Abstract
Samples of humus and B-and C-horizon till collected from the north and east margins of the Sudbury Basin were analyzed for about 30 trace elements. The data consist of two sets of analyses, one being a conventional “near total” analysis following an aqua regia digestion, the other being a “partia” analysis from a selective leach designed to extract the metals bound to the soluble organic fraction of humus and to the amorphous Fe and Mn oxides of B- and C-horizon till. Statistical processing, using both standard approaches and some newly developed methods of spatial analysis, were applied to evaluate spatial geochemical patterns and their relationship to geological factors such as proximity to known mineral occurrences. In particular, the information content of the partial analyses was evaluated to determine whether the partial analyses reveal interpretable patterns not detected in the “near total” analyses. From a visual appraisal of dotplots of Ni and Cu in till, it is difficult to determine whether the partial data add anything not already seen in the “total” data. However, when residuals obtained by removing that part of the partial variation explained by the “total” variation are mapped, distinctive patterns are produced. These patterns are enhanced by applying an adaptive filtering technique using a spatial U-statistic. Multielement groups (“total” data, 30 elements in till) determined by principal components analysis show that the first two components are due to Ni-Co-Cr-Cu-Zn and Pd-Au-Pt-Sb associations. A multifractal area-concentration model fitted to component scores allows multielement anomalies to be mapped. The first component is shown to be spatially associated with Ni-Cu deposits, the second with Au and Ni-Cu-Au deposits. Analysis of variance, with “total”, partial and residual data taken in turn as the dependent (“response”) variable, shows that both Ni and Cu in till are significantly “explained” by geological factors (underlying rock type, proximity to contacts and to mineralization). Neither the “total” nor the partial analyses on their own show significant associations with these geological factors for either element in C-horizon till. This demonstrates the value of selective leach analyses, where they are carried out in addition to the “total” analyses, for this dataset. A multivariate analysis of variance shows that if all three surfical media (humus, B- and C-horizon till) are used, the selective extraction data are not so advantageous, although still adding some predictive capability, because additional “explanatory” information comes from multimedia rather than multiphase sources.
Published Version
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