Supplementary Information for

Quantitative assessment of tarsal morphology illuminates locomotor behaviour in

Paleocene mammals following the end-Cretaceous mass extinction

Sarah L. Shelleya,b,1, Stephen L. Brusattea, Thomas E. Williamsonc

aSchool of GeoSciences, Grant Institute, University of Edinburgh, James Hutton Road,

King's Buildings, Edinburgh, EH9 3FE, United Kingdom. bSection of Mammals, Carnegie Museum of Natural History, 5800 Baum Blvd, Pittsburgh,

Pennsylvania, 15206, United States of America (previous address). cNew Mexico Museum of Natural History and Science, 1801 Mountain Rd NW,

Albuquerque, New Mexico, 87104, United States of America.

1To whom correspondence should be addressed. Email: [email protected] (SLS)

This PDF file includes:

Supplementary text Figs. S1 to S24 Tables S1 to S16 References for SI

Other supplementary materials for this manuscript include the following:

Datasets S1 to S5

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Supplementary Information Text

Methods Datasets

Tarsal data. Measurements. 29 tarsal measurements (Fig. S1) were taken from the astragalus and calcaneum for a sample of extant and fossil mammals (Dataset S1). Note we refer to these measurements as tarsal measurements for ease of reading but recognise that they are from only two tarsal bones. Measurements were taken with the tarsals orientated as if the taxon being measured were plantigrade to maintain consistency in terminology. The following list of measurements is based on personal observation of tarsal osteology and compiled to describe the morphological and functional variation of the bones thoroughly, whilst also remaining measurable for as many taxa as possible. Note that there are some zero values in our measurements: zero values indicate the absence or loss of a given feature in the view measured which in itself is a character. In some instances, extinct taxon measurements are composited. This was done with care and only where the specimens closely approximate each other in size (often times the specimens are found in close association but cannot be determined to be from the same individual or have been accessioned separately). Specimen numbers are listed in Dataset S1.

List of measurements used in this study corresponding to those illustrated in Fig. S1b:

17 measurements were taken from the astragalus:

A1 maximum anteroposterior length of the astragalus A2 maximum anteroposterior length of the astragalar body A3 maximum anteroposterior length of the medial trochlear keel (highest edge) A4 maximum anteroposterior length of the lateral trochlear keel (highest edge) A5 maximum mediolateral width of astragalar body A6 maximum width or length of posteromedial expansion

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A7 maximum width of fibial facet in dorsal view A8 maximum mediolateral width of trochlea at anterior border A9 maximum mediolateral width of astragalar head A10 maximum length of ectal facet A11 maximum anteroposterior length of sustentacular facet A12 maximum mediolateral width of sustentacular facet A13 maximum dorsoplantar depth of astragalar body A14 maximum dorsoplantar depth of astragalar head A15 maximum dorsoplantar height of lateral trochlear keel A16 maximum dorsoplantar height of medial trochlear keel A17 maximum anteroposterior length between anterior medial rim of trochlear and anterior margin of astragalar head

12 measurements were taken from the calcaneum:

C1 maximum anteroposterior length of the calcaneum C2 maximum anteroposterior length of the calcaneal tuber C3 maximum mediolateral width of the posterior end of the calcaneum C4 maximum mediolateral width of the calcaneal body C5 minimum mediolateral width of the calcaneal tuber C6 maximum anteroposterior length of the sustentacular facet C7 maximum mediolateral width of the sustentacular facet C8 maximum length of the ectal facet C9 maximum width of the ectal facet C10 maximum dorsoplantar depth of the calcaneal tuber C11 maximum dorsoplantar depth of the cuboid facet C12 maximum mediolateral width of the cuboid facet

Taxon sample. Extant taxa. We sampled a total of 85 extant therian taxa. Given the improbability of measuring tarsals for every extant mammal species, we aimed to build a proxy dataset by

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selecting taxa that were relatively straightforward to assign to a given locomotor group, covered all extant orders that locomote primarily on land, and covered a broad range of locomotor behaviours that occur on land. This number includes representatives for every pertinent placental order with the exception of Chiroptera, Dermoptera, Pholidota and Sirenia. We did not include extant representatives for Chiroptera given they do not use their hindlimbs for sustained locomotion on land (although we recognise the unusual exception of mystacinid bats). We also chose to not include dermopterans in this study given their extreme morphologies and outlier position in morphospace associated with gliding behaviour (e.g. see [1] but also [2]) and the fact we were not able to obtain enough measurements for ostensible Paleocene dermopterans to include in our dataset (e.g. Mixodectes) [3]. We did not include Pholidota given they possess highly unusual tarsal bones (i.e. extreme reduction of the sustentacular facet) making meaningful inclusion into this dataset difficult. We also excluded Sirenia given that they lack tarsal bones. We note that 85 out of 6490 extant eutherian mammals species or 72 out of 1311 genera [4] is sampling slightly over 1% of extant mammal species and 5.5% of genera. This value is diminutive, however, consider that how species are defined does likely not directly correlate with tarsal diversity. Furthermore, when breaking down the taxonomic composition of extant species, 2552 of extant species are rodents (many of which are recognised by genotypic rather than phenotypic features) and we have sampled across a range of rodents exhibiting an exemplary range of morphologies and locomotor behaviours; 1386 species are bats which are not pertinent to this current study; 551 are artiodactyls which although relevant are relatively constrained in their tarsal morphology and locomotor behaviours (with the exception of extant cetaceans which lack tarsals and were therefore not included in our dataset). This is the same rationale commonly used in phylogenetic analyses using morphological data; for example, the Mammal Tree of Life project used 46 taxa to represent the diversity of extant mammals [5]. Furthermore, we utilise discriminant analyses to test the validity of our data sample at predicting locomotor behaviour—the results of this analysis show that tarsals can be used to predict locomotor behaviour accurately in our dataset, and thus this dataset is useful for our purposes.

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Paleocene taxa. We were able to measure a total of 40 Paleocene taxa. A core aim of this project was to incorporate as many Paleocene mammals as possible. These mostly belonged to so-called ‘archaic’ groups but also included species considered to be members (or stem members) of extant orders. In our sample we have chosen to include species of Eocene age known for tarsal bones which have a generic temporal range that extends back into the Paleocene. Taxon age information is provided in Dataset S1.

Cretaceous taxa. We sampled a total of five Cretaceous species. We chose to not extend our sample outside of Cladotheria as taking homologous measurements would have become difficult. To this end, our sample includes cladotherians known from three- dimensionally preserved tarsal specimens for which we were able to obtain the necessary measurements. Notable exceptions include Zalambdalestes [6] and Asioryctes which are known for tarsal bones but for which we could not obtain enough measurements to include in this study.

Regression data. Five measurements were taken for a sample of 79 extant therian taxa and four extinct Paleocene taxa (Dataset S5). Our fossil sample was limited to specimens that allowed for body weight estimates to be calculated using associated postcranial material (see below)

List of measurements used for regression analyses:

Maximum proximodistal length of the humerus Minimum midshaft circumference of the humerus Maximum mediolateral width of the humerus Maximum proximodistal length of the femur Minimum midshaft circumference of the femur

Institutional abbreviations AMNH, American Museum of Natural History, New York, New York, USA CM, Carnegie Museum of Natural History, Pittsburgh, Pennsylvania, USA

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CNHM, Chicago Natural History Museum, Chicago, Illinois, USA DGM, Divisão Nacional de Producão Mineral, Rio de Janeiro, Brazil IMM, Inner Mongolian Museum, Hohhot, Inner Mongolia, China IPPAS, Institute of Palaeozoology, Polish Academy of Sciences, Warsaw, Poland IRSNB, Royal Belgian Institute of Natural Sciences, Brussels, Belgium. ISEZ, Institute of Systematics and Evolution of Animals, Polish Academy of Sciences, Kraków, Poland IVPP, Institute of Vertebrate Paleontology and Paleoanthropology, Beijing, China; MACN, Museo Argentino de Ciencias Naturales, Buenos Aires, Argentina MHNC, Museo de Historia Natural “Alcide d’Orbigny”, Cochabamba, Bolivia; MNHN, Muséum national d’Histoire naturelle, Paris, France NMMNH, New Mexico Museum of Natural History and Science, Albuquerque, New Mexico, USA NMS, National Museum of Scotland, Edinburgh, UK PSS-MAE, Paleontological and Stratigraphy Branch (Geological Institute), Mongolian Academy of Sciences – American Museum of Natural History Expeditions, Ulaanbaatar, Mongolia UCMP, Museum of Paleontology, University of California, Berkeley, California, USA; UF, Vertebrate Paleontology collection, Florida Museum of Natural History, University of Florida, Gainesville, FL, USA UM, University of Minnesota, Bell Museum of Natural History, Minneapolis, Minnesota, USA UNLSNC, Universidade Nova de Lisboa, Silveirinha New Collection, Lisbon, Portugal USGS, United States Geological Survey now housed at the USNM USNM, United States National Museum of Natural History, Smithsonian Institution, Washington, D.C., USA VPL, Vertebrate Paleontology Laboratory, University of Jammu, Jammu Tawi, India.

Locomotor categories Discrete categorisations of locomotor behaviour are inherently difficult to define and allocate with taxa often exhibiting multiple behaviours that are best defined by means of a

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multivariate continuum. For this study, species were assigned to the most appropriate locomotor category for the purpose of broadly defining areas of locomotor morphospace and predicting the locomotor behaviours of fossil taxa using discriminant analysis. Locomotor allocations were based on the literature, consideration of other closely related species and our discretion based on observation of their behaviour (Dataset S1). In numerous cases there are gradations between categories but by using multivariate analyses we aim to capture the nuances of tarsal morphology and how they locomotor behaviour.

Locomotor definitions: Arboreal – adept at climbing and moving about on supports with steeply sloping, vertical or inverted surfaces and spends most of the time in trees (or off-ground) for feeding, shelter, rest, reproduction and socializing. May come down to ground but these occurrences are infrequent. Cursorial – adept at moving over ground at speed and/or with endurance over long distances. Scansorial – adept at climbing and moving about on supports with steeply sloping, vertical or inverted surfaces for feeding, shelter, rest, reproduction and socializing but will also routinely partake in some of these activities on the ground. Semi-aquatic – adept at swimming and routinely enters bodies of water for feeding, refuge, dispersal and socializing. Generally capable of diving and swimming underwater. Semi-fossorial – adept at excavating substrate to build shelters or for accessing food resources but does not possess an exclusively subterranean lifestyle. Terrestrial – spends majority of time on the ground for feeding, shelter, rest, reproduction and socializing but may be able to climb, run, swim, dig on occasion.

Multivariate Analyses The raw data were assessed for multivariate normality using a Mardia test which showed the raw dataset does not meet the requirements of multivariate normality (skewness = 12343.806 [p = 0], kurtosis = 45.871 [p = 0]). Univariate tests for normality (Shapiro-Wilk test) and visualisation using Quantile-Quantile (Q-Q) plots for each measurement show that no raw measurements are normally distributed in our sample and highlight a substantial

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number of outliers (Fig. S2, Table S1). To address this, the data were first Box-Cox transformed (transformation conducted on all data plus one to eliminate zero values). We use a Box-Cox transformation for all transformations in this study because the lambda value is determined by the distribution of data being transformed rather than a logarithmic transformation where the lambda value is assumed to be 0. This results in a ‘better’ transformation although we note that it does not always bring our data into normality, but this was not a requisite of the transformation for the subsequent analyses in this study. The data were then standardised using a Z-transformation to minimize the effects of tarsal size on the dataset, whereby:

푥 − 퐺푀 푧 = 푖 푖 휎 [1]

The Z-transformation (zi) is calculated for each species (not the measurement for all species): the geometric mean (GM) of all measurements for each species is subtracted from each measurement for that species (푥i) and then divided by the standard deviation (σ) of all measurements for that species. The Z-transformation was conducted on the Box-Cox data plus one to eliminate zero values produced during Box-Cox transformation. We have used the geometric mean rather than the arithmetic mean as the geometric mean better accounts for range in values and does not give overwhelming weight to higher values.

A Mardia test on the transformed and standardised dataset showed it still did not meet the requirements for multivariate normality despite transformation (skewness = 5851.268 [p = 2.08 x 10-39], kurtosis = 6.12 [p = 9.08 x 10-10]). Univariate tests for normality and visualisation using Quantile-Quantile (Q-Q) plots for each measurement show 6 out of the 29 measurements are not normally distributed (Fig. S3, Table S1). Q-Q plots show that although the data are more linearly distributed a number of outliers remain. It is worth noting here that we also experimented using several other transformations including the standard logarithm, dividing by the square root and dividing values by their mean absolute deviation. However, no transformation was as good as the Box-Cox at rendering linearity. At this point we could have chosen to remove the outliers and non-normal measurements;

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however, all the measurements and outliers record important anatomical information that is useful to include. This raises the question of how important multivariate normality is for Principal Components Analysis (PCA) and Discriminants Analysis (DA)? We are using the PCA as a means of reducing the dimensionality of the data and projecting it into linear subspaces which best explain the data for the purpose of visualisation and exploration of tarsal morphospace. The dimension reduction capability of a PCA on non-normal data is still greater than other non-parametric methods. For inferential purposes multivariate normality is usually assumed, however, PCA as a descriptive tool needs no distributional assumptions [7–9]. It is worth recognising that the data do not meet the requirements of multivariate normality and although it is not an issue to restrict our data to linear combinations of the raw variables there be some suppression of outlier information, but suppression is better than complete omission in this case. Future work using robust PCA on anatomical measurement data which spans a range of magnitude may prove fruitful if wanting to use the PCA beyond visualisation. Non-normality is not an issue for PCA and DA as visualisation techniques; however, it requires further consideration when using DA as a classification method. Discriminant Analysis differs from PCA in that the data have to be categorised a priori, the DA then seeks to ordinate the data of known categorisation into reduced dimensions which best separate those groups. Data of unknown categorisation can then be ordinated into those reduced dimensions and classifications predicted. This supervision of outcomes is fundamentally different to a PCA in which there are no a priori assumptions of the data. Linear Discriminant Analysis requires homogeneity of the group variances. We tested for this using a Fligner-Killeen test – a non-parametric version of the Box-M test given our data are not normal. Our tarsal dataset does not possess equal group variances (p = 2.2 x 10-16). Therefore, it is more appropriate to explore an alternative DA method. Quadratic Discriminant Analysis (QDA) does not require equal group variances; however, it performs better when the group sample size exceeds the number of variables. This is not the case for our tarsal dataset, so we chose to use a Regularised Discriminant Analysis (RDA). RDA is a flexible alternative to LDA and QDA. It is also extremely effective when you have many variables that are likely to be highly linearly correlated (multicollinearity) as may occur with anatomical measurements.

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RDA regularises the data, it achieves this by stabilising the variance and reducing the bias of the discriminant functions. Both sample size and data dimensions inform and regularise the discriminant analysis optimisation process which involves two parameters: lambda and gamma. Lambda is a complexity parameter (0 ≤ λ ≤ 1) that controls the shrinkage of the individual group covariance matrix estimates towards the pooled total estimate of the dataset [10,11]. For LDA, λ = 1 with a high control over shrinkage whereas for a QDA λ = 0. Lambda values of less than 1 can improve the performance of the analysis when the group covariance matrices are of different sizes. Gamma is a regularisation parameter (0 ≤ γ ≤ 1) which controls shrinkage of the eigenvalues towards equality by decreasing the effects of larger eigenvalues and increasing the effect of smaller ones [10,11]. Both LDA and QDA optimise gamma at 0. Setting gamma to 1 introduces two other methods (conditional independent variables [λ = 0, γ = 1] and equalised Euclidean distance variables [λ = 1, γ = 1]). For the RDA, we are interested in optimising the lambda and gamma variables to best suit our specific dataset. This is achieved using a Nelder- Mead-(Simplex-)algorithm – a widely used heuristic search algorithm for finding optimised parameters. Simulated annealing was applied using the default settings. The optimisation search converged after 13 iterations. For our dataset lambda was optimised at 0.7682688and gamma at 0.2347024. Error rates associated with the RDA optimisation parameters were estimated using cross-validation and bootstrapping. Cross-validation was run with 10 folds. Bootstrapping was run using an 80:20 train-test data division with 200 bootstrap replicates. Mahalanobis (scaled Euclidean) distances were calculated for each taxon relative to the distribution of the entire sample to quantifiably identify divergent taxa and statistical outliers. Calculations were conducted in R using Mahalanobis function using PC scores for all 29 axes and DFs for all 5 axes.

Statistical Analyses Bayes Factor Bound values. We have supplemented probability values with an upper Bayes Factor or Bayes Factor Bound (BFB) (equation 2)[12], data-based odds representing the strongest case for the alternative hypothesis relative to the null hypothesis [12–14] whereby:

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1 BF ≤ BFB ≡ −푒 푝 log 푝 [2] The BFB is calculated as a function of the p value using the natural logarithm and its base, the constant e. This method of translating a p value into a BFB does not require a specific alternative hypothesis and provides greater context when interpreting probability values.

PERMANOVA. Significant separation of group centroids in morphospace were tested for using a PERMANOVA (Permutational Multivariate Analysis of Variance). This method emulates the utility of an ANOVA but does not require the data to be normally distributed [15,16].

Multiplicity adjustment. Probability values were adjusted for multiplicity using the Benjamini and Yekutieli (BY) method [17] rather than Bonferroni-type procedures. Bonferroni correction procedures control the familywise type I error rate. This is a more appropriate correction method when there are only a small number of comparisons and only a few significant comparisons are expected as all inputted probability values are penalised which may produce type II errors in a larger number of comparisons or when more than a few significant comparisons are expected [18–20]. For our study, the BY method is preferable as it controls the expected proportion of false discoveries amongst the rejected hypotheses while making no assumptions about test dependency (as is the case for the Benjamini-Hochberg [BH or FDR] procedure)[17,19]. Corrections were implemented in R using the p.adjust function using the ‘BY’ method:

BY = { i <- lp:1L o <- order(p, decreasing = TRUE) ro <- order(o) q <- sum(1L/(1L:n)) pmin(1, cummin(q * n / i * p[o]))[ro] }

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Disparity Analyses Disparity metrics. We used sum of ranges, and two variance measures: sum of variances and mean pairwise distance to quantify morphospace volume. Range measures seek to quantify the entire spread of morphological variation (morphospace size) whereas variance measures denote mean dissimilarity between forms (the spread of taxa in morphospace compared to a fixed point) [21–23]. Sum of variances quantifies dissimilarity among species in morphospace relative to the group mean whereas and mean pairwise distance quantifies average density of species in morphospace relative each other.

Range measures are sensitive to sample size and sampling bias whereas variance measures are less sensitive to sampling biases but may be influenced by the taxonomic sampling although taxonomic rank and relatedness does not imply any particular level of morphological distinctness [21,23]. In conjunction with one another they provide a quantitative measure of the magnitude of morphological variation in morphospace while determining the average dissimilarity between forms.

Disparity tests. In order to assess disparity between groups we used three tests on each disparity metric for the PC and DF data. A Wilcoxon Rank sum test was used to assess whether group mean ranks differ and the Bhattacharyya Coefficient was calculated to quantify the probability of overlap between group distributions. Both these tests were conducted on resampled and rarefied disparity data to account for sampling biases. The permutation test is an alternative method to assess whether the difference in disparity values between groups were statistically significant. We do not intend for any of these tests to provide an absolute measure of the value of our results, no test is ‘better’ or provides more valid results – the results of the permutation tests do not negate the results of the Wilcoxon rank sum tests. Both are statistically robust in so much as a probability value can be but may provide differing conclusions. Where they differ, we do not necessarily think this is due to inadequacies in our data or methodology, although we note there are caveats to both, instead it suggests there is more knowledge to be gleaned along the lines of the caveats of the test. To this end, we want to emphasize the exploratory nature of our study

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by including multiple tests: there is always more data that can be added, and fossils are only ever providing a snapshot of events.

Regression analyses

We compared limb proportions of Paleocene mammals to extant mammals using bivariate regression analyses on limb measurements and body mass estimates to assess morphological robusticity (Dataset S5). Body mass estimates were calculated for extinct and extant species using Campione and Evans long bone scaling equation [24] (equation 3). The data were Box-Cox transformed to better render linear relationships. Regression analyses and ANOVA tests to assess correlation between limb measurements and body mass were performed in R version 4.0.2 [25].

Body weight was estimated for the extant and extinct taxa using Campione and Evans [24] scaling equation whereby:

log Body Weight = 2.749 · logCH+F − 1.104 [3]

where CH+F is the sum of minimum humeral and femoral circumferences. This method allowed for the use of a universal body weight estimation method for both the extant and extinct taxa with all measurements for each species obtained from the same individual.

