Coprolite samples were scanned using a Zeiss Xradia 510 Versa µCT microscope at the X-ray Microanalysis Laboratory (MizzoµX), University of Missouri, for non-destructive analyses. Optimal scanning parameters for the coprolites varied, with source voltage ranging between 80 and 140 kV, source power between 7 and 10 W, and exposure time between 1 and 5 s(s). All scans captured 1,601 projections through 360° of rotation and used a ×0.4 objective. Two types of Zeiss low-energy filters were used based on sample transmittance values, with 12 scans using the LE5 filter, and two using the LE2 filter. Voxel size ranged from 3.4618 to 30.12 µm. The scanning parameters for each sample are summarized in the Supplementary Table S2.

Visualization of the 3D data was achieved by importing serial tomogram stacks into Dragonfly software v. 2020.2 Build 941–v. 2022.2 for Windows, Object Research Systems (ORS, 2020) Inc., Montreal, Canada, 2018 (http://www.theobjects.com/dragonfly). Segmentation via labeled voxels was performed using upper and lower Otsu thresholding of greyscale values, in combination with other operations such as fill inner areas, Boolean calculations, and in certain cases manual segmentation throughout the image stacks to extract internal constituents and features of the coprolites (e.g., bones and pore spaces) from the matrix. Volume measurements and relative volumetric proportions of pore space and bone inclusions were calculated for each coprolite tomogram. Note for pores, the remaining porosity was measured, which excluded pores that were secondarily infilled. For more delicate features such as the tubular voids inferred to be moldic preservation of hair, a subsample of 300 slices was classified using the Trainable Weka Segmentation Fiji plugin (Arganda-Carreras et al., 2017) to differentiate these features from other volumetric elements, and subsequently imported into ORS Dragonfly for visualization and quantification in 3D. Feret diameters (i.e., caliper diameter, defined as the distance between the two parallel planes restricting the object perpendicular to that direction) for the bones and pores were measured within Dragonfly. The minimum feret diameter for bones was set at 0.14 mm and the minimum feret diameter for pores set at 0.196 mm. A multi-ROI (Region Of Interest) was extracted from the bone segmentation into group-labeled voxels to identify individual bone components. Select components were then extracted as meshes (.stl files) and smoothed for one iteration in Dragonfly before being exported to Meshmixer, 1995 [Autodesk Meshmixer 3.5, (RRID:SCR_015736)]. The 3D meshes were rendered to remove islands and unrelated material and applied with a shader. Each bone was examined individually for identification and to determine the general shape and signs of fragmentation.

A single specimen (RAM 17540) was prepared and sectioned for examination via optical and scanning electron microscopy (SEM). The coprolite was strengthened with PALEObond Penetrant Stabilizer, embedded in epoxy, and cut diagonally along a section predetermined from observation of the µCT data. One of the two-halves was polished using a Buehler EcoMet250, while the other was left unpolished. Both halves were then analyzed using a Zeiss Sigma 500 VP SEM equipped with a high-definition 5-segment backscattered electron detector at the MizzoµX lab and imaged using the Bruker ATLAS workflow for large-area SEM mosaics. Elemental mapping was conducted on specific regions of interest using dual Bruker XFlash energy dispersive X-ray spectrometers (EDS). All SEM analyses were conducted at their optimal operating conditions of 20 keV beam accelerating voltage, 40 nA beam current, 60 µm aperture for imaging (120 µm aperture for EDS elemental mapping), chamber pressure at 20 Pa, and a working distance of 16.5 mm.

Analyses were conducted and figures produced using software package R (R core Team, 2017; Version 4.1.0) and associated R packages boot, diptest, ggplot2, ggthemes, ggpubr and mclust (Davison and Hinkley, 1997; Scrucca et al., 2016; Wickham, 2016; Arnold, 2021; Canty and Ripley, 2021; Maechler, 2021). Raw data is provided in Supplementary Tables S3–S6 along with R scripts (Supplementary Scripts S1). Using the volumetric data in Supplementary Table S4, two bar graphs were produced in Microsoft Excel in order to assess the respective contributions of matrix, bones, and pores to total coprolite volume (mm³) and the relative proportions of these components for each sample.

The coprolites were divided into two different size classes previously defined by Lofgren et al. (2017) based on their diameter, with larger coprolites ranging between 16 and 29 mm and smaller coprolites between 4 and 15 mm. Within our subset we had seven larger class coprolites (Class I; RAM 17370, 17405, 17517, 17540, 17546, 17547, and RAM 18171) and five smaller class coprolites (Class II; RAM 17557, 31209, 31211, 31212, and 31214). Size measurements (i.e., mass, length, and width) are summarized in Table 1. Coprolites exhibited three different colors, including yellow gray (5Y 7/2), grayish yellow (5Y 8/4), or yellowish gray (5Y 8/1), as defined in the Munsell Color Chart (2010). There was no obvious color difference between the classes of coprolites, though all Class II coprolites are yellowish gray, 5Y 8/1.

Most of the examined Class I coprolites (5/7) have a smooth, relatively homogenous surface and tend to share a similar cylinder-like shape, circular in cross-section though occasionally flattened on one side (i.e., RAM 17517) (Figure 1). Notable exceptions include RAM 17546 (Figure 1F) and RAM 17370 (Figure 1G), which both display a rough, topographically complex surface, while simultaneously showing signs of constrictions. The examined Class II coprolites also have homogenous, smooth surfaces but are less uniform in shape. As noted by Lofgren et al. (2017), the smaller forms exhibit blunt or tapered ends, and occasionally both. Though few, coprolites within both size classes I and II show small black bone inclusions on their surface visible to the naked eye. In-depth descriptions of each specimen can be found in the Supplementary Text S1.

The relationships between coprolite volumetric measurements and relative proportion of inclusions (i.e., matrix, pores, bones) are compared for individual coprolite samples (Figures 11A, B, respectively). The proportion of pores within the matrix was consistently greater when compared to that of bone inclusions (Figure 11B). The lowest percentage of pores in any sample was in RAM 17370, with 3.89%, and the highest percentage was 14.32% in RAM 31211. Bone inclusions, on the other hand range from 0.09% in RAM 17546% to 11.64% in RAM 31211.

All 12 coprolites (Class I, n = 7; Class II, n = 5) were included in statistical analyses to test for differences between the two classes of coprolites. The distribution of coprolite widths based on Lofgren et al.’s (2017) data is best modelled as two Gaussian distributions with unequal variance values. Component 1, the small size class, has a median width of 10.6 mm and comprises 79% of the data. Component 2, the large size class, has a median width of 18.4 mm and comprises 21% of the data. We interpret the coprolite specimens analyzed in this study to cleanly fall into one of the two size categories (n_small = 5, n_large = 7) (Supplementary Figure S1).

Coprolite length, width, mass, proportion of pore volume, and proportion of bone volume values for coprolites cannot be shown to not be normally distributed (Supplementary Table S7). The Shapiro tests results for bone volume, maximum feret diameter, mean feret diameter, and minimum feret diameter suggest that these values are not normally distributed, however, the Dip Test for Unimodality results cannot refute unimodality (Supplementary Table S7), therefore the Wilcoxon test is appropriate for these comparisons.

The Wilcoxon Rank-Sum test revealed significant differences in length (p = 0.003), width (p = 0.003), and mass (p = 0.003) between Class I and Class II coprolites (Figure 11C). We bootstraped 95% confidence intervals for the median proportion of pore volume between Class I (0.054 mm³) and Class II (0.082 mm³) coprolites and found no significant difference. Conversely, bootstrapping for the median proportion of skeletal material between Class I and Class II suggests that there is a significant difference in the median.

Differences in median bone size between the two coprolite classes were tested with a Wilcoxon Rank-Sum test, comparing bone volume, maximum feret diameter, mean feret diameter, and minimum feret diameter (Figures 12A–D; Supplementary Table S7). In total 437 bone values were used in the analysis (Class I, n = 172; Class II, n = 265). There was no significant difference (p = 0.176) between the median bone volumes of Class I (0.1 mm³) and Class II (0.09 mm³). The median value of the maximum feret diameters of bones for Class I (1.58 mm) was significantly larger (p = 0.002) than Class II (1.250 mm). Similarly, there was a significant difference (p < 0.001) between the median value of mean feret diameters of bones of Class I (1.015 mm) and Class II (0.870 mm). The same result can be seen with the median value of minimum feret diameters of bones, with Class I (0.495 mm) significantly larger (p=0.004) than Class II (0.460 mm).

