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

Today’s birds are divided into two deeply divergent and historically well-documented groups: Palaeognathae and Neognathae. Palaeognaths include both the flight-capable tinamous as well as the flightless ratites (ostriches, rheas, kiwis, cassowaries, and kin). Neognaths include all other modern birds, ranging from sparrows to penguins to hummingbirds. The clade names refer to the anatomy of the palate, with the “old jaws” (palaeognaths) originally thought to more closely resemble an ancestral reptilian condition and the “new jaws” (neognaths) showing a uniquely modified bony configuration. This particularly manifests in the pterygoid-palatine complex (PPC) in the palate, formed from pairs of pterygoids and palatines alongside a single midline vomer. In palaeognaths, the vomer is comparatively large and the pterygoid and palatine are relatively tightly connected. The PPC is more mobile in neognaths, with a variably shaped vomer, which is sometimes even absent. Although both groups of birds show cranial kinesis, neognaths exhibit a much more pronounced degree of kinesis versus palaeognaths, due in part to the tighter nature of the palaeognath pterygoid/palatine interfaces.

A previous paper (Hu et al. 2019) used 3D geometric morphometrics to compare the shape of the vomer across neognaths and palaeognaths. Among other findings, this work suggested that each clade had a distinct vomer morphology, with palaeognaths more similar to the ancestral condition (i.e., that of non-avian dinosaurs). This observation was extended to support inferences of limited vs. less limited cranial kinesis in various extinct species, based in part on observations of vomer shape. A new preprint by Plateau and Foth (2021) presents a reanalysis of Hu et al.’s data, specifically focusing on allometric effects. In short, the new analysis looks at how size correlates (or doesn't correlate) with vomer shape. 

Plateau and Foth (2021) found that when size effects are included, differences between palaeognaths and neognaths are less than the “raw” (uncorrected) shape data suggest. It is much harder to tell bird groups apart! Certainly, there are still some general differences, but some separations in morphospace close up when allometry—the interrelationship between shape and size—is considered. Plateau and Foth (2021) use this finding to suggest that 1) vomer shape alone is not a completely reliable proxy for inferring the phylogenetic affinities of a particular bird; and 2) the vomer is only one small component of the cranial kinetic system, and thus its shape is of limited utility for inferring cranial kinesis capabilities when considered independently from the rest of the relevant skull bones.

References

Hu, H., Sansalone, G., Wroe, S., McDonald, P. G., O’Connor, J. K., Li, Z., Xu, X., & Zhou, Z. (2019). Evolution of the vomer and its implications for cranial kinesis in Paraves. Proceedings of the National Academy of Sciences, 116(39), 19571–19578. doi: 10.1073/pnas.1907754116

Plateau, O., & Foth, C. (2021). The impact of allometry on vomer shape and its implications for the taxonomy and cranial kinesis of crown-group birds. BioRxiv, 184101, ver. 3 peer-reviewed by PCI Paleo. doi: 10.1101/2020.07.02.184101

Calcareous plankton gives us perhaps the most complete record of microevolutionary changes in the fossil record (e.g. Tong et al., 2018; Weinkauf et al., 2019), but this opportunity is not exploited enough, as it requires meticulous work in documenting assemblage-level variation through time. Especially in organisms such as coccolithophores, understanding the meaning of secular trends in morphology warrants an understanding of the functional biology and ecology of these organisms. Razmjooei and Thibault (2022) achieve this in their painstaking analysis of two coccolithophore lineages, Cribrosphaerella ehrenbergii and Microrhabdulus, in the Late Cretaceous of Iran. They propose two episodes of morphological change. The first one, starting around 76 Ma in the late Campanian, is marked by a sudden shift towards larger sizes of C. ehrenbergii and the appearance of a new species M. zagrosensis from M. undulatus. The second episode around 69 Ma (Maastrichtian) is inferred from a gradual size increase and morphological changes leading to probably anagenetic speciation of M. sinuosus n.sp.