Results

Regression analyses. Regression analyses show positive correlation between limb bone dimensions against to body mass in mammals (Fig. S23). The Paleocene taxa possess relatively more robust limb proportions, being shorter and broader than average for their body mass and falling out with robustly built extant mammals. However, bivariate comparisons are limited in that they do not capture the nuances of anatomy by comparing a single measurement to body mass. To investigate the morphology and locomotor ecology

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of Paleocene species in more detail and allow for the inclusion of as many Paleocene species as possible we used a suite of multivariate analyses on the tarsus.

Morphospace interpretations. In the following section, we provide interpretations for the first three axes of our PCA and DFA tarsal morphospaces. Functional inferences are specific to our morphospaces and taxon sample but are grounded in study of the tarsals we measured with reference to the literature [26–38].

PC1 (22.84%) - stability at the astragalocalcaneal joint and robustness in Paleocene species (Fig. 1 and Supplementary Figs. S4-7)

PC1 captures morphologies that best separate Paleocene species from extant mammals with no supervised input on the groupings. This axis captures tarsal stability relating to features of the astragalocalcaneal articulation and how movement is permitted between these two bones. Low PC1 scores are associated with a mediolaterally broader astragalar and calcaneal body allowing a greater arc of rotation between the facets and therefore promoting a more mobile joint. This mediolaterally expansion of the astragalar body is decoupled from the width of the trochlea. Therefore, taxa with low PC1 scores have a relatively wider astragalar body (made up by the fibular facet and the medial plantar process) compared to their trochlea, while a wider astragalar trochlea relative to body width is associated with higher PC1 scores. Functionally, increasing PC1 scores are associated with a more stable joint and tightly interlocking facets indicating a decreasing range of rotational movement. The enlargement of the astragalar and calcaneal bodies relative to the astragalar trochlea, that defines lower PC1 morphospace and distinguishes Paleocene mammals from extant ones, is also what gives them their distinctive robustness particularly in dorsal profile. This robustness is markedly different from what might be considered a robust tarsal morphology in an extant mammal where robustness is more frequently achieved through dorsoplantar expansion of the tarsal bones.

PC2 (13.66%) - plane and force of movement at the cruropedal joint (Fig. 1 and Supplementary Figs. S4-7)

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The plane and force of movement at the cruropedal joint is captured by measurements describing the lever action of the calcaneum and lateral projection of the astragalus though the fibular and ectal facet dimensions. The distribution of taxa by plane of movement is correlated to a reduction and/or loss of the fibula facet and the shift of the ectal facet from a weight-bearing/movement role to a lateral stablising role as PC2 values decrease. Lower PC2 values are also strongly correlated with an increase in calcaneal tuber length corresponding to a more efficient effort arm when considering the astragalocalcaneal complex as a lever. The width of the astragalar head also increases relative to the width of the astragalar body as PC2 values decrease. This increase in head width permits a more even weight distribution through the pes and limits inversion and eversion of the transverse tarsal joint. Higher PC2 values are related to curopedal movement not restricted to a parasagittal plane and a less efficient but more rapid calcaneal lever. It is worth recognising PC2 captures the distinction between parasagittal and non-parasagittal movement, but non- parasagittal movement can still be restricted to a single oblique plane e.g. Hystrix.

PC3 (11.78%) - weight distribution through the astragalocalcaneal joint (Fig. 1 and Supplementary Figs. S4-7)

The distribution of weight through the astragalocalcaneal joint is captured by measurements describing the relative sizes of the ectal and sustentacular facets on both the astragalus and calcaneum. The difference in sizes between the associated astragalar facets and their calcaneal counterparts also captures aspects relating to mobility (inversion/eversion) between the two bones if applicable. Higher PC3 scores are associated with a relatively large ectal facet and more even weight distribution through the bones, and negative scores with a larger sustentacular facet relative to the sustentacular facet. Note that the sustentacular facet is always weight bearing and a large sustentacular facet can be associated with a non-weight bearing ectal facet (instead the ectal facet serves as a lateral stabiliser) but an ectal facet cannot take on the primary role of bearing weight (we note that pangolins could be an exception to this finding but were not included in this study given their unusual tarsal anatomy).

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DF1 (63.67%) – stance (Fig. 1 and Supplementary Figs. S8-10)

The distribution of taxa by stance along DF1 is captured by measurements relating to the mediolateral width and dorsoplantar depth of the astragalus and mediolateral width of the calcaneum. Negative DF scores are associated with a fully plantigrade stance largely indicated by a mediolaterally broader astragalus and calcaneum. Higher DF scores are associated with a heel-elevated stance progressing through to digitigrady and the highest DF scores associated with unguligrady which is indicated by a mediolateral narrow and dorsoplantarly deeper astragalus and calcaneum. Deepening of the astragalus along the DF1 axis reflects the changing position of weight distribution on the bone as the pes becomes more elevated.

DF2 (17.32%) – pedal lever action (Fig. 1 and Supplementary Figs. S8-10)

The distribution of taxa by pedal lever action along DF2 is captured by measurements associated with the relative lengths of the calcaneal tuber and the astragalar head and neck. The calcaneal tuber acts as an effort arm, the astragalar head and neck act as a load arm with the fulcum being formed by the pivot action between the astragalar trochlea and the crus. A longer effort arm increases the amount of outforce produced by a given in-force and facilitates a more forceful and efficient foot stroke. A longer load arm facilitates greater speed of motion. Thus, this axis distributes taxa by the force and speed of the pes (and by association, the hindlimb). Negative DF2 scores are associated with a more equal length effort and lever arm equating to rapid but less forceful and efficient movement. Positive DF2 scores are associated with a longer effort arm and more forceful and efficient movement of the pes (hindlimb). Note that the load arm of the pes can be extended by the other tarsal bones and digits. For example, Equus has an extremely short astragalar head and neck but the pedal structure below is tightly articulated to form a long load arm. This configuration relates to the fact that the forces generated during cursorial locomotion are extremely high for Equus and are borne through a single weight bearing axis which would

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likely be too great to be transmitted through a load arm comprising an elongate astragalar head and neck [39].

DF3 (10.83%) – rotational movement (Fig. 1 and Supplementary Figs. S8-10) The distribution of taxa by rotational movement along DF3 is captured by measurements associated with development of features on either side of the two bones. For example, broadening of the medial side through increased length and/or height of the medial trochlear keel and widening of the sustentacular facet and posteromedial plantar process and broadening of the lateral side through increased length and/or height of the lateral trochlear keel and widening and lengthening of the ectal and fibial facets. As such, this axis is related to the range of inversion and eversion of the pes and the anatomies which serve to stabilise against these movements. Negative DF3 scores are associated with a higher degree of movement and loading through the medial side. Low DF3 scores are also associated with increased width of the calcaneal cuboid facet which facilitates greater eversion at the transverse tarsal joint and a larger medial plantar process serves to stabilise against over extension during eversion. Positive DF3 scores are associated with a greater degree of movement and loading through the lateral side. This is best captured through the increased height and length of lateral trochlear keel which allows the crus to transcribe arcs of different radii about the astragalar trochlear and acts to stabilise the cruropedal joint during inversion. Midrange values are associated with a relatively even distribution of movement and loading through the astragalus and calcaneum (it may be centralised to a single axis) with little habitual eversion or inversion of the pes. This axis is similar to some aspects of morphology capture by PC1 and PC2 in the PCA but differs in that it is able to distinguish if movement is favoured on a particular side.

Locomotor morphospace. In the following section, we provide broad descriptions for each locomotor group as defined by our tarsal PC and DF morphospaces with interpretation. Axes ranges are broadly defined relative to other extant locomotor groups. See also Supplementary Figs. S4-7 for additional PCA figures and Supplementary Figs. S8-10 for additional DA figures.

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Arboreal locomotor group:

PC1 – variable range of PC1 scores PC2 - middle range to highest PC2 scores PC3 - variable low to high range PC3 values

DF1 - middle range DF1 values DF2 - middle to low range DF2 values, highest range of values. DF3 - middle range DF3 values

Functional interpretation: variable robustness to more elongate tarsal proportions, second only to terrestrial group. Variable range of movement permitted between the astragalus and calcaneum but with high degree of multiaxial movements permitted at the cruropedal joint. Variable facet sizes with some correspondence to fibula development or lack thereof. Heel- elevated plantigrade stance. Generally, tarsal lever comprising more equal length effort and load arms corresponding to rapid but lower force movement. Loading and movement equally distributed through astragalus and calcaneum – habitual movement not favoured on a particular side.

Cursorial locomotor group:

PC1 – among highest PC1 values PC2 – lowest PC2 values PC3 - middle to low range PC3 values

DF1 - highest DF1 scores DF2 - middle to high DF2 scores DF3 - middle to slightly higher range DF3 scores

Functional interpretation: elongate tarsals with limited to no movement permitted between the astragalus and calcaneum. Movement at the cruropedal joint limited to a single plane

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(parasagittal). Generally, sustentacular facet is enlarged and bears most of the animal’s weight, the ectal facet is reduced and acts as a lateral stabiliser bearing little to no weight. Unguligrade stance. Tarsal lever comprising much longer effort arm, load arm extremely reduced corresponding to forceful and efficient movement (note other pedal elements may form a tightly lock load arm to facilitate greater speed). Loading and movement equally distributed through the astragalus and calcaneum – habitual movement not favoured on a particular side.

Scansorial locomotor group:

PC1 - middle range to moderately high PC1 scores PC2 - middle range to moderately high PC2 scores PC3 - middle range to PC3 scores

DF1 - middle range to moderately high DF1 values DF2 - moderately low DF2 scores DF3 – moderately low DF3 scores

Functional interpretation: average tarsal proportions compared to other locomotor groups with variable degree of movement permitted between the astragalus and calcaneum combined with a somewhat mobile cruropedal joint but showing favourable plane of movement. Sustentacular and ectal facets of a similar size. Plantigrade to slight heel- elevated stance, more heel-elevated than arboreal group. Tarsal lever comprising more equal length effort and load arms corresponding to rapid but less forceful movement. Loading and movement equally distributed through astragalus and calcaneum – habitual movement not favoured on a particular side.

Semi-aquatic locomotor group:

PC1 - middle range to moderately high PC1 scores PC2 - middle range to moderately high PC2 scores

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PC3 - middle range to PC3 scores

DF1 - middle range to lower DF1 scores DF2 - middle range to moderately high DF2 scores, most constrained of locomotor groups DF3 - middle range to moderately high DF3 scores

Functional interpretation: average tarsal proportions compared to other locomotor groups with variable degree of movement permitted between the astragalus and calcaneum combined with a somewhat mobile cruropedal joint but showing favourable plane of movement. Sustentacular and ectal facets of a similar size. Plantigrade to slight heel- elevated stance. Tarsal lever comprising a longer effort arm, load arm reduced corresponding to forceful and efficient movement. Loading and movement generally equally distributed through the astragalus and calcaneum with some favouring of the lateral side indicating some pedal inversion.

Semi-fossorial locomotor group:

PC1 - middle range to moderately high PC1 scores PC2 - middle range PC2 scores PC3 - middle range PC3 scores, most contrained of the locomotor groups

DF1 - low DF1 scores DF2 - middle to high range DF2 scores DF3 - middle to highest range DF3 scores

Functional interpretation: average tarsal proportions compared to other locomotor groups with variable degree of movement permitted between the astragalus and calcaneum combined with a somewhat mobile cruropedal joint but showing tendences towards a favourable plane of movement. Sustentacular and ectal facets of a similar size – distribution highly constrained compared to other locomotor groups. Fully plantigrade stance. Tarsal lever comprising a longer effort arm, load arm strongly reduced corresponding to forceful

20

and efficient movement. Loading and movement showing some favourability towards the lateral side indicating habitual pedal inversion.

Terrestrial locomotor group:

PC1 middle range to high PC1 scores PC2 variable, broad range from moderately low to moderately high PC2 scores PC3 variable, broad range from moderately low to highest PC3 scores

DF1 middle to high range DF1 scores DF2 middle to high range DF2 scores DF3 lowest to middle range DF3 scores

Functional interpretation: greatest range of overall tarsal proportions with variable degree of movement permitted between the astragalus and calcaneum although majority of taxa occupy morphospace associated with more limited movement. Also, a variably mobile cruropedal joint. Variable facet sizes. Stance ranging from heel-elevated through to digitigrady. Tarsal lever comprising a longer effort arm, load arm shorter but not necessarily reduced. Loading and movement showing some favourability towards the medial side indicating some pedal eversion. Development of posteromedial expansion is also common in these taxa to stabilise cruropedial joint during eversion and prevent over extension (note that eversion at the cruropedal joint is secondary to movement at the transverse tarsal joint).

Discriminant Analysis classification. We conducted both cross-validation and bootstrap validation to assess the predictive power of the RDA model. We acknowledge that the cross-validation and bootstrap correct classification percentages are lower than the apparent classification percentage likely as a result of our sample which although carefully curated to cover the diversity of locomotor morphospace exhibited by extant mammals (with the exception of the locomotor groups previously mentioned) is not extensively sampled so as to limit phylogenetic signal. However, we assert that the lower cross-

21

validation and bootstrap percentages are not an issue for the purpose of our study given that we know we are sampling from a finite extant morphological dataset. Validation methods are useful when sampling variables from an infinite data source but that is not the case here. Visual inspection of the morphospaces show they are capturing the diversity of tarsal morphologies and functions exhibited by the extant mammals relevant to this study. Furthermore, predictions of locomotor behaviour for fossil species are derived from the apparent RDA using the full dataset which performs well. We also note that the variable classification rates for the extant taxa using cross-validation and bootstrapping are explained by overlapping locomotor behaviours of the taxon. For example, Tamandua is classified as arboreal but has high posteriors values for both arboreal and semi-fossorial behaviours which fits with observed behaviour for this taxon (Supplementary Table S9) [40]. For a more targeted analysis e.g. looking at a particular locomotor behaviour or taxonomic group, we do recommend supplementing this data set with more extant taxa but for the of purpose of looking at mammalian locomotion at a broader scale and providing probabilistic estimate of locomotor behaviour for fossil species we assert that this dataset is more than sufficient. We also note here the potential of phylogenetically flexible discriminant analysis [41,42] in future developments of this project once a phylogeny of Paleocene mammals has been established and tested.

Disparity analyses. Disparity trends were tested using a Wilcoxon rank sum test and Bhattacharyya coefficient on rarefied and bootstrapped data and a permutation test on raw data. The results from these tests gave contradictory indications of statistical significance for the same comparisons. This raises obvious concerns over the cogency of our findings. This is likely due to the stringency of the permutation test. For example, our range disparity metrics show a marked increase from the Cretaceous into the Paleocene which is recognised by the Wilcoxon rank sum test, however our limited Cretaceous sample may inhibit the permutation test from finding a significant result over 10000 permutations. That doesn’t void the usefulness of the Cretaceous taxa in our study – they provide valuable temporal context on tarsal shape diversity. Given the dispersion of the Cretaceous species in morphospace it would appear that despite not being numerically diverse our dataset has captured a reasonable range of morphological diversity.

22

Marsupial and placental disparity results. Statistical tests of morphospace occupation show the extant marsupial sample exhibits smaller range disparity values in both PC and DF morphospace (Fig. S14a and d, Table S14). In PC morphospace, the extant marsupial sample exhibits higher variance (dissimilarity within the group) compared to the extant placental, Paleocene and Cretaceous samples (Fig. S14b and c). However, in DF morphospace extant marsupials possess the lowest variance (Fig. S14e and f) likely due to the fact that the DFA ordinates taxa in morphospace by predetermined locomotor behaviour which maximises separation among groups combining both marsupials and placentals. Overall, subdividing the extant sample into marsupial and placental subgroups does affect the disparity trends observed in the data.

Discussion In using multivariate analyses to assess tarsal morphology and predict locomotor behaviour for a sample of Paleocene taxa, a number of species have been indicated as outliers or classified into a locomotor group which does not align with previous inferences. Two species of particular interest are Ignacius and Ectoganus. Afrodon was also classified as an outlier but is not well known to provide further comment on how unusual its tarsal morphology is, except to further confirm it is an unusual and enigmatic taxon.

Regarding the locomotor classification of Ignacius:

Ignacius is a paromomyid plesiadapiform inferred to be a frugivorous arborealist with the skeleton of Ignacius indicating a versatile arboreal locomotor repertoire for vertical climbing and traversing horizonal substrates [43,44]. Our RDA classifies Ignacius as semi- fossorial with a posterior value of 0.585 and an arboreal posterior value of 0.302. A semi- fossorial classification is related to Ignacius possessing a high DF2 value compared to other Paleocene plesiadapiforms/primates and extant arborealists. A higher DF2 value corresponds to a relatively longer calcaneal effort arm compared to the load arm equating to more forceful and efficient movement of the pes. In Ignacius, the calcaneal tuber is not noticeably longer than in other Paleocene plesiadapiforms or primates, however, when

23

considered with the astragalus, the load arm is relatively short, giving the lever arm relatively greater advantage and explaining the relatively high DF2 value for a seemingly more arboreal taxon. Interestingly, in PC morphospace, Ignacius plots close to extant primates and arborealists, more so than the other Paleocene plesiadapiforms and primates, distinguished by a relatively high PC2 value corresponding a greater degree of non-parasagittal movement at the cruropedal joint providing further evidence for some arboreal capability. The skeleton of Ignacius indicates a versatile arboreal locomotor repertoire for holding vertical postures but also more adeptly traversing horizonal substrates than other plesiadapforms [43,44]. In describing new material of Ignacius, Bloch et al. (2007) [44] identify anatomical features of the tarsus indicative of arboreal adaptations in plesiadapiforms, these include: a mobile tarsus with adaptations towards stabilising against inversion and multiaxial mobility rather than parasagittal movement. Our morphospace results agree with the findings in Bloch et al. (2007)[44], however, the lever and load arm proportions cause it to be classified as semi-fossorial with a high arboreal posterior value further supporting a diversity of locomotor strategies in Paleocene plesiadapiforms. The lever and load arm proportions of the tarsus of Ignacius may have facilitated more agile and efficient horizontal arboreal locomotion.

Regarding the position of Ectoganus:

Ectoganus is a large-bodied taeniodont and has been inferred to be semi-fossorial based on its postcranial morphology [45]. Our multivariate analyses plot Ectoganus at a statistical outlier in both the PC and DF morphospaces (Fig. 1-2, Supplementary Figs. S12-14). Despite its divergent position in morphospace, the RDA classifies it as semi-fossorial with a 0.51 posterior albeit with a cursorial posterior of 0.291 and terrestrial posterior of 0.186 (Supplementary Table S10). A semi-fossorial classification for Ectoganus does make sense given its tarsal anatomy and other aspects of its postcranial morphology inlcuding enlarged unguals and insertion sites for extremely well-developed forelimb musculature; however, Ectoganus does also exhibit tarsal morphologies comparable to extant cursors which may explain its

24

outlier position. The astragalus and calcaneum of Ectoganus are mediolaterally compressed and dorsoplantarly deep, the distal end of the calcaneal tuber exhibits a distinctive hook shaped insertion site for the soleus and gastrocnemius muscles that would have enabled forceful plantarflexion of the pes and precluded a plantigrade stance (as is typical of most extant semi-fossors) (see [45]). These morphologies are adaptations towards withstanding high levels of dorsoplantar loading on the pes [34,35]. In extant cursors, such morphologies serve to enable efficient running [34,35]; however, in Ectoganus it makes sense that they served as an efficient morphology for a large-bodied mammal to dig. These morphological similarities between extant semi-fossors and cursors are also evident in our morphospace (see Dasypus, Zaedyus and Odocoileus in Supplementary Figs. S8, S11-14). This example of Ectoganus illustrates the usefulness of combining qualitative inferences on anatomy with quantitative multivariate and discriminant analyses in order to assess fossil taxa.

Acknowledgments

We would like to credit and thank www.phylopic.org and the individual artists who provided the silhouettes used in Figure 3 of this manuscript.

Ptilocercus by T. Michael Keesey (after Joseph Wolf) This image is available for reuse under the Public Domain Mark 1.0 license. https://creativecommons.org/publicdomain/zero/1.0/legalcode

Odocoileus by xgirouxb This image is available for reuse under the Public Domain Mark 1.0 license. https://creativecommons.org/publicdomain/zero/1.0/legalcode

Eira by Ferran Sayol This image is available for reuse under the Public Domain Mark 1.0 license. https://creativecommons.org/publicdomain/zero/1.0/legalcode

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Lontra by José Infante (modified for use here) Creative Commons Attribution-Non Commercial 3.0 Unported license. https://creativecommons.org/licenses/by/3.0/legalcode

Zaedyus by Zimices Creative Commons Attribution-Non Commercial 3.0 Unported license. https://creativecommons.org/licenses/by/3.0/legalcode

Ursus by xgirouxb This image is available for reuse under the Public Domain Mark 1.0 license. https://creativecommons.org/publicdomain/zero/1.0/legalcode

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Supplementary Information Figures

Figure S1. Measurement schematic. (a) Postcranial bones used for analyses highlighted in red. (b) Tarsal measurements used in this study. A full description of the measurements is listed in the supplementary text.

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A1 A2 A3 A4 A5 200 150 100 50 0

A6 A7 A8 A9 A10 200 150 100 50 0

A11 A12 A13 A14 A15 200 150 100 50

0

d

e

v

r e

s A16 A17 C1 C2 C3

b 200 O 150 100 50 0

C4 C5 C6 C7 C8 200 150 100 50 0

−2 −1 0 1 2 C9 C10 C11 C12 200 150 100 50 0

−2 −1 0 1 2 −2 −1 0 1 2 −2 −1 0 1 2 −2 −1 0 1 2 Theoretical

Figure S2. Quantile-Quantile plots for the raw tarsal measurements. Measurement codes correspond to the list provide in the supplementary information text and Fig. 1b.

28

A1 A2 A3 A4 A5

2

0

−2

−4

A6 A7 A8 A9 A10

2

0

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−4

A11 A12 A13 A14 A15

2

0

−2

d −4

e

v

r e

s A16 A17 C1 C2 C3

b O 2

0

−2

−4

C4 C5 C6 C7 C8

2

0

−2

−4 −2 −1 0 1 2 C9 C10 C11 C12

2

0

−2

−4 −2 −1 0 1 2 −2 −1 0 1 2 −2 −1 0 1 2 −2 −1 0 1 2 Theoretical Figure S3. Quantile-Quantile plots for transformed and standardised tarsal measurements. Measurement codes correspond to the list provide in the supplementary information text and Fig. 1b.

29

(a) (b)

1 2

)

)

%

% 6

0 2 0

4

9

.

.

2

6

1

1

(

(

−2 2

−1 2

F

C

D P −4 −2

−6 −2 −1 0 1 −5 0 5 10 PC1 (21.40%) DF1 (67.02%) (c) (d)

4

1

)

)

% %

0 2

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5

. 9

0 .

1

7

1

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3

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)

% %

0 2

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1

(

(

3

3 0

F C

−1 D P

−2

−2

−2 −1 0 1 −6 −4 −2 0 2 PC2 (12.46%) DF2 (16.92%) Figure S4. Morphospace occupation of Paleocene mammals relative to extant mammals (differentiated into marsupials and placentals) and Cretaceous mammals derived from tarsal measurements. (a) PC1 versus PC2 (b) DF1 versus DF2 (c) PC1 versus PC3 (d) DF1 versus DF3 (e) PC2 versus PC3 (f) DF2 versus DF3. Extant marsupial species are denoted by triangular datapoints, extant placental species are denoted by inverted triangular datapoints, extinct species are denoted by diamond datapoints. In the PC morphospaces taxa are grouped by time subset with Cretaceous (red), Paleocene (yellow) and extant (blue) groups. In the DF morphospace extant taxa are grouped by locomotor mode: arboreal (dark-green), cursorial (purple), scansorial (yellow-green), semi-aquatic (blue), semi- fossorial (light-pink), terrestrial (hot-pink).

30

(a) (b) 1.5 2.5

1.0

)

)

%

% 6

0.5 2 0.0

4

9

.

.

2

6 1

0.0 1

(

(

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2 F

C −0.5 −2.5

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−2 −1 0 1 0 5 10 PC1 (21.40%) DF1 (67.02%)

(c) (d) 3

1 2

)

) %

% 1

0

6

5

. 9

0 .

1 7

1 0

(

(

3

3 F

C −1

−1 D P

−2 −2 −3 −2 −1 0 1 0 5 10 PC1 (21.40%) DF1 (67.02%)

(e) (f) 3

1 2

)

) %

% 1

0

6

5

. 9

0 .

1 7

1 0

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(

3

3 F

C −1

−1 D P

−2 −2 −3 −1.0 −0.5 0.0 0.5 1.0 1.5 −2.5 0.0 2.5 PC2 (12.46%) DF2 (16.92%) Figure S5. Morphospace occupation of extant mammals differentiated into marsupials and placentals derived from tarsal measurements. (a) PC1 versus PC2 (b) DF1 versus DF2 (c) PC1 versus PC3 (d) DF1 versus DF3 (e) PC2 versus PC3 (f) DF2 versus DF3. In the PC morphospaces taxa marsupial species are denoted by light blue triangular datapoints, placental species are denoted by inverted blue triangular datapoints. In the DF morphospace extant taxa are grouped by locomotor mode: arboreal (dark-green), cursorial (purple), scansorial (yellow-green), semi-aquatic (blue), semi-fossorial (light-pink), terrestrial (hot-pink). Placental species are denoted by inverted triangle datapoints. Marsupials are denoted by triangle datapoints in a lighter colour tone to the corresponding placental locomotor group.

31

Figure S6. PC tarsal locomotor morphospace plots of Cretaceous (red diamonds), Paleocene (yellow diamonds) and extant (blue circles) mammals with associated biplots. (a) Morphospace with biplot of structure correlations between measurements and PC1 and PC2 (b) Morphospace with biplot of structure correlations between measurements and PC1 and PC3 (c) Morphospace with biplot of structure correlations between measurements and PC2 and PC3.

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(a) 0.2

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−0.6 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement (b) 0.6

0.3

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A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement (c)

0.4

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A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement

Figure S7. Barplots of Principle Component loadings for each measurement for (a) PC1 (b) PC2 (c) PC3. A full summary of the PC loadings for each of the 29 axes is provided in Supplementary table S3.

33

Figure S8. PCA morphospace (a) tarsal schematics illustrating the first three PC axes (b) three-dimensional morphospace scatterplot of the first three PC axes (c-e) Morphospace scatterplots illustrated with the astragali and calcanea of extant exemplar taxa (c) PC1 versus PC2 (d) PC1 versus PC3 (e) PC2 versus PC3. Tarsal schematic arrow colour coded by function with articular movement (green), lever load motion (purple), distribution of body weight (yellow). In the morphospaces, taxa are subset by time with Cretaceous (red), Paleocene (yellow), and extant (blue) groups. Extant marsupials and placental mammals are differentiated, marsupials are denoted by lighter blue data points, placental mammals are denoted by darker blue data points.

34

Figure S9. DA tarsal morphospace plots of Cretaceous (red diamonds), Paleocene (yellow diamonds) and extant (circles coloured by locomotor mode) mammals with associated biplots. (a) Morphospace with biplot of structure correlations between measurements and DF1 and DF2 (b) Morphospace with biplot of structure correlations between measurements and DF1 and DF3 (c) Morphospace with biplot of structure correlations between measurements and DF2 and DF3. Extant taxa are grouped by known locomotor mode: arboreal (dark green), cursorial (purple), scansorial (yellow-green), semi-aquatic (light blue), semi-fossorial (light pink), terrestrial (hot pink).

35

(a)

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i −3

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−9 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement (b) 4

2

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a o

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A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement

(c) 4

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A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Measurement

Figure S10. Barplots of Discriminant Function loadings for each measurement for (a) DF1 (b) DF2 (c) DF3. A full summary of the DF loadings for each of the 5 axes is provided in Supplementary table S6.

36

Figure S11. DA morphospace (a) tarsal schematics illustrating functional changes along the first three DF axes. Arrows indicate increasing DF values (b) three-dimensional morphospace scatterplot of the first three DF axes with extant mammals grouped by locomotor mode alongside Cretaceous (red) and Paleocene (yellow) species (c-e) Morphospace scatterplots illustrated with the astragali and calcanea of extant exemplar taxa for each locomotor group (c) DF1 versus DF2 (d) DF1 versus DF3 (e) DF2 versus DF3. Tarsal schematic arrows colour coded by function with articular movement (green), lever

37

load motion (purple), body weight loading (yellow). Extant taxa are grouped by known locomotor mode: arboreal (dark green), cursorial (purple), scansorial (yellow-green), semi- aquatic (light blue), semi-fossorial (light pink), terrestrial (hot pink). Extant placental mammals (inverted triangle datapoints) are further differentiated from marsupial mammals (triangular datapoints) in c-e.

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(a) (b) 86 103 122 95 1 94 87 113 91 100 109 113 96 88 92 115 2 101 118 110 95 125 120 121

116 112 99 ) 104 ) 124 88 108 93 99 111

125 114 92 97 % 0 93 124 % 102 105 102 104 90

6 105 2 0 96 117 89 122 89

4 120

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119 100 107 2

90 6

103 98 118 106 117 1

109 94 1 91 ( ( 123

121

−1 97 −2 119 114 2

107 108 123 2 116 F

C 101

D P −4 115 111 −2 87 110 86 −6 −2 −1 0 1 −5 0 5 PC1 (21.40%) DF1 (67.02%)

(c) 112 (d) 100 101 89 1.0 96 95 110 99 91 124 4 121 92 119 106 109 121 ) 102 93 ) 125 0.5 90 102 117

% 108

111 % 123 0 117 2 103 98 118

97 6 91 5

. 100 98 9 97 86 . 90 105

1 109 120

116 125 107 113 7 86 1 113 118 (

( 107 0.0 87 88 104 116 92 94 122 88 3 93 111 3 0

F 104 122 89

C 106 108 123 120 87 114

D P −0.5 105 110 94 112 115 119 103 101 −2 99 95 114 124 115 96

−2 −1 0 1 −5 0 5 PC1 (21.40%) DF1 (67.02%)

(e) 89 112 (f) 101 100 1.0 95 96 110 99 121 124 91 4 92 119 106 121 ) 109 93 102 102 )

0.5 117 125 %

97 90 % 103 0 111 117 2 108 118 6 98 123 5 86

. 98 9 90

118 . 120 1 116 91 94 125 113 7 86 97 113 1 100

107 ( 109 ( 0.0 107 105 87 116 88 105 104 3

3 0 92 110 122 114 122 F 87 115 111 93 C 108 106 120 D 89 88 P 104 94 −0.5 123 112 101 119 124 99 95 103 −2 114 115 96

−2 −1 0 1 −6 −4 −2 0 2 PC2 (12.46%) DF2 (16.92%) Figure S12. Annotated morphospace occupation of Paleocene mammals with inferred locomotor group as predicted by the RDA (a) Morphospace of PC1 versus PC2 (b) Morphospace of DF1 versus DF2 (c) Morphospace of PC1 versus PC3 (d) Morphospace of DF1 versus DF3 (e) Morphospace of PC2 versus PC3 (f) Morphspace of DF2 versus DF3. Data point colouration corresponds to inferred locomotor mode: arboreal (dark green), cursorial (purple), scansorial (yellow-green), semi-aquatic (light blue), semi- fossorial (light pink), terrestrial (hot pink). Numerical designations for species correspond to those provided in Dataset S2.

39

(a) (b) 16 21

1 1 22

1.0

) )

127 20 %

% 126 19 6

0 6 18 4

4 15 . . 96

17 2

2 0.5 1

1 115

(

(

2 14 2

−1 2 116 C

C 13 P P 0.0 128 24 117 106 −2 114 23 −0.5 −2 −1 0 1 −2 −1 0 1 PC1 (21.40%) PC1 (21.40%)

(c) 1.2 86 5 4 36 (d) 113 51 52 0.5 44

0.8 3 7 ) 91 ) 104 49

87 35 46 % % 125

53 50 6

6 0.0 102 4

0.4 37 4 89 .

33 . 45 2 112 2

119 1

1 118 48 (

38 (

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100 121 C

C 107 P P 103 47 108 −0.4 32 −1.0 34 101 −0.8 −2 −1 0 1 −1 0 1 PC1 (21.40%) PC1 (21.40%)

(e) 84 76 78 10 77 73 60 1 85 59 11 72 54 65 75 ) 99 70 74 63 95 61

% 71 57

6 9 92 67 0 129 80 83 4 93 56 . 105 66 58 2 88 120 69 124 8 79 1 109

( 12

97 122 68 94 90 64 81 2 −1 98

C 130 123 62 82 55 P

111 −2 110

−1 0 1 PC1 (21.40%) Figure S13. Tarsal morphospace plots of Paleocene and extant mammals comparing equivalent locomotor groups in PC morphospace. Extant taxa are grouped by predesignated locomotor group and Paleocene taxa are grouped by locomotor mode predicted by the RDA. (a) Morphospace of the first two Principal Components (PCs) with all extant (circles) and Paleocene (diamonds) taxa grouped by locomotor mode. Data point colours correspond to subsequent plots. (b) Arboreal morphospace of the first two PCs with extant taxa (green circles) and fossil taxa (green diamonds). (c) Scansorial morphospace of the first two PCs with extant taxa (yellow-green circles) and fossil taxa (yellow-green diamonds). (d) Semi- fossorial morphospace of the first two PCs with extant taxa (light pink circles) and fossil taxa (gold diamonds). (e) Terrestrial morphospace of the first two PCs with extant taxa (hot pink circles) and fossil taxa (hot pink diamonds).

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(a) (b) 15

2 0 117 14 96

1 )

) 128 106 %

% −1 114 2 2 0 2

13 9

9 18 .

. 16 6

6 17 1

1 −2 24 (

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F −3 22 D D 126 19 −4 127 −4 115 −6 −5 0 5 10 −4 −2 0 2 DF1 (67.02%) DF1 (67.02%)

(c) 0 112 (d) 103 47 34 91 48 53 37 100 32 33 2 50 125

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. 7 6

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(e) 95 3 9 94 122 69 64 92 82 83 129 109 84 ) 2 8 72 63 110 120 79 % 88 75

2 78 61 99 76 93 80 74 9 71 62 . 1 97 60 58 6 57 90 124 65 1 73 11 ( 10 67 55 56 105 2 70 12 111 0 123 54 F 59 68 81 D 98 77 130 85 −1 66

−5.0 −2.5 0.0 2.5 DF1 (67.02%) Figure S14. Tarsal morphospace plots of Paleocene and extant mammals comparing equivalent locomotor groups in DF morphospace. Extant taxa are grouped by predesignated locomotor group and Paleocene taxa are grouped by locomotor mode predicted by the RDA. (a) Morphospace of the first two Discriminant Functions (DFs) with all extant (circles) and Paleocene (diamonds) taxa grouped by locomotor mode. Data point colours correspond to subsequent plots. (b) Arboreal morphospace of the first two DFs with extant taxa (green circles) and fossil taxa (green diamonds). (c) Scansorial morphospace of the first two DFs with extant taxa (yellow-green circles) and fossil taxa (yellow-green diamonds). (d) Semi-fossorial morphospace of the first two DFs with extant taxa (light pink circles) and fossil taxa (gold diamonds). (e) Terrestrial morphospace of the first two DFs with extant taxa (hot pink circles) and fossil taxa (hot pink diamonds).

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Cretaceous Paleocene Marsupials Placentals Cretaceous Paleocene Marsupials Placentals Cretaceous Paleocene Marsupials Placentals

Figure S15. Morphological disparity calculated for PC and DF scores with Cretaceous (red), Paleocene (yellow), extant marsupials (light blue) and extant placentals (blue) with 95% confidence intervals. (a) PC Sum of ranges (b) PC Sum of variances (c) PC Mean pairwise distance (d) DF Sum of ranges (e) DF Sum of variances (f) DF Mean pairwise distance.

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−25 −20 −15 −10 −2 0 2 −1.0 −0.5 0.0 0.5 1.0 Sum of Ranges Sum of Variances Mean Pairwise Distances Figure S16. Permutation plots showing comparisons between the disparity of Paleocene mammals with extant and Cretaceous taxa derived from the PC scores. Each histogram depicts a pairwise comparison for the disparity metric on the 29 PC axes: (a) Extant vs. Paleocene sum of ranges (b) Extant vs. Paleocene sum of variances (c) Extant vs. Paleocene mean pairwise distances (d) Extant vs. Cretaceous sum of ranges (e) Extant vs. Cretaceous sum of variances (f) Extant vs. Cretaceous mean pairwise distances (g) Paleocene vs. Cretaceous sum of ranges (h) Paleocene vs. Cretaceous sum of variances (i) Paleocene vs. Cretaceous mean pairwise distances. Histogram values represent the disparity differences between the two groups under examination for each metric over 10000 randomisations of a permutation test. The dashed blue line indicates expected difference in disparity under the null hypothesis, calculated as the mean of the 10000 randomisations. The dashed red line indicates observed difference in disparity between the two groups.

43

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−40 −30 −20 −10 0 −25 0 25 −4 −2 0 2 4 Sum of Ranges Sum of Variances Mean Pairwise Distances Figure S17. Permutation plots showing comparisons between the disparity of Paleocene mammals with extant and Cretaceous taxa derived from the DF scores. Each histogram depicts a pairwise comparison for the disparity metric on the 29 PC axes: (a) Extant vs. Paleocene sum of ranges (b) Extant vs. Paleocene sum of variances (c) Extant vs. Paleocene mean pairwise distances (d) Extant vs. Cretaceous sum of ranges (e) Extant vs. Cretaceous sum of variances (f) Extant vs. Cretaceous mean pairwise distances (g) Paleocene vs. Cretaceous sum of ranges (h) Paleocene vs. Cretaceous sum of variances (i) Paleocene vs. Cretaceous mean pairwise distances. Histogram values represent the disparity differences between the two groups under examination for each metric over 10000 randomisations of a permutation test. The dashed blue line indicates expected difference in disparity under the null hypothesis, calculated as the mean of the 10000 randomisations. The dashed red line indicates observed difference in disparity between the two groups.

44

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−16 −12 −8 −4 −30 −25 −20 −15 10 15 20 Sum of Ranges Sum of Ranges Sum of Ranges Figure S18. Permutation plots showing comparisons between the sum of ranges disparity of Paleocene mammals with extant marsupials, extant placentals and Cretaceous taxa derived from the PC scores. Each histogram depicts a pairwise comparison for the disparity metric on the 29 PC axes: (a) Marsupials vs. Placentals (b) Marsupials vs. Paleocene (c) Marsupials vs. Cretaceous (d) Placentals vs. Paleocene (e) Placentals vs. Cretaceous (f) Paleocene vs. Cretaceous. Histogram values represent the disparity differences between the two groups under examination for each metric over 10000 randomisations of a permutation test. The dashed blue line indicates expected difference in disparity under the null hypothesis, calculated as the mean of the 10000 randomisations. The dashed red line indicates observed difference in disparity between the two groups.

