Authors: MARÍA ABDELALY RIVERA-GÓMEZ, JOHN SELVAMONY ARMSTRONG-ALTRIN, SURENDRA P. VERMA, LORENA DÍAZ-GONZÁLEZ
Abstract: An online computer program called APMdisc (Active and Passive Margin discrimination) for the discrimination of siliciclastic sediments from active and passive margin settings was written in Java along with the ZK framework. APMdisc calculates four complex discriminant functions (DFilr(A-P)M and DFmlr(A-P)M; DFilr(A-P)MT and DFmlr(A-P)MT), which represent linear combinations of log-ratios of all ten major elements (M) and ten major and six trace elements (MT), respectively. In these equations, ilr and mlr stand for isometric log-ratio and modified log-ratio transformations of the chemical composition of active and passive margin sediments, respectively. The ilr transformation provided the same results as the mlr as documented for five case studies of Quaternary sediments from California, Antarctica, Nigeria, India, and Japan. We also present 9 other case studies (for Neogene to Quaternary sediments from known tectonic settings) and 11 application studies (Tertiary to Neoproterozoic sediments and sedimentary rocks) to show the functioning of the multidimensional discrimination proposed in this paper. In most cases, the results from the APMdisc were consistent with the literature conclusions inferred from different geological and geochemical techniques. Nevertheless, APMdisc provides probability estimates for both tectonic settings, which allows the decision to be made based on the probability concept. We also added a new Robustness module to APMdisc, which allows the user to test the robustness of a sample against field changes, such as weathering and diagenesis, and laboratory analytical errors or uncertainties. This program can therefore be recommended for deciphering the margin type of older terrains. The APMdisc program can be used online by researchers for tectonic discrimination based on sediment composition. The users can process the data file at our web portal http://tlaloc.ier.unam.mx.
Keywords: Data processing, sedimentology, geostatistics, tectonic discrimination, multidimensional techniques
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