The study remarkably analyzed the entire distributions of coccolith length and rod width, rather than focusing on summary statistics (De Baets et al., in press). This is important, because the range of variation determines the taxon’s evolvability with respect to the considered trait (Love et al., 2022). As the authors discuss, cell size in photosymbiotic unicellular organisms is not subject to the same constraints that will be familiar to researchers working e.g. on mammals (Niklas, 1994; Payne et al., 2009; Smith et al., 2016). Furthermore, temporal changes in size alone cannot be interpreted as evolutionary without knowledge of phenotypic plasticity and environmental clines present in the basin (Aloisi, 2015). The more important is that this study cross-tests size changes with other morphological parameters to examine whether their covariation supports inferred speciation events. The article addresses as well the effects of varying sedimentation rates (Hohmann, 2021) by, somewhat implicitly, correcting for the stratophenetic trend using an age-depth model and accounting for a hiatus. Such multifaceted approach as applied in this work is fundamental to unlock the dynamics of speciation offered by the microfossil record. 

The study highlights also the link between shifts in size and diversity. Klug et al. (2015) have previously demonstrated that these two variables are related, as higher diversity is more likely to lead to extreme values of morphological traits, but this study suggests that the relationship is more intertwined: environmentally-driven rise in morphological variability (and thus in size) can lead to diversification. It is a fantastic illustration of the complexity of morphological evolution that, if it can be evaluated in terms of mechanisms, provides an insight into the dynamics of speciation.

References

Aloisi, G. (2015). Covariation of metabolic rates and cell size in coccolithophores. Biogeosciences, 12(15), 4665–4692. doi: 10.5194/bg-12-4665-2015

De Baets, K., Jarochowska, E., Buchwald, S. Z., Klug, C., and Korn, D. (In Press). Lithology controls ammonoid size distribution. Palaios.

Hohmann, N. (2021). Incorporating information on varying sedimentation rates into palaeontological analyses. PALAIOS, 36(2), 53–67. doi: 10.2110/palo.2020.038

Klug, C., De Baets, K., Kröger, B., Bell, M. A., Korn, D., and Payne, J. L. (2015). Normal giants? Temporal and latitudinal shifts of Palaeozoic marine invertebrate gigantism and global change. Lethaia, 48(2), 267–288. doi: 10.1111/let.12104

Love, A. C., Grabowski, M., Houle, D., Liow, L. H., Porto, A., Tsuboi, M., Voje, K.L., and Hunt, G. (2022). Evolvability in the fossil record. Paleobiology, 48(2), 186–209. doi: 10.1017/pab.2021.36

Niklas, K. J. (1994). Plant allometry: The scaling of form and process. Chicago: University of Chicago Press.

Payne, J. L., Boyer, A. G., Brown, J. H., Finnegan, S., Kowalewski, M., Krause, R. A., Lyons, S.K., McClain, C.R., McShea, D.W., Novack-Gottshall, P.M., Smith, F.A., Stempien, J.A., and Wang, S. C. (2009). Two-phase increase in the maximum size of life over 3.5 billion years reflects biological innovation and environmental opportunity. Proceedings of the National Academy of Sciences, 106(1), 24–27. doi: 10.1073/pnas.0806314106

Razmjooei, M. J., and Thibault, N. (2022). Morphometric changes in two Late Cretaceous calcareous nannofossil lineages support diversification fueled by long-term climate change. PaleorXiv, nfyc9, ver. 4, peer-reviewed by PCI Paleo. doi: 10.31233/osf.io/nfyc9

Smith, F. A., Payne, J. L., Heim, N. A., Balk, M. A., Finnegan, S., Kowalewski, M., Lyons, S.K., McClain, C.R., McShea, D.W., Novack-Gottshall, P.M., Anich, P.S., and Wang, S. C. (2016). Body size evolution across the Geozoic. Annual Review of Earth and Planetary Sciences, 44(1), 523–553. doi: 10.1146/annurev-earth-060115-012147

Tong, S., Gao, K., and Hutchins, D. A. (2018). Adaptive evolution in the coccolithophore Gephyrocapsa oceanica following 1,000 generations of selection under elevated CO2. Global Change Biology, 24(7), 3055–3064. doi: 10.1111/gcb.14065