45

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46

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50

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51

Supplementary Information Tables

Table S1. Univariate Shapiro-Wilk test results on the raw and prepared data Raw values Prepared values Measurement Statistic p value Normality Statistic p value Normality A1 0.8259 <0.001 NO 0.9885 0.6582 YES A2 0.7873 <0.001 NO 0.9736 0.0781 YES A3 0.8152 <0.001 NO 0.9775 0.1438 YES A4 0.8045 <0.001 NO 0.942 0.0008 NO A5 0.7874 <0.001 NO 0.9709 0.0512 YES A6 0.6295 <0.001 NO 0.9939 0.9632 YES A7 0.8936 <0.001 NO 0.9895 0.7294 YES A8 0.7827 <0.001 NO 0.9673 0.0294 YES A9 0.7026 <0.001 NO 0.9327 0.0003 NO A10 0.7037 <0.001 NO 0.9147 <0.001 NO A11 0.7438 <0.001 NO 0.9801 0.214 YES A12 0.7317 <0.001 NO 0.9718 0.0596 YES A13 0.7778 <0.001 NO 0.9753 0.1018 YES A14 0.7552 <0.001 NO 0.9773 0.1394 YES A15 0.7724 <0.001 NO 0.9589 0.0085 YES A16 0.765 <0.001 NO 0.9434 0.001 NO A17 0.8311 <0.001 NO 0.9709 0.0514 YES C1 0.7975 <0.001 NO 0.9946 0.9808 YES C2 0.7394 <0.001 NO 0.9639 0.0175 YES C3 0.7355 <0.001 NO 0.9789 0.1778 YES C4 0.7381 <0.001 NO 0.9165 <0.001 NO C5 0.6774 <0.001 NO 0.9878 0.6099 YES C6 0.732 <0.001 NO 0.9932 0.9427 YES C7 0.7212 <0.001 NO 0.9857 0.4701 YES C8 0.6888 <0.001 NO 0.97 0.0445 YES C9 0.7347 <0.001 NO 0.9595 0.0091 YES C10 0.7645 <0.001 NO 0.988 0.6245 YES C11 0.7131 <0.001 NO 0.9248 0.0001 NO C12 0.7969 <0.001 NO 0.9643 0.0188 YES

52

Table S2. PCA summary table Cumulative Standard deviation Proportion of Variance Proportion PC1 0.902268 0.214 0.214 PC2 0.6884534 0.1246 0.3385 PC3 0.6614512 0.115 0.4535 PC4 0.6048052 0.0961 0.5496 PC5 0.4927412 0.0638 0.6135 PC6 0.4323062 0.0491 0.6626 PC7 0.3920383 0.0404 0.703 PC8 0.3822643 0.0384 0.7414 PC9 0.359476 0.034 0.7753 PC10 0.3251428 0.0278 0.8031 PC11 0.3155673 0.0262 0.8293 PC12 0.305961 0.0246 0.8539 PC13 0.2661993 0.0186 0.8725 PC14 0.2488748 0.0163 0.8888 PC15 0.2292288 0.0138 0.9026 PC16 0.2224853 0.013 0.9156 PC17 0.2180863 0.0125 0.9281 PC18 0.2037874 0.0109 0.939 PC19 0.1938331 0.0099 0.9489 PC20 0.1853101 0.009 0.9579 PC21 0.1751411 0.0081 0.966 PC22 0.1680613 0.0074 0.9734 PC23 0.1606425 0.0068 0.9802 PC24 0.1428584 0.0054 0.9856 PC25 0.1330931 0.0047 0.9902 PC26 0.1198025 0.0038 0.994 PC27 0.1166253 0.0036 0.9976 PC28 0.07847793 0.0016 0.9992 PC29 0.0558767 0.0008 1

53

Table S3. PCA loadings PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20 PC21 PC22 PC23 PC24 PC25 PC26 PC27 PC28 PC29 A1 -0.2384 0.1137 -0.1349 0.1545 -0.1296 0.0363 -0.0667 0.0068 0.0538 -0.0534 -0.047 0.0668 0.2149 -0.0698 -0.07 -0.1028 -0.0681 0.1017 0.122 0.0139 0.2707 -0.1465 -0.0881 -0.0934 -1.00E-04 -0.0986 -0.1348 0.7317 -0.2866 A2 -0.0359 0.1348 -0.0078 -0.1423 -0.1923 0.0768 -0.0182 0.0227 -0.016 -0.0566 -0.0822 0.1151 0.2034 0.0812 0.1325 0.0694 0.0413 0.161 -0.0178 -0.2522 -0.0235 0.0614 0.0799 -0.0701 0.2935 -0.3633 -0.6516 -0.2667 -0.0423 A3 0.1009 0.1148 -0.0144 -0.1541 -0.2722 0.1713 -0.0903 0.0577 0.0147 0.0519 -0.2315 0.0238 0.4064 0.0429 0.0932 -0.0389 0.1448 -0.0391 -0.3976 0.364 0.278 0.0412 -0.1547 0.2244 -0.0795 -0.0769 0.2469 -0.1853 -0.1722 A4 0.0922 0.0402 -0.0206 -0.0867 -0.0433 0.1867 0.0202 -0.0813 -0.0201 -0.122 -0.0899 0.0635 0.2341 0.0589 0.13 0.3137 0.0535 0.2393 -0.0534 -0.341 -0.1409 0.1562 0.185 -0.4989 -0.2265 0.2339 0.2873 0.0325 -0.2026 A5 -0.1635 0.0902 0.1328 -0.1097 0.0724 0.1146 0.2265 -0.0513 0.0883 -0.181 0.2384 -0.0237 -0.1979 -0.097 -0.1045 0.1024 0.064 0.1617 -0.1685 0.3052 -0.0272 -0.1401 0.2417 0.0687 -0.5452 -0.051 -0.2997 -0.0763 -0.2538 A6 -0.5673 -0.5217 -0.0984 -0.3299 -0.0976 0.0042 0.0395 -0.0322 0.137 -0.0737 -0.0229 -0.0157 0.0739 -0.0054 0.0618 0.0611 -0.053 -0.1013 -0.0214 -0.0475 -0.2022 -0.1585 0.156 0.1301 0.1856 -0.1034 0.2181 -0.0273 -0.1442 A7 -0.3176 0.6368 0.4306 0.1368 -0.0146 -0.0148 -0.0862 -0.0298 0.0092 -0.0383 -0.0685 -0.0245 -0.1025 0.054 0.0331 0.0362 -0.0414 -0.1713 -0.0582 -0.0677 -0.2305 -0.1205 0.1228 0.0537 0.2039 -0.0966 0.2615 -0.0204 -0.117 A8 0.2025 0.0194 -0.0403 -0.0237 0.0521 0.1741 0.1687 -0.1111 0.0524 -0.4631 0.3793 -0.1103 0.0311 -0.2824 -0.25 0.0211 0.2648 -0.251 -0.0517 -0.1438 0.1181 0.0639 -0.1449 -0.0113 0.3361 -0.0682 0.1047 -0.0304 -0.2015 A9 0.0468 -0.1029 -0.0141 0.0845 -0.1707 0.2436 0.1576 0.1455 -0.0081 0.0047 0.168 0.1728 -0.3321 0.569 -0.0207 -0.4067 -0.1495 -0.0585 -0.2204 -0.1476 0.1227 -0.0493 -4.00E-04 -0.1635 0.0331 -0.0301 0.0745 -0.039 -0.1948 A10 0.0546 0.1036 -0.1938 0.0429 0.0421 0.2369 0.2381 -0.2634 -0.0575 0.1344 -0.1674 -0.1724 -0.0763 -0.1401 0.0204 -0.2178 -0.1614 0.3395 0.0451 -0.3084 -0.1646 0.1439 -0.0779 0.5146 -0.0313 0.0134 0.0743 -0.0107 -0.2158 A11 0.2036 -0.0911 -0.0044 0.0189 -0.3172 -0.1415 -0.1681 -0.2293 0.1962 -0.0686 -0.487 0.1538 -0.2613 0.023 -0.4545 0.0206 0.1573 -0.1723 0.1733 -0.0063 -0.1056 0.0141 0.0906 -0.001 -0.0921 -0.0303 -0.0473 -0.0513 -0.2242 A12 0.1277 -0.1066 0.2124 0.0886 -0.2223 -0.1011 0.1871 -0.1044 -0.1219 -0.1475 0.0688 0.0897 -0.0899 0.0122 0.0629 0.289 -0.4542 0.2715 0.2582 0.3527 0.1892 0.1935 0.0665 0.0144 0.2589 -0.0932 0.1481 -0.059 -0.1365 A13 0.0475 -0.0037 0.0181 0.0576 -0.0719 0.1511 -0.1109 0.1391 0.0458 0.2392 0.1265 0.0424 0.0856 -0.1142 -0.0282 -0.1285 0.1063 0.1151 0.121 0.2316 -0.1687 -0.1806 0.1495 -0.0146 0.3492 0.6173 -0.1726 -0.121 -0.3095 A14 0.1966 -0.0414 0.1447 -0.0035 0.0649 0.0609 0.1 -0.0772 0.189 0.0795 0.0068 0.0189 0.3559 -0.1231 -0.0606 -0.0439 -0.6323 -0.4375 -0.0392 -0.0788 -0.1549 -0.1456 -0.0983 -0.0758 -0.1633 0.027 -0.1504 -0.0692 -0.1032 A15 0.0494 -0.0214 0.0643 0.0774 -0.088 0.0894 0.0177 0.2051 0.1653 0.0841 0.2043 0.0638 0.1656 -0.015 0.1927 -0.2809 0.2016 -0.143 0.4412 0.1442 -0.2924 0.4317 0.1166 0.0075 -0.1875 -0.2948 0.0976 0.0358 -0.1001 A16 0.1227 -0.0979 -0.0104 0.0769 -0.1461 0.1672 -0.3383 0.2996 0.0327 0.4056 0.1952 -0.3482 -0.1952 -0.1665 -0.1657 0.3226 -0.0865 0.0912 -0.1072 -0.1172 -0.0258 -0.0789 -0.0372 -0.0565 -0.0177 -0.3295 0.0818 0.0012 -0.1597 A17 -0.0984 -0.1083 -0.3157 0.7502 0.1098 -0.0331 -0.1404 -0.1659 0.1161 -0.1442 0.0799 -0.0016 0.1942 0.2139 0.0332 0.1799 0.0208 -0.0085 -0.1284 0.0707 -0.1028 -0.0267 0.0943 0.107 -0.0172 -0.0573 -0.0188 -0.1945 -0.0518 C1 -0.3051 0.0106 -0.0256 0.0765 0.0819 -0.1154 -0.2113 -0.0129 -0.0931 -0.0538 -0.0384 -0.0263 -0.0592 -0.2611 0.0661 -0.2721 -0.0701 0.0603 0.2666 -0.1078 0.3381 -0.042 -0.2449 -0.262 -0.18 -0.0062 0.0765 -0.4909 -0.2375 C2 0.0934 -0.3528 0.5125 0.0767 0.3862 0.0781 -0.3371 -0.1494 -0.0059 -0.0709 -0.1555 -0.0452 -0.0272 -0.0577 0.1389 -0.1904 0.0408 0.0804 -0.2532 -0.0177 0.0814 0.2175 0.1313 0.0207 0.0927 -0.0528 -0.1057 0.1551 -0.1598 C3 0.1716 -0.0355 -0.0265 -0.013 0.2248 -0.1326 0.2186 -0.0157 0.1133 -0.0052 -0.1874 -0.075 -0.0869 0.07 0.2175 -0.0079 0.1402 0.175 -0.023 0.2473 -0.3647 -0.2959 -0.4684 -0.2712 0.1191 -0.2263 0.0278 0.0265 -0.2154 C4 -0.2461 0.0341 -0.0335 -0.0531 0.045 -0.3368 0.0559 -0.0943 -0.075 0.3029 0.1848 0.212 -0.0363 0.0382 -0.1602 0.1539 0.0119 -0.0923 -0.277 -0.0021 -0.1032 0.5244 -0.3265 -0.028 0.0228 0.1219 -0.1142 0.0434 -0.2637 C5 0.1037 0.0511 -0.0049 0.014 0.3431 -0.2159 0.2752 0.1956 0.4566 0.2746 -0.0544 0.3048 0.035 -0.0588 -0.0143 0.0971 0.0873 0.0727 0.0161 -0.1803 0.3482 -0.0895 0.2629 0.094 0.0937 -0.1038 0.143 -0.0729 -0.1258 C6 0.1839 0.1059 -0.1611 -0.1225 -0.2123 -0.5223 -0.1574 0.0629 0.2685 -0.2219 0.1152 -0.3589 -0.1113 0.0206 0.3792 -0.1181 -0.1115 -0.0235 -0.1474 -0.0947 0.02 0.0616 0.1445 0.0783 -0.0216 0.1443 -0.0481 0.0651 -0.1753 C7 0.1595 -0.1615 0.1845 0.1498 -0.2035 -0.3976 0.1577 0.0201 -0.5425 0.0819 0.1308 0.1361 0.2067 -0.1302 -0.0225 -0.131 0.1703 0.0244 -0.0924 -0.1926 -0.1026 -0.3015 0.1443 0.0923 -0.1077 -0.1169 0.0732 0.0114 -0.128 C8 0.0063 0.071 -0.3413 0.0294 0.0921 0.0782 0.1864 -0.1754 -0.2925 0.2278 -0.198 -0.139 -0.1723 -0.2161 0.1868 -0.054 -0.0166 -0.3479 -0.1191 0.2103 0.0866 0.0964 0.4052 -0.2849 0.1301 -0.1299 -0.0324 0.0318 -0.098 C9 0.1824 0.1669 -0.2749 -0.3393 0.2694 -0.0379 -0.4579 -0.2855 -0.1229 0.0069 0.2867 0.3196 0.0344 0.1304 -0.0796 -0.0815 -0.1351 0.0997 0.0708 0.1074 -0.1003 -0.1378 0.1222 0.055 0.025 -0.1869 0.136 0.0063 -0.0806 C10 0.0725 -0.0442 0.0495 -0.0551 0.0883 0.1358 -0.0551 -0.0327 -0.1924 0.0437 0.002 0.0517 -0.1341 0.2357 0.3961 0.3883 0.1478 -0.3641 0.3033 -0.1262 0.171 -0.1289 -0.1573 0.2825 -0.1154 0.1121 -0.1168 0.05 -0.2817 C11 0.0225 0.028 -0.1931 0.0039 0.2349 -0.004 -0.0633 0.6656 -0.2578 -0.368 -0.2626 0.1787 -0.0631 -0.1006 -0.1015 0.0516 -0.1886 -0.0366 -0.0653 0.0196 -0.1708 0.121 0.0269 0.1363 -0.0015 0.0223 -0.0103 0.0083 -0.1551 C12 -0.0268 0.0308 0.0426 -0.1335 0.254 -0.1472 0.1016 0.0585 -0.1555 0.0396 -0.0665 -0.5439 0.2906 0.466 -0.3775 -0.024 0.0257 0.0093 0.2107 0.0477 0.0964 0.0597 0.1249 -0.0233 0.0244 -0.0117 -0.0241 -0.0546 -0.1657

54

Table S4. PERMANOVA results on PC scores for taxa grouped by time period Sums of Comparison Df F model R2 p value p adjusted BFB squares Extant vs Paleocene 1 40.8360372 11.9661675 0.0886605 1.00E-04 0.00054995 89.124 Extant vs Cretaceous 1 18.7153898 5.22665797 0.05606399 0.00029997 0.00082492 62.809 Paleocene vs Cretaceous 1 9.25016571 2.92544741 0.06369992 0.00249975 0.00458288 14.906

55

Table S5. PERMANOVA results on PC scores for taxa grouped by time period with extant marsupials and placentals as separate groups Sums of Comparison Df F model R2 p value p adjusted BFB squares Marsupials vs Placentals 1 35.6911668 11.231456 0.11919009 1.00E-04 0.00036746 126.583 Marsupials vs Paleocene 1 22.8018915 6.95097585 0.12205192 1.00E-04 0.00036746 126.583 Marsupials vs Cretaceous 1 9.38169371 2.3701876 0.13645147 0.00749925 0.01837316 5.010 Placentals vs Paleocene 1 47.3137431 15.4307654 0.12204913 1.00E-04 0.00036746 126.583 Placentals vs Cretaceous 1 21.8378477 7.04143491 0.08479423 1.00E-04 0.00036746 126.583 Paleocene vs Cretaceous 1 9.25016571 2.92544741 0.06369992 0.00329967 0.00970103 8.181

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Table S6. Coefficients of the discriminant functions with the proportion of variance for each discriminant function noted in the header DF1 DF2 DF3 DF4 DF5 (67.02%) (16.92%) (7.96%) (5.43%) (2.68%) A1 -0.6361519 -2.1743697 1.932112 -0.0104714 5.24469803 A2 -2.3766715 -0.3992301 -3.2799198 0.66934475 -2.0901708 A3 -1.0969998 0.08255387 0.439748 5.14737952 -0.7911997 A4 1.23703309 1.34705444 1.3226484 -1.8642664 -0.4746419 A5 -8.8225603 0.67654189 3.900873 1.33875235 -1.4942932 A6 1.39182498 -0.7040204 1.482972 0.83386701 -0.0169197 A7 1.88993205 -0.4327583 0.3007236 -0.0126028 -0.2861606 A8 0.64058619 1.33053059 1.132955 -0.0819016 0.18125717 A9 0.55825592 1.11671768 0.2048715 -0.2263573 -0.2687663 A10 -1.419834 -1.6866962 -0.4097896 2.97170905 1.50267064 A11 -2.7724662 0.05557906 1.963495 0.38562754 -1.200676 A12 -1.0380222 -1.4749334 1.9678887 1.55592386 0.15163039 A13 1.34143465 1.11727486 1.2585651 0.19437511 -3.2865982 A14 0.80974038 -0.0371912 -2.6952629 -1.6190494 -2.2178951 A15 -2.2366758 -1.9732266 1.756144 -0.3778945 0.39624828 A16 -2.6649146 1.43305141 0.6180146 0.00023395 -2.021713 A17 -1.3215335 -0.1608773 0.9373444 0.82707431 -1.7499617 C1 -6.2849629 3.73306488 1.0008872 1.04499818 -4.9585882 C2 0.01709653 1.61171033 0.1960446 0.98541252 1.76406994 C3 -3.0074432 2.62892938 0.4376891 0.87601431 0.85376123 C4 -1.9431032 -0.4874653 -1.011636 -0.610732 -0.0592816 C5 -0.8280896 0.36149377 1.1383181 2.4920398 -1.300539 C6 2.02152622 -0.2548626 1.0859623 0.78777734 -0.8549579 C7 -0.2832125 0.49256439 1.7414264 0.45972105 0.83028357 C8 -3.0535876 2.16895435 0.402547 -2.3858226 -0.5609379 C9 -1.4659697 -0.718189 1.0685298 1.75300405 -0.0966798 C10 0.78258102 -0.5628502 2.520028 -0.6216837 -0.7506837 C11 -1.6061993 -0.9413402 0.4623627 0.6774253 0.16582354 C12 -2.3619085 0.09636988 1.4431229 -0.7069037 0.22947195

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Table S7. Prior probabilities for locomotor groups derived from the RDA Locomotor group Prior probability Arboreal 0.16470588 Cursorial 0.08235294 Scansorial 0.11764706 Semi-aquatic 0.07058824 Semi-fossorial 0.12941176 Terrestrial 0.43529412

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Table S8. RDA error matrix (2.353 % incorrectly classified) Arboreal Cursorial Scansorial Semi-aquatic Semi-fossorial Terrestrial Sum Arboreal 12 0 0 0 0 2 2 Cursorial 0 7 0 0 0 0 0 Scansorial 0 0 10 0 0 0 0 Semi-aquatic 0 0 0 5 0 1 1 Semi-fossorial 0 0 0 0 10 1 1 Terrestrial 0 1 1 0 1 34 3 Sum 0 1 1 0 1 4 7

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Table S9. RDA classification results for extant sample with associated posterior values Semi- Species Designated Predicted Arboreal Cursorial Scansorial Semi-aquatic Terrestrial fossorial Marmosa mexicana arboreal arboreal 0.9998123 2.4302E-14 2.3829E-05 0.00013296 8.7525E-06 2.2186E-05 Dromiciops gliroides arboreal arboreal 0.9968349 6.8757E-12 0.00223188 0.00010073 0.00064403 0.00018848 Didelphis virginiana scansorial scansorial 8.0009E-08 4.195E-18 0.9999999 2.4949E-09 1.1395E-08 8.5399E-10 Trichosorus vulpecula scansorial scansorial 0.00121526 6.3886E-13 0.9987744 3.3554E-08 2.8454E-06 7.4273E-06 Caenolestes sp. scansorial scansorial 6.1134E-05 3.4104E-13 0.9999381 5.3312E-07 1.3288E-09 2.6172E-07

Chironectes minimus semi-aquatic semi-aquatic 7.4159E-05 1.3121E-10 4.0436E-05 0.9827059 1.1573E-05 0.01716792 Vombatus ursinus semi-fossorial semi-fossorial 2.353E-07 1.1946E-14 3.7478E-06 1.6291E-08 0.9999955 5.4111E-07 Sarcophilus harrisi terrestrial semi-fossorial 0.00343329 5.216E-09 0.00124764 0.00020137 0.7062053 0.2889124 Thylacinus cynocephalus terrestrial terrestrial 7.9345E-08 1.2841E-11 4.5235E-07 7.3315E-06 0.00118543 0.9988067 Metachirus nudicaudatus terrestrial terrestrial 0.00068744 4.0703E-15 0.00083331 0.00682453 0.00089967 0.9907551

Macropus giganteus terrestrial terrestrial 0.00057343 3.7235E-07 0.00054216 0.00031771 0.00043217 0.9981342 Thylogale thetis terrestrial terrestrial 2.2775E-05 4.0047E-09 0.00021253 0.0004594 0.00017973 0.9991256 Ailurus fulgens arboreal arboreal 0.7629001 1.5155E-12 0.2049339 0.00622938 0.00097309 0.02496345 Genetta genetta arboreal terrestrial 0.2459339 3.6796E-08 0.05648307 0.02441262 0.04411847 0.6290519 Tamandua tetradactyla arboreal terrestrial 0.1841215 1.6941E-09 0.00213338 0.001915 0.2575419 0.5542882

Alouatta seniculus arboreal arboreal 0.9999996 1.0719E-20 2.7738E-07 2.8989E-09 2.4859E-08 6.5336E-08 Cercopithecus neglectus arboreal arboreal 0.6257062 4.1562E-10 0.1990815 0.02446352 0.00508704 0.1456617 Colobus (Piliocolobus) arboreal arboreal 0.9490499 1.0364E-12 0.0196056 0.00258081 0.00128823 0.02747543 rufomitratus Hylobates pileatus arboreal arboreal 0.9997602 3.9404E-18 0.00023617 7.9746E-07 3.694E-07 2.4238E-06

Lagothrix lagotricha arboreal arboreal 0.9893032 2.732E-13 0.00939043 0.00045002 0.00012774 0.00072861 Perodicticus potto arboreal arboreal 0.993544 2.084E-09 0.00522575 0.00011819 7.9156E-05 0.00103296 Glis glis arboreal arboreal 0.8712588 1.3844E-14 0.1251091 5.5442E-05 0.00213368 0.00144294 Sciurus carolinensis arboreal arboreal 0.9760965 5.0406E-09 0.02267856 1.1149E-05 0.00011278 0.00110095 Ptilocercus lowii arboreal arboreal 0.9972665 3.0354E-11 0.00241563 1.442E-05 2.0387E-06 0.00030139

