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.

The compositional zoning styles of natural crystals produced during magma intrusion can be used to investigate the structure of magmatic plumbing systems and its relation to expressions of volcanic unrest (seismic, deformation, volatiles). However, magma intrusion is a progressive, dynamic process and yields non-monotonic heterogeneities in physio-chemical variables such as complex spatial variations in temperature and liquid composition with time. Such changes in variables are difficult to incorporate in models of crystal zoning in natural systems. Here we take another approach by integrating the results of a numerical multiphase simulation of melt arrival in an olivine-rich reservoir with models of chemical re-equilibration of olivine. We evaluate the diversity of chemical zoning styles and the inferred time scales using Fe–Mg diffusion in olivine for a limited range of system geometries and time-composition-temperature values. Although our models are still a large simplification of the processes that may occur in natural systems we find several time-dependent and systematic relations between variables that can be used to better interpret natural data. The proportions of zoned and unzoned crystals, the zoning length scales, and the calculated diffusion times from the crystals, vary with time and the initial position of the crystal in the reservoir. These relationships can be used, for example, to better constrain the plumbing structure and dynamics of mafic eruptions from monogenetic volcanoes by detailed studies of changes in the zoning of the crystal cargo with eruptive sequence. Moreover, we also find that the time scales obtained from modeling of crystals at a single temperature and boundary condition tend to be shorter (> about 25%) than the residence time, which could also be tested in natural studies by combining crystal time scale records with monitoring datasets.

It is nowadays common to collect large‐area backscattered electron images and X‐ray maps of entire standard petrographic thin sections. These images can be calibrated for compositions of some minerals (e.g., plagioclase) with a small number of electron microprobe analyses, and thus provide a wealth of quantitative data for hundreds of crystals. However, to effectively make use of the textures and compositions of large numbers of crystals we need to be able to efficiently outline and segregate the crystals of interest from the rest of the sample. Here we present CEmin, a set of MATLAB routines that are user‐friendly and allow users to semiautomatically separate plagioclase crystals in grayscale images of volcanic rocks for further processing. These data can then be used for textural and chemical zoning studies. Efficiently extracting large amounts of crystal data allows for identification of plagioclase populations that are indicative of magmatic processes (e.g., closed versus open system) and statistical comparison to thermodynamic models.