Weinkauf, M. F. G., Bonitz, F. G. W., Martini, R., and Kučera, M. (2019). An extinction event in planktonic Foraminifera preceded by stabilizing selection. PLOS ONE, 14(10), e0223490. doi: 10.1371/journal.pone.0223490

Trilobites are arthropods that became extinct at the greatest marine mass extinction over 250 Ma ago. Because of their often bizarre forms, their great diversity and disparity of shapes, they have attracted the interest of researchers and laypersons alike. Due to their calcified exoskeleton, their remains are quite abundant in many marine strata. One particularly interesting aspect, however, is the fossilization of various molting stages. This allows the reconstruction of both juvenile strategies (lecitotrophic versus planktotrophic) and the entire life history of at least some well-documented taxa (e.g., Hughes 2003, 2007; Laibl 2017). For example, life history of trilobites is, based on certain morphological changes, classically subdivided in the three phases protaspis (hatchling, one dorsal shield with few segments with no articulation between), meraspis (juvenile, two and more shields connected by articulations) and holaspis (when the terminal number of thoracic segments is reached). At most molting events, a new skeletal element is added (only in the holaspis, the number of thoracic segments does not change). Nevertheless, many trilobites are known mainly from late meraspid and holaspid stages, because the dorsal shields of the first ontogenetic stages are usually very small and thus often either dissolved or overlooked. An improved understanding of trilobite ontogeny could thus help filling in these gaps in fossil preservation and subsequently, to better understand evolutionary pathways. This is where this paper comes in. In a very clever approach, the New-York-based researcher Melanie Hopkins modeled the growth of these segmented animals (Hopkins 2020). Previous growth models of invertebrates focused on, e.g., mollusks, whose shells grow by accretion. Modelling arthropod ontogeny represented a challenge, which is now overcome by Hopkins' brilliant paper. Her generative growth model is based on empirical data of *Aulacopleura koninckii* (Barrande, 1846). Hong et al. (2014) and Hughes et al. (2017) documented the ontogeny of this 429 Ma old trilobite species in great detail. In the Silurian of the Barrandian region (Czech Republic), this species is locally very common and all growth stages are well known. I could imagine that the paper of Hughes et al. (2017) planted the seed into Melanie Hopkins’ mind to approach trilobite development in general in a quantitative way with a mathematical approach comparable to the mollusk-research by, e.g., David Raup (1961, 1966) and George McGhee (2015). Hopkins’ growth model requires “a minimum of nine parameters […] to model basic trilobite growth and segmentation, and three additional parameters […] to allow a transition to a new growth gradient for the trunk region during ontogeny” (Hopkins 2020: p. 21). It is now possible to play with parameters such as protaspid size, segment dimensions, segment numbers, etc., in order to estimate changes in body size or morphology. Furthermore, the model could be applied to similarly organized arthropod exoskeletons like many early Cambrian arthropods (e.g., marellomorphs) or even crustaceans (e.g., conchostracans or copepods). Of great interest could also be to assess influences of environmental changes on arthropod ontogeny. Also, her work will help to reconstruct unknown developmental information missing from trilobite species (and possibly other arthropods) and also to explore their morphospace. **References** Barrande, J. (1846). Notice préliminaire sur le système Silurien et les trilobites de Bohême. Leipzig: Hirschfield. Hong, P. S., Hughes, N. C., & Sheets, H. D. (2014). Size, shape, and systematics of the Silurian trilobite *Aulacopleura koninckii*. Journal of Paleontology, 88(6), 1120–1138. doi: [ 10.1666/13-142](https://dx.doi.org/ 10.1666/13-142) Hopkins, M. J. (2020). A simple generative model of trilobite segmentation and growth. PaleorXiv, version 3, peer-reviewed by PCI Paleo. doi: [ 10.31233/osf.io/zt642](https://dx.doi.org/ 10.31233/osf.io/zt642) Hughes, N. C. (2003). Trilobite tagmosis and body patterning from morphological and developmental perspectives. Integrative and Comparative Biology, 43(1), 185–206. doi: [ 10.1093/icb/43.1.185](https://dx.doi.org/ 10.1093/icb/43.1.185) Hughes, N. C. (2007). The evolution of trilobite body patterning. Annual Review of Earth and Planetary Sciences, 35(1), 401–434. doi: [ 10.1146/annurev.earth.35.031306.140258](https://dx.doi.org/ 10.1146/annurev.earth.35.031306.140258) Hughes, N. C., Hong, P. S., Hou, J., & Fusco, G. (2017). The development of the Silurian trilobite *Aulacopleura koninckii* reconstructed by applying inferred growth and segmentation dynamics: A case study in paleo-evo-devo. Frontiers in Ecology and Evolution, 5, 00037. doi: [ 10.3389/fevo.2017.00037](https://dx.doi.org/ 10.3389/fevo.2017.00037) Laibl, L. (2017). Patterns in Palaeontology: The development of trilobites. Palaeontology Online, 7(10), 1–9. McGhee, G. R. (2015). Limits in the evolution of biological form: a theoretical morphologic perspective. Interface Focus, 5(6), 20150034. doi: [ 10.1098/rsfs.2015.0034](https://dx.doi.org/ 10.1098/rsfs.2015.0034) Raup, D. M. (1961). The geometry of coiling in gastropods. Proceedings of the National Academy of Sciences, 47(4), 602–609. doi: [ 10.1073/pnas.47.4.602](https://dx.doi.org/ 10.1073/pnas.47.4.602) Raup, D. M. (1966). Geometric analysis of shell coiling: general problems. Journal of Paleontology, 40, 1178–1190.