Alces alces cursorial cursorial 5.8494E-11 0.9999999 5.8294E-11 4.0831E-11 9.6855E-11 8.1519E-08 Bos taurus cursorial cursorial 4.3518E-11 0.9999999 1.7363E-11 3.1808E-12 4.2079E-12 1.1412E-07 Camelus sp. cursorial cursorial 1.7844E-09 0.9999888 2.306E-09 2.0461E-09 2.98E-09 1.1204E-05 Giraffa sp. cursorial cursorial 2.261E-12 1 3.0277E-12 6.8452E-13 1.2924E-13 1.3776E-08

Odocoileus virginianu cursorial cursorial 3.6366E-15 1 5.4503E-15 2.4719E-15 1.6774E-16 1.0355E-10

Ovis aries cursorial cursorial 1.2474E-13 1 1.6944E-14 1.4119E-15 2.5858E-16 5.1531E-11 Equus ferus caballus cursorial cursorial 1.8629E-09 0.999982 5.2467E-09 5.3852E-10 3.5257E-10 1.8032E-05 Eira barbara scansorial scansorial 0.14881 1.9352E-10 0.6793643 0.05136519 0.02901795 0.09144253 Felis wiedii scansorial scansorial 0.2600431 4.9056E-10 0.399586 0.01866501 0.00487965 0.3168263 Gulo gulo scansorial scansorial 0.01089922 5.4349E-10 0.6118079 0.01294343 0.01148511 0.3528643

Solenodon paradoxus scansorial scansorial 0.07316033 4.0352E-11 0.8640772 0.00163059 0.00062098 0.0605109

Papio ursinus scansorial scansorial 0.01695687 6.0747E-11 0.9478605 0.00335687 7.9136E-05 0.03174665 Erethizon dorsatum scansorial scansorial 0.02096928 3.3196E-08 0.737721 0.05942702 0.09895893 0.08292377

60

Rattus norvegicus scansorial scansorial 0.00398762 1.1661E-12 0.9959658 1.6355E-07 5.6369E-06 4.0797E-05 Enhydra lutris semi-aquatic semi-aquatic 0.01760501 3.3163E-10 0.00722176 0.758402 0.1404118 0.0763594 Lontra canadensis semi-aquatic terrestrial 0.00217007 2.1136E-09 0.00422801 0.3223952 0.00849483 0.6627118

Mustela (Neovison) vison semi-aquatic semi-aquatic 0.01558748 3.0424E-11 0.03819834 0.9083321 0.01050559 0.02737648 Castor canadensis semi-aquatic semi-aquatic 1.1197E-11 1.4139E-17 8.9733E-11 1 4.5409E-10 6.0689E-09 Ondatra zibethicus semi-aquatic semi-aquatic 0.01297634 1.3435E-11 0.00354236 0.9482313 0.01483459 0.02041545 Mellivora capensis semi-fossorial semi-fossorial 0.02663862 9.2908E-14 0.01359672 0.01182679 0.9359819 0.01195598 Mephitis mephitis semi-fossorial semi-fossorial 0.01004982 6.4321E-13 0.00181788 0.00756471 0.9668071 0.0137605

Taxidea taxus semi-fossorial terrestrial 0.00362575 7.8024E-09 0.00826489 0.02044796 0.4495008 0.5181606 Dasypus novemcinctus semi-fossorial semi-fossorial 1.2049E-05 3.4276E-11 6.6373E-07 1.024E-06 0.9993007 0.00068559 Priodontes maximus semi-fossorial semi-fossorial 6.9484E-06 1.3164E-08 1.3441E-05 0.00158168 0.9895355 0.00886243 Zaedyus pichiy semi-fossorial semi-fossorial 3.1822E-06 1.8918E-16 1.397E-06 1.8721E-06 0.999982 1.1598E-05 Cricetus cricetus semi-fossorial semi-fossorial 0.00172061 5.8911E-13 0.00066958 0.00371548 0.871038 0.1228563

Cynomys ludovicianus semi-fossorial semi-fossorial 0.04714444 7.6391E-11 0.03615623 0.03127859 0.5599614 0.3254594 Marmota monax semi-fossorial semi-fossorial 0.0449666 5.5589E-12 0.01028093 0.00738756 0.7125805 0.2247844 Orycteropus afer semi-fossorial semi-fossorial 3.077E-06 3.2892E-11 4.426E-07 0.00012772 0.9985736 0.00129516 Echinops telfairi terrestrial terrestrial 0.03584158 4.6218E-15 0.0345071 0.00123621 0.00114335 0.9272718 Hexaprotodon liberiensis terrestrial cursorial 1.4102E-08 0.9998119 2.2543E-08 1.6886E-07 4.7123E-08 0.00018789

Atilax paludinosus terrestrial terrestrial 0.08504581 9.0185E-10 0.01039076 0.09995654 0.2117557 0.5928512 Canis latrans terrestrial terrestrial 0.0038225 2.2441E-08 0.00054019 0.00114934 0.00242996 0.992058 Canis lupus terrestrial terrestrial 0.0011524 2.0957E-06 0.00137711 0.00911004 0.00112487 0.9872335 Canis mesomelas terrestrial terrestrial 0.00347418 4.5789E-09 0.0003917 0.00161864 0.00369928 0.9908162 Crocuta crocuta terrestrial terrestrial 0.00056241 1.3967E-09 0.0006312 0.01918433 0.00045788 0.9791642

Felis (Puma) concolor terrestrial terrestrial 0.00071128 6.5212E-08 0.00103802 0.01764397 0.00189612 0.9787105 Galictis vittata terrestrial terrestrial 0.00027304 3.868E-10 0.00062235 0.00650044 0.00164793 0.9909562 Herpestes javanicus terrestrial terrestrial 0.01623655 5.1562E-10 0.00461171 0.00563331 0.02307876 0.9504397 Hyaena hyaena terrestrial terrestrial 0.00039469 1.0285E-06 0.00061509 0.09560355 0.0006977 0.9026879 Lynx canadensis terrestrial terrestrial 0.01091594 6.08E-08 0.00956756 0.03677397 0.03450742 0.9082351

Prokenia pennanti terrestrial scansorial 0.2884447 2.3704E-11 0.5126356 0.02510972 0.01353258 0.1602775 Panthera leo terrestrial terrestrial 0.00096456 7.2509E-08 0.00164492 0.00276177 0.00691053 0.9877181 Panthera onca terrestrial terrestrial 0.00468973 7.9088E-08 0.03052894 0.00284945 0.00744803 0.9544838 Panthera tigris terrestrial terrestrial 0.00027215 6.4082E-10 0.00105486 0.00308797 0.01637487 0.9792102 Procyon lotor terrestrial terrestrial 0.1011148 5.7922E-09 0.07162826 0.01402744 0.05538845 0.757841 Pseudalopex (Lycalopex) terrestrial terrestrial 0.01529829 9.5698E-11 0.00530269 0.01558251 0.01626344 0.9475531 griseus Uncia (Panthera) uncia terrestrial terrestrial 0.00170687 6.3577E-09 0.0028142 0.00429419 0.01022031 0.9809644 Urocyon cinereoargenteus terrestrial terrestrial 0.01234706 3.0519E-08 0.00090204 0.00541175 0.00351469 0.9778244 Ursus arctos terrestrial terrestrial 0.00018697 1.9229E-05 0.00023246 7.2633E-05 0.00036747 0.9991212

Ursus maritimus terrestrial terrestrial 0.00128129 1.4514E-06 0.00156968 0.0034254 0.03725833 0.9564639 Vulpes vulpes terrestrial terrestrial 0.00327275 9.3518E-09 0.00044155 0.00793368 0.00088423 0.9874678 Erinaceus europaeus terrestrial terrestrial 0.07030162 1.8138E-11 0.01188835 0.03385121 0.01094778 0.873011

61

Procavia capensis terrestrial terrestrial 0.01106014 1.2666E-08 0.00727954 0.00194635 0.00790273 0.9718112 Lepus americanus terrestrial terrestrial 0.00013017 1.4205E-08 0.00042256 0.01152615 0.00515604 0.9827651 Rhynchocyon cirnei terrestrial terrestrial 0.00229346 1.3714E-12 0.01346394 0.00429064 0.02373469 0.9562173

Tapirus sp. terrestrial terrestrial 0.00336466 9.3887E-05 0.0009962 0.00161809 0.00314171 0.9907854 Loxodonta africana terrestrial terrestrial 9.3055E-06 1.5558E-09 2.0942E-05 5.9459E-05 0.00036582 0.9995445 Hydrochoerus sp. terrestrial terrestrial 0.00048409 1.7145E-06 0.00050683 0.0081635 0.0173623 0.9734816 Hystrix cristata terrestrial terrestrial 0.00019375 3.0334E-10 0.00011169 0.00193196 0.00273795 0.9950247 Pedetes capensis terrestrial terrestrial 0.1018324 1.561E-08 0.0330731 0.00885619 0.00308462 0.8531537

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Table S10. Predictions of locomotion classification with associated posteriors for extinct species derived from RDA Semi- Semi- Species Predicted Arboreal Cursorial Scansorial Terrestrial aquatic fossorial Afrodon gheerbranti scansorial 4.86E-05 1.18E-22 1.00E+00 2.18E-07 3.96E-05 1.28E-05 Bustylus marandati scansorial 4.99E-03 2.41E-21 9.95E-01 5.29E-05 2.37E-05 1.43E-05 Palaeostylops iturus terrestrial 1.46E-03 4.53E-11 6.96E-03 1.58E-02 3.29E-01 6.47E-01 Alcidedorbignya inopinata semi-fossorial 8.27E-03 3.38E-10 2.35E-01 6.39E-06 4.48E-01 3.09E-01 Pantolambda bathmodon terrestrial 1.19E-02 2.80E-08 1.34E-02 3.91E-03 1.92E-01 7.79E-01 Chriacus sp. scansorial 3.11E-01 6.69E-11 5.56E-01 2.21E-02 1.01E-02 1.00E-01 Ectoconus ditrigonus terrestrial 1.44E-04 2.02E-06 3.00E-04 7.75E-04 4.67E-02 9.52E-01 Periptychus carinidens terrestrial 3.09E-02 1.17E-08 8.92E-02 1.71E-05 2.58E-01 6.22E-01 Protungulatum sp. terrestrial 2.98E-03 1.00E-12 1.10E-03 9.99E-03 1.44E-01 8.42E-01 Claenodon corrugatus terrestrial 8.54E-04 2.72E-07 4.57E-04 5.01E-05 6.08E-03 9.93E-01 Arctocyon primaevus arboreal 5.08E-01 1.71E-07 2.57E-01 1.27E-04 5.78E-04 2.34E-01 Tetraclaenodon puercensis terrestrial 2.43E-01 5.96E-08 9.61E-03 8.51E-03 1.70E-01 5.68E-01 Goniacodon levisanus terrestrial 2.56E-02 8.65E-09 7.77E-02 2.59E-02 1.43E-01 7.28E-01 Phenacodus intermedius terrestrial 2.49E-03 4.77E-08 8.50E-03 2.02E-05 2.96E-02 9.59E-01 Pleuraspidotherium aumonieri semi-fossorial 5.44E-06 4.47E-15 2.09E-05 5.16E-05 1.00E+00 3.72E-04 Orthaspidotherium edwardsi semi-fossorial 3.19E-05 4.11E-13 1.29E-03 4.80E-03 9.81E-01 1.26E-02 Hyopsodus paulus semi-fossorial 3.04E-01 2.27E-10 8.62E-03 1.03E-03 6.18E-01 6.85E-02 Microhyus reisi semi-fossorial 3.85E-03 1.78E-13 3.60E-03 1.43E-04 8.50E-01 1.42E-01 Paschatherium dolloi semi-fossorial 1.88E-02 4.35E-15 7.15E-02 5.61E-04 7.42E-01 1.67E-01 Macrocranion vandebroeki terrestrial 2.11E-01 2.53E-08 4.24E-02 3.01E-02 1.76E-01 5.41E-01 Plagioctenodon rosei arboreal 8.14E-01 1.32E-12 8.04E-02 3.70E-03 9.80E-02 3.97E-03 Prodiacodon puercensis semi-fossorial 1.42E-01 2.97E-09 2.08E-01 7.63E-05 3.62E-01 2.88E-01 Apheliscus insidiosus semi-fossorial 1.43E-02 3.20E-09 6.28E-03 1.02E-03 5.41E-01 4.37E-01 Haplomylus speirianus terrestrial 4.60E-03 4.16E-10 1.78E-03 4.56E-04 4.11E-01 5.82E-01 Dissacus navajovius terrestrial 5.87E-05 6.99E-05 4.70E-03 5.27E-05 9.49E-02 9.00E-01 Pachyaena gracilis terrestrial 4.92E-04 5.45E-05 3.99E-01 8.29E-07 8.10E-04 6.00E-01 Colbertia magellanica scansorial 3.38E-01 5.54E-11 4.04E-01 4.88E-05 1.03E-01 1.55E-01 Ignacius graybullianus semi-fossorial 3.02E-01 7.27E-11 1.48E-02 1.29E-03 5.85E-01 9.68E-02 Plesiadapis cookei arboreal 5.96E-01 6.80E-11 3.24E-01 2.69E-03 5.53E-03 7.21E-02 Carpolestes simpsoni arboreal 8.05E-01 2.75E-14 1.95E-01 3.50E-05 3.97E-05 6.01E-05 Dryomomys szalayi arboreal 7.80E-01 1.92E-14 2.16E-01 1.75E-03 1.26E-03 8.50E-04 Purgatorius sp. arboreal 5.02E-01 1.28E-09 3.04E-01 1.09E-03 1.44E-01 4.89E-02 Pseudictops lophiodon semi-fossorial 3.55E-03 5.06E-09 1.80E-03 1.13E-02 7.33E-01 2.50E-01 Tribosphenomys minutus semi-fossorial 8.24E-04 8.57E-20 5.55E-04 1.02E-06 9.99E-01 1.55E-05 Conoryctes comma terrestrial 1.35E-01 7.56E-09 1.25E-02 2.02E-01 2.54E-01 3.96E-01 Ectoganus sp. semi-fossorial 2.09E-03 2.91E-01 1.04E-02 2.60E-05 5.10E-01 1.86E-01 Onychodectes tisonensis terrestrial 4.25E-03 1.73E-10 1.44E-02 1.11E-03 2.90E-01 6.90E-01 Didymictis protenus terrestrial 3.92E-03 1.76E-09 8.07E-03 8.20E-04 3.69E-01 6.18E-01 Carodnia vierai terrestrial 9.61E-04 4.20E-09 7.61E-04 2.12E-04 9.01E-04 9.97E-01 Procerberus formicarum semi-fossorial 4.11E-01 4.16E-12 1.30E-02 2.78E-04 5.10E-01 6.48E-02 Ukhaatherium nessovi arboreal 8.01E-01 4.74E-19 1.96E-01 1.25E-04 3.27E-03 1.94E-05 Sulestes karakshi arboreal 9.56E-01 1.38E-11 4.29E-02 6.55E-04 1.55E-06 5.80E-04 Deccanolestes hislopi arboreal 8.95E-01 2.51E-18 9.89E-02 6.76E-05 4.82E-03 1.09E-03 Vincelestes neuquenianus terrestrial 1.64E-01 3.04E-13 2.97E-02 8.24E-02 1.58E-01 5.66E-01 Kulbeckia kulbecke terrestrial 4.17E-02 1.74E-04 4.62E-01 1.84E-03 6.20E-03 4.89E-01

63

Table S11. PERMANOVA results on Principal Component scores and Discriminant Functions for Paleocene species grouped by locomotor mode as determine by the RDA Comparison Df Sums of F model R2 p value p adjusted BFB squares scansorial vs

terrestrial 1 15.3342262 5.65502566 0.22936604 0.00029997 0.00220478 27.277

scansorial vs semi- fossorial 1 10.5762081 3.6706774 0.19660119 0.00059994 0.00293971 21.467 scansorial vs arboreal 1 6.25768319 2.33056774 0.22559919 0.01939806 0.0570303 2.252 terrestrial vs semi- fossorial 1 4.93719015 1.89036219 0.0632432 0.02479752 0.06075392 2.162 terrestrial vs

Principal Component scores PrincipalComponent arboreal 1 9.00700036 3.68055551 0.14912774 1.00E-04 0.00146985 38.372 semi-fossorial vs arboreal 1 5.6921737 2.24572939 0.11668715 0.01049895 0.03858364 2.929 scansorial vs terrestrial 1 87.931496 6.05771952 0.24175063 0.00139986 0.01028897 7.812

scansorial vs semi- fossorial 1 115.803938 5.7848662 0.27832107 0.00069993 0.01028897 7.812 scansorial vs arboreal 1 40.9847819 2.04598797 0.2036622 0.05569443 0.13645135 1.354 terrestrial vs semi- fossorial 1 64.589607 4.37859255 0.1352311 0.00609939 0.02241526 4.321

terrestrial vs Discriminant Functions Discriminant arboreal 1 52.7342112 4.05629775 0.16188735 0.0049995 0.02241526 4.321 semi-fossorial vs arboreal 1 62.1817097 3.55333649 0.17288368 0.02229777 0.06555544 2.059

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Table S12. PERMANOVA results on the Discriminant Functions for extant species grouped by locomotor mode Sums of p Comparison Df F model R2 p value BFB squares adjusted

arboreal vs scansorial 1 32.561675 6.0414136 0.21544611 0.00039996 0.00142196 39.464

arboreal vs semi-aquatic 1 64.9819116 11.6725436 0.3933786 0.00019998 0.00082947 62.513 arboreal vs semi-fossorial 1 89.7506441 18.5783028 0.44682687 1.00E-04 0.00045244 105.586

arboreal vs terrestrial 1 107.66837 20.9179912 0.29917895 1.00E-04 0.00045244 105.586

arboreal vs cursorial 1 422.857308 95.4233164 0.83394993 1.00E-04 0.00045244 105.586 scansorial vs semi-aquatic 1 73.2827532 12.3414158 0.46851756 0.00029997 0.0011485 47.318 scansorial vs semi-fossorial 1 121.413105 24.5316525 0.56353598 1.00E-04 0.00045244 105.586

scansorial vs terrestrial 1 96.5883502 18.4850108 0.29117126 1.00E-04 0.00045244 105.586

scansorial vs cursorial 1 318.723582 71.2281271 0.82604284 1.00E-04 0.00045244 105.586 semi-aquatic vs semi- fossorial 1 46.8225684 9.28177399 0.38225271 1.00E-04 0.00045244 105.586 semi-aquatic vs terrestrial 1 77.5998442 14.6774069 0.26361513 1.00E-04 0.00045244 105.586

semi-aquatic vs cursorial 1 359.915206 81.2062072 0.88070217 0.00079992 0.00265432 23.366 semi-fossorial vs terrestrial 1 117.60455 23.7613788 0.34060936 1.00E-04 0.00045244 105.586 semi-fossorial vs cursorial 1 498.700533 133.750248 0.89315544 1.00E-04 0.00045244 105.586

terrestrial vs cursorial 1 403.262431 84.3657616 0.66763149 1.00E-04 0.00045244 105.586

65

Table S13. PERMANOVA results on equivalent extant versus extinct locomotor groups (fossil species classified using apparent RDA classification) Comparison Df Sums of F model R2 p value p adjusted BFB squares arboreal vs Paleocene 1 10.7982171 3.36763697 0.13820121 0.0019998 0.01363813 6.281 arboreal scansorial vs

1 10.2894374 2.4853373 0.17157607 0.02149785 0.11810242 1.458 Paleocene scansorial semi-fossorial vs scores Paleocene semi- 1 8.21729362 2.93920229 0.1178547 0.00139986 0.01064823 7.606 fossorial

Principal Component PrincipalComponent terrestrial vs 1 20.2545405 7.19532547 0.11757966 1.00E-04 0.00131835 42.079 Paleocene terrestrial

arboreal vs Paleocene 1 16.1239073 1.56947468 0.06953971 0.19058094 0.83759335 2.478 arboreal scansorial vs 1 24.7799745 2.24815099 0.15778546 0.05809419 0.26719635 1.043 Paleocene scansorial semi-fossorial vs Paleocene semi- 1 21.4844383 1.80373732 0.07577538 0.13078692 0.58786541 1.178 fossorial terrestrial vs Discriminant Functions Discriminant 1 454.551084 42.6341312 0.63982422 1.00E-04 0.00082397 45.962 Paleocene terrestrial

