DOI: 10.5061/dryad.8gtht76sp
title: Data from: Morphological disparity of mammalian limb bones throughout the Cenozoic: the role of biotic and abiotic factors

description: Mammals exhibit ecology-related diversity in long bone morphology,
 revealing an ample spectrum of adaptations both within and between clades.
 Their occupation of unique ecological niches in postcranial morphology is
 thought to have occurred at different chronological phases in relation to
 abiotic factors such as climate and biotic interactions amongst major
 clades. Mammalian morphologies rapidly evolved throughout the Cenozoic,
 with several orders following different paths in locomotory adaptations.
 We assessed morphological variation in limb proportions for a rich sample
 of extant and fossil large mammalian clades (mainly carnivores and
 ungulates) to test associations with ecological adaptations and to
 identify temporal patterns of diversification. Phylogenetic relationships
 among species were incorporated into the analysis of limb bone
 proportions, showing significant morphological changes in relation to
 species substrate preference. Major climatic events appeared to have no
 temporal impact on patterns of morphological diversification, expressed as
 morphological disparity, in either clades or ecological groups. Linear
 stochastic differential equations supported a double-wedge diversification
 model for limb proportions of carnivorous clades (‘Creodonta’ and
 Carnivora). The concomitant increase in morphological disparity throughout
 the Cenozoic for the orders Carnivora and Artiodactyla had a significative
 impact on the disparity of Perissodactyla supporting biotic interaction as
 the primary driver of mammalian morphological diversification. Our
 findings challenge the classic idea of abiotic factors as primary driving
 forces in the evolution of postcranial morphologies for large terrestrial
 mammals and propose clade competition as a key factor in temporal
 diversification.
description: <strong>Data collection</strong>
 <em>Morphological data </em> To
 compute the analyses of the study entitled  "<em>Morphological
 disparity of mammalian limb bones throughout the cenozoic: the role of
 biotic and abiotic factors</em>”, we assembled from the literature
 and published databases 793 humerus, 805 radius, 668 femur, and 663 tibia
 lengths belonging to 246 living and 177 fossil species. These data were
 combined into the brachial index (i.e., radius to humerus ratio) and the
 crural index (i.e., tibia to femur ratio). Also, because the body mass of
 fossil species is usually estimated using long bone length, to account for
 the allometry in the analyses, we also collected the greatest skull length
 (1883 values), which is a good predictor of body mass. Collected data
 represented 423 species from the order Acreodi (1), Artiodactyla (206),
 Carnivora (178), Cimolesta (4), Condylarthra (3), Hyaenodonta (5),
 Oxyaenodonta (4), Dinocerata (1), Litopterna (1), Perissodactyla (59) and
 Procreodi (2) spanning throughout the Cenozoic. On average, data for each
 species were assembled by merging multiple individual references and for
 this reason, the collected values were checked for errors. The error
 checking followed the protocol proposed by (Cooper & Purvis, 2009)
 to estimate typographical and measurement errors.
 <em>Ecological data</em> To
 identify the selective pressures affecting long bones evolution, we
 collected for both extant and extinct species trophic level, diet, and
 locomotor behaviour, while only for extant species collected habitat
 type. The <strong>trophic level</strong>
 category was built using body mass as a reference. This category
 includes: -<strong>large
 predators</strong> Extant and extinct Carnivora
 weighting ≥21.5 kg (Carbone et al., 1999). Examples of fossil genera
 included in this category were amphicyonids, nimravids, barbourofelids,
 machairodonts, and arctocyonids. -<strong>large
 prey</strong> Extant and extinct Perissodactyla
 and Artiodactyla including the fossil groups of phenacodontids,
 merycoidodonts, agriochoerids, and uintatherids weighting from 10 kg up to
 900 kg (Estes, 1974). -<strong>small predators
 </strong> Small carnivores, weighing less than
 21.5 kg (Carbone et al., 1999; Carbone et al.,
 2007),<strong> </strong>and feed on small vertebrate and
 invertebrate food sources. Examples of fossil species included in this
 category were <em>Desmocyon, Cormocyon, Phlaocyon, </em>and
 <em>Archaeocyon </em>as well as <em>Eucyon, Limocyon,
 Thinocyon, Palaeonictis, Buxolestes, Paleosinopa, </em>and
 <em>Chriacus</em>. -<strong>small
 prey</strong> Small ungulates weigh less than 10
 kg (Carbone et al., 1999; Carbone et al., 2007).
