Three-dimensional microwear analysis is a very potent method in capturing the diet and, thus, reconstructing trophic relationships. It is widely applied in archaeology, palaeontology, neontology and (palaeo)anthropology. The method had been developed for mammal teeth (Walker et al., 1978; Teaford, 1988; Calandra and Merceron, 2016), but it has proven to be applicable to sharks (McLennan and Purnell, 2021) and reptiles, including fossil taxa with rather mysterious trophic ecologies (e.g., Bestwick et al., 2020; Holwerda et al., 2023). Microwear analysis has brought about landmark discoveries extending beyond autecology and reaching into palaeoenvironmental reconstructions (e.g., Merceron et al., 2016), niche evolution (e.g., Thiery et al., 2021), and assessment of food availability and niche partitioning (Ősi et al., 2022). Furthermore, microwear analysis is a testable method, which can be investigated experimentally in extant animals in order to ground-truth dietary interpretations in extinct organisms. 

The study by Thiery et al. (2024) addresses important limitations of 3D microwear analysis: 1) the unequal access to commercial software required to analyze surface data obtained using confocal profilometers; 2) lack of replicability resulting from the use of commercial software with graphical user interface only. The latter point results in that documenting precisely what has been analyzed and how is nearly impossible.

The use of algorithms such as scale-sensitive fractal analysis (Ungar et al., 2003; Scott et al., 2006) and surface texture analysis has greatly improved replicability of DMTA and nearly eliminated intra- and inter-observer errors. Substantial effort has been made to quantify and minimize systematic and random errors in microwear analyses, such as intraspecific variation, use of different equipment (Arman et al., 2016), use of casts (Mihlbachler et al., 2019) or non-dietary variables (Bestwick et al., 2021). But even the best designed study cannot be replicated if the analysis is carried out with a “black box” software that many researchers may not afford. The trident package for R Software (https://github.com/nialsiG/trident) presented by Thiery et al. (2024) allows users to calculate 24 variables used in DMTA, transform them, calculate their variation across a surface, and rank them according to a sophisticated workflow that takes into account their normality and heteroscedasticity. A graphical user interface (GUI) is included in the form of a ShinyApp, but the power of the package, in my opinion, lies in that all steps of the analyses can be saved as R code and shared together with a study. This is a fundamental contribution to replicability and validation of microwear analyses. As best practices in code quality and replication become better known and accessible to palaeobiologists (The Turing Way Community, 2022; Trisovic et al., 2022). The presentation of the trident package is associated with three case studies, each with associated instructions on reproducing the results. These instructions partly use the literate programming approach, so that each step of the analysis is discussed and the methods are presented, either as screen shots when the GUI is used, or code. This is an excellent contribution, which hopefully will be followed by future microwear studies.

References

Arman, S. D., Ungar, P. S., Brown, C. A., DeSantis, L. R. G., Schmidt, C., and Prideaux, G. J. (2016). Minimizing inter-microscope variability in dental microwear texture analysis. Surface Topography: Metrology and Properties, 4(2), 024007. https://doi.org/10.1088/2051-672X/4/2/024007

Bestwick, J., Unwin, D. M., Butler, R. J., and Purnell, M. A. (2020). Dietary diversity and evolution of the earliest flying vertebrates revealed by dental microwear texture analysis. Nature Communications, 11(1), 5293. https://doi.org/10.1038/s41467-020-19022-2

Bestwick, J., Unwin, D. M., Henderson, D. M., and Purnell, M. A. (2021). Dental microwear texture analysis along reptile tooth rows: Complex variation with non-dietary variables. Royal Society Open Science, 8(2), 201754. https://doi.org/10.1098/rsos.201754

Calandra, I., and Merceron, G. (2016). Dental microwear texture analysis in mammalian ecology. Mammal Review, 46(3), 215–228. https://doi.org/10.1111/mam.12063

Holwerda, F. M., Bestwick, J., Purnell, M. A., Jagt, J. W. M., and Schulp, A. S. (2023). Three-dimensional dental microwear in type-Maastrichtian mosasaur teeth (Reptilia, Squamata). Scientific Reports, 13(1), 18720. https://doi.org/10.1038/s41598-023-42369-7

