involve the examination of the original data source.