 -<strong>mega-herbivores </strong>
 Large ungulates weighing more than 900 kg (Sunquist &
 Sunquist, 1989; Owen‐Smith & Mills, 2008). Among the fossil genera
 included in this category were <em>Toxodon</em>,
 <em>Palaeosyops, Parvicornus, Coelodonta, Stephanorhinus,
 Chilotherium, Teleoceras, Paraceratherium, Amynodon, Chalicotherium,
 </em>and <em>Moropus</em>.
 -<strong>non-specialized predators</strong>
 This category included species belonging to the family Ursidae
 which did not show particular predator morphology. Ursids consume less
 than 10% of ungulates meat (Penteriani & Melletti, 2020). Fossil
 species belonging to this category were representative of the cave bear
 group. The only exception was the short-faced bear <em>Arctodus
 simus</em> which is the largest omnivorous that ever
 lived (Figueirido et al., 2010; Meloro, 2011; Figueirido et al., 2017).
 The red panda (<em>Ailurus fulgens</em>) was also included in
 this category, even though it is not an ursid, as it is well-adapted to a
 mostly folivorous diet, similar to that of the unrelated giant
 panda <em>Ailuropoda melanoleuca</em> (Roka et al.,
 2021). The <strong>diet</strong>
 category included: insectivore, carnivorous, omnivore, piscivore,
 frugivore, folivore, browser, grazer, and mixed feeders.
 <strong>- Insectivores</strong>
 Species feeding on insects such as herpestids, the hyena
 <em>Proteles, </em>the canid <em>Otocyon</em>, and
 the extinct genus <em>Hemihegetotherium</em>.  
 <strong>- carnivorous</strong>
 Carnivorans feed on vertebrate food, such as most of the
 Carnivora, Hyaenodonta, Oxyaenodonta, and the genus
 <em>Pachyaena.</em> <strong>-
 omnivore</strong> This category included
 generalist species such as suids and bears.
 <strong>- piscivore</strong> This
 category included Pantolestidae and otters.
 <strong>- frugivore</strong>
 Species feed mainly on fruits, such as the ring-tailed cat and
 the genus <em>Bassariscus.</em>
 <strong>- folivores</strong>
 Non-ungulates herbivores as for example the
 genera <em>Coryphodon</em>, <em>Ailurus</em>,
 <em>Ailuropoda, </em>and
 <em>Tremarctos.</em>
 <strong>-browser</strong>
 Ungulates feeding on leaves. Examples of species belonging to
 this category are <em>Eurygenium, Uintatherium, </em>the basal
 perissodactyls <em>Hyracotherium</em>, most rhinoceroses, and
 camelids. <strong>-grazer
 </strong> Species feeding on grass as for example
 the genera <em>Equus, Cervus, Bos, and Bison.</em>
 <strong>-mixed feeders</strong>
 This category included species that feed on both leaves and
 grass. The extinct Mericoidodontinae that lived before
 the early Miocene, were classified as browsers, while those that lived
 from the middle Miocene forward were considered grazers (Mihlbachler
 & Solounias, 2006). The <strong>locomotor
 behaviour</strong> category included amphibious, arboreal,
 terrestrial, scansorial, and semi-fossorial categories.
 <strong>-arboreal</strong> This
 category included species living on trees. Viverrids, procyonids, small
 felids, and the genus <em>Miacis </em>are examples of species
 in this category.
 <strong>-terrestrial</strong> This
 category included most of the carnivoran and ungulate species.