Suidae are well-represented in Plio-Pleistocene African hominin sites and are particularly important for biochronological assessments. Their ubiquity in hominin sites combined with multiple appearances of what appears to be graminivorous adaptations in the lineage (Harris & White, 1979) suggest that they have the potential to contribute to our understanding of Plio-Pleistocene paleoenvironments. While they have been generally understudied in this respect, there has been recent focus on their diets to understand the paleoenvironments of early hominin habitats. Of particular interest is Kolpochoerus, one of the most abundant suid genera in the Plio-Pleistocene with a wide geographic distribution and diverse dental morphologies (Harris & White, 1979). 

In this study, Louail et al. (2024) present the results of the first dental microwear texture analysis (DMTA) conducted on suids from the Shungura Formation of the Omo Valley, an important Plio-Pleistocene hominin site that records an almost continuous sedimentary record from ca. 3.75 Ma to 1.0 Ma (Heinzelin 1983; McDougall et al., 2012; Kidane et al., 2014). Dental microwear is one of the main proxies in understanding diet in fossil mammals, particularly herbivores, and DMTA has been shown to be effective in differentiating inter- and intra-species dietary differences (e.g., Scott et al., 2006; 2012; Merceron et al., 2010). However, only a few studies have applied this method to extinct suids (Souron et al., 2015; Ungar et al., 2020), making this study especially pertinent for those interested in suid dietary evolution or hominin paleoecology.

In addition to examining DMT variations of Kolpochoerus specimens from Omo, Louail et al. (2024) also expanded the modern comparative data set to include larger samples of African suids with different diets from herbivores to omnivores to better interpret the fossil data. They found that DMTA distinguishes between extant suid taxa, reflecting differences in diet, indicating that DMT can be used to examine the diets of fossil suids. The results suggest that Kolpochoerus at Omo had a substantially different diet from any extant suid taxon and that although its anistropy values increased through time, they remain well below those observed in modern Phacochoerus that specializes in fibrous, abrasive plants. Based on these results, in combination with comparative and experimental DMT, enamel carbon isotopic, and morphological data, Louail et al. (2024) propose that Omo Kolpochoerus preferred short, soft and low abrasive herbaceous plants (e.g., fresh grass shoots), probably in more mesic habitats. Louail et al. (2024) note that with the wide temporal and geographic distribution of Kolpochoerus, different species and populations may have had different feeding habits as they exploited different local habitats. However, it is noteworthy that similar inferences were made at other hominin sites based on other types of dietary data (e.g., Harris & Cerling, 2002; Rannikko et al., 2017, 2020; Yang et al., 2022). If this is an indication of their habitat preferences, the wide-ranging distribution of Kolpochoerus may suggest that mesic habitats with short, soft herbaceous plants were present in various proportions at most Plio-Pleistocene hominin sites. 

