bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
1 Evolution of bone cortical compactness in slow arboreal mammals
2
3 Alfieri F.1,2, Nyakatura J.A.1, Amson E.2
4 1. Institut für Biologie, Humboldt Universität zu Berlin, Berlin, Germany. 5 6 2. Museum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Berlin, 7 Germany. 8 9
10 Abstract
11 Lifestyle convergences and related phenotypes are a major topic in evolutionary biology. Low bone
12 cortical compactness (CC), shared by the two genera of ‘tree sloths’, has been linked to their convergently
13 evolved slow arboreal ecology. The proposed relationship of low CC with ‘tree sloths’ lifestyle suggests a
14 potential convergent acquisition of this trait in other slow arboreal mammals. ‘Tree sloths’, ‘Lorisidae’,
15 Palaeopropithecidae, Megaladapis and koalas were included in a phylogenetically informed CC analysis of
16 the humerus and femur, as well as closely related but ecologically distinct taxa. We found that ‘tree sloths’ are
17 unparalleled by any analysed clade, in featuring an extremely low CC. A tendency for low CC was however
18 found in palaeopropithecids (especially Palaeopropithecus) and Megaladapis. On the other hand, low CC was
19 not found in ‘Lorisidae’. Koalas, although deviating from the compact structure generally observed in
20 mammals, are not clearly distinct from their sister taxon (wombats) and show humeral CC that is higher than
21 femoral CC. Multiple factors seem to influence CC, preventing the recognition of a simple relationship
22 between slow arborealism and low CC. Highly compact cortical bone in extinct sloths confirms that low CC
23 in ‘tree sloths’ likely represents a recent convergence.
24
25 Corresponding author: Fabio Alfieri, email: [email protected]
26
27 Keywords: convergent evolution, bone microstructure, humerus, femur, tree sloths, subfossil lemurs bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
28 1. Background
29 Tetrapod long bones microstructure is known to reflect life history, physiology, phylogeny, ontogenetic
30 growth and lifestyle [1–3]. Indeed, diaphyseal microstructure has been related to ecology [2,4,5] and employed
31 to infer it in extinct tetrapods (e.g. [6,7]). Moreover, this relationship potentially enables to recognise patterns
32 of convergent evolution [8].
33 To highlight convergent phenotypes, mammals are particularly suitable to be investigated given their
34 remarkable diversity of lifestyles. Mammalian groups with different ecological adaptations can be
35 discriminated analyzing several diaphyseal microstructural parameters (e.g. [9,10]). The amount of porosities
36 in the diaphyseal compact cortical bone, or cortical compactness (CC), was recently quantified in the humerus
37 of adult extant and extinct xenarthrans. The two lineages of extant sloths (Choloepus and Bradypus),
38 characterised by an exceptionally slow arboreal lifestyle [11], were found to feature lower CC in respect to
39 other similar-sized taxa which conversely follow the generalised mammalian condition of high CC [12].
40 Because ‘tree sloths’ are not monophyletic (hence the quotation marks employed herein), this trait was
41 identified as one of the convergent traits related to their independently acquired slow arboreal lifestyle [11,12].
42 If indeed driven by adaptation to this lifestyle, a low CC may have convergently evolved in other slow arboreal
43 therians, too. With ‘Slow Arboreal’, we refer to species characterised by exceptionally slow and cautious
44 movements on trees and daily activities budgets dominated by rest and quiescence. This set of traits is generally
45 associated with unusually low metabolic rate. To date, no CC analyses were performed on slow arboreal
46 mammals, beside the one on ‘tree sloths’ [12]. Following the latter, we quantified CC in the humerus.
47 Moreover, we also investigated CC of the femur, since this bone is often employed in microstructural analysis
48 (e.g. [13,14]).
49 Together with ‘tree sloths’, we analysed other known slow arboreal lineages, namely the koala
50 Phascolarctos cinereus [15] and ‘lorisids’ [16], with the latter arguably representing a paraphyletic group (see
51 Materials and Methods). Moreover, taxa from two late Quaternary-Holocene subfossil lineages of Malagasy
52 strepsirrhines, Palaeopropithecidae (Palaeopropithecus, Mesopropithecus and Babakotia) and Megaladapidae
53 (Megaladapis) [17,18], are here investigated. They were described as slow and poorly agile arboreal, through
54 postcranial (gross anatomy, e.g. [17,19], diaphyseal and epiphyseal geometric properties, [20]) and cranial [21] bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
55 evidences (reviewed in [18,20]). Beside the taxa introduced above, a set of close relatives, conversely
56 characterised by different lifestyles, is also studied (Figure 1, Table S1). Taking into account phylogenetic
57 relationships, this ecologically heterogeneous sample enables to identify convergent acquisitions of slow
58 arboreality in the sampled taxa and to highlight a potential pattern of convergent low CC in slow arboreal
59 therians. Noticeably, the sample characterised by distinct lifestyles includes specimens of extinct sloths from
60 the Patagonian Early Miocene Santa Cruz Formation [22–24]. Analyzing them can additionally inform on the
61 evolution of low CC in the two lineages of ‘tree sloths’ and corroborate the proposed recent convergence [12].
62 In this study, