Stem- and crown-group turtles have a rich and varied fossil record dating back to the Triassic Period. By far the most common remains of these peculiar reptiles are their bony shells and fragments of shells. Furthermore, if historical specimens preserved skulls the preparation techniques at that time were inadequate for elucidating details of the cranial structure. Thus, it comes as no surprise that most of the early research on turtles focused on the structure of the shell with little attention paid to other parts of the skeleton. Starting in the 1960s, this changed as researchers realized that there is considerable variation in the structure of turtle shells even within species and that new methods of fossil preparation, especially chemical methods, could reveal a wealth of phylogenetically important features in the structure of the skulls of turtles. The principal worker was Eugene S. Gaffney of the American Museum of Natural History (New York) who in a series of exquisitely illustrated monographs revolutionized our understanding of turtle osteology and phylogeny.

Over the last decade or so, a new generation of researchers has further refined the phylogenetic framework for turtles and continued the work by Gaffney. One of the specialists from this new generation is Jérémy Anquetin who, with a number of colleagues, has revised many of the Jurassic-age stem-turtles that existed in coastal marine settings in what is now Europe. Collections in France, Germany, Switzerland, and the UK house numerous specimens of these forms, which attracted the interest of researchers as early as the first decades of the nineteenth century. Despite this long history, however, the diversity and interrelationships of these marine taxa remained poorly understood.

In the present study, Anquetin and his colleague Charlotte André extend the fossil record of these stem-turtles, recently hypothesized as a clade Thalassochelydia, into the Early Cretaceous (Anquetin & André 2020). They present an excellent anatomical account on a well-preserved cranium from the Purbeck Formation of Dorset (England) that can be referred to Thalassochelydia and augments our knowledge of the cranial morphology of this clade. Anquetin & André (2020) make a good case that this specimen belongs to the same taxon as shell material long ago described as Hylaeochelys belli.

References

Anquetin, J., & André, C. (2020). The last surviving Thalassochelydia—A new turtle cranium from the Early Cretaceous of the Purbeck Group (Dorset, UK). PaleorXiv, 7pa5c, version 3, peer-reviewed by PCI Paleo. doi: 10.31233/osf.io/7pa5c

The Baenidae form a diverse extinct clade of exclusively North American paracryptodiran turtles known from the Early Cretaceous to the Eocene (Hay, 1908; Gaffney, 1972; Joyce and Lyson, 2015). Their fossil record was recently extended down to the Berriasian-Valanginian (Joyce et al. 2020), but the group probably originates in the Late Jurassic because it is usually retrieved as the sister group of Pleurosternidae in phylogenetic analyses. However, baenids only became abundant during the Late Cretaceous, when they are restricted in distribution to the western United States, Alberta and Saskatchewan (Joyce and Lyson, 2015).

During the Campanian, baenids are abundant in the northern (Alberta, Montana) and southern (Texas, New Mexico, Utah) parts of their range, but in the middle part of this range they are mostly represented by poorly diagnosable shell fragments. In their new contribution, Wu et al. (2023) describe a new articulated baenid specimen from the Campanian Mesaverde Formation of Wyoming. Despite its poor preservation, they are able to confidently assign this partial shell to Neurankylus sp., hence definitively confirming the presence of baenids and Neurankylus in this formation. Incidentally, this new specimen was found in a non-fluvial depositional environment, which would also confirm the interpretation of Neurankylus as a pond turtle (Hutchinson and Archibald, 1986; Sullivan et al., 1988; Wu et al., 2023; see also comments from the second reviewer).

The study of Wu et al. (2023) also includes a detailed account of the state of the fossil when it was discovered and the subsequent extraction and preparation procedures followed by the team. This may seem excessive or out of place to some, but I agree with the authors that such information, when available, should be more commonly integrated into scientific articles describing new fossil specimens. Preparation and restoration can have a significant impact on the perceived morphology. This must be taken into account when working with fossil specimens. The chemicals or products used to treat, prepare, or consolidate the specimens are also important information for long-term curation. Therefore, it is important that such information is recorded and made available for researchers, curators, and preparators.

References

Gaffney, E. S. (1972). The systematics of the North American family Baenidae (Reptilia, Cryptodira). Bulletin of the American Museum of Natural History, 147(5), 241–320.