References

Harris, J. M., and Cerling, T. E. (2002). Dietary adaptations of extant and Neogene African suids. Journal of Zoology, 256(1), 45–54. https://doi.org/10.1017/S0952836902000067

Harris, J. M., and White, T. D. (1979). Evolution of the Plio-Pleistocene African Suidae. Transactions of the American Philosophical Society, 69(2), 1–128. https://doi.org/10.2307/1006288

Heinzelin, J. de. (1983). The Omo Group. Archives of the International Omo Research Expedition. Volume 85. Annales du Musée Royal de l’Afrique Centrale, série 8, Sciences géologiques, Tervuren, 388 p.

Kidane, T., Brown, F. H., and Kidney, C. (2014). Magnetostratigraphy of the fossil-rich Shungura Formation, southwest Ethiopia. Journal of African Earth Sciences, 97, 207–223. https://doi.org/10.1016/j.jafrearsci.2014.05.005

Louail, M., Souron, A., Merceron, G., and Boisserie, J.-R. (2024). New insights on feeding habits of Kolpochoerus from the Shungura Formation (Lower Omo Valley, Ethiopia) using dental microwear texture analysis. PaleorXiv, dbgtp, ver. 3, peer-reviewed by PCI Paleo. https://doi.org/10.31233/osf.io/dbgtp

McDougall, I., Brown, F. H., Vasconcelos, P. M., Cohen, B. E., Thiede, D. S., and Buchanan, M. J. (2012). New single crystal 40Ar/39Ar ages improve time scale for deposition of the Omo Group, Omo–Turkana Basin, East Africa. Journal of the Geological Society, 169(2), 213–226. https://doi.org/10.1144/0016-76492010-188

Merceron, G., Escarguel, G., Angibault, J.-M., and Verheyden-Tixier, H. (2010). Can dental microwear textures record inter-individual dietary variations? PLoS ONE, 5(3), e9542. https://doi.org/10.1371/journal.pone.0009542

Rannikko, J., Adhikari, H., Karme, A., Žliobaitė, I., and Fortelius, M. (2020). The case of the grass‐eating suids in the Plio‐Pleistocene Turkana Basin: 3D dental topography in relation to diet in extant and fossil pigs. Journal of Morphology, 281(3), 348–364. https://doi.org/10.1002/jmor.21103

Rannikko, J., Žliobaitė, I., and Fortelius, M. (2017). Relative abundances and palaeoecology of four suid genera in the Turkana Basin, Kenya, during the late Miocene to Pleistocene. Palaeogeography, Palaeoclimatology, Palaeoecology, 487, 187–193. https://doi.org/10.1016/j.palaeo.2017.08.033

Scott, R. S., Teaford, M. F., and Ungar, P. S. (2012). Dental microwear texture and anthropoid diets. American Journal of Physical Anthropology, 147(4), 551–579. https://doi.org/10.1002/ajpa.22007

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

Souron, A., Merceron, G., Blondel, C., Brunetière, N., Colyn, M., Hofman-Kamińska, E., and Boisserie, J.-R. (2015). Three-dimensional dental microwear texture analysis and diet in extant Suidae (Mammalia: Cetartiodactyla). Mammalia, 79(3). https://doi.org/10.1515/mammalia-2014-0023

Ungar, P. S., Abella, E. F., Burgman, J. H. E., Lazagabaster, I. A., Scott, J. R., Delezene, L. K., Manthi, F. K., Plavcan, J. M., and Ward, C. V. (2020). Dental microwear and Pliocene paleocommunity ecology of bovids, primates, rodents, and suids at Kanapoi. Journal of Human Evolution, 140, 102315. https://doi.org/10.1016/j.jhevol.2017.03.005

Yang, D., Pisano, A., Kolasa, J., Jashashvili, T., Kibii, J., Gomez Cano, A. R., Viriot, L., Grine, F. E., and Souron, A. (2022). Why the long teeth? Morphometric analysis suggests different selective pressures on functional occlusal traits in Plio-Pleistocene African suids. Paleobiology, 48(4), 655–676. https://doi.org/10.1017/pab.2022.11