 <strong>-amphibious</strong> This
 category included species living close to bodies of water such as extant
 polar bears, otters, the hippopotamus, some <em>Tapirus</em>,
 and the extinct <em>Teleoceras, Buxolestes, Palaeosinopa,
 </em>and <em>Metamynodon</em>.
 <strong>-scansorial</strong> This
 category included species capable of climbing. Most felids, Mephitidae,
 Mustelidae, Procyonidae, and the extinct <em>Agriochoerus antiquus
 </em>and <em>Chriacus </em>were in this
 category.<em> </em>
 <strong>-semifossorial</strong>
 This category included <em>Meles meles, Mellivora capensis,
 </em>and <em>Taxidea taxus.</em> For
 living species only we collected also habitat preferences by merging the
 IUCN Red List of Threatened Species (www.iucnredlist.org), the primary
 source, and Animal Diversity Web (animaldiversity.org) information. This
 category included open, mixed, closed, and wetland habitat
 types. <em>Phylogenetic tree</em>
 The phylogenetic position of both living and fossil species and
 node ages were collected from published articles. These data were used to
 assemble and calibrate the phylogenetic tree used to take the
 non-independence of the species into account when computing in the
 statistical analyses. <em>Time
 bins</em> In our work entitled
 "<em>Morphological disparity of mammalian limb bones throughout
 the Cenozoic: the role of biotic and abiotic factors</em>” we
 computed morphological disparity of long bones functional indices over the
 Cenozoic. To bin both species and the estimated ancestral character state
 according to the Cenozoic stages, we collected the Geological dates from
 the International Chronostratigraphic Chart 2021
 (https://stratigraphy.org/ICSchart/ChronostratChart2021-07.pdf (Cohen et
 al., 2021). The species first and last appearance in the fossil record
 were collected from Fossilworks (http://fossilworks.org/), Paleobiology
 database (https://paleobiodb.org/#/), and Now database
 (https://nowdatabase.org/).
 <strong>Analyses</strong> For the
 aim of this work, we first investigated the allometric effect studying the
 relationships between phenotypic traits such as radius to humerus and
 tibia to femur ratios with the greatest skull length using Phylogenetic
 Generalised Least Squares regression (PGLS; Harris & Steudel,
 1997). The PGLS method incorporates phylogeny as an error term by
 estimating the lambda parameter, which accounts for different degrees of
 phylogenetic signal. To determine the functional
 morphospace taking into account both the effect of the allometry and
 phylogeny, we computed the size and phylogenetic corrected PCA (Phy-PCA;
 Revell, 2009). The function <em>phyl.resid</em> (R package
 phytools; Revell, 2012) was used to remove the allometric effect from the
 functional ratios, and the function <em>phyl.pca</em> (R
 package phytools; Revell, 2012) was used to obtain
 evolutionary-independent Principal Component (PCs). In this study, we also
 analysed the effect of trophic level, diet, substrate preferences, and
 habitat on limb proportions using the permutation ANOVA (Collyer &
 Adams, 2018). In addition, we estimated the ancestral
 characters at tree nodes to correct morphological disparity computation
 accounting for sample incompleteness within Cenozoic time bins. The best
 mode of evolution was assessed for each PC vector using
 <em>fitContinuous</em> function (R package geiger; Pennell et
 al., 2014) which allowed testing evolutionary models alternative to
 Brownian Motion. The Akaike Information Criterion (AIC) was computed to
 compare the fitted models, with the best models selected based on the
 lowest AICc and a ΔAIC of less than 2. The best model of evolution for the
 categorical variables was investigated using <em>fitDiscrete
 </em>function (R package geiger; Pennell et al., 2014), and selected
 by comparing AICs and ΔAICs. The best model parameters were used to
 estimate the ancestral character states for both continuous and discrete
 variables. Disparity through time, which is a metric
 that represents morphological variance among species within a specific
 time interval, was computed by accounting or not for the reconstructed
 ancestral state. The Partial Disparity Analysis (PDA) was also computed to
 explore how ecological groups and orders contributed to the changes in
 morphological disparity. Because our study aimed to
 investigate the effect of temperature and primary productivity on
 morphological disparity in mammalian limb proportions throughout the
 Cenozoic, we collected climatic data from Zachos et al. (2008) and used
 the linear stochastic differential equation (SDE) approach to test the
 hypothesis that environmental changes and/or clade interactions affected
 morphological variation. Finally, we used the
 <em>swapOne</em> function (R package RRphylo; (Raia et al.,
 2019) to validate the results in light of phylogenetic
 uncertainty.