Hay, O. P. (1908). The Fossil Turtles of North America. Carnegie Institution of Washington, Washington, D.C. https://doi.org/10.5962/bhl.title.12500

Hutchison, J. H., and Archibald, J. D. (1986). Diversity of turtles across the Cretaceous/Tertiary boundary in Northeastern Montana. Palaeogeography, Palaeoclimatology, Palaeoecology, 55(1), 1–22. https://doi.org/10.1016/0031-0182(86)90133-1

Joyce, W. G., and Lyson, T. R. (2015). A review of the fossil record of turtles of the clade Baenidae. Bulletin of the Peabody Museum of Natural History, 56(2), 147–183. https://doi.org/10.3374/014.058.0105

Joyce, W. G., Rollot, Y., and Cifelli, R. L. (2020). A new species of baenid turtle from the Early Cretaceous Lakota Formation of South Dakota. Fossil Record, 23(1), 1–13. https://doi.org/10.5194/fr-23-1-2020

Sullivan, R. M., Lucas, S. G., Hunt, A. P., and Fritts, T. H. (1988). Color pattern on the selmacryptodiran turtle Neurankylus from the Early Paleocene (Puercan) of the San Juan Basin, New Mexico. Contributions in Science, 401, 1–9. https://doi.org/10.5962/p.241286

Wu, K. Y., Heuck, J., Varriale, F. J., and Farke, A. (2023). A baenid turtle shell from the Mesaverde Formation (Campanian, Late Cretaceous) of Park County, Wyoming, USA. PaleorXiv, uk3ac, ver. 5, peer-reviewed and recommended by Peer Community In Paleontology. https://doi.org/10.31233/osf.io/uk3ac

I am a non-avian dinosaur palaeontologist by trade with a particular interest in their palaeoecology. This can be an endless source of both fascination and frustration. Fascination, because non-avian dinosaurs are quite unlike anything alive today, warranting some use of creative license when imagining them as living animals. Frustration, because the lack of good, extant ecological analogues frequently makes reconstruction of their ancient ecologies an almost insurmountable challenge.

The Canadian Museum of Nature where I work has a good collection of Late Cretaceous turtles. I took an interest in these some years ago because it struck me that, despite the quality of our collection, relatively few people come to study them. I thought, "Someone should work on these. Why not me?" I figured studying a new fossil group would present a fun change of pace and perhaps a more straightforward object of palaeoecological reconstruction. After all, fossil turtles are a lot like living turtles, so how hard can it be? Right?

In 2018, I took a special interest in one recently prepared fossil turtle, which I determined to be a new species of Basilemys (Mallon and Brinkman, 2018). Basilemys held my interest because, although it is a relatively common form, there has been some debate concerning the palaeohabitat of this animal and its closest relatives, the nanhsiungchelyids. Some have argued for an aquatic habitat for these animals; others, for a terrestrial one. It seems that where one comes down on the issue depends on which aspect of ecomorphology is emphasized. If it is on the flat carapace, nanhsiungchelyids must have been aquatic; if it is on the stout feet, terrestrial. This is how I came to appreciate the numerous ecomorphological proxies (e.g., skull shape, shell shape, limb proportions) that are used in turtle palaeoecology and how incongruent they can sometimes be. So much for easy answers!

The present study by Evers et al. is a response to an original piece of research by Lichtig and Lucas (2017), who claimed to be able to use simple shell measurements (carapacial doming and relative plastral width) to accurately deduce/infer the habitats of living turtles and, by extension, fossil ones. In short, they found that terrestrial turtles tend to have more domed carapaces and wider plastra, yielding some unconventional palaeoecological reconstructions of particular stem turtles. Evers et al. take issue with several aspects of this study, including issues of faulty data entry, inappropriate removal of extant taxa from the model, and insufficient accounting for phylogenetic non-independence. By correcting for these overights, they find that the model of Lichtig and Lucas (2017) performs more poorly than advertised and that the palaeoecological classification it produces should be questioned. "The map is not the territory", as Alfred Korzybski put it, and this latest study by Evers et al. serves as an important reminder of that lesson.
Still, even if Lichtig and Lucas's model is overly simplistic, it is true that aquatic turtles, on average, have lower carapaces and narrower plastra, and that they have relatively lower skulls and longer toes. Surely, there is merit in each of these anatomical proxies, even if no single one predicts ecology with total accuracy. I would love to see a model that combines them all. Until then, Evers et al. have inched us closer to knowing what turtle morphology can (and cannot) tell us about habitat.