66

Table S14. Results of disparity tests when extant sample is differentiated into marsupial and placental taxa. Abbreviations: Bhatt. Coeff., Bhattacharyya Coefficient, K, Cretaceous, Ma., Marsupials, Pc, Paleocene, Pl., Placentals PCA disparity DFA disparity Wilcoxon Rank-Sum Bhatt. Permutation test Wilcoxon Rank-Sum Bhatt. Permutation test

p value BFB Coeff. p value BFB p value BFB Coeff. p value BFB -66 63 -66 63

Ma vs. Pl 2.37x10 1.03x10 0.000 0.004 17.757 1.76x10 1.38x10 0.000 0.761 1.772 Ma vs. Pc 3.28x10-66 7.44x1062 0.092 0.022 4.426 1.76x10-66 1.38x1063 0.000 0.044 2.677 anges Ma vs. K 1.25x10-65 1.97x1062 0.080 0.381 1.001 8.06x10-43 4.71x1039 0.455 0.119 1.451 Pl vs. Pc 2.49x10-52 1.24x1049 0.494 0.258 1.052 3.88x10-54 7.71x1050 0.365 0.002 37.718 Pl vs. K 2.37x10-66 1.03x1063 0.000 0.010 7.806 1.76x10-66 1.38x1063 0.000 0.261 1.049 SumR of Pc vs. K 2.37x10-66 1.03E+63 0.000 0.057 2.248 1.76x10-66 1.38x1063 0.000 0.974 14.447 Ma vs. Pl 7.24x10-55 4.08x1051 0.386 0.133 1.369 1.83x10-29 3.04x1026 0.721 0.717 1.543

Ma vs. Pc 4.08x10-50 7.93x1046 0.496 0.079 1.832 5.23x10-60 5.15x1056 0.309 0.174 1.211 Ma vs. K 1.76x10-22 4.17x1019 0.731 0.918 4.700 3.85x10-28 1.51x1025 0.576 0.130 1.386

Pl vs. Pc 0.624 1.25 0.899 0.916 4.567 2.73x10-37 1.60x1034 0.694 0.144 1.317 Sum of Variances Pl vs. K 2.01x10-04 215.023 0.690 0.406 1.005 9.59x10-06 3.32x103 0.835 0.645 1.299 Pc vs. K 1.33x10-04 309.04 0.809 0.322 1.008 1.32x10-15 8.13x1012 0.797 0.949 7.349 Ma vs. Pl 4.50x10-42 8.59x1038 0.567 0.081 1.811 1.69x10-12 8.03x109 0.866 0.992 45.602 -40 37 -57 53 Ma vs. Pc 1.50x10 2.67x10 0.628 0.048 2.524 3.52x10 8.04x10 0.351 0.249 1.062 Ma vs. K 1.40x10-28 4.10x1025 0.644 0.998 167.402 1.33x10-10 1.22x108 0.686 0.102 1.583 Pl vs. Pc 0.250 1.06 0.916 0.840 2.515 2.79x10-45 1.29x1042 0.574 0.047 2.560 Distance Pl vs. K 0.104 1.56 0.585 0.295 1.021 0.00307 20.724 0.725 0.370 1.000 Mean Pairwise Pairwise Mean Pc vs. K 0.153 1.28 0.756 0.272 1.039 9.44x10-15 1.21x1012 0.746 0.724 1.575

67

Table S15. Mahalanobis distances (scaled Euclidean distances) using the 29 PC scores and five DFs for each taxon PC scores DFs Mahalanobis Mahalanobis p value BFB p value BFB distance distance Marmosa mexicana 48.0260311 0.01064715 7.606 3.14003187 0.53467091 1.099 Dromiciops gliroides 45.9688767 0.01755791 5.183 3.53347863 0.47280614 1.039 Didelphis virginiana 61.5411632 0.00025788 172.643 8.44896827 0.07644926 1.872 Trichosorus vulpecula 34.2052355 0.19419745 1.156 7.80310235 0.09906298 1.606 Caenolestes sp. 43.7736708 0.02925215 3.561 7.51565021 0.11102116 1.508 Chironectes minimus 31.9385979 0.27701685 1.035 7.17791822 0.12677951 1.405 Vombatus ursinus 62.1458833 0.00021512 202.517 3.8988709 0.41986516 1.010 Sarcophilus harrisi 27.1930777 0.50775256 1.069 1.36060067 0.85101307 2.680 Thylacinus cynocephalus 49.8232827 0.00676744 10.882 5.83915492 0.21148661 1.120 Metachirus nudicaudatus 40.5333332 0.05922657 2.198 1.96855309 0.74154298 1.659 Macropus giganteus 42.2397147 0.04115523 2.802 1.10317312 0.89376843 3.665 Thylogale thetis 51.124483 0.00483151 14.279 0.70977808 0.95011763 7.567 Ailurus fulgens 23.6433145 0.70021516 1.474 2.25094127 0.68971461 1.436 Genetta genetta 12.8753663 0.993439 56.256 0.17662005 0.99632281 100.228 Tamandua tetradactyla 29.3427793 0.39529956 1.003 0.20070295 0.99528931 78.279 Alouatta seniculus 72.6746674 7.80E-06 4010.074 11.1413071 0.02502099 3.987 Cercopithecus neglectus 20.3048733 0.85309828 2.714 1.50555192 0.82565756 2.326 Colobus (Piliocolobus) rufomitratus 22.4867717 0.75827332 1.753 2.44387393 0.65471344 1.327 Hylobates pileatus 46.1664903 0.01674913 5.371 5.35566243 0.25271119 1.058 Lagothrix lagotricha 29.5859332 0.38327898 1.001 3.9033408 0.41924527 1.009 Perodicticus potto 32.7699154 0.24432023 1.068 4.70044287 0.31943707 1.009 Glis glis 36.9242735 0.12053996 1.442 6.32874466 0.17590578 1.203 Sciurus carolinensis 39.5472876 0.0725133 1.933 2.77192549 0.59668853 1.194 Ptilocercus lowii 33.1327598 0.23089024 1.087 2.75613266 0.59942846 1.199 Alces alces 29.4686469 0.3890557 1.002 10.1995556 0.03719706 3.005 Bos taurus 24.968506 0.62954902 1.263 11.7045711 0.01968884 4.757 Camelus sp. 28.0104831 0.46389212 1.032 9.99767015 0.04046695 2.834 Giraffa sp. 32.0952841 0.27065071 1.040 12.2535466 0.01556213 5.679 Odocoileus virginianu 37.8097436 0.10205259 1.579 13.3646644 0.00962483 8.231 Ovis aries 35.4818626 0.15627181 1.268 14.655272 0.0054723 12.908 Equus ferus caballus 45.6086938 0.01912422 4.862 8.00127537 0.09153149 1.681 Eira barbara 17.9228764 0.92807519 5.311 0.60268961 0.96276434 10.070 Felis wiedii 12.2067093 0.9958008 87.792 1.86959283 0.75972838 1.762 Gulo gulo 23.6051562 0.70219486 1.482 1.85219931 0.76291962 1.782 Solenodon paradoxus 32.4263911 0.25750774 1.053 2.32015426 0.6771021 1.393 Papio ursinus 27.2511837 0.50460266 1.066 5.08143962 0.27904289 1.033 Erethizon dorsatum 24.3248508 0.66427857 1.354 1.38472792 0.84684499 2.613 Rattus norvegicus 31.2966171 0.30406792 1.016 4.20272165 0.37926511 1.000 Enhydra lutris 16.8112032 0.95222557 7.892 3.4772533 0.48134545 1.045 Lontra canadensis 13.69654 0.98920529 34.265 4.22108308 0.37691156 1.000 Mustela(Neovison) vison 22.4499792 0.76004565 1.764 3.39360465 0.49423924 1.056 Castor canadensis 56.3300692 0.00117233 46.498 16.9865575 0.00194461 30.304 Ondatra zibethicus 18.7892449 0.90451208 4.053 5.2455852 0.26301415 1.047 Mellivora capensis 23.5388969 0.70562337 1.495 1.42016386 0.84068298 2.522 Mephitis mephitis 28.5468773 0.43577059 1.016 2.63161745 0.62123257 1.244 Taxidea taxus 13.954706 0.98750683 29.632 0.86692236 0.92925763 5.396 Dasypus novemcinctus 39.6923445 0.07041255 1.969 4.11779575 0.3902986 1.002 Priodontes maximus 37.0962031 0.11675405 1.467 4.02149693 0.40310437 1.004 Zaedyus pichiy 36.2221915 0.13702668 1.351 5.33480819 0.25463605 1.056 Cricetus cricetus 14.5192343 0.98307575 21.923 1.83734766 0.76564276 1.799 Cynomys ludovicianus 17.1618031 0.94532401 6.921 0.24091737 0.99330199 55.109 Marmota monax 19.0849889 0.89549324 3.722 0.6834131 0.95335856 8.079 Orycteropus afer 36.8055358 0.12321142 1.426 3.61244838 0.46098752 1.031 Echinops telfairi 41.3703903 0.04964685 2.468 4.03989856 0.4006331 1.004 Hexaprotodon liberiensis 25.7998234 0.58404683 1.171 8.18429475 0.0850558 1.755 Atilax paludinosus 15.5572721 0.97193208 13.295 1.55218659 0.81735879 2.232 Canis latrans 24.8725379 0.63476389 1.275 2.21954801 0.69545208 1.456 Canis lupus 18.5243508 0.91216777 4.387 2.54641624 0.63634398 1.279 Canis mesomelas 32.1432954 0.26871881 1.042 1.72066064 0.78696126 1.951 Crocuta crocuta 29.1224331 0.40633762 1.005 3.36625561 0.49850354 1.060 Felis (Puma) concolor 22.3306809 0.76575672 1.800 2.04117467 0.72818575 1.593 Galictis vittata 24.6676271 0.64585949 1.303 2.4682004 0.65033891 1.315 Herpestes javanicus 38.4979589 0.08934216 1.705 1.1216911 0.89081558 3.572 Hyaena hyaena 23.1304969 0.72648202 1.585 5.26174054 0.26147989 1.049 68

Lynx canadensis 14.0853187 0.98657219 27.583 0.70610103 0.95057441 7.635 Martes pennanti 15.9778624 0.96614599 11.056 1.54239393 0.81910631 2.251 Panthera leo 19.0593312 0.89629538 3.749 4.38804774 0.35602927 1.001 Panthera onca 12.4865314 0.9949145 72.524 1.52728836 0.82179693 2.281 Panthera tigris 13.1626604 0.99214375 47.011 3.48029369 0.48088105 1.045 Procyon lotor 99.9121382 5.23E-10 32913195.584 0.50050297 0.973452 14.045 Pseudalopex (Lycalopex) griseus 13.6919771 0.98923359 34.355 1.48893894 0.82859897 2.361 Uncia (Panthera) uncia 12.8740563 0.99344449 56.303 2.32925259 0.67544837 1.388 Urocyon cinereoargenteus 14.3763524 0.98429596 23.612 1.47828431 0.83048104 2.385 Ursus arctos 22.016052 0.78054747 1.902 3.58876591 0.46451026 1.033 Ursus maritimus 14.5461895 0.98283768 21.622 0.60271881 0.96276109 10.069 Vulpes vulpes 24.7130113 0.64340695 1.297 4.34129335 0.36178285 1.000 Erinaceus europaeus 33.6678865 0.21202205 1.119 2.68683184 0.61152083 1.223 Procavia capensis 35.1853322 0.16453654 1.239 3.00382792 0.55718501 1.129 Lepus americanus 27.4695839 0.49280231 1.055 2.08363654 0.72037919 1.557 Rhynchocyon cirnei 34.1771348 0.19510188 1.154 3.41968909 0.49019438 1.053 Tapirus sp. 22.7783414 0.74405163 1.672 1.08371146 0.89684788 3.768 Loxodonta africana 43.020639 0.03464574 3.158 2.37530727 0.66709417 1.362 Hydrochoerus sp. 14.4269104 0.98387215 22.997 2.38781882 0.66482971 1.355 Hystrix cristata 29.7773066 0.37394147 1.000 2.09332729 0.71859837 1.549 Pedetes capensis 26.5865621 0.54083643 1.107 1.57887715 0.81258346 2.181 Afrodon gheerbranti 75.0526125 3.56E-06 8236.807 26.7734814 2.21E-05 1552.820 Bustylus marandati 32.7105552 0.24656621 1.066 18.1971739 0.00112926 48.005 Palaeostylops iturus 25.2788493 0.61261924 1.225 1.32278703 0.85749769 2.791 Alcidedorbignya inopinata 33.9620313 0.20212617 1.138 2.14343482 0.70939735 1.510 Pantolambda bathmodon 17.814035 0.93073678 5.507 2.79465448 0.5927558 1.187 Chriacus sp. 40.7487385 0.05662023 2.263 6.61806683 0.15750158 1.264 Ectoconus ditrigonus 17.1452863 0.94566361 6.963 2.51523629 0.64190959 1.293 Periptychus carinidens 16.2215244 0.96242413 9.980 3.86632543 0.42439891 1.011 Protungulatum sp. 27.4401897 0.49438671 1.056 6.71313607 0.15184676 1.285 Claenodon corrugatus 34.6051772 0.18165373 1.187 13.0428958 0.01106809 7.380 Arctocyon primaevus 32.0461987 0.27263496 1.038 5.9382655 0.20380632 1.135 Tetraclaenodon puercensis 22.7166201 0.74708771 1.689 0.49184719 0.97428979 14.497 Goniacodon levisanus 41.4473226 0.04883812 2.495 6.47695662 0.16624811 1.233 Phenacodus intermedius 27.2863504 0.50269831 1.064 10.6132683 0.031272 3.395 Pleuraspidotherium aumonieri 30.6322907 0.33364826 1.004 14.8022482 0.00512944 13.602 Orthaspidotherium edwardsi 26.4813947 0.5466018 1.114 11.7954749 0.01893877 4.897 Hyopsodus paulus 24.4346516 0.65839982 1.337 3.53884536 0.47199646 1.038 Microhyus reisi 28.4113798 0.44281605 1.020 8.10502212 0.08780598 1.722 Paschatherium dolloi 23.0873481 0.72865655 1.595 5.28566902 0.25922149 1.051 Macrocranion vandebroeki 19.0526602 0.89650332 3.756 1.24610809 0.87045044 3.046 Plagioctenodon rosei 20.037154 0.86310624 2.895 5.61599683 0.22971986 1.089 Prodiacodon puercensis 17.3511618 0.94132658 6.463 4.67571927 0.32221706 1.008 Apheliscus insidiosus 16.1289983 0.96387031 10.372 1.93855596 0.74705908 1.689 Haplomylus speirianus 22.5068043 0.75730619 1.747 3.96587939 0.41064327 1.007 Dissacus navajovius 32.6842786 0.24756481 1.064 9.65745873 0.04661046 2.574 Pachyaena gracilis 41.3371958 0.04999939 2.456 3.14318745 0.53415571 1.098 Colbertia magellanica 37.6518388 0.10516869 1.553 3.5717006 0.46706018 1.035 Ignacius graybullianus 28.4588988 0.44034048 1.019 6.3310632 0.17575089 1.204 Plesiadapis cookei 33.3694807 0.22240568 1.100 1.57621304 0.8130609 2.186 Carpolestes simpsoni 27.1189911 0.51177456 1.073 11.9208341 0.01794978 5.098 Dryomomys szalayi 24.265577 0.66744298 1.363 3.58579825 0.464953 1.033 Purgatorius sp. 21.5073704 0.8035712 2.093 2.12464264 0.71284654 1.525 Pseudictops lophiodon 17.3284118 0.94181699 6.516 1.80233559 0.77205502 1.842 Tribosphenomys minutus 35.0186763 0.16932433 1.223 11.4482509 0.0219624 4.387 Conoryctes comma 28.4600187 0.4402822 1.019 1.1334718 0.88892582 3.515 Ectoganus sp 72.2582399 8.95E-06 3536.163 19.2950403 0.00068768 73.461 Onychodectes tisonensis 18.7379553 0.90602556 4.114 2.70992804 0.60747845 1.215 Didymictis protenus 23.2427433 0.72079816 1.559 1.05722193 0.90099866 3.917 Carodnia vierai 49.5075143 0.00733598 10.203 9.64670051 0.04681861 2.567 Procerberus formicarum 18.5264845 0.91210769 4.384 3.77598013 0.43717169 1.017 Ukhaatherium nessovi 63.5811431 0.00013929 297.462 17.0670355 0.00187583 31.235 Sulestes karakshi 56.6652567 0.00106645 50.407 15.3437866 0.00403881 16.526 Deccanolestes hislopi 50.6423334 0.00547867 12.896 7.4432937 0.11423595 1.484 Vincelestes neuquenianus 26.3319023 0.55480632 1.126 6.14262061 0.18874745 1.169 Kulbeckia kulbecke 44.5537057 0.0244699 4.052 4.92178996 0.29541688 1.021