 <strong>References</strong> 
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 D. W. (1999). Energetic constraints on the diet of terrestrial carnivores.
 <em>Nature</em>,<em> 402</em>(6759), 286-288.
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description: # Data from: Morphological disparity of mammalian limb bones throughout
 the Cenozoic: the role of biotic and abiotic factors
 [https://doi.org/10.5061/dryad.8gtht76sp.](https://doi.org/10.5061/dryad.8gtht76sp) We submitted the raw data (**Data 1.csv**), species phylogenetic position and ecological categories with references (**Data 2.csv**), node age references (**Data 3.csv**), time bin intervals for tips (**Data 4.csv**), time bin intervals for tips plus nodes (**Data 5. csv**), disparity computed using data from the swapped – tree (**Data 6.zip**). --- ## Descriptions **Data 1- Rawdata** * *Species:* species name * *Locality*: the paleontological site where the specimen was found * *Cat:* museum catalogue number * *Humerus (mm)*: humerus length in millimetres * *Radius (mm)*: radius length in millimetres * *Femur  (mm):* femur length in millimetres * *Tibia  (mm)*: tibia length in millimetres * *Brachial index (R/H)*: brachial index computed as the radius to humerus ratio  * *Crural index (T/F):* crural index computed as the tibia-to-femur ratio * *Greatest skull length (mm)*: the greatest skull length in millimetres * *Note*: additional information on collected specimen * *Source*: references **Data 2 - Species phylogenetic position and ecological categories with references** * *Species:* species name * *Source phylogeny 1*: Reference at low level taxon * *Source phylogeny 2*: Reference at high level taxon * *Order*: species order * *First appearance (FA):* age of the first appearance of the species in the fossil record * *Last appearance (LA):* age of the last appearance of the species in the fossil record * *Source FA-LA*: Reference for both FA and LA * *Synonymous*: species synonymous * *Trophic level*: trophic level category * *Source Trophic level*: reference for trophic level category * *Substrate*: Locomotor behaviour category * *Source substrate*: Locomotor behaviour category references * *Diet*: diet category * *Source Diet*: diet category references * *Habitat*: habitat category * *Source habitat 1*: the primary references for the habitat category * *Source habitat 2*:  the secondary references for the habitat category                           **Data 3 - Node age references** * *Node*: node name associated with the phylogenetic tree. If NA there is no node label defined in the phylogenetic tree structure * *Species1- Species2*: specie pairs used to identify the most recent common ancestor to calibrate the phylogenetic tree in R software * Ages: node age * *source1*: the primary source for the node age * *source2*: the secondary source for the node age **Data 4 - Time bin intervals for tips** * *stage*: Cenozoic stage names * *max.age:* minimum stage age * *min.age*: maximum stage age **Data 5 - Time bins intervals for tips plus nodes.** * *stage:* Late Cretaceous and Cenozoic stage names * *max.age:* minimum stage age * *min.age*: maximum stage age **Data 6 - Disparity computed using data from the swapped – tree** Disparity plots were computed using data derived from the phylogenetic uncertainty analyses. In this case, we employed the *swapOne* function (RRphylo R package) to validate results in light of phylogenetic uncertainty. The function allowed random changes in tree tip positions and branch lengths, producing "swapped trees". The sensitivity analysis was performed on a comprehensive dataset, including living and fossil species. **Key Information Sources** Diet, locomotor behaviour, habitat, first and last appearance, and node ages were derived from the following sources: * Animal Diversity Web * IUCN Red List * Fossilworks * Paleobiology database * Now