Paper No. 1
Presentation Time: 8:05 AM
UTILITY OF STATISTICAL METHODS AND DATA PRESENTATION IN DETRITAL FISSION TRACK THERMOCHRONOLOGY
The use of detrital fission track thermochonology, in particular on apatites (AFT), has proven a valuable tool to interpret the maximum depositional age of sedimentary strata and the thermal history of the sediment sources and basins; however, the interpretation of detrital AFT data contains unique and serious challenges. These challenges include: 1) High error associated with a single grain age renders this individual data inconsequential. To represent a meaningful age requires the combination of multiple grains’ ages which in practical application can be difficult in a detrital sample. 2) Extraction of populations in AFT analysis requires unmixing of data by grouping grain ages with high errors into these meaningfully populated groups. Although multiple statistical methods address this feat, all typically represent the unmixed result as discrete age peaks representative of a broad population. Furthermore, these methods cannot consistently reproduce the expected results from synthetic mixed samples with known single peak ages. 3) The combination of the previous two limitations necessitates accurate and appropriate presentation of results. In detrital AFT, the extraction and presentation of exhumation peaks may be statistically and visually misleading.
The statistical interpretation and visual representation of detrital AFT analyses need to be uniquely suited to the limitations of this data source to ensure the integrity of the data. This study explores the utility of various interpretative methods and proposes appropriate presentation of the data that respects the statistical limitations of this approach. Statistical methods employed in unmixing detrital AFT ages must account for the uniquely large error produced in this process and ensure data presentation accurately preserves the integrity of the data. Although improvement on statistical techniques may be limited by practicality (the number of grains possible to collect and analyze) and ability of statistics to work within these practical constraints, the presentation and resulting interpretation of the data available can be made most useful by conforming to the unique requirements of this medium instead of mimicking tools better used in methods with tighter error constraints.