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Data from: First application of dental microwear texture analysis to infer theropod feeding ecology

Cite this dataset

Winkler, Daniela Eileen et al. (2022). Data from: First application of dental microwear texture analysis to infer theropod feeding ecology [Dataset]. Dryad. https://doi.org/10.5061/dryad.7d7wm37xk

Abstract

Theropods were the dominating apex predators in most Jurassic and Cretaceous terrestrial ecosystems. Their feeding ecology has always been of great interest, and new computational methods have yielded more detailed reconstructions of differences in theropod feedings behaviour. Many approaches however rely on well-preserved skulls. Dental microwear texture analysis (DMTA) is potentially applicable to isolated teeth, and here employed for the first time to investigate dietary ecology of theropods. In particular, we test whether tyrannosaurids show DMT associated with more hard-object feeding than compared to Allosaurus – which would be a sign for higher levels of osteophagy, as has often been suggested. We find no significant difference in complexity and roughness of enamel surfaces between Herrerasaurus, Allosaurus, and tyrannosaurids, which conflicts with inferences of more frequent osteophagic behaviour in Tyrannosaurus as compared to other theropods. Orientation of wear features reveals a more pronounced bi-directional puncture-and-pull feeding mode in Allosaurus than in tyrannosaurids. Our results further indicate ontogenetic niche shift in theropods and crocodylians, significantly larger height parameters in juvenile theropods might indicate frequent scavenging, resulting in more bone-tooth contact during feeding. Overall, DMTA is found to be very similar between theropods and extant large, broad-snouted crocodylians and shows great similarity in feeding ecology of theropod apex predators throughout the Mesozoic.

Usage notes

It is recommended to use MountainsMap v.8.0 or higher for data inspection and further processing, but the data files can also be accessed through open source packages including the following python packages: https://github.com/vincenzooo/read_metrology_formats

Funding

European Research Council, Award: 681450

Japan Society for the Promotion of Science, Award: 20F20325