ABSTRACT: A method for detecting glacial dispersal trains in regional till geochemical data.

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Abstract

A new algorithm for identifying potential glacial dispersal trains in till geochemical data is introduced. The algorithm, referred to as the dispersal train identification algorithm (DTIA), requires a set of user input parameters used for simulating dispersal train characteristics. The algorithm employs a succession of wedge-shaped search regions (each one shaped like an isosceles triangle with the search point at the principal vertex) to ‘look’ in user-specified directions from a set of search points that may be mineral prospects, geochemical anomalies in rock or a homogeneous grid of points. The values of the till sample points occurring within the wedge are analysed as candidates for a dispersal train using a set of criteria. The geologist specifies the length and angle of the wedge, where the length reflects the distance of down-ice dispersal and the angle is used to model a ribbon or fan-shaped dispersal train. For each search position, DTIA calculates the average of the values within the wedge (pmed), the difference between wedge average and the local average (diff), and fits an exponential model to the within-wedge points (geochemical value as a function of distance from the search point). Candidate search points for the heads of dispersal trains are selected based on high values of pmed and diff, as well as best fit lines that show high negative slopes (b), significant values of a test statistic for the slope magnitude (ts), and large negative correlation coefficients (R). DTIA was tested on two datasets: a dataset in Cape Breton where documented till dispersal trains exist and in the Swayze greenstone belt where no documented trains are known. The effects of varying the input parameters were studied as well as different search strategies with the objective of identifying the most appropriate parameters for successfully identifying points that represent the heads (or source zones) of potential till dispersal trains. The algorithm performed well with the Cape Breton data. The results are particularly sensitive to both direction of search and the wedge angle. Application to the Swayze data revealed candidate trains whose directions are consistent with glacial transport directions known from data on glacial striations. Although this method shows promise as a data exploration tool, more work is needed to improve the algorithm and to test it under a greater range of conditions.

Bibliography of Canadian Geomorphology