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Table S16. Total evidence summary table on Paleocene mammal locomotor classifications derived from this study and compared with existing literature. Morphospace nearest neighbours calculated using all axes. PC morphospace DF morphospace RDA Posterior values for RDA classification Literature Species nearest neighbour nearest neighbour classification Arboreal Cursorial Scansorial Semi-aquatic Semi-fossorial Terrestrial Classification Based on References Afrodon gheerbranti Metachirus nudicaudatus Didelphis virginiana scansorial 0.0000486 1.18E-22 1 0.000000218 0.0000396 0.0000128 Arboreal Tarsals and limb bones [46–48] Bustylus marandati Didelphis virginiana Didelphis virginiana scansorial 0.00499 2.41E-21 0.995 0.0000529 0.0000237 0.0000143 Arboreal Tarsals [46] Palaeostylops iturus Cricetus cricetus Marmota monax terrestrial 0.00146 4.53E-11 0.00696 0.0158 0.329 0.647 Terrestrial Tarsals [49] Alcidedorbignya inopinata Sarcophilus harrisi Ursus maritimus semi-fossorial 0.00827 3.38E-10 0.235 0.00000639 0.448 0.309 Terrestrial Skeleton [29] Pantolambda bathmodon Sciurus carolinensis Taxidea taxus terrestrial 0.0119 0.000000028 0.0134 0.00391 0.192 0.779 - - - Chriacus sp. Dromiciops gliroides Enhydra lutris scansorial 0.311 6.69E-11 0.556 0.0221 0.0101 0.1 Arboreal Skeleton [50] Ectoconus ditrigonus Taxidea taxus Thylacinus cynocephalus terrestrial 0.000144 0.00000202 0.0003 0.000775 0.0467 0.952 Terrestrial Skeleton [51,52] Periptychus carinidens Uncia (Panthera) uncia Vombatus ursinus terrestrial 0.0309 1.17E-08 0.0892 0.0000171 0.258 0.622 Terrestrial Skeleton [52] Protungulatum sp. Rhynchocyon cirnei Cricetus cricetus terrestrial 0.00298 1E-12 0.0011 0.00999 0.144 0.842 Terrestrial Tarsals and fragmentary skeleton [31] Claenodon corrugatus Hydrochoerus sp. Ursus arctos terrestrial 0.000854 0.000000272 0.000457 0.0000501 0.00608 0.993 - - - Arctocyon primaevus Trichosorus vulpecula Ursus arctos arboreal 0.508 0.000000171 0.257 0.000127 0.000578 0.234 Scansorial Skeleton [53,54] Tetraclaenodon puercensis Mephitis mephitis Taxidea taxus terrestrial 0.243 5.96E-08 0.00961 0.00851 0.17 0.568 Terrestrial Skeleton [55] Goniacodon levisanus Uncia (Panthera) uncia Enhydra lutris terrestrial 0.0256 8.65E-09 0.0777 0.0259 0.143 0.728 - - - Phenacodus intermedius Hydrochoerus sp. Canis latrans terrestrial 0.00249 4.77E-08 0.0085 0.0000202 0.0296 0.959 Cursorial Skeleton [56] Pleuraspidotherium aumonieri Cricetus cricetus Zaedyus pichiy semi-fossorial 0.00000544 4.47E-15 0.0000209 0.0000516 1 0.000372 Terrestrial/Scansorial Tarsals [57,58] Orthaspidotherium edwardsi Cricetus cricetus Zaedyus pichiy semi-fossorial 0.0000319 4.11E-13 0.00129 0.0048 0.981 0.0126 Terrestrial/Scansorial Tarsals [58] Hyopsodus paulus Mephitis mephitis Mephitis mephitis semi-fossorial 0.304 2.27E-10 0.00862 0.00103 0.618 0.0685 Terrestrial Tarsals [59] Microhyus reisi Rhynchocyon cirnei Dasypus novemcinctus semi-fossorial 0.00385 1.78E-13 0.0036 0.000143 0.85 0.142 Terrestrial Tarsals [59] Paschatherium dolloi Rhynchocyon cirnei Marmota monax semi-fossorial 0.0188 4.35E-15 0.0715 0.000561 0.742 0.167 Arboreal Tarsals [60] Macrocranion vandebroeki Herpestes javanicus Sarcophilus harrisi terrestrial 0.211 2.53E-08 0.0424 0.0301 0.176 0.541 Terrestrial Tarsals [60] Plagioctenodon rosei Ptilocercus lowii Mephitis mephitis arboreal 0.814 1.32E-12 0.0804 0.0037 0.098 0.00397 Arboreal Tarsals [61] Prodiacodon puercensis Rattus norvegicus Vombatus ursinus semi-fossorial 0.142 2.97E-09 0.208 0.0000763 0.362 0.288 Scansorial Tarsals [62] Apheliscus insidiosus Mephitis mephitis Mephitis mephitis semi-fossorial 0.0143 3.2E-09 0.00628 0.00102 0.541 0.437 Terrestrial Tarsals and limb bones [63] Haplomylus speirianus Cricetus cricetus Dasypus novemcinctus terrestrial 0.0046 4.16E-10 0.00178 0.000456 0.411 0.582 Terrestrial Tarsals and limb bones [63] Dissacus navajovius Gulo gulo Vombatus ursinus terrestrial 0.0000587 0.0000699 0.0047 0.0000527 0.0949 0.9 Terrestrial/Cursorial Tarsals and limb bones [57] Pachyaena gracilis Sciurus carolinensis Panthera onca terrestrial 0.000492 0.0000545 0.399 0.000000829 0.00081 0.6 Terrestrial/Cursorial Tarsals and limb bones [64] Colbertia magellanica Ptilocercus lowii Marmota monax scansorial 0.338 5.54E-11 0.404 0.0000488 0.103 0.155 - - - Ignacius graybullianus Marmota monax Dasypus novemcinctus semi-fossorial 0.302 7.27E-11 0.0148 0.00129 0.585 0.0968 Arboreal Tarsals and limb bones [44] Plesiadapis cookei Eira barbara Cynomys ludovicianus arboreal 0.596 6.8E-11 0.324 0.00269 0.00553 0.0721 Arboreal Skeleton [65] Carpolestes simpsoni Pekania pennanti Ptilocercus lowii arboreal 0.805 2.75E-14 0.195 0.000035 0.0000397 0.0000601 Arboreal Skeleton [66] Dryomomys szalayi Dromiciops gliroides Glis glis arboreal 0.78 1.92E-14 0.216 0.00175 0.00126 0.00085 Arboreal Tarsals and limb bones [44] Purgatorius sp. Dromiciops gliroides Mellivora capensis arboreal 0.502 1.28E-09 0.304 0.00109 0.144 0.0489 Arboreal Tarsals [2] Pseudictops lophiodon Cricetus cricetus Taxidea taxus semi-fossorial 0.00355 5.06E-09 0.0018 0.0113 0.733 0.25 Terrestrial Limb bones [49,67] Tribosphenomys minutus Zaedyus pichiy Zaedyus pichiy semi-fossorial 0.000824 8.57E-20 0.000555 0.00000102 0.999 0.0000155 Uncertain Tarsals [68] Conoryctes comma Ondatra zibethicus Taxidea taxus terrestrial 0.135 7.56E-09 0.0125 0.202 0.254 0.396 Terrestrial/Semi-fossorial Tarsals and limb bones [45,69] Ectoganus sp. Alces alces Camelus sp. semi-fossorial 0.00209 0.291 0.0104 0.000026 0.51 0.186 Semi-fossorial Skeleton [45] Onychodectes tisonensis Pseudalopex griseus Cricetus cricetus terrestrial 0.00425 1.73E-10 0.0144 0.00111 0.29 0.69 Scansorial/Terrestrial/Semi-fossorial Tarsus [45,69] Didymictis protenus Pseudalopex griseus Taxidea taxus terrestrial 0.00392 1.76E-09 0.00807 0.00082 0.369 0.618 Terrestrial Skeleton [70] Carodnia vierai Ursus maritimus Rhynchocyon cirnei terrestrial 0.000961 4.2E-09 0.000761 0.000212 0.000901 0.997 Terrestrial Tarsus [71,72] Procerberus formicarum Herpestes javanicus Dasypus novemcinctus semi-fossorial 0.411 4.16E-12 0.013 0.000278 0.51 0.0648 Terrestrial Tarsus [31] Ukhaatherium nessovi Ptilocercus lowii Alouatta seniculus arboreal 0.801 4.74E-19 0.196 0.000125 0.00327 0.0000194 Terrestrial Skeleton [1] Sulestes karakshi Marmosa mexicana Alouatta seniculus arboreal 0.956 1.38E-11 0.0429 0.000655 0.00000155 0.00058 - - - Deccanolestes hislopi Marmosa mexicana Mellivora capensis arboreal 0.895 2.51E-18 0.0989 0.0000676 0.00482 0.00109 Arboreal Tarsus and humerus [46,73] Vincelestes neuquenianus Pekania pennanti Atilax paludinosus terrestrial 0.164 3.04E-13 0.0297 0.0824 0.158 0.566 Terrestrial Skeleton [74] Kulbeckia kulbecke Sarcophilus harrisi Pedetes capensis terrestrial 0.0417 0.000174 0.462 0.00184 0.0062 0.489 Terrestrial Tarsus [75]

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List of Supplementary Datasets

Dataset S1 Tarsal Dataset. Separate file formatted as an Excel file (.xlsx) and includes four sheets: sheet 1, tarsal measurements and associated metadata; sheet 2, Z-transformed tarsal data; sheet 3, Principal Component scores; sheet 4, Discriminant Function scores.

Dataset S2 Phylogenetic dataset. Separate file formatted as a Nexus file (.nex) containing the 50% majority rule consensus tree derived from the 10000 birth-death node dated trees downloaded from the www.vertlife.org database. (separate file, available at: https://figshare.com/s/7c79c4986d5916ba551b (private link - DELETE FOR PUBLICATION), DOI: 10.6084/m9.figshare.10250084 (pre-generated DOI))

Dataset S3 Disparity Code. Separate file formatted as Rez source code for opening in R or as a text file and includes the disparity code used in this study (separate file, available at: https://figshare.com/s/7c79c4986d5916ba551b (private link - DELETE FOR PUBLICATION), DOI: 10.6084/m9.figshare.10250084 (pre-generated DOI))

Dataset S4 Permutation code. Separate file formatted as Rez source code for opening in R or as a text file and includes the https://figshare.com/s/7c79c4986d5916ba551b (private link - DELETE FOR PUBLICATION), DOI: 10.6084/m9.figshare.10250084 (pre- generated DOI))

Dataset S5 Regression Dataset. Separate file formatted as an Excel file (.xlsx) and includes three sheets: sheet 1, humerus robustness index values; sheet 2, femur robustness index values; sheet 3, calcaneum robustness index values.

Text for Mendeley citations in Datasets S2 and S3: Fostowicz-Frelik et al. 2018[68] Szalay and Drawhorn 1980[76] O'Leary et al. 2013[5] Smith et al. 2010 [46] Missiaen et al. 2006 [49] Muizon et al. 2015[29] see Matthew 1937[77] Szalay and Lucas 1996 [50] see Shelley et al. 2018[52] see Szalay & Decker 1974[31] see Argot 2013[53] see Kondrashov & Lucas 2012[55] Godinot 1996 [60] Tabuce et al. 2006 [59] Coillot 2013 [78] Manz et al. 2015[61] Szalay 1966[62] Zack et al 2005 [79] O’Leary and Rose 1995 [64] Cifelli 1983[71] Chester et al. 2017 [80] Boyer and Gingerich 2019 [65] Chester et al. 2015[2] Sulimski 1968 [67] Meng and Wyss 2001[81] see Schoch 1986[45] Heinrich and Rose 1997 [70] Szalay 1977[82] Horovitz 2000[83] Averianov & Archiabld 2017; Szalay and Sargis 2006[75,84] Prasad and Godinot 1994[73] Rougier 1993[74]

Marmosa mexicana [85–87] Dromiciops gliroides [85,86,88–90] Didelphis virginiana [1,85,86,91] Trichosorus vulpecula[1,85,86] Caenolestes sp.[85,86] Chironectes minimus [1,85,86,92] Vombatus ursinus [85,86] Sarcophilus harrisii [1,85,86,93] Thylacinus cynocephalus [86] Metachirus nudicaudatus [1,85,94] Macropus giganteus[85,86,95] Thylogale thetis[85,86,96] Ailurus fulgens [85,86,97,98] Genetta genetta [1,85,86,97,99] Tamandua tetradactyla[ 85,86,100] Alouatta seniculus[85,86,101] Cercopithecus neglectus[85,86,101] Piliocolobus rufomitratus [85,86,102] Hylobates pileatus [85,86,103] Lagothrix lagotricha [85,86,104] Perodicticus potto [85,86,105] Glis glis[1,85,86,106] Sciurus carolinensis [1,32,85,86,107] Ptilocercus lowii[85,86,108] Alces alces[85,86,109] Bos taurus [85,86,110] Camelus sp.[85,86,111] Giraffa sp. [85,86,112] Odocoileus virginianu[85,86,113] Ovis aries[85,86,114,115] Equus ferus caballus [85,86,116] Eira Barbara [ 85,86,97,117] Felis wiedii[85,86,97,118] Gulo gulo[1,85,86,97,119] Solenodon paradoxus[1,85,86,120] Papio ursinus[85,86] Erethizon dorsatum[32,85,86,121] Rattus norvegicus[32,85,86,122,123] Enhydra lutris [85,86,97,124] Lontra canadensis [1,85,86,97,125] Mustela vison [1,85,86,97,126] Castor canadensis [32,85,86,127] Ondatra zibethicus [1,32,85,86,128] Mellivora capensis[86,97,129] Mephitis mephitis[1,86,97,130] Taxidea taxus[1,85,86,97,131] Dasypus novemcinctus[1,85,86,132] Priodontes maximus[85,86,133] Zaedyus pichiy[85,86,134] Cricetus cricetus[85,86,135] Cynomys ludovicianus[1,32,85,86,136] Marmota monax[32,85,86,137] Orycteropus afer[85,86,138] Echinops telfairi[1,139] Hexaprotodon liberiensis[85,86,140] Atilax paludinosus [86,97,141] Canis latrans[85,86,97,142] Canis lupus[85,86,97,143] Canis mesomelas[86,97,144] Crocuta crocuta[85,97] Felis concolor (Puma)[85,86,97,145] Galictis vittata[1,86,97,146] Herpestes javanicus [1,85,86,97,147] Hyaena hyaena[85,86,97,148] Lynx canadensis[85,86,97,149] Pekania pennanti[86,97,150] Panthera leo[85,86,97,151] Panthera onca[86,152] Panthera tig ris[85,86,153] Procyon lotor [85,86,97,154] Pseudalopex griseus (Lycalopex)[86,97,155] (Pantheria (Uncia) uncia [86,97,156] Urocyon cinereoargenteus [1,86,97,157] Ursus arctos[85,86,97,158] Ursus maritimus[86,97,159] Vulpes vulpes[1,85,86,97,160] Erinaceus europaeus[85,86] Procavia capensis [85,86,161] Lepus americanus [85,86,162–164] Rhynchocyon cirnei [85,86,165] Tapirus sp.[85,86,166,167] Loxodonta Africana [85,86,168] Hydrochoerus sp. [85,86,169] Hystrix cristata[32,85,86,170] Pedetes capensis[32,85,86]

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References 1. Chen M, Wilson GP. 2015 A multivariate approach to infer locomotor modes in Mesozoic mammals. Paleobiology 41, 280–312. 2. Chester SGB, Bloch JI, Boyer DM, Clemens WA. 2015 Oldest known euarchontan tarsals and affinities of Paleocene Purgatorius to Primates. Proc. Natl. Acad. Sci. 112, 1487–1492. (doi:10.1073/pnas.1421707112) 3. Rose KD. 2008 Plagiomenidae and Mixodectidae. In Evolution of Tertiary Mammals of North America: Volume 2: Small Mammals, Xenarthrans, and Marine Mammals, pp. 198–206. Cambridge University Press. 4. Burgin CJ, Colella JP, Kahn PL, Upham NS. 2018 How many species of mammals are there? J. Mammal. 99, 1–14. (doi:10.1093/jmammal/gyx147) 5. O’Leary MA et al. 2013 The Placental Mammal Ancestor and the Post-K-Pg Radiation of Placentals. Science (80-. ). 339, 662–667. (doi:10.1126/science.1229237) 6. Kielan-Jaworowska Z. 1978 Evolution of the therian mammals in the Late Cretaceous of Asia. Part III. Postcranial skeleton in Zalambdalestidae. Palaeontol Pol 38. 7. Jolliffe IT, Cadima J. 2016 Principal component analysis: a review and recent developments. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 374, 20150202. 8. Li T, Zhu S, Ogihara M. 2006 Using discriminant analysis for multi-class classification: an experimental investigation. Knowl. Inf. Syst. 10, 453–472. 9. Duda RO, Hart PE, Stork DG. 2001 Pattern classification. New York: Wiley. 10. Friedman JH. 1989 Regularized Discriminant Analysis. J. Am. Stat. Assoc. 84, 165–175. (doi:10.1080/01621459.1989.10478752) 11. Mkhadri A, Celeux G, Nasroallah A. 1997 Regularization in discriminant analysis: an overview. Comput. Stat. Data Anal. 23, 403–423. 12. Held L, Ott M. 2018 On p-Values and Bayes Factors. Annu. Rev. Stat. Its Appl. 5, 393–419. (doi:10.1146/annurev-statistics-031017-100307) 13. Benjamin DJ et al. 2018 Redefine statistical significance. Nat. Hum. Behav. 2, 6– 10. (doi:10.1038/s41562-017-0189-z) 14. Benjamin DJ, Berger JO. 2019 Three Recommendations for Improving the Use of p-Values. Am. Stat. 73, 186–191. (doi:10.1080/00031305.2018.1543135) 15. Anderson MJ. 2017 Permutational Multivariate Analysis of Variance (PERMANOVA). Wiley StatsRef Stat. Ref. Online. , 1–15. 16. Martinez, Arbizu P. 2019 pairwiseAdonis: Pairwise multilevel comparison using adonis. R package version 0.3. 17. Benjamini Y, Yekutieli D. 2001 The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 29, 1165–1188. 18. Simes RJ. 1986 An improved Bonferroni procedure for multiple tests of significance. Biometrika 73, 751–754. (doi:10.1093/biomet/73.3.751) 19. Benjamini Y, Hochberg Y. 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300. (doi:https://doi.org/10.1111/j.2517-6161.1995.tb02031.x) 20. McDonald JH. 2009 Handbook of biological statistics. 3rd edn. Baltimore: Sparky House Publishing. 21. Ciampaglio CN, Kemp M, McShea DW. 2001 Detecting changes in morphospace occupation patterns in the fossil record: characterization and analysis of measures 72

of disparity. Paleobiology 27, 695–715. (doi:DOI: 10.1666/0094- 8373(2001)027<0695:DCIMOP>2.0.CO;2) 22. Erwin DH. 2007 Disparity: morphological pattern and developmental context. Palaeontology 50, 57–73. (doi:10.1111/j.1475-4983.2006.00614.x) 23. Brusatte SL, Montanari S, Yi H, Norell MA. 2011 Phylogenetic corrections for morphological disparity analysis: new methodology and case studies. Paleobiology 37, 1–22. (doi:10.1666/09057.1) 24. Campione NE, Evans DC. 2012 A universal scaling relationship between body mass and proximal limb bone dimensions in quadrupedal terrestrial tetrapods. BMC Biol. 10, 60. (doi:10.1186/1741-7007-10-60) 25. Team RC. 2016 R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2014. 26. Smith JM, Savage RJG. 1956 Some locomotory adaptations in mammals. Zool. J. Linn. Soc. 42, 603–622. 27. Van Valkenburgh B. 1985 Locomotor diversity within past and present guilds of large predatory mammals. Paleobiology , 406–428. 28. Carrano MT. 1999 What, if anything, is a cursor? Categories versus continua for determining locomotor habit in mammals and dinosaurs. J. Zool. 247, 29–42. 29. Muizon C de, Billet G, Argot C, Ladevèze S, Goussard F. 2015 Alcidedorbignya inopinata, a basal pantodont (Placentalia, Mammalia) from the early Palaeocene of Bolivia: anatomy, phylogeny and palaeobiology. Geodiversitas 37, 397–634. 30. Szalay FS. 2006 Evolutionary history of the marsupials and an analysis of osteological characters. Cambridge University Press. 31. Szalay FS, Decker RL. 1974 Origins, evolution, and function of the tarsus in Late Cretaceous Eutheria and Paleocene primates. In Primate Locomotion (ed FAJ Jenkins), pp. 223–259. Elsevier. 32. Samuels JX, Van Valkenburgh B. 2008 Skeletal indicators of locomotor adaptations in living and extinct rodents. J. Morphol. 269, 1387–1411. (doi:10.1002/jmor.10662) 33. Hildebrand M. 1959 Motions of the running cheetah and horse. J. Mammal. 40, 481–495. 34. Hildebrand M, Bramble DM, Liem KF, Wake DB. 1985 Functional vertebrate morphology. Belknap Press of Harvard University Press. 35. Hildebrand M, Goslow GE. 2001 Analysis of vertebrate structure. 5th edn. John Wiley & Sons. 36. Gregory WK. 1912 Notes on the principles of quadrupedal locomotion and of the mechanism of the limbs in hoofed animals. New York Academy of Sciences. 37. Salton JA, Szalay FS. 2004 The tarsal complex of Afro-Malagasy Tenrecoidea: A search for phylogenetically meaningful characters. J. Mamm. Evol. 11, 73–104. (doi:10.1023/B:JOMM.0000041190.83655.1d) 38. Carrano MT. 1997 Morphological indicators of foot posture in mammals: a statistical and biomechanical analysis. Zool. J. Linn. Soc. 121, 77–104. 39. Biewener AA, Thomason JJ, Lanyon LE. 1988 Mechanics of locomotion and jumping in the horse (Equus): in vivo stress in the tibia and metatarsus. J. Zool. 214, 547–565. 40. Zefrank1. 2018 True Facts: Pangolins Posse. Youtube. See

73

https://youtu.be/mbnBYh-BJ1g?t=34 (accessed on 1 August 2020). 41. Motani R, Schmitz L. 2011 Phylogenetic versus functional signals in the evolution of form-function relationships in terrestrial vision. Evolution (N. Y). 65, 2245– 2257. (doi:10.1111/j.1558-5646.2011.01271.x) 42. Maga AM, Beck RMD. 2017 Skeleton of an unusual, cat-sized marsupial relative (Metatheria: Marsupialiformes) from the middle Eocene (Lutetian: 44-43 million years ago) of Turkey. PLoS One 12, e0181712. 43. Bloch JI, Boyer DM. 2007 New Skeletons of Paleocene-Eocene Plesiadapiformes: A Diversity of Arboreal Positional Behaviors in Early Primates BT - PRIMATE ORIGINS: Adaptations and Evolution. In (eds MJ Ravosa, M Dagosto), pp. 535– 581. Boston, MA: Springer US. (doi:10.1007/978-0-387-33507-0_16) 44. Bloch JI, Silcox MT, Boyer DM, Sargis EJ. 2007 New Paleocene skeletons and the relationship of plesiadapiforms to crown-clade primates. Proc. Natl. Acad. Sci. 104, 1159–1164. 45. Schoch RM. 1986 Systematics, functional morphology and macroevolution of the extinction mammalian order Taeniodonta. Bull. Peabody Museum Nat. Hist. Yale Univ. , 1–307. 46. Smith T, De Bast E, Sigé B. 2010 Euarchontan affinity of Paleocene Afro- European adapisoriculid mammals and their origin in the late Cretaceous Deccan Traps of India. Naturwissenschaften 97, 417–422. 47. Storch G. 2008 Skeletal remains of a diminutive primate from the Paleocene of Germany. Naturwissenschaften 95, 927–930. (doi:10.1007/s00114-008-0401-0) 48. Gheerbrant E, Russell DE. 1989 Presence of the genus Afrodon [Mammalia, Lipotyphla (?), Adapisoriculidae] in Europe; new data for the problem of trans- Tethyan relations between Africa and Europe around the K/T boundary. Palaeogeogr. Palaeoclimatol. Palaeoecol. 76, 1–15. (doi:https://doi.org/10.1016/0031-0182(89)90099-0) 49. Missiaen P, Smith T, Guo D-Y, Bloch JI, Gingerich PD. 2006 Asian gliriform origin for arctostylopid mammals. Naturwissenschaften 93, 407–411. 50. Szalay FS, Lucas SG. 1996 The Postcranial Morphology of Paleocene Chiacus and Mixodectes and the Phylogenetic Relationships of Archontan Mammals. New Mex. Museum Nat. Hist. Sci. Bull. 7, 1–47. 51. Shelley SL. 2018 Rise of placental mammals: the anatomy, palaeobiology and phylogeny of Periptychus and the Periptychidae. 52. Shelley SL, Williamson TE, Brusatte SL. 2018 The osteology of Periptychus carinidens: A robust, ungulate-like placental mammal (Mammalia: Periptychidae) from the Paleocene of North America. PLoS One 13, e0200132. (doi:doi.org/10.1371/journal.pone.0200132) 53. Argot C. 2013 Postcranial Analysis of a Carnivoran-Like Archaic Ungulate: The Case of Arctocyon primaevus (Arctocyonidae, Mammalia) from the Late Paleocene of France. J. Mamm. Evol. 20, 83–114. (doi:10.1007/s10914-012-9198- x) 54. Gould FDH, Rose KD. 2014 Gnathic and postcranial skeleton of the largest known arctocyonid ‘condylarth’ Arctocyon mumak (Mammalia, Procreodi) and ecomorphological diversity in Procreodi. J. Vertebr. Paleontol. 34, 1180–1202. (doi:10.1080/02724634.2014.841707)