Thanks to D. Brinkman and H. Smith for their helpful reviews of the manuscript.

References

Evers, S. W., Foth, C., Joyce, W. G., and Hermanson, G. (2024). Simple shell measurements do not consistently predict habitat in turtles: A reply to Lichtig and Lucas (2017). bioRxiv, 586561, ver. 3 peer-reviewed by PCI Paleo. https://doi.org/10.1101/2024.03.25.586561

Lichtig, A. J., and Lucas, S. G. (2017). A simple method for inferring habitats of extinct turtles. Palaeoworld, 26(3), 581–588. https://doi.org/10.1016/j.palwor.2017.02.001

Mallon, J. C., and Brinkman, D. B. (2018). Basilemys morrinensis, a new species of nanhsiungchelyid turtle from the Horseshoe Canyon Formation (Upper Cretaceous) of Alberta, Canada. Journal of Vertebrate Paleontology, 38(2), e1431922. https://doi.org/10.1080/02724634.2018.1431922

One of the most recent technological advances in paleontology enables the characterization of ancient proteins, a new discipline known as palaeoproteomics (Ostrom et al., 2000; Warinner et al., 2022). Palaeoproteomics has superficial similarities with ancient DNA, as both work with ancient molecules, however the former focuses on peptides and the latter on nucleotides. While the study of ancient DNA is more established (e.g., Shapiro et al., 2019), palaeoproteomics is experiencing a rapid diversification of application, from deep time paleontology (e.g., Schroeter et al., 2022) to taxonomic identification of bone fragments (e.g., Douka et al., 2019), and determining genetic sex of ancient individuals (e.g., Lugli et al., 2022). However, as Patramanis et al. (2023) note in this manuscript, tools for analyzing protein sequence data are still in the informal stage, making the application of this methodology a challenge for many new-comers to the discipline, especially those with little bioinformatics expertise.

In the spirit of democratizing the field of palaeoproteomics, Patramanis et al. (2023) developed an open-source pipeline, PaleoProPhyler released under a CC-BY license (https://github.com/johnpatramanis/Proteomic_Pipeline). Here, Patramanis et al. (2023) introduce their workflow designed to facilitate the phylogenetic analysis of ancient proteins. This pipeline is built on the methods from earlier studies probing the phylogenetic relationships of an extinct genus of rhinoceros Stephanorhinus (Cappellini et al., 2019), the large extinct ape Gigantopithecus (Welker et al., 2019), and Homo antecessor (Welker et al., 2020). PaleoProPhyler has three interacting modules that initialize, construct, and analyze an input dataset. The authors provide a demonstration of application, presenting a molecular hominid phyloproteomic tree. 

In order to run some of the analyses within the pipeline, the authors also generated the Hominid Palaeoproteomic Reference Dataset which includes 10,058 protein sequences per individual translated from publicly available whole genomes of extant hominids (orangutans, gorillas, chimpanzees, and humans) as well as some ancient genomes of Neanderthals and Denisovans. This valuable research resource is also publicly available, on Zenodo (Patramanis et al., 2022). 

Three reviewers reported positively about the development of this program, noting its importance in advancing the application of palaeoproteomics more broadly in paleontology.

