This paper describes an estimation of endmember compositions followed by the assessment of those results by log-ratio variance analysis. As an appraisal, it deals only with the first objective of an endmember analysis namely, to identify endmembers if they exist by estimating their compositions. Following the creation of the endmember estimates, the computation of an array of log-ratio variances was a key innovation in this type of study. Log-ratio variances revealed intrinsic linear associations between the dominant elements on each of the estimated endmember compositions, largely confirming the endmember analysis. The dataset under study contained the concentrations of 16 elements in 93 samples of deep-sea manganese nodules from the Central Indian Ocean Basin. Many previous analyses of these nodules were undertaken to assess the economic potential of the deposits. This study by contrast, quantified the interelement associations that account for the nodule compositions. Four endmembers were identified. The elements loaded on each were: (1) Mn, Zn, Ni, Cu, Mn-rich, (2) Fe, Ti, P, Co, Fe-rich, (3) Si, Al, Na, K, clay minerals, (3) Mg, ultramafic material, possibly including Mn, Cr, V, Ca, Na. These latter elements were also detected by their log-ratio variances to be associated with Mg on the 4th endmember.
Volume 131, 2022
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