Matches in SemOpenAlex for { <https://semopenalex.org/work/W2755582632> ?p ?o ?g. }
- W2755582632 endingPage "44" @default.
- W2755582632 startingPage "1" @default.
- W2755582632 abstract "We define tephras and cryptotephras and their components (mainly ash-sized particles of glass ± crystals in distal deposits) and summarize the basis of tephrochronology as a chronostratigraphic correlational and dating tool for palaeoenvironmental, geological, and archaeological research. We then document and appraise recent advances in analytical methods used to determine the major, minor, and trace elements of individual glass shards from tephra or cryptotephra deposits to aid their correlation and application. Protocols developed recently for the electron probe microanalysis of major elements in individual glass shards help to improve data quality and standardize reporting procedures. A narrow electron beam (diameter ∼3–5 μm) can now be used to analyze smaller glass shards than previously attainable. Reliable analyses of ‘microshards’ (defined here as glass shards <32 μm in diameter) using narrow beams are useful for fine-grained samples from distal or ultra-distal geographic locations, and for vesicular or microlite-rich glass shards or small melt inclusions. Caveats apply, however, in the microprobe analysis of very small microshards (≤∼5 μm in diameter), where particle geometry becomes important, and of microlite-rich glass shards where the potential problem of secondary fluorescence across phase boundaries needs to be recognised. Trace element analyses of individual glass shards using laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS), with crater diameters of 20 μm and 10 μm, are now effectively routine, giving detection limits well below 1 ppm. Smaller ablation craters (<10 μm) can be subject to significant element fractionation during analysis, but the systematic relationship of such fractionation with glass composition suggests that analyses for some elements at these resolutions may be quantifiable. In undertaking analyses, either by microprobe or LA-ICP-MS, reference material data acquired using the same procedure, and preferably from the same analytical session, should be presented alongside new analytical data. In part 2 of the review, we describe, critically assess, and recommend ways in which tephras or cryptotephras can be correlated (in conjunction with other information) using numerical or statistical analyses of compositional data. Statistical methods provide a less subjective means of dealing with analytical data pertaining to tephra components (usually glass or crystals/phenocrysts) than heuristic alternatives. They enable a better understanding of relationships among the data from multiple viewpoints to be developed and help quantify the degree of uncertainty in establishing correlations. In common with other scientific hypothesis testing, it is easier to infer using such analysis that two or more tephras are different rather than the same. Adding stratigraphic, chronological, spatial, or palaeoenvironmental data (i.e. multiple criteria) is usually necessary and allows for more robust correlations to be made. A two-stage approach is useful, the first focussed on differences in the mean composition of samples, or their range, which can be visualised graphically via scatterplot matrices or bivariate plots coupled with the use of statistical tools such as distance measures, similarity coefficients, hierarchical cluster analysis (informed by distance measures or similarity or cophenetic coefficients), and principal components analysis (PCA). Some statistical methods (cluster analysis, discriminant analysis) are referred to as ‘machine learning’ in the computing literature. The second stage examines sample variance and the degree of compositional similarity so that sample equivalence or otherwise can be established on a statistical basis. This stage may involve discriminant function analysis (DFA), support vector machines (SVMs), canonical variates analysis (CVA), and ANOVA or MANOVA (or its two-sample special case, the Hotelling two-sample T2 test). Randomization tests can be used where distributional assumptions such as multivariate normality underlying parametric tests are doubtful. Compositional data may be transformed and scaled before being subjected to multivariate statistical procedures including calculation of distance matrices, hierarchical cluster analysis, and PCA. Such transformations may make the assumption of multivariate normality more appropriate. A sequential procedure using Mahalanobis distance and the Hotelling two-sample T2 test is illustrated using glass major element data from trachytic to phonolitic Kenyan tephras. All these methods require a broad range of high-quality compositional data which can be used to compare ‘unknowns’ with reference (training) sets that are sufficiently complete to account for all possible correlatives, including tephras with heterogeneous glasses that contain multiple compositional groups. Currently, incomplete databases are tending to limit correlation efficacy. The development of an open, online global database to facilitate progress towards integrated, high-quality tephrostratigraphic frameworks for different regions is encouraged." @default.
- W2755582632 created "2017-09-25" @default.
- W2755582632 creator A5040018271 @default.
- W2755582632 creator A5048072709 @default.
- W2755582632 creator A5055141360 @default.
- W2755582632 creator A5055238451 @default.
- W2755582632 creator A5057260929 @default.