The PSMP coprolites are well-preserved, excluding extensive surface abrasion, and possess minor diagenetic alteration or secondary mineralization. The limited evidence of adverse taphonomic processes within the subsample conforms to deposition in relatively dry and stable paleoenvironmental conditions. In addition to their in-tact or complete nature, surface features of the coprolites indicate that specimens may have been exposed at the surface for a prolonged period pre-burial due to high degrees of abrasion, likely from wind erosion, and the presence of desiccation cracks. Distortion exhibited by flattened ventral surfaces of the coprolites also suggests these rested relatively undisturbed soon after defecation. Desiccation cracks are relatively sparse and are most conspicuous on the larger size Class I specimens. Post-burial diagenesis is similarly limited with minimal evidence of compaction and only minor influence from percolating fluids. Thin botryoidal silica crusts on the surface of internal pores indicate incursion of silica-rich fluids through the porous matrix. Silica is likely derived from adjacent ashfall lapilli tuffs and the coarse fraction (including volcanic glass, quartz, plagioclase, potassium feldspar, and granitic fragments) of the silty mudstone which characterizes the Pipestone Springs strata (Hanneman et al., 2022). Silica infill observed in thin section and SEM data is notably thin, coating pores to a thickness of between ∼8 and 354 µm. The lack of homogeneous silica infill or secondary remobilization of phosphate suggests that between phases of burial and exposure, conditions were predominantly devoid of moisture.

The porous nature of the PSMP coprolites is a key morphological attribute that has been overlooked in prior studies. Pores compose the largest percentage of internal structural components after the matrix (Figures 11A, B). Moreover, this represents a minimum estimate of the true porosity, as several pores have been secondarily infilled with silica. As seen in Figure 6, the irregular pores (excluding hair molds) dramatically vary in size from 0.196 to 50.562 mm and are distributed relatively evenly throughout the matrix when not occupied by skeletal remains. Though pores are known to frequently occur within the matrix of coprolites (Horwitz and Goldberg, 1989; Herbig, 1993), their origins remain uncertain, owing to several different processes associated with their formation. One explanation for their formation is decay of some degradable materials within the feces, including smaller bone fragments, soft tissue (muscle, tendons, ligaments, etc.), or insect parts that might not have been digested, and subsequently decayed to form these pores. Given the relatively even distribution of pores throughout the matrix, this seems unlikely. An alternative explanation is that the pores were already present at defecation (including on the surface) caused by trapped gases within the feces—a product of bacterial respiration in the intestine (Herbig, 1993; Magondu, 2021). Gases produced during digestion are typical and varied (Levitt and Bond, 1970); however, reporting the preservation of these gaseous vesicles and their relative abundance within a coprolite is often neglected. As excess gas can relate to bacterial overgrowth within the gut, which may have deleterious consequences for the individual or indicate an intestinal disease (Suarez et al., 2000; Pimentel et al., 2006; Kalantar-Zadeh et al., 2019), the prevalence of such gaseous vesicles may be useful in understanding the gut biome and physiological attributes of coprolite producers. A third explanation for the pores relates to desiccation; as the sample loses moisture, smaller pores (possibly those formed by gases) are enlarged in conjunction with the reduction in overall coprolite volume. As few actualistic studies exist investigating the complete taphonomic processes (from defecation to burial) of modern feces in natural environments, much of this remains speculative (Northwood, 2005; though see Brachaniec et al., 2022).

Another constituent of the porous volumes within the coprolites are the moldic remains of keratinous material, specifically hair. Whilst targeted higher resolution scanning was only performed on one specimen (RAM 17540; Figure 7), other coprolites from this sample subset exhibit similar structures. These small tube-like pores generally fall within the shaft shape and size range of hair, with distinct circular cross-sections. Because these pores are small, isolated, and many terminate without contacting the surface of the coprolite, these tubules can readily be distinguished from desiccation cracks, insect burrows or fungal hyphae. Hair molds can also be observed on the surface of select PSMP coprolites (see RAM 17540, Figure 2C). However, not all small pores exhibit this tube-like form and hence hairs cannot account for all the small topographic depressions observed. Due to keratinous material possessing highly resistant molecules that few extant taxa are able to digest (Leprince et al., 1980), hair is relatively resistant to digestive and early lithification processes (Taru and Backwell, 2013). Though the hair eventually decayed, it was preserved long enough to form molds of the shafts within the interior of the coprolite. This pathway conforms with previous studies where hair tubules have been found as casts and impressions both on the surface and interior of coprolites, often preserving exceptional details of the cuticular surface (Crooper et al., 1997; Taru and Backwell, 2013; Bajdek et al., 2016). Similar to the irregular pores, these molds display a siliceous coating caused by secondary infilling during diagenesis.