McLennan, L. J., and Purnell, M. A. (2021). Dental microwear texture analysis as a tool for dietary discrimination in elasmobranchs. Scientific Reports, 11(1), 2444. https://doi.org/10.1038/s41598-021-81258-9

Merceron, G., Novello, A., and Scott, R. S. (2016). Paleoenvironments inferred from phytoliths and Dental Microwear Texture Analyses of meso-herbivores. Geobios, 49(1–2), 135–146. https://doi.org/10.1016/j.geobios.2016.01.004

Mihlbachler, M. C., Foy, M., and Beatty, B. L. (2019). Surface replication, fidelity and data loss in traditional dental microwear and dental microwear texture analysis. Scientific Reports, 9(1), 1595. https://doi.org/10.1038/s41598-018-37682-5

Ősi, A., Barrett, P. M., Evans, A. R., Nagy, A. L., Szenti, I., Kukovecz, Á., Magyar, J., Segesdi, M., Gere, K., and Jó, V. (2022). Multi-proxy dentition analyses reveal niche partitioning between sympatric herbivorous dinosaurs. Scientific Reports, 12(1), 20813. https://doi.org/10.1038/s41598-022-24816-z

Scott, R. S., Ungar, P. S., Bergstrom, T. S., Brown, C. A., Childs, B. E., Teaford, M. F., and Walker, A. (2006). Dental microwear texture analysis: Technical considerations. Journal of Human Evolution, 51(4), 339–349. https://doi.org/10.1016/j.jhevol.2006.04.006

Teaford, M. F. (1988). A review of dental microwear and diet in modern mammals. Scanning Microscopy, 2, 1149–1166.

The Turing Way Community. (2022). The Turing Way: A handbook for reproducible, ethical and collaborative research (Version 1.0.2). Zenodo. https://doi.org/10.5281/ZENODO.3233853

Thiery, G., Francisco, A., Louail, M., Berlioz, É., Blondel, C., Brunetière, N., Ramdarshan, A., Walker, A. E. C., and Merceron, G. (2024). Introducing “trident”: A graphical interface for discriminating groups using dental microwear texture analysis. HAL, hal-04222508, ver. 4 peer-reviewed by PCI Paleo. https://hal.science/hal-04222508v4

Thiery, G., Gibert, C., Guy, F., Lazzari, V., Geraads, D., Spassov, N., and Merceron, G. (2021). From leaves to seeds? The dietary shift in late Miocene colobine monkeys of southeastern Europe. Evolution, 75(8), 1983–1997. https://doi.org/10.1111/evo.14283

Trisovic, A., Lau, M. K., Pasquier, T., and Crosas, M. (2022). A large-scale study on research code quality and execution. Scientific Data, 9(1), 60. https://doi.org/10.1038/s41597-022-01143-6

Ungar, P. S., Brown, C. A., Bergstrom, T. S., and Walker, A. (2003). Quantification of dental microwear by tandem scanning confocal microscopy and scale‐sensitive fractal analyses. Scanning, 25(4), 185–193. https://doi.org/10.1002/sca.4950250405

Walker, A., Hoeck, H. N., and Perez, L. (1978). Microwear of mammalian teeth as an indicator of diet. Science, 201(4359), 908–910. https://doi.org/10.1126/science.684415

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

There are less and less experts on taxonomy of particular groups particularly among early career paleontologists and (paleo)biologists – this also includes ammonoid cephalopods. Techniques cannot replace this taxonomic expertise (Engel et al. 2021) but machine learning approaches can make taxonomy more efficient, reproducible as well as passing it over more sustainable. Initially ammonoid taxonomy was a black box with small differences sometimes sufficient to erect different species as well as really idiosyncratic groupings of superficially similar specimens (see De Baets et al. 2015 for a review). In the meantime, scientists have embraced more quantitative assessments of conch shape and morphology more generally (see Klug et al. 2015 for a more recent review). The approaches still rely on important but time-intensive collection work and seeing through daisy chains of more or less accessible papers and monographs without really knowing how these approaches perform (other than expert opinion). In addition, younger scientists are usually trained by more experienced scientists, but this practice is becoming more and more difficult which makes it difficult to resolve the taxonomic gap. This relates to the fact that less and less experienced researchers with this kind of expertise get employed as well as graduate students or postdocs choosing different research or job avenues after their initial training effectively leading to a leaky pipeline and taxonomic impediment.

