Southeastern Section - 66th Annual Meeting - 2017

Paper No. 3-9
Presentation Time: 11:20 AM


WOOD, R. Seth1, MANNING-BERG, Ashley R.1, WILLIFORD, Kenneth H.2 and KAH, Linda C.1, (1)Earth and Planetary Sciences, University of Tennessee, 1412 Circle Drive, Knoxville, TN 37996, (2)Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109,

Here we explore the use of Gigapan technology in the detailed petrography and taphonomic analysis of permineralized microbial mats. Gigapan mosaics compile numerous images taken through a high-power objective into a single stitched image, which results in a highly-detailed image with a broad field of view. Shifts between mesoscopic and microscopic views can be done rapidly using Gigapan mosaics, which may improve the analysis of Precambrian mats by permitting individual microfossils and microbial taphonomy to be observed within the spatial framework of mat fabrics. Unfortunately, high-resolution Gigapans can easily exceed a gigabyte in size. Thus, manipulating images can be taxing for consumer level computers. It is possible to convert images into compressed formats, such as JPEG, but this results in substantial degradation of image quality.

In order to assess the overall taphonomic state of a silicified microbial mat, we rely on a modified form of quadrat sampling, typically used in ecological studies. Unlike point counting, this method assesses the taphonomy of all microfossils within a quadrat, assuring data on both common and rare forms. To do this, each Gigapan image is split into 25 equal partitions saved as lossless TIF files. Partitioning helps create files of manageable size. Each partition is then overlain by an 8x8 grid, creating a total of 64 quadrats per partition, or 1,600 quadrats per thin section. A random number generator is used to choose 25 values, corresponding to a single quadrat in each partition. This method allows random sampling across the entire thin section. To increase total coverage of a thin section, random sampling can be repeated.

Based on our experience, analyzing a set of quadrats takes less time than point-counting and provides spatially relevant taphonomic data. Also, unlike point counting, this method is designed to be modular; meaning new data sets are built upon previous analysis. Here we show the results of this methodology using two samples from the Mesoproterozoic Angmaat chert, northern Baffin Island. These samples illustrate the effectiveness of Gigapan technology for thin section analysis determining the taphonomic state of complex microbial mat facies.