Qualitative and quantitative analyses of the two coprolite size classes observed reveal notable differences with respect to the morphology of the inclusions, which may inform about feeding habits and physiological differences of their respective producers. Results of our analyses reveal a discernable statistical difference in the relative proportions of bone inclusions to total coprolite volume between Classes I and II. Notably, the proportion of bone volume was greater in the smaller Class II coprolites by comparison to the larger Class I coprolites (Figure 12A). However, there was no significant difference in the extracted bone volumes between the two classes indicating that, despite the relative size of the smaller Class II coprolites, the bone constituent was comparable to that observed in larger Class I coprolites.

In the case of Class I coprolites, bones tended to be larger overall with respect to their feret diameters (Figures 12B–D). Bone inclusions within the Class I coprolites also showed more degradation and evidence of intense fragmentation from mastication, such that few bones could be reliably identified. This implies that the Class I producers were capable of consuming larger prey compared to the Class II producers. Bones extracted from the Class I coprolites, including Bone 1 of RAM 17547 (Figure 9K) and Bone 1 of RAM 17517 (Figure 9L), lacked an identifiable shape but revealed internal features such as cancellous tissue associated with larger bones (e.g., pelvic bones, vertebrae, etc.). The ambiguous shapes, incomplete condition of the bones, and preponderance of homogeneous phosphatic matrix contained within Class I coprolites, aligns with specific feeding habits and digestive processes. Principally, the evidence presented herein supports a durophagous carnivorous producer with a bone crushing habit, which is comparable to previous findings in relation to late Miocene carnivoran coprolites from California (Wang et al., 2018). The producers of these latter coprolites are inferred to have been borophagine canids that filled a unique ecological niche in North America, comparable to extant hyenas, until their disappearance approximately 2 million years ago (Lofgren et al., 2017; for further discussion see section 2.4.2 below). Like the California specimens, the PSMP coprolites also exhibit a powdered homogenous matrix of bone residues (Figures 3A, B) indicative of a producer with a highly acidic gastrointestinal system (Wang et al., 2018). Examples of corrosion are visible in Bone 1 RAM 17547 (Figure 9K) where internal thin trabecular material is revealed. Bone dissolution could also account for the diffuse boundaries exhibited by several bone inclusions during the segmentation process.

Class II coprolites overall have a statistically larger proportion of bones compared to total coprolite volume than Class I, though there is notable variation within the sampled dataset (Figure 11D). Such variation is also evident in the condition of extracted inclusions. Most identifiable bones in the PSMP material are associated with specimens in Class II, though this is slightly skewed as most of these bones were also recovered from a single specimen, RAM 31212 (Figure 8J). This coprolite has the second largest amount of bone inclusions of those examined here (Supplementary Table S4, 11.28%), while RAM 31211 has the highest overall proportion (Supplementary Table S4, 11.64%). Three of the Class II coprolites (RAM 31211, 31212, and 17557) are more densely packed with larger bone inclusions suggesting that the producers were capable of consuming the bones whole, with limited mastication of prey items compared to the producers of the Class I coprolites. In this case, producers of these Class II coprolites were able to extract nutrients with minimal bone-crushing required to consume the prey item. Most likely, this is attributed to the smaller size of the prey item itself for which durophagous mastication was not necessary (Pokines and Tersigni-Tarrant, 2012). On the other hand, the Class II coprolites also preserve smaller bones compared to Class I coprolites, as seen by the significantly smaller median values in feret diameters in Class II compared to Class I coprolites (Figures 12B–D). These smaller bones show evidence of intense fragmentation (RAM 31209, Figure 8I and RAM 31214, Figure 8L) which lends support to the capacity for bone-crushing when required for larger prey items, or once the higher-return nutrient-rich organs had been eaten (Pokines and Tersigni-Tarrant, 2012). More direct evidence for a bone-crushing habit is displayed in Bone 1 of RAM 31209 (Figure 10A) which features a clear indent on the flat surface of the bone where the bone has been partially crushed, as well as tooth marks in Bone 6 of RAM 17517 (Figure 9E). There is also some tentative evidence to suggest gnawing or bone cracking in Bone 12 of RAM 31212 (Figure 9D) exhibited by the somewhat rounded edges on the proximal base plate. It is worth noting that the degree to which stomach acids have caused shrinkage or subsequent breakage of the ingested bone material in the Class II coprolites is difficult to discern and could potentially further account for some reduction in bone fragment size (Fernández-Jalvo et al., 2014). However, the clear boundaries visible between the matrix and the bone material via the CT tomogram slices might attest to the relative resistance of these bone fragments to acid dissolution.