- W2755582632 creator A5077882918 @default.
- W2755582632 date "2017-11-01" @default.
- W2755582632 modified "2023-10-17" @default.
- W2755582632 title "Correlating tephras and cryptotephras using glass compositional analyses and numerical and statistical methods: Review and evaluation" @default.
- W2755582632 cites W1126797883 @default.
- W2755582632 cites W1164012781 @default.
- W2755582632 cites W1496595574 @default.
- W2755582632 cites W1499416433 @default.
- W2755582632 cites W1514402410 @default.
- W2755582632 cites W1525516619 @default.
- W2755582632 cites W1527567466 @default.
- W2755582632 cites W1536427886 @default.
- W2755582632 cites W1557583296 @default.
- W2755582632 cites W1559314423 @default.
- W2755582632 cites W1583922376 @default.
- W2755582632 cites W1585966230 @default.
- W2755582632 cites W1623582059 @default.
- W2755582632 cites W1632626761 @default.
- W2755582632 cites W1647116289 @default.
- W2755582632 cites W1658808526 @default.
- W2755582632 cites W1794463924 @default.
- W2755582632 cites W1862189943 @default.
- W2755582632 cites W1877770312 @default.
- W2755582632 cites W1895344422 @default.
- W2755582632 cites W1902887711 @default.
- W2755582632 cites W1934739210 @default.
- W2755582632 cites W1964294434 @default.
- W2755582632 cites W1964905613 @default.
- W2755582632 cites W1965071119 @default.
- W2755582632 cites W1965342462 @default.
- W2755582632 cites W1965640968 @default.
- W2755582632 cites W1969182989 @default.
- W2755582632 cites W1971847097 @default.
- W2755582632 cites W1972566019 @default.
- W2755582632 cites W1972862806 @default.
- W2755582632 cites W1973828225 @default.
- W2755582632 cites W1973937208 @default.
- W2755582632 cites W1974766431 @default.
- W2755582632 cites W1975316228 @default.
- W2755582632 cites W1976957354 @default.
- W2755582632 cites W1977755276 @default.
- W2755582632 cites W1978169959 @default.
- W2755582632 cites W1978853469 @default.
- W2755582632 cites W1978857480 @default.
- W2755582632 cites W1979527597 @default.
- W2755582632 cites W1979547821 @default.
- W2755582632 cites W1980050100 @default.
- W2755582632 cites W1981188514 @default.
- W2755582632 cites W1981577625 @default.
- W2755582632 cites W1981712640 @default.
- W2755582632 cites W1982722253 @default.
- W2755582632 cites W1982923197 @default.
- W2755582632 cites W1984437881 @default.
- W2755582632 cites W1985012794 @default.
- W2755582632 cites W1987387818 @default.
- W2755582632 cites W1988501076 @default.
- W2755582632 cites W1989036348 @default.
- W2755582632 cites W1989397170 @default.
- W2755582632 cites W1989898362 @default.
- W2755582632 cites W1989935075 @default.
- W2755582632 cites W1991055106 @default.
- W2755582632 cites W1991588287 @default.
- W2755582632 cites W1991814985 @default.
- W2755582632 cites W1992002291 @default.
- W2755582632 cites W1993290622 @default.
- W2755582632 cites W1993868180 @default.
- W2755582632 cites W1994019761 @default.
- W2755582632 cites W1994048768 @default.
- W2755582632 cites W1995004931 @default.
- W2755582632 cites W1995450389 @default.
- W2755582632 cites W1997371892 @default.
- W2755582632 cites W1997393365 @default.
- W2755582632 cites W1997661280 @default.
- W2755582632 cites W1998434106 @default.
- W2755582632 cites W1998461086 @default.
- W2755582632 cites W1998837704 @default.
- W2755582632 cites W1999207748 @default.
- W2755582632 cites W1999597013 @default.
- W2755582632 cites W1999742774 @default.
- W2755582632 cites W1999926660 @default.
- W2755582632 cites W2000023571 @default.
- W2755582632 cites W2000661853 @default.
- W2755582632 cites W2002635299 @default.
- W2755582632 cites W2002972888 @default.
- W2755582632 cites W2003201377 @default.
- W2755582632 cites W2004561988 @default.
- W2755582632 cites W2004828174 @default.
- W2755582632 cites W2005939667 @default.
- W2755582632 cites W2006096439 @default.
- W2755582632 cites W2006498769 @default.
- W2755582632 cites W2007133633 @default.