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Species identification of ancient Lithuanian fish remains using collagen fingerprinting

Author:
Harvey, Virginia L., Daugnora, Linas, Buckley, Michael
Source:
Journal of archaeological science 2018
ISSN:
0305-4403
Subject:
Salmo, Scophthalmus, archaeology, bones, collagen, cost effectiveness, fauna, fisheries, mass spectrometry, salmon, species identification, turbot
Abstract:
Morphological identification of ancient bone is often problematic due to heavy fragmentation that generally influences zooarchaeological assemblages. Fish bones are more taphonomically sensitive than those of other vertebrates as they are typically smaller and less biomineralised. Thus, taxonomic identification based on the preservation of morphological features is often extremely limited and can reduce or eliminate the usefulness of an assemblage for inferring taxon information. Currently, one of the most time- and cost-efficient methods of achieving faunal identity from ancient bone is by the collagen fingerprinting technique known as ZooMS (Zooarchaeology by Mass Spectrometry). ZooMS harnesses the potential of preserved collagen, which is the most dominant and time-stable protein in bone. In this research, ZooMS is applied to ancient Baltic region fish assemblages that are between 500 and 6000 years old in order to define species identity and construct assemblage compositions. Alongside inferences into environmental and biological shifts from the Neolithic era to present day in the Baltic region, we demonstrate for the first time the ability to distinguish between recently diverged members of the Salmo (salmon) and Scophthalmus (turbot) genera. ZooMS analysis highlights 7% of the collagen-containing assemblage as having been morphologically identified incorrectly and has facilitated taxonomic refinement of a further 28% of samples, including some of the morphologically indeterminate bone fragments. This research emphasises the great potential of ZooMS in identifying ichthyoarchaeological bone remains to species-level, and provides a case for the use of collagen fingerprinting in contributing to baseline fisheries and ecological data to inform modern management.
Agid:
6108415