Compositional variations of ignimbrite magmas in the Central Andes over the past 26 Ma - A multivariate statistical perspective

被引:39
作者
Brandmeier, M. [1 ]
Woerner, G. [1 ]
机构
[1] Univ Gottingen, Inst Geochem, GZG, Goldschmidtstr 1, D-37077 Gottingen, Germany
关键词
Andes; Ignimbrite flare-ups; Log-ratios; Multivariate statistics; Discriminant analysis; Cluster analysis; SOUTHERN CENTRAL ANDES; PUNA VOLCANIC COMPLEX; LA-PACANA CALDERA; NORTHERN CHILE; COLLAPSE CALDERA; LATE MIOCENE; TECTONIC EVOLUTION; CANYON INCISION; CERRO PANIZOS; IGNEOUS ROCKS;
D O I
10.1016/j.lithos.2016.07.011
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Multivariate statistical and geospatial analyses based on a compilation of 890 geochemical and similar to 1200 geochronological data for 194 mapped ignimbrites from the Central Andes document the compositional and temporal patterns of large-volume ignimbrites (so-called "ignimbrite flare-ups") during Neogene times. Rapid advances in computational science during the past decade led to a growing pool of algorithms for multivariate statistics for large datasets with many predictor variables. This study applies cluster analysis (CA) and linear discriminant analysis (LDA) on log-ratio transformed data with the aim of (1) testing a tool for ignimbrite correlation and (2) distinguishing compositional groups that reflect different processes and sources of ignimbrite magmatism during the geodynamic evolution of the Central Andes. CA on major and trace elements allows grouping of ignimbrites according to their geochemical characteristics into rhyolitic and dacitic "end-members" and to differentiate characteristic trace element signatures with respect to Eu anomaly, depletions in middle and heavy rare earth elements (REE) and variable enrichments in light REE. To highlight these distinct compositional signatures, we applied LDA to selected ignimbrites for which comprehensive datasets were available. In comparison to traditional geochemical parameters we found that the advantage of multivariate statistics is their capability of dealing with large datasets and many variables (elements) and to take advantage of this n-dimensional space to detect subtle compositional differences contained in the data. The most important predictors for discriminating ignimbrites are La, Yb, Eu, Al2O3, K2O, P2O5, MgO, FeOt, and TiO2. However, other REE such as Gd, Pr, Tm, Sm, Dy and Er also contribute to the discrimination functions. Significant compositional differences were found between (1) the older (>13 Ma) large-volume plateau-forming ignimbrites in northernmost Chile and southern Peru and (2) the younger (<10 Ma) Altiplano-Puna-Volcanic Complex (APVC) ignimbrites that are of similar volumes. Older ignimbrites are less depleted in HREE and less radiogenic in Sr isotopes, indicating smaller crustal contributions during evolution in a thinner and thermally less evolved crust. These compositional variations indicate a relation to crustal thickening with a "transition" from plagioclase to amphibole and garnet residual mineralogy between 13 and 9 Ma. Compositional and volumetric variations correlate to the N-S passage of the Juan-Fernandez-Ridge, crustal shortening and thickening, and increased average crustal temperatures during the past 26 Ma. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:713 / 728
页数:16
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