References

Cappellini, E., Welker, F., Pandolfi, L., Ramos-Madrigal, J., Samodova, D., Rüther, P. L., Fotakis, A. K., Lyon, D., Moreno-Mayar, J. V., Bukhsianidze, M., Rakownikow Jersie-Christensen, R., Mackie, M., Ginolhac, A., Ferring, R., Tappen, M., Palkopoulou, E., Dickinson, M. R., Stafford, T. W., Chan, Y. L., … Willerslev, E. (2019). Early Pleistocene enamel proteome from Dmanisi resolves Stephanorhinus phylogeny. Nature, 574(7776), 103–107. https://doi.org/10.1038/s41586-019-1555-y

Douka, K., Brown, S., Higham, T., Pääbo, S., Derevianko, A., and Shunkov, M. (2019). FINDER project: Collagen fingerprinting (ZooMS) for the identification of new human fossils. Antiquity, 93(367), e1. https://doi.org/10.15184/aqy.2019.3 

Lugli, F., Nava, A., Sorrentino, R., Vazzana, A., Bortolini, E., Oxilia, G., Silvestrini, S., Nannini, N., Bondioli, L., Fewlass, H., Talamo, S., Bard, E., Mancini, L., Müller, W., Romandini, M., and Benazzi, S. (2022). Tracing the mobility of a Late Epigravettian (~ 13 ka) male infant from Grotte di Pradis (Northeastern Italian Prealps) at high-temporal resolution. Scientific Reports, 12(1), 8104. https://doi.org/10.1038/s41598-022-12193-6

Ostrom, P. H., Schall, M., Gandhi, H., Shen, T.-L., Hauschka, P. V., Strahler, J. R., and Gage, D. A. (2000). New strategies for characterizing ancient proteins using matrix-assisted laser desorption ionization mass spectrometry. Geochimica et Cosmochimica Acta, 64(6), 1043–1050. https://doi.org/10.1016/S0016-7037(99)00381-6

Patramanis, I., Ramos-Madrigal, J., Cappellini, E., and Racimo, F. (2022). Hominid Palaeoproteomic Reference Dataset (1.0.1) [dataset]. Zenodo. https://doi.org/10.5281/ZENODO.7333226

Patramanis, I., Ramos-Madrigal, J., Cappellini, E., and Racimo, F. (2023). PaleoProPhyler: A reproducible pipeline for phylogenetic inference using ancient proteins. BioRxiv, 519721, ver. 3 peer-reviewed by PCI Paleo. https://doi.org/10.1101/2022.12.12.519721

Schroeter, E. R., Cleland, T. P., and Schweitzer, M. H. (2022). Deep Time Paleoproteomics: Looking Forward. Journal of Proteome Research, 21(1), 9–19. https://doi.org/10.1021/acs.jproteome.1c00755

Shapiro, B., Barlow, A., Heintzman, P. D., Hofreiter, M., Paijmans, J. L. A., and Soares, A. E. R. (Eds.). (2019). Ancient DNA: Methods and Protocols (2nd ed., Vol. 1963). Humana, New York. https://doi.org/10.1007/978-1-4939-9176-1

Warinner, C., Korzow Richter, K., and Collins, M. J. (2022). Paleoproteomics. Chemical Reviews, 122(16), 13401–13446. https://doi.org/10.1021/acs.chemrev.1c00703

Welker, F., Ramos-Madrigal, J., Gutenbrunner, P., Mackie, M., Tiwary, S., Rakownikow Jersie-Christensen, R., Chiva, C., Dickinson, M. R., Kuhlwilm, M., De Manuel, M., Gelabert, P., Martinón-Torres, M., Margvelashvili, A., Arsuaga, J. L., Carbonell, E., Marques-Bonet, T., Penkman, K., Sabidó, E., Cox, J., … Cappellini, E. (2020). The dental proteome of Homo antecessor. Nature, 580(7802), 235–238. https://doi.org/10.1038/s41586-020-2153-8

Welker, F., Ramos-Madrigal, J., Kuhlwilm, M., Liao, W., Gutenbrunner, P., De Manuel, M., Samodova, D., Mackie, M., Allentoft, M. E., Bacon, A.-M., Collins, M. J., Cox, J., Lalueza-Fox, C., Olsen, J. V., Demeter, F., Wang, W., Marques-Bonet, T., and Cappellini, E. (2019). Enamel proteome shows that Gigantopithecus was an early diverging pongine. Nature, 576(7786), 262–265. https://doi.org/10.1038/s41586-019-1728-8

