Alteration Geochemistry: Methods and Results

Assessing the Parentage of Altered Rocks

Aphyric and sparsely porphyritic glassy lavas from Pual Ridge ranging from basaltic andesite to rhyodacite display highly constrained geochemical fractionation trends for most major and trace elements (Binns et al., 2002b). Systematic increase in Zr content and decrease of TiO2 content plotted, for example, against SiO2 in Harker-type diagrams make the Zr/TiO2 ratio a sensitive measure of fractionation status. These elements are widely considered immobile during hydrothermal alteration. In Leg 193 altered cores the concept of Ti and Zr immobility is supported by their presence in resistate minerals rutile and zircon, respectively, and by consistency in Zr/TiO2 ratios across zoned samples with varying alteration assemblages (see Table T2).

Algorithms for calculating precursor compositions, assuming consanguinity of seabed and subseafloor lavas at Pual Ridge, are listed in Table AT1. These have been derived from the glassy lava database (~70 samples, recalculated to 100% anhydrous totals) by plotting each element against Zr/TiO2 and selecting the better of logarithmic or exponential functions calculated to illustrate the trend. Zirconium is expressed in parts per million and TiO2 in weight percent. Resultant precursor compositions are also in 100% anhydrous format.

Relative precision of the algorithms for different elements is indicated by cited variances in the ratio of calculated to actual element abundances obtained by reapplying the algorithms to the fresh lava database itself. Algorithms for Cr, Ni, S, and certain other low-abundance elements (e.g., Te) that display scatter in fresh lavas are useful only to assess gross changes in composition and should be applied with due consideration of potential errors. For Cu, the algorithm is derived using only fresh lavas with >60 wt% SiO2 to avoid the abrupt change in fractionation behavior displayed by this element in more mafic rocks (Sun et al., 2004), but even so scatter remains in Cu contents, leading to an elevated variance. Of the major elements, only Mg shows significant variance, but this is caused by a small number of anomalous samples in the fresh lava database and the algorithm is considered valid overall.

In comparing altered rock compositions with their (anhydrous) precursors it is necessary to take account of water contents of the (clay dominated) former. Structurally combined water has not been separately analyzed for CSIRO samples from Leg 193, and "loss on ignition" determinations for sulfide-bearing samples are an unreliable measure of water. To remove the effects of hydration in comparative plots (e.g., Figure AF1) a factor, calculated from the average for Zr and TiO2, respectively, of the ratios between actual and algorithm-derived precursor contents of these two constituents, must be applied. Thereby we are comparing a fixed weight of precursor rock with whatever its weight has become after alteration. On diagrams like Figure AF1, Ti and Zr will plot exactly at the unity ratio as required by the immobility concept, except for any minor analytical errors in either element. By restricting the study of alteration geochemistry to CSIRO samples analyzed by the same methods as used for glassy lavas, we avoid interlaboratory variability.

To assess mass changes on a volume basis, it is necessary to use measured or estimated SGs of altered rocks, and precursor SGs (at calculated precursor compositions) derived from measurements on Pual Ridge glasses. This was necessary, for example, in assessing volume changes during alteration (see Fig. F10).

Summary of Results

Abbreviations used below for alteration categories are set out in Table T1 of the main chapter.

Lithophile Elements
Chalcophile Elements