Visualizing the sedimentary response through the orogenic cycle: A multidimensional scaling approach

Abstract

Changing patterns in detrital provenance through time have the ability to resolve salient features of an orogenic cycle. Such changes in the age spectrum of detrital minerals may be attributable to fluctuations in the geodynamic regime (e.g., opening of seaways, initiation of subduction and arc magmatism, and transition from subduction to collisional tectonics with arrival of exotic crustal material). This changing geodynamic regime leads to a variety of sedimentary responses driven by basin formation, transition from rift to drift sedimentation, or inversion and basement unroofing. Detrital zircon grains within sedimentary rocks chart the aforementioned processes by the presence of older detrital zircon populations during basement unroofing events, followed by a successive younging in the detrital zircon age signature either through arrival of young island arc terranes or the progression of subduction magmatism along a continental margin. Hence, the response within the detrital zircon cargo to the geodynamic environment can be visualized in their changing age patterns. However, such patterns are often cryptic and evaluated on the basis of visual comparisons. In an effort to enhance objectivity in the diagnosis of the sedimentary response to the orogenic cycle, we illustrate the utility of a multidimensional scaling approach to detrital zircon age spectra. This statistical tool characterizes the "dissimilarity" of age spectra from various sedimentary successions, but it importantly also charts this measure through time. We present three case studies in which multidimensional scaling reveals additional useful information on the style of basin evolution within the orogenic cycle. The Albany-Fraser orogen in Western Australia and Grenville orogen (sensu stricto) in Laurentia demonstrate clear patterns in which detrital zircon age spectra become more dissimilar with time. In stark contrast, sedimentary successions from the Mesoproterozoic to Neoproterozoic North Atlantic region reveal no consistent pattern. Rather, the North Atlantic region reflects a signature consistent with significant zircon age communication due to a distal position from the orogenic front, oblique translation of terranes, and complexity of the continental margin. This statistical approach provides a mechanism to connect the evolutionary patterns of detrital zircon age spectra to the geodynamics of an orogenic system, which in many cases is a direct function of proximity to the orogenic front.

The source of Dalradian detritus in the Buchan Block, NE Scotland: application of new tools to detrital datasets

“…This is achieved by means of a Kolmogorov-Smirnov (K-S) test, which is widely used to test the null hypothesis that two distributions come from the same population. To further visualize the results of this statistical test we apply multi-dimensional scaling of the D value in the K-S test, as discussed by Vermeesch (2013) and Spencer & Kirkland (2016). This approach creates a 2D map of points that summarizes the differences in the age population structure (Fig.…”

A Late Jurassic to Early Cretaceous record of orogenic wedge evolution in the Western Interior basin, USA and Canada

“…MDS analysis is based on D-values, which are produced as part of the Kolmogorov-Smirnov test and represent "distance" between two samples (Vermeesch, 2013;Spencer and Kirkland, 2015). D-values are arranged in a matrix and plotted on a Euclidian plane while attempting to honor the "distances" in the matrix.…”

“…D-values are arranged in a matrix and plotted on a Euclidian plane while attempting to honor the "distances" in the matrix. Normal-distribution, synthetic age populations were created in Excel and added to the MDS plot to show important age inputs (Spencer and Kirkland, 2015). …”

Pairwise sample comparisons and multidimensional scaling of detrital zircon ages with examples from the North American platform, basin, and passive margin settings

“…Multidimensional scaling (MDS) is a typically iterative ordination technique that graphically represents the relative dissimilarities among samples arrayed in N-dimensional space. It is not new to geologic applications (e.g., Doveton, 1976;Hayward and Smale, 1992;Hounslow and Morton, 2004;Honarkhah and Caers, 2010); however, more widespread application to detrital zircon data sets is relatively recent (e.g., Vermeesch, 2013;Spencer and Kirkland, 2015;Vermeesch and Garzanti, 2015;Arboit et al, 2016;Saylor et al, 2017;Xu et al, 2017). Although a detailed description of the approach is beyond the scope of this paper, we offer a brief overview.…”