Robust taxonomy and stratigraphy is the basis for all other studies we do as paleontologists/paleobiologists so Foxon (2021) represents the first step to use supervised and unsupervised machine-learning approaches and test their efficiency on ammonoid conch properties. This pilot study demonstrates that machine learning approaches can be reasonably accurate (60-70%) in identifying ammonoid species (Foxon, 2021) – at least similar to that in other mollusk taxa (e.g., Klinkenbuß et al. 2020) - and might also be interesting to assist in cases where more traditional methods are not feasible. Novel approaches might even allow to further approve the accuracy as has been demonstrated for other research objects like pollen (Romero et al. 2020). Further applying of machine learning approaches on larger datasets and additional morphological features (e.g., suture line) are now necessary in order to test and improve the robustness of these approaches for ammonoids as well as test their performance more broadly within paleontology.

References

De Baets K, Bert D, Hoffmann R, Monnet C, Yacobucci M, and Klug C (2015). Ammonoid intraspecific variability. In: Ammonoid Paleobiology: From anatomy to ecology. Ed. by Klug C, Korn D, De Baets K, Kruta I, and Mapes R. Vol. 43. Topics in Geobiology. Dordrecht: Springer, pp. 359–426.

Engel MS, Ceríaco LMP, Daniel GM, Dellapé PM, Löbl I, Marinov M, Reis RE, Young MT, Dubois A, Agarwal I, Lehmann A. P, Alvarado M, Alvarez N, Andreone F, Araujo-Vieira K, Ascher JS, Baêta D, Baldo D, Bandeira SA, Barden P, Barrasso DA, Bendifallah L, Bockmann FA, Böhme W, Borkent A, Brandão CRF, Busack SD, Bybee SM, Channing A, Chatzimanolis S, Christenhusz MJM, Crisci JV, D’elía G, Da Costa LM, Davis SR, De Lucena CAS, Deuve T, Fernandes Elizalde S, Faivovich J, Farooq H, Ferguson AW, Gippoliti S, Gonçalves FMP, Gonzalez VH, Greenbaum E, Hinojosa-Díaz IA, Ineich I, Jiang J, Kahono S, Kury AB, Lucinda PHF, Lynch JD, Malécot V, Marques MP, Marris JWM, Mckellar RC, Mendes LF, Nihei SS, Nishikawa K, Ohler A, Orrico VGD, Ota H, Paiva J, Parrinha D, Pauwels OSG, Pereyra MO, Pestana LB, Pinheiro PDP, Prendini L, Prokop J, Rasmussen C, Rödel MO, Rodrigues MT, Rodríguez SM, Salatnaya H, Sampaio Í, Sánchez-García A, Shebl MA, Santos BS, Solórzano-Kraemer MM, Sousa ACA, Stoev P, Teta P, Trape JF, Dos Santos CVD, Vasudevan K, Vink CJ, Vogel G, Wagner P, Wappler T, Ware JL, Wedmann S, and Zacharie CK (2021). The taxonomic impediment: a shortage of taxonomists, not the lack of technical approaches. Zoological Journal of the Linnean Society 193, 381–387. doi: 10. 1093/zoolinnean/zlab072

Foxon F (2021). Ammonoid taxonomy with supervised and unsupervised machine learning algorithms. PaleorXiv ewkx9, ver. 3, peer-reviewed by PCI Paleo. doi: 10.31233/osf.io/ewkx9

Klinkenbuß D, Metz O, Reichert J, Hauffe T, Neubauer TA, Wesselingh FP, and Wilke T (2020). Performance of 3D morphological methods in the machine learning assisted classification of closely related fossil bivalve species of the genus Dreissena. Malacologia 63, 95. doi: 10.4002/040.063.0109

Klug C, Korn D, Landman NH, Tanabe K, De Baets K, and Naglik C (2015). Ammonoid conchs. In: Ammonoid Paleobiology: From anatomy to ecology. Ed. by Klug C, Korn D, De Baets K, Kruta I, and Mapes RH. Vol. 43. Dordrecht: Springer, pp. 3–24.