In a previous study employing comparable µCT methods, evidence of an osteophagous diet was inferred from two carnivoran coprolites of discrete sizes from the late Miocene, Spain (Abella et al., 2022). Evidence of osteophagy was based on abundant skeletal inclusions including fragments that appeared to belong to larger bones while others display depressions resembling partial tooth marks. Similar to the Class I PSMP coprolites, the larger specimen of the Spanish coprolites (specimen BAT-3′9.178) preserves irregular bone fragments not identifiable to a specific anatomical bone but does show evidence of digestive corrosion (Abella et al., 2022). The smaller coprolite (BAT-3′10.153), which is comparable in length to the PSMP Class I coprolites exhibits more complete skeletal elements and has a greater proportion of bone inclusions relative to the larger coprolite at the same locality (Abella et al., 2022; Figures 4, 6). Several medium-sized carnivores were suggested as the producer of the smaller coprolite though the most probable was Protictitherium crassum, a member of Hyaenidae.

These findings conform with the borophagine canids interpretation of Lofgren et al. (2017), to the extent that 1) some of the predators consumed whole bones; 2) there was a degree of bone fracturing that occurred, especially in the smaller coprolites; and 3) evidence of digestive corrosion was present.

In previous work, Lofgren et al. (2017) hypothesize that the relationship between the diameter of a producer’s feces and its body mass, in conjunction with the relative abundance of the respective carnivore species in the PSMP could be applied to determine the likelihood of the producer itself. Several different mammalian predators have been recovered from the PSMP site, belonging to eight different species (Lofgren et al., 2017) including Hyaenodon microdon (Mellett, 1977), Hyaenodon crucians (Leidy, 1853), H. gregarius (Cope, 1873), Mustelavus priscus (Clark, 1936, in Scott and Jepsen, 1936), B. dodgei (Scott, 1898), Parictis montanus (Clark and Guensburg, 1972), Daphoenictis tedfordi (Hunt, 1974), and Palaeogale sectoria (Gervais, 1848). After estimating the overall body mass of the predators and their mean prey mass (see Table 2), Lofgren et al. (2017) deduced that the range in diameters of larger coprolites may have represented multiple species, concluding that B. dodgei was most likely due to the abundance of dentigerous elements in the deposit (77% of the larger species). Similarly, the smaller coprolites could have been produced by P. sectoria, P. montanus, Hyaenodon crucians, H. microdon, and H. gregarius (Lofgren et al., 2017). Although the body mass estimates are congruent with Hy. crucians as a likely producer, the bone alteration observed in the smaller coprolites is more consistent with extant canids and hence Hes. gregarius was inferred as the main producer of the smaller coprolites (Lofgren et al., 2017).

While the coprolite interior volumes and bone inclusions observed herein did not reveal any unambiguous details as to which taxon might have excreted the coprolites, they did show that at least the Class I producers had aggressive gastrointestinal environments that could digest bone material and cartilage. This is presumably comparable to the bone-crushing habits of modern spotted hyaenas (Crocuta), which are also known to consume (and occasionally regurgitate) indigestible materials such as hair (Kruuk, 1972; Di Silvestre et al., 2000). However, as noted by Wang et al. (2018) in their assessment of the California carnivoran coprolites, there is a paucity of literature investigating gastric pH across broader Carnivora, and hence it is highly speculative to make further inferences as to the identity of the producer based on broad assumptions of a bone-dissolving gastrointestinal system alone.