A fundamental question in evolutionary biology and paleobiology is how quickly populations and/or species evolve and under what circumstances. Because the fossil record affords us the most direct view of how species lineages have changed in the past, considerable effort has gone into developing methodological approaches for assessing rates of evolution as well as what has been termed “mode of evolution” which generally describes pattern of evolution, for example whether the morphological change captured in fossil time series are best characterized as static, punctuated, or trending (e.g., Sheets and Mitchell, 2001; Hunt, 2006, 2008; Voje et al., 2018). The rock record from which these samples are taken, however, is incomplete, due to spatially and temporally heterogenous sediment deposition and erosion. The resulting structure of the stratigraphic record may confound the direct application of evolutionary models to fossil time series, most of which come from single localities. This pressing issue is tackled in a new study entitled “Identification of the mode of evolution in incomplete carbonate successions” (Hohmann et al., 2024).

The “carbonate successions” part of the title is important. Previous similar work (Hannisdal, 2006) used models for siliciclastic depositional systems to simulate the rock record. Here, the authors simulate sediment deposition across a carbonate platform, a system that has been treated as fundamentally different from siliciclastic settings, from both the point of view of geology (see Wagoner et al., 1990; Schlager, 2005) and ecology (Hopkins et al., 2014). The authors do find that stratigraphic structure impacts the identification of mode of evolution but not necessarily in the way one might expect; specifically, it is less important how much time is represented compared to the size and distribution of gaps, regardless of where you are sampling along the platform. This result provides an important guiding principle for selecting fossil time series for future investigations. 

Another very useful result of this study is the impact of time series length, which in this case should be understood as the density of sampling over a particular time interval. Counterintuitively, the probability of selecting the data-generating model as the best model decreases with increased length. The authors propose several explanations for this, all of which should inspire further work. There are also many other variables that could be explored in the simulations of the carbonate models as well as the fossil time series. For example, the authors chose to minimize within-sample variation in order to avoid conflating variability with evolutionary trends. But greater variance also potentially impacts model selection results and underlies questions about how variation relates to evolvability and the potential for directional change. 

Lastly, readers of Hohmann et al. (2024) are encouraged to also peruse the reviews and author replies associated with the PCI Paleo peer review process. The discussion contained in these documents touch on several important topics, including model performance and model selection, the nature of nested model systems, and the potential of the forwarding modeling approach.  

References

Hannisdal, B. (2006). Phenotypic evolution in the fossil record: Numerical experiments. The Journal of Geology, 114(2), 133–153. https://doi.org/10.1086/499569

Hohmann, N., Koelewijn, J. R., Burgess, P., and Jarochowska, E. (2024). Identification of the mode of evolution in incomplete carbonate successions. bioRxiv, 572098, ver. 4 peer-reviewed by PCI Paleo. https://doi.org/10.1101/2023.12.18.572098

Hopkins, M. J., Simpson, C., and Kiessling, W. (2014). Differential niche dynamics among major marine invertebrate clades. Ecology Letters, 17(3), 314–323. https://doi.org/10.1111/ele.12232

Hunt, G. (2006). Fitting and comparing models of phyletic evolution: Random walks and beyond. Paleobiology, 32(4), 578–601. https://doi.org/10.1666/05070.1

Hunt, G. (2008). Gradual or pulsed evolution: When should punctuational explanations be preferred? Paleobiology, 34(3), 360–377. https://doi.org/10.1666/07073.1

Schlager, W. (Ed.). (2005). Carbonate Sedimentology and Sequence Stratigraphy. SEPM Concepts in Sedimentology and Paleontology No. 8. https://doi.org/10.2110/csp.05.08

Sheets, H. D., and Mitchell, C. E. (2001). Why the null matters: Statistical tests, random walks and evolution. Genetica, 112, 105–125. https://doi.org/10.1023/A:1013308409951

Voje, K. L., Starrfelt, J., and Liow, L. H. (2018). Model adequacy and microevolutionary explanations for stasis in the fossil record. The American Naturalist, 191(4), 509–523. https://doi.org/10.1086/696265

Wagoner, J. C. V., Mitchum, R. M., Campion, K. M., and Rahmanian, V. D. (1990). Siliciclastic Sequence Stratigraphy in Well Logs, Cores, and Outcrops: Concepts for High-Resolution Correlation of Time and Facies. AAPG Methods in Exploration Series No. 7. https://doi.org/10.1306/Mth7510