Soil pH Effects on the Distribution and Plant Availability of Manganese, Copper, and Zinc

Abstract Crop response to micronutrient fertilization on the poorly buffered coastal plain soils of Delaware has received renewed interest in recent years. Specifically, given the susceptibility of these soils to overliming and the widespread use of manures, questions have been raised concerning the influence of soil pH and micronutrient source on the distribution and plant availability of Mn, Cu, and Zn, Four soils that varied widely in organic matter content (16‐100 g/kg), texture, and cation exchange capacity (CEC) were studied. A fractionation scheme was utilized that partitioned Mn, Cu, and Zn into the exchangeable, organic, Mn‐oxide bound, amorphous Fe‐oxide bound, and crystalline Fe‐oxide bound forms. Micronutrient distribution among these fractions was studied over a pH range of 4.0 to 7.7 in the soils alone, and in the same soils amended with poultry manure (PM) or (MnSO 4 + CuSO 4 + ZnSO 4 ). The various fractions of each element were then correlated with Mn, Cu, and Zn uptake by wheat ( Triticum aestivum L.) in a greenhouse experiment. Soil pH markedly altered the distribution of Mn and Zn but had little effect on Cu. Although soil type did have some influence, exchangeable Mn and Zn were generally the dominant species of the elements below pH 5.2, while at higher pH values organically complexed and Fe‐oxide bound forms were dominant. The majority of soil Cu was in the organic fraction, but considerable percentages were found in the amorphous Fe‐oxide fraction. Significant source by pH interactions were observed only for exchangeable Mn and Zn. Organic ligands in the manure retained more Zn in a nonexchangeable form under acidic conditions, but had only minor effects on exchangeable Mn. Plant uptake of Mn and Zn was primarily related to the exchangeable fractions; however, predictive models were significantly enhanced by the inclusion of soil pH. Inconsistent correlations and low r 2 values for all models involving Cu illustrate the difficulty in predicting crop response to native or added Cu.