The value of using µCT as a non-destructive method in extracting information on the internal inclusions of coprolite samples has been well-demonstrated (Qvarnström et al., 2017; 2019). However, specific advantages, limitations, and implicit biases encountered herein are worthy of discussion. We note that while X-ray microscopy can certainly add value to the study of coprolites, results depend on the resolution of the CT scan and the nature of the specimen. In some cases, using μCT alone may not be sufficient to fully describe the internal constituents of bromalites for a particular investigation, and it is recommended to use it in conjunction with other techniques for a more comprehensive analysis. The difficulty of identifying bone inclusions within the PSMP coprolites using µCT to a level beyond generic bone type was not a limitation of µCT itself, but rather a consequence of how much the bones were masticated and digested. Similar results were documented by Abella et al. (2022), wherein they solely used µCT, but found many of the bones were not identifiable to a certain anatomical bone or taxon, and instead the authors relied on describing the general shape and features. Studies comparing the results of mechanical extraction and µCT analysis have encountered similar difficulties. For example, investigations of neolithic midden deposits from Swifterbant, Netherlands, used paired µCT and physical extraction methods to examine phytoliths and bone fragments from finely layered and coprolite-hosting deposits (Huisman et al., 2014). Results showed that many bone features were visible using both methods, though comparably more recognizable bone elements were identified in the sieved material (n = 32) compared to µCT (n = 7 with confidence, 5 unable to be attributed to species level) (Huisman et al., 2014). The benefit of using µCT in the case of the Swifterbant material, was the ability to provide microstratigraphic context as well as recognize articulated remains and material too small to appear in the sieved fraction (Huisman et al., 2014). A noteworthy finding comparable to observations made in the material herein was that identification of the skeletal components was not dependent on how the bones were extracted, but rather on how completely the bones were preserved (Huisman et al., 2014). Bones with few distinguishable features as a consequence of mastication and digestive processes are going to appear almost identical whether observed virtually or as physically extracted material. In the case of the present study, surface renders of select bones were blurred by ill-defined edges and significant degradation due to the digestive processes which reduced the phase contrast between bone inclusions and the surrounding phosphatic matrix. This further emphasizes that potential limitations on µCT are associated with the degree of preservation of the inclusions and not solely the imaging technique.

The primary advantage of using µCT in this study was the ability to reveal volumes, including pores and moldic remains of fossil hair, that would not otherwise be attainable via traditional disaggregation methods. These structures were readily visible in tomographic slices, in both standard and targeted higher resolution scans, and could be extracted to display their morphology as well as their distribution in 3D space (Figure 7). Because hair tubules represent external molds, mechanical or chemical extraction of inclusions would impede the detection of such features at all. Even thin sectioning only provides a very shallow 3D view of these fossil hair follicles and may preclude unambiguous identification of the elongate molds from other potential explanations (i.e., burrows, desiccation cracks). Hair imprints in phosphate aggregates from a Palaeolithic cave site in Western Slovenia have similarly been revealed by µCT methods (Turk et al., 2015). Though the PSMP hair molds could not be attributed to any specific taxon, their prevalence throughout the coprolite may provide insight into the higher taxonomic affiliation to prey items (i.e., mammalian), or alternatively could allude to the affinity of the consumer (e.g., if they ingested their own hair while grooming). Based on analysis of modern vertebrate carnivore scat, the digestibility of hair varies between predator and prey item, however, under most circumstances, it is significantly less digestible compared to bone (Ackerman et al., 1984; Baker et al., 1993; Gamberg and Atkinson, 2016). The presence of hair in feces also can persist for several days after initial consumption depending on the rate of passage through the intestine (Helm, 1984; Kelly and Garton, 1997; Pires et al., 2011). Consequently, we hypothesize that coprolites have a higher likelihood of preserving hair remains when compared to body fossils, and introduce taphonomic bias toward bromalites as a source of information on hair structures and morphology. This supports previous studies that demonstrate the potential of bromalites to facilitate exceptional preservation of soft tissues (Chin et al., 2003; Qvarnstrom et al., 2017; Gordon et al., 2020).

Internal porosity and associated characteristics of the pores were overlooked in previous examination of this material (Lofgren et al., 2017) and are easily removed via consumptive sampling methods. Though it is difficult to ascertain whether such original features were considered or overlooked in other coprolite studies (Wang et al., 2018; Romaniuk et al., 2020; Abella et al., 2022), this raises concern for a potential reporting bias in the visualization of segmented volume renders in isolation to tomographic slice data. Ideally, pairing cross-sectional tomographic data directly with volumetric reconstructions (e.g., Turk et al., 2015; figures 4, 5; Shillito et al., 2020; figure 3) promotes transparency in documenting coprolite internal composition. Moreover, tomographic slices should be made available upon publication (whether via the journal or repository institution) to facilitate reproducibility of the analysis. Porosity of coprolites is likely an important primary and taphonomic feature. The presence of pores may have broader implications for gut function and health, hence understanding pore morphology, abundance, and distribution is relevant to revealing both palaeobiological data of the producer and the diagenetic history of the overall coprolite specimen.