Title

Testing the navigational efficiency of desert-dwelling Jurassic arthropods

Document Type

Abstract

Publication Date

9-26-2016

Publication Title

Geological Society of America: Abstracts with Programs

Volume

48

Issue

7

Abstract

The Jurassic Aztec Sandstone preserves part of a vast ancient desert in western North America which was home to a diverse ecosystem of vertebrates and invertebrates. The movement and behavior of these animals are preserved in eolian sand dune deposits as trace fossils. One particular assemblage of supposed arthropod burrows, found near the top of the Aztec Sandstone west of Bridge Mountain in the Red Rock Canyon National Conservation Area, was selected for this study. These burrows were documented using photogrammetry, a method that uses overlapping photographs in order to digitally create a 3D model. Photogrammetry has been applied to vertebrate trackways in many studies but has not been widely used with invertebrate trace fossils. This study has helped evaluate photogrammetry as a useful tool when applied to invertebrate burrows. The unlined and unornamented branching arthropod burrows have been identified as Skolithos and Planolites isp. In order to study the behavior preserved in these fossil burrows, a quantitative analysis was conducted of the branching patterns using fractal dimension in order to quantify how efficiently the animal used the surrounding space. The fractal dimension, calculated using the box-counting method, is a number between 1 and 2 where a higher value indicates a more complete coverage of the surrounding space. Previous studies have suggested that trace fossils with a fractal dimension close to 1 may be dwelling structures, whereas trace fossils with a fractal dimension close to 2 tend to belong to deposit feeding burrows. The fractal dimension of 15 grouped assemblages from a single bedding plane varied from 1.46 to 1.66. This suggests that the function of the burrows may have been a combination of dwelling and grazing based on the fractal dimension data.

UNLV article access

Share

COinS