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doi: 10.5061/dryad.657cc
Ichthyosaurs were highly successful marine reptiles with an abundant and well-studied fossil record. However, their occurrences through geological time and space are sporadic, and it is important to understand whether times of apparent species richness and rarity are real or the result of sampling bias. Here, we explore the skeletal completeness of 351 dated and identified ichthyosaur specimens, belonging to all 102 species, the first time that such a study has been carried out on vertebrates from the marine realm. No correlations were found between time series of different skeletal metrics and ichthyosaur diversity. There is a significant geographical variation in completeness, with the well-studied northern hemisphere producing fossils of much higher quality than the southern hemisphere. Medium-sized ichthyosaurs are significantly more complete than small or large taxa: the incompleteness of small specimens was expected, but it was a surprise that larger specimens were also relatively incomplete. Completeness varies greatly between facies, with fine-grained, siliciclastic sediments preserving the most complete specimens. These findings may explain why the ichthyosaur diversity record is low at times, corresponding to facies of poor preservation potential, such as in the Early Cretaceous. Unexpectedly, we find a strong negative correlation between skeletal completeness and sea level, meaning the most complete specimens occurred at times of global low sea level, and vice versa. Completeness metrics, however, do not replicate the sampling signal and have limited use as a global-scale sampling proxy.
Appendix 1Excel file containing all data on ichthyosaur completeness, environmental parameters, references, and model outputs.SupplementSupplementary information, including additional tables, figures, data, and R codes.
completeness, sampling metrics, geological bias, Ichthyosauria, Jurassic, Triassic, sampling bias
completeness, sampling metrics, geological bias, Ichthyosauria, Jurassic, Triassic, sampling bias
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