Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach

Abstract

Many plagioclase phenocrysts from volcanic and plutonic rocks display quite complex chemical and textural zoning patterns. Understanding the zoning patterns and variety of crystal populations holds clues to the processes and timescales that lead to the formation of the igneous rocks. However, in addition to a "true" natural complexity of the crystal population, the large variety of plagioclase types can be partly artifacts of the use of two-dimensional (2D) petrographic thin sections and random cuts of three-dimensional (3D) plagioclase crystals. Thus, the identification of the true number of plagioclase populations, and the decision of which are "representative" crystal sections to be used for detailed trace element and isotope analysis is not obvious and tends to be subjective.Here we approach this problem with a series of numerical simulations and statistical analyses of a variety of plagioclase crystals zoned in 3D. We analyze the effect of increasing complexity of zoning based on 2D chemical maps (e.g., backscattered electron images, BSE). We first analyze the random sections of single crystals, and then study the effect of mixing of different crystal populations in the samples. By quantifying the similarity of the compositional histogram of about a hundred 2D plagioclase sections it is possible to identify the so-called reference and ideal sections that are representative of the real 3D crystal populations. These section types allow filtering out the random-cut effects and explain more than 90% of the plagioclase compositional data of a given sample. Our method allows the identification of the main crystal populations and representative crystals that can then be used for a more robust interpretation of magmatic processes and timescales.

A Data Driven Approach to Investigate the Chemical Variability of Clinopyroxenes From the 2014–2015 Holuhraun–Bárdarbunga Eruption (Iceland)

“…The Holuhraun-Bárdarbunga eruption lasted for approximately 6 months during which the bulk magma chemistry remained substantially the same (Halldórsson et al, 2018). However, mineral chemistry can gives more resolution on the chemical processes occurring within magmatic systems (Wallace and Bergantz, 2002;Perugini et al, 2005;Kahl et al, 2011;Cheng et al, 2017;Forni et al, 2018;Probst et al, 2018). Using HC we have identified five groups of cpx compositions in major and trace element space that constitute different zones of the crystals.…”

Statistical analysis of crystal populations and links to volcano deformation for more robust estimates of magma replenishment volumes

“…In total, we obtained 243 and 236 plagioclase phenocryst compositional data for each sample of the 2006 eruption respectively, and 273 and 283 phenocrysts for each sample of the 2010 eruption. These numbers are high enough to obtain representative sampling of the crystal populations (Cheng et al, 2017).…”

“…To identify the various plagioclase populations, we used a recently developed approach by Cheng et al (2017). The most complex part of this approach is to filter out the effect of random cuts of three-dimensional (3-D) plagioclase crystals into two-dimensional (2-D) sections from the real variety caused by the presence of multiple populations.…”

CEmin: A MATLAB‐Based Software for Computational Phenocryst Extraction and Statistical Petrology

“…For example, to distinguish different eruptive units or sequences in chronostratigraphic context, or comparing eruptive events of different magnitude or character at an active volcanic system. The overall shape and breath of plagioclase An distribution provides the most reliable information to evaluate crystallization processes and magma evolution. Deconvolution routines might identify subpopulations within a plagioclase distribution indicative of episodic crystallization or magma mixing (e.g., Cheng et al, ). Full range of compositional histogram distributions of An can be compared with the distributions obtained from exploring a range of parameter values in thermodynamic models (e.g., MELTS; Ghiorso & Sack, ) for constraining conditions of crystallization (Kahl et al, ). The output of CEmin might also be used in combination with other statistical approaches, such as CSD's, to provide additional perspective on the relationship between crystal size and composition (Kent et al, ).…”

“…The overall shape and breath of plagioclase An distribution provides the most reliable information to evaluate crystallization processes and magma evolution. Deconvolution routines might identify subpopulations within a plagioclase distribution indicative of episodic crystallization or magma mixing (e.g., Cheng et al, 2017). 3.…”