Romero IC, Kong S, Fowlkes CC, Jaramillo C, Urban MA, Oboh-Ikuenobe F, D’Apolito C, and Punyasena SW (2020). Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy. Proceedings of the National Academy of Sciences 117, 28496–28505. doi: 10.1073/pnas.2007324117

Mesozoic fishes are extremely diverse. In fact, fishes are the most diverse group of vertebrates during the Mesozoic─just as during any other era. Yet, their study is severely underrepresented in comparison to other fossil groups. There are just too few palaeoichthyologists to deal with such a vast diversity of fishes. Nonetheless, thanks to the huge efforts they have made over the last few decades, we have come a long way in our understanding of Mesozoic ichthyofaunas. One of such devoted palaeoichthyologists is Dr. Adriana López-Arbarello, whose contributions have been crucial in elucidating the phylogenetic interrelationships and taxonomic diversity of Mesozoic actinopterygian fishes (e.g., López-Arbarello, 2012; López-Arbarello & Sferco, 2018; López-Arbarello & Ebert, 2023). In her most recent manuscript, Dr. López-Arbarello has joined forces with Dr. Rainer Brocke to tackle the taxonomy and systematics of the halecomorph fishes from one of the most relevant Triassic sites, the upper Ladinian Perledo locality from Italy (López-Arbarello & Brocke, 2024). 

Fossil fishes were reported for the first time from Perledo in the first half of the 19th century (Balsamo-Crivelli, 1839), and up to 30 different species were described from the locality in the subsequent decades. Unfortunately, this is one of the multiple examples of fossil collections that suffered the effects of World War II, and most of the type material was lost. As a consequence, many of those 30 species that have been described over the years are in need of a revision. Based on the study of additional material that was transferred to Germany and is housed at the Senckenberg Research Institute and Natural History Museum, López-Arbarello & Brocke (2024) confirm the presence of four different species of halecomorph fishes in Perledo, which were previously put under synonymy (Lombardo, 2001). They provide new detailed information on the anatomy of two of those species, together with their respective diagnoses. But more importantly, they carry out a thorough exercise of taxonomy, rigorously applying the International Code of Zoological Nomenclature to disentangle the intricacies in the taxonomic story of the species placed in the genus Allolepidotus. As a result, they propose the presence of the species A. ruppelii, which they propose to be the type species for that genus (instead of A. bellottii, which they transfer to the genus Eoeugnathus). They also propose a new genus for the other species originally included in Allolepidotus, A. nothosomoides. Finally, they provide a set of measurements and ratios for Pholidophorus oblongus and Pholidophorus curionii, the other two species previously put in synonymy with A. bellottii, to demonstrate their validity as different species. However, due to the loss of the type material, the authors propose that these two species remain as nomina dubia. 

In summary, apart from providing new detailed anatomical descriptions of two species and solving some long-standing issues with the taxonomy of the halecomorphs from the relevant Triassic Perledo locality, the paper by López-Arbarello & Rainer (2024) highlights three important topics for the study of the fossil record: 1) we should never forget that world-scale problems, such as World Wars, also affect our capacity to understand the natural world in which we live, and the whole society should be aware if this; 2) the importance of exhaustively following the International Code of Zoological Nomenclature when describing new species; and 3) we are in need of new palaeoichthyologists to, in Dr. López-Arbarello’s own words, “unveil the mysteries of those marvellous Mesozoic ichthyofaunas.”

References

Balsamo-Crivelli, G. (1839). Descrizione di un nuovo rettile fossile, della famiglia dei Paleosauri, e di due pesci fossili, trovati nel calcare nero, sopra Varenna sul lago di Como, dal nobile sig. Ludovico Trotti, con alcune riflessioni geologiche. Il politecnico repertorio mensile di studj applicati alla prosperita e coltura sociale, 1, 421–431.

