Rapid Tephra Identification in Geological Archives With Computed Tomography: Experimental Results and Natural Applications

Volcanic ash (tephra) horizons represent powerful chronological and stratigraphic markers: rapid and widespread deposition allows for correlation of geological records in time and space. Recent analytical advances enable identification of invisible ash (cryptotephra) up to thousands of kilometers from its volcanic source. This momentum has greatly expanded the reach and potential of tephrochronology: some deposits can now be traced across continents and oceans. However, the laborious laboratory procedures required to identify tephra horizons in geological archives hold back the pace of progress. By allowing the rapid visualization of ash at micrometer (µm) scales, computed tomography (CT) holds great promise to overcome these restrictions. In this study, we further demonstrate the potential of this tool for the tephra community with experimental results and applications on conventionally analyzed archives. A custom-made scanner helps us strike a balance between the convenience of whole-core medical scanners and the µm-resolution of micro-CT systems. Using basic image processing tools that can be readily mastered by tephrochronologists, we identified invisible horizons down to ∼500 shards in synthetic cores. In addition, procedures for the removal of image artifacts can be used to visualize other paleoenvironmental indicators such as bioturbation burrows, ice rafted debris or mineral dust. When applied on segments of manually counted natural archives, our approach captures cryptic glass shard maxima down to ∼300 shards/cm3. We also highlight the value of CT to help optimize sampling strategies by identifying micrometer-scale ash horizons that were not detected in shard count profiles. In conclusion, this work helps broaden the applicability of CT as a promising frontier in tephrochronology that can advance the field by optimizing the efficiency and accuracy of isochron detection.publishedVersio