74

55. Kondrashov PE, Lucas SG. 2012 Nearly complete skeleton of Tetraclaenodon (Mammalia, Phenacodontidae) from the early Paleocene of New Mexico: morpho- functional analysis. J. Paleontol. 86, 25–43. 56. Thewissen JGM. 1990 Evolution of Paleocene and Eocene Phenacodontidae (Mammalia, Condylarthra). 57. Thewissen JGM. 1991 Limb osteology and function of the primitive Paleocene ungulate Pleuraspidotherium with notes on Tricuspiodon and Dissacus (Mammalia). Geobios 24, 483–495. 58. Ladevèze S, Missiaen P, Smith T. 2010 First skull of Orthaspidotherium edwardsi (Mammalia,“Condylarthra”) from the late Paleocene of Berru (France) and phylogenetic affinities of the enigmatic European family Pleuraspidotheriidae. J. Vertebr. Paleontol. 30, 1559–1578. 59. Tabuce R, Antunes MT, Smith R, Smith T. 2006 Dental and tarsal morphology of the European Paleocene-Eocene ‘condylarth’ mammal Microhyus. Acta Palaeontol. Pol. 51. 60. Godinot M, Smith T, Smith R. 1996 Lifestyle and affinity of Paschatherium (Condylarthra, Hyopsodontidae) from its tarsal bones. Palaeovertebrata 25, 225- 242. 61. Manz CL, Chester SGB, Bloch JI, Silcox MT, Sargis EJ. 2015 New partial skeletons of Palaeocene Nyctitheriidae and evaluation of proposed euarchontan affinities. Biol. Lett. 11, 20140911. (doi:10.1098/rsbl.2014.0911) 62. Szalay FS. 1966 The tarsus of the Paleocene lepticid Prodiacodon (Insectivora, Mammalia). Am. Museum Novit. , 1–14. 63. Penkrot TA, Zack SP, Rose KD, Bloch JI. 2008 Postcranial Morphology of Apheliscus and Haplomylus (Condylarthra, Apheliscidae): Evidence for a Paleocene Holarctic Origin of Macroscelidea BT - Mammalian Evolutionary Morphology: A Tribute to Frederick S. Szalay. In (eds EJ Sargis, M Dagosto), pp. 73–106. Dordrecht: Springer Netherlands. (doi:10.1007/978-1-4020-6997-0_5) 64. O’Leary MA, Rose KD. 1995 Postcranial Skeleton of the Early Eocene Mesonychid Pachyaena (Mammalia : Mesonychia ). J. Vertebr. Paleontol. 15, 401–430. 65. Boyer DM, Gingerich PD. 2019 Skeleton of Late Paleocene Plesiadapis cookei (Mammalia, Euarchonta): Life History, Locomotion, and Phylogenetic Relationships. Univ. Michigan Pap. Paleontol. , 1–287. 66. Bloch JI, Boyer DM. 2002 Grasping Primate Origins. Science (80-. ). 298, 1606– 1610. (doi:10.1126/science.1078249) 67. Sulimski A. 1968 Paleocene genus Pseudictops Matthew, Granger and Simpson 1929 (Mammalia) and its revision. Palaeontol. Pol. 19, 101–132. 68. Fostowicz-Frelik Ł, Li Q, Ni X. 2018 Oldest ctenodactyloid tarsals from the Eocene of China and evolution of locomotor adaptations in early rodents. BMC Evol. Biol. 18, 150. (doi:10.1186/s12862-018-1259-1) 69. Williamson TE, Brusatte SL. 2013 New Specimens of the Rare Taeniodont Wortmania (Mammalia: Eutheria) from the San Juan Basin of New Mexico and Comments on the Phylogeny and Functional Morphology of ‘Archaic’ Mammals. PLoS One 8, 1–35. (doi:10.1371/journal.pone.0075886) 70. Heinrich RE, Rose KD. 1997 Postcranial morphology and locomotor behaviour of

75

two early Eocene miacoid carnivorans, Vulpavus and Didymictis. Palaeontology 40, 279–306. 71. Cifelli RL. 1983 Eutherian tarsals from the late Paleocene of Brazil. Am. Museum Novit. 2761, 1–31. 72. Rose KD. 2006 The beginning of the age of mammals. Johns Hopkins Press. 73. Prasad GVR, Godinot M. 1994 Eutherian tarsal bones from the Late Cretaceous of India. J. Paleontol. 68, 892–902. (doi:10.1017/S0022336000026342) 74. Rougier GW. 1993 Vincelestes neuquenianus Bonaparte (Mammalia, Theria), un primitivo mamífero del Cretácico inferior de la Cuenca Neuquina. Universidad Nacional de Buenos Aires. 75. Averianov AO, Archibald JD. 2017 Therian postcranial bones from the Upper Cretaceous Bissekty Formation of Uzbekistan. Proc. Zool. Inst. RAS 321, 433– 484. 76. Szalay FS, Drawhorn G. 1980 Evolution and Diversification of the Archonta in an Arboreal Milieu. In Comparative biology and evolutionary relationships of tree shrews. (ed WP Luckett), pp. 133–169. Boston, MA: Springer US. 77. Matthew WD. 1937 Paleocene faunas of the San Juan Basin, New Mexico. Trans. Am. Philos. Soc. 30, 1–510. 78. Coillot T, Smith R, Gigase P, Smith T. 2013 Tarsal diversity in the earliest Eocene mammal fauna of Dormaal, Belgium. Geol. Belgica 16, 274–284. 79. Zack SP, Penkrot TA, Krause DW, Maas MC. 2005 A new apheliscine ‘condylarth’ mammal from the Late Paleocene of Montana and Alberta and the phylogeny of ‘hyopsodontids’. Acta Palaeontol. Pol. 50, 809–830. 80. Chester SGB, Williamson TE, Bloch JI, Silcox MT, Sargis EJ. 2017 Oldest skeleton of a plesiadapiform provides additional evidence for an exclusively arboreal radiation of stem primates in the Palaeocene. R. Soc. Open Sci. 4, 170329. (doi:10.1098/rsos.170329) 81. Meng J, Wyss AR. 2001 The Morphology of Tribosphenomys (Rodentiaformes, Mammalia): Phylogenetic Implications for Basal Glires. J. Mamm. Evol. 8, 1–71. (doi:10.1023/A:1011328616715) 82. Szalay FS. 1977 Phylogenetic Relationships and a Classification of the Eutherian Mammalia. In Major Patterns in Vertebrate Evolution. NATO Advanced Study Institutes Series (Series A: Life Sciences) (eds MK Hecht, PC Goody, BM Hecht), pp. 315–374. Boston, MA: Springer US. (doi:10.1007/978-1-4684-8851-7_12) 83. Horovitz I. 2000 The tarsus of Ukhaatherium nessovi (Eutheria, Mammalia) from the Late Cretaceous of Mongolia: an appraisal of the evolution of the ankle in basal therians. J. Vertebr. Paleontol. 20, 547–560. (doi:10.1671/0272- 4634(2000)020[0547:TTOUNE]2.0.CO;2) 84. Szalay FS, Sargis EJ. 2006 Cretaceous Therian Tarsals and the Metatherian- Eutherian Dichotomy. J. Mamm. Evol. 13, 171–210. (doi:10.1007/s10914-006- 9024-4) 85. Nowak RM. 1999 Walker’s Mammals of the World. Johns Hopkins Press. 86. Myers P, Espinosa R, Parr CS, Jones T, Hammond GS, Dewey TA. 2021 The Animal Diversity Web. See https://animaldiversity.org. 87. Alonso-Mejía A, Medellín RA. 1992 Marmosa mexicana. Mamm. species 421, 1– 4.

76

88. Marshall LG. 1978 Dromiciops australis. Mamm. Species 99, 1–5. 89. Godoy-Güinao J, Díaz IA, Celis-Diez JL. 2018 Confirmation of arboreal habits in Dromiciops gliroides: a key role in Chilean Temperate Rainforests. Ecosphere 9, e02424. (doi:https://doi.org/10.1002/ecs2.2424) 90. Pearson OP. 1983 Characteristics of a mammalian fauna from forests in Patagonia, southern Argentina. J. Mammal. 64, 476–492. 91. McManus JJ. 1974 Didelphis virginiana. Mamm. species 40, 1–6. 92. Marshall LG. 1978 Chironectes minimus. Mamm. Species 109, 1–6. (doi:10.2307/0.109.1) 93. Rose RK, Pemberton DA, Mooney NJ, Jones ME. 2017 Sarcophilus harrisii(Dasyuromorphia: Dasyuridae). Mamm. Species 49, 1–17. (doi:10.1093/mspecies/sex001) 94. Cunha AA, Vieira M V. 2002 Support diameter, incline, and vertical movements of four didelphid marsupials in the Atlantic forest of Brazil. J. Zool. 258, 419–426. (doi:https://doi.org/10.1017/S0952836902001565) 95. Poole WE. 1982 Macropus giganteus. Mamm. Species 187, 1–8. (doi:10.2307/3504005) 96. Rose RW, Rose RK. 2018 Thylogale billardierii (Diprotodontia: Macropodidae). Mamm. Species 50, 100–108. (doi:10.1093/mspecies/sey012) 97. Samuels JX, Meachen JA, Sakai SA. 2013 Postcranial morphology and the locomotor habits of living and extinct carnivorans. J. Morphol. 274, 121–146. 98. Roberts MS, Gittleman JL. 1984 Ailurus fulgens. Mamm. Species 222, 1–8. (doi:10.2307/3503840) 99. Larivière S, Calzada J. 2001 Genetta genetta. Mamm. Species 680, 1–6. (doi:10.2307/0.680.1) 100. Hayssen V. 2011 Tamandua tetradactyla (Pilosa: Myrmecophagidae). Mamm. Species 43, 64–74. (doi:10.1644/875.1) 101. Clutton-Brock TH. 2012 Primate ecology: studies of feeding and ranging behavior in lemurs, monkey and apes. Elsevier. 102. Butynski TM, de Jong YA, King J. 2019 Piliocolobus rufomitratus. IUCN Red List Threat. Species e.T136939A. 103. Vanhoof MJM, van Leeuwen T, Vereecke EE. 2020 The forearm and hand musculature of semi-terrestrial rhesus macaques (Macaca mulatta) and arboreal gibbons (Fam. Hylobatidae). Part I. Description and comparison of the muscle configuration. J. Anat. 237, 774–790. (doi:https://doi.org/10.1111/joa.13222) 104. Defler TR. 1999 Locomotion and posture in Lagothrix lagotricha. Folia Primatol. 70, 313–327. 105. Walker A. 1969 The locomotion of the lorises, with special reference to the potto. Afr. J. Ecol. 7, 1–5. (doi:https://doi.org/10.1111/j.1365-2028.1969.tb01187.x) 106. Kryštufek B. 2010 Glis glis (Rodentia: Gliridae). Mamm. Species 42, 195–206. (doi:10.1644/865.1) 107. Koprowski JL. 1994 Sciurus carolinensis. Mamm. Species 480, 1–9. (doi:10.2307/3504224) 108. Gould E. 1978 The behavior of the moonrat, Echinosorex gymnurus (Erinaceidae) and the pentail shrew, Ptilocercus lowii (Tupaiidae) with comments on the behavior of other Insectivora. Z. Tierpsychol. 48, 1–27.

77

109. Franzmann AW. 1981 Alces alces. Mamm. Species 154, 1–7. (doi:10.2307/3503876) 110. Ahrestani FS. 2018 Bos frontalis and Bos gaurus (Artiodactyla: Bovidae). Mamm. Species 50, 34–50. (doi:10.1093/mspecies/sey004) 111. Köhler-Rollefson IU. 1991 Camelus dromedarius. Mamm. Species 375, 1–8. (doi:10.2307/3504297) 112. Dagg AI. 1971 Giraffa camelopardalis. Mamm. Species 5, 1–8. (doi:10.2307/3503830) 113. Smith WP. 1991 Odocoileus virginianus. Mamm. Species 388, 1–13. (doi:10.2307/3504281) 114. Fedosenko AK, Blank DA. 2005 Ovis ammon. Mamm. Species 773, 1–15. (doi:10.1644/773) 115. Shackleton DM. 1985 Ovis canadensis. Mamm. Species 230, 1–9. (doi:10.2307/3504034) 116. Bennett D, Hoffmann RS. 1999 ,Equus caballus. Mamm. Species 628, 1–14. (doi:10.2307/3504442) 117. Presley SJ. 2000 Eira barbara. Mamm. Species 636, 1–6. (doi:10.2307/0.636.1) 118. de Oliveira TG. 1998 Leopardus wiedii. Mamm. Species 579, 1–6. (doi:10.2307/3504400) 119. Pasitschniak-Arts M, Larivière S. 1995 Gulo gulo. Mamm. Species 499, 1–10. (doi:10.1644/0.499.1) 120. Derbridge JJ, Posthumus EE, Chen HL, Koprowski JL. 2015 Solenodon paradoxus(Soricomorpha: Solenodontidae). Mamm. Species 47, 100–106. (doi:10.1093/mspecies/sev010) 121. Woods CA. 1973 Erethizon dorsatum. Mamm. Species 29, 1–6. (doi:10.2307/3504036) 122. Bonnan MF, Shulman J, Varadharajan R, Gilbert C, Wilkes M, Horner A, Brainerd E. 2016 Forelimb kinematics of rats using XROMM, with implications for small eutherians and their fossil relatives. PLoS One 11, e0149377. 123. Schmidt A, Fischer MS. 2010 Arboreal locomotion in rats – the challenge of maintaining stability. J. Exp. Biol. 213, 3615 LP – 3624. (doi:10.1242/jeb.045278) 124. Estes JA. 1980 Enhydra lutris. Mamm. Species 133, 1–8. (doi:10.2307/3503844) 125. Larivière S, Walton LR. 1998 Lontra canadensis. Mamm. Species 587, 1–8. (doi:10.2307/3504417) 126. Larivière S. 1999 Mustela vison. Mamm. Species 608, 1–9. (doi:10.2307/3504420) 127. Jenkins SH, Busher PE. 1979 Castor canadensis. Mamm. Species 120, 1–8. (doi:10.2307/3503787) 128. Willner GR, Feldhamer GA, Zueker EE, Chapman JA. 1980 Ondatra zibethicus. Mamm. Species 141, 1–8. (doi:10.2307/3504016) 129. Vanderhaar JM, Hwang Y Ten. 2003 Mellivora Capensis. Mamm. Species 721, 1– 8. (doi:10.1644/0.721.1) 130. Wade-Smith J, Verts BJ. 1982 Mephitis mephitis. Mamm. Species 173, 1–7. (doi:10.2307/3503883) 131. Long CA. 1973 Taxidea taxus. Mamm. Species 26, 1–4. (doi:10.2307/3504047) 132. McBee K, Baker RJ. 1982 Dasypus novemcinctus. Mamm. Species 162, 1–9. (doi:10.2307/3503864)

78

133. Carter TS, Superina M, Leslie Jr. DM. 2016 Priodontes maximus (Cingulata: Chlamyphoridae). Mamm. Species 48, 21–34. (doi:10.1093/mspecies/sew002) 134. Superina M, Abba AM. 2014 Zaedyus pichiy (Cingulata: Dasypodidae). Mamm. Species 46, 1–10. (doi:10.1644/905.1) 135. Kryštufek B, Hoffmann IE, Nedyalkov N, Pozdnyakov A, Vohralík V. 2020 Cricetus cricetus (Rodentia: Cricetidae). Mamm. Species 52, 10–26. (doi:10.1093/mspecies/seaa001) 136. Hoogland JL. 1996 Cynomys ludovicianus. Mamm. Species 535, 1–10. (doi:10.2307/3504202) 137. Kwiecinski GG. 1998 Marmota monax. Mamm. Species 591, 1–8. (doi:10.2307/3504364) 138. Shoshani J, Goldman CA, Thewissen JGM. 1988 Orycteropus afer. Mamm. Species 300, 1–8. (doi:10.2307/3503996) 139. Stephenson PJ, Soarimalala V, Goodman S. 2016 Echinops Telfairi. IUCN Red List Threat. Species 2016 e. T40592A97188634 , 2011–2016. 140. Flacke GL, Decher J. 2019 Choeropsis liberiensis (Artiodactyla: Hippopotamidae). Mamm. Species 51, 100–118. (doi:10.1093/mspecies/sez017) 141. Baker CM. 1992 Atilax paludinosus. Mamm. Species 408, 1–6. (doi:10.2307/3504291) 142. Bekoff M. 1977 Canis latrans. Mamm. Species 79, 1–9. (doi:10.2307/3503817) 143. Mech LD. 1974 Canis lupus. Mamm. Species 37, 1–6. (doi:10.2307/3503924) 144. Walton LR, Joly DO. 2003 Canis mesomelas. Mamm. Species 715, 1–9. (doi:10.1644/0.715.1) 145. Currier MJP. 1983 Felis concolor. Mamm. Species 200, 1–7. (doi:10.2307/3503951) 146. Yensen E, Tarifa T. 2003 Galictis vittata. Mamm. Species 727, 1–8. (doi:10.1644/0.727.1) 147. Nellis DW. 1989 Herpestes auropunctatus. Mamm. Species 342, 1–6. (doi:10.2307/3504091) 148. Rieger I. 1981 Hyaena hyaena. Mamm. Species 150, 1–5. (doi:10.2307/41353899) 149. Lavoie M, Renard A, Larivière S. 2019 Lynx canadensis (Carnivora: Felidae). Mamm. Species 51, 136–154. (doi:10.1093/mspecies/sez019) 150. Powell RA. 1981 Martes pennanti. Mamm. Species 156, 1–6. (doi:10.2307/3504050) 151. Haas SK, Hayssen V, Krausman PR. 2005 Panthera leo. Mamm. Species 762, 1– 11. (doi:10.2307/3504539) 152. Seymour KL. 1989 Panthera onca. Mamm. Species 340, 1–9. (doi:10.2307/3504096) 153. Mazák V. 1981 Panthera tigris. Mamm. Species 152, 1–8. (doi:10.2307/3504004) 154. Lotze J-H, Anderson S. 1979 Procyon lotor. Mamm. Species 119, 1–8. (doi:10.2307/3503959) 155. Novaro AJ. 1997 Pseudalopex culpaeus. Mamm. Species 558, 1–8. (doi:10.2307/3504483) 156. Hemmer H. 1972 Uncia uncia. Mamm. Species 20, 1–5. (doi:10.2307/3503882) 157. Fritzell EK, Haroldson KJ. 1982 Urocyon cinereoargenteus. Mamm. Species 189, 1–8. (doi:10.2307/3503957)

79

158. Pasitschniak-Arts M. 1993 Ursus arctos. Mamm. Species 439, 1–10. (doi:10.2307/3504138) 159. DeMaster DP, Stirling I. 1981 Ursus maritimus. Mamm. Species 145, 1–7. (doi:10.2307/3503828) 160. Larivière S, Pasitschniak-Arts M. 1996 Vulpes vulpes. Mamm. Species 537, 1–11. (doi:10.2307/3504236) 161. Olds N, Shoshani J. 1982 Procavia capensis. Mamm. Species 171, 1–7. (doi:10.2307/3503802) 162. Best TL, Henry TH. 1994 Lepus arcticus. Mamm. Species 457, 1–9. (doi:10.2307/3504088) 163. Best TL, Henry TH. 1994 Lepus othus. Mamm. Species 495, 1–5. (doi:10.2307/3504196) 164. Angerbjörn A, Flux JEC. 1995 Lepus timidus. Mamm. Species 495, 1–11. (doi:10.2307/3504302) 165. Rathbun GB. 1979 Rhynchocyon chrysopygus. Mamm. Species 117, 1–4. (doi:10.2307/3503789) 166. Padilla M, Dowler RC. 1994 Tapirus terrestris. Mamm. Species 481, 1–8. (doi:10.2307/3504109) 167. Padilla M, Dowler RC, Downer CC. 2010 Tapirus pinchaque (Perissodactyla: Tapiridae). Mamm. Species 42, 166–182. (doi:10.1644/863.1) 168. Laursen L, Bekoff M. 1978 Loxodonta africana. Mamm. Species 92, 1–8. (doi:10.2307/3503889) 169. Mones A, Ojasti J. 1986 Hydrochoerus hydrochaeris. Mamm. Species 264, 1–7. (doi:10.2307/3503784) 170. Barthelmess EL. 2006 Hystrix africaeaustralis. Mamm. Species 788, 1–7. (doi:10.1644/788.1)

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