Lombardo, C. (2001). Actinopterygians from the Middle Triassic of northern Italy and Canton Ticino (Switzerland): Anatomical descriptions and nomenclatural problems. Rivista Italiana di Paleontologia e Stratigrafia, 107, 345–369. https://doi.org/10.13130/2039-4942/5439

López-Arbarello, A. (2012). Phylogenetic interrelationships of ginglymodian fishes (Actinopterygii: Neopterygii). PLOS ONE, 7(7), e39370. https://doi.org/10.1371/journal.pone.0039370

López-Arbarello, A., and Brocke, R. (2024). New generic name for a small Triassic ray-finned fish from Perledo (Italy). PaleorXiv, bxmg5, ver. 4, peer-reviewed by PCI Paleo. https://doi.org/10.31233/osf.io/bxmg5

López-Arbarello, A., and Ebert, M. (2023). Taxonomic status of the caturid genera (Halecomorphi, Caturidae) and their Late Jurassic species. Royal Society Open Science, 10(1), 221318. https://doi.org/10.1098/rsos.221318

López-Arbarello, A., and Sferco, E. (2018). Neopterygian phylogeny: The merger assay. Royal Society Open Science, 5(3), 172337. https://doi.org/10.1098/rsos.172337

Fossils get around. Any one fossil locality might be sampled by several collectors from as many institutions around the world. Alternatively, a single collector might heavily sample a site, and sell or trade parts of their collection to other institutions, scattering the fossils far and wide. These practices have the advantage of making fossils from any one locality available to researchers across the globe. However, they also have the disadvantage that, in order to systematically survey any one species, a researcher must follow innumerable trails of breadcrumb to get to where the relevant materials are held.

This is true of many famous fossil localities, such as the Eocene Green River Formation in the USA, the Cretaceous Kem Kem beds of Morocco, or the Devonian Miguasha cliffs of Canada. It is especially true of the Upper Jurassic deposits of the Morrison Formation in the western USA, which have yielded an impressive assemblage of megaherbivorous sauropod dinosaurs over the last 150 years. Today, these bones are to be found in museums not just in the USA, but also in Canada, Argentina, Japan, Australia, Malaysia, South Africa, and throughout Europe. Trawling museum databases in search of sauropod material from the Morrison Formation can therefore be a daunting task, never mind traveling the globe to actually study them.

A new paper by Tschopp et al. (2019) seeks to ease the burden on sauropod researchers by introducing a database of Morrison Formation sauropods, consisting of over 3000 specimens housed in nearly 40 institutions around the world. The authors are themselves sauropod workers and, having suffered first-hand the plight of studying material from the Morrison Formation, came up with a solution to the problem of keeping track of it all. The database is founded largely on material personally seen by the authors, supplemented by information from the literature and museum catalogs. The database further provides information on bone representation, ontogeny, locality details, and fine-scale stratigraphy, among other fields. Like any database, it is a living document that will continue to grow as new finds are made. Tschopp et al. (2019) have wisely chosen to allow others to contribute to the listing, but changes must first be vetted for accuracy. This product represents 10 years of work, and I have little doubt that it will be well-received by those of us who work on dinosaurs. Speaking personally, my PhD research on megaherbivorous dinosaurs from the Dinosaur Park Formation of Canada led me to institutions in Canada, the USA, and the UK, and further stops to Spain and Argentina would have been beneficial, if affordable. Planning for this work would have been greatly assisted by a database like the one provided us by Tschopp et al. (2019). Many a future graduate student will undoubtedly owe them a debt of gratitude.

References

Tschopp, E., Whitlock, J. A., Woodruff, D. C., Foster, J. R., Lei, R., & Giovanardi, S. (2019). The Morrison Formation Sauropod Consensus: A freely accessible online spreadsheet of collected sauropod specimens, their housing institutions, contents, references, localities, and other potentially useful information. PaleorXiv, version 3, peer-reviewed by PCI Paleo. doi: 10.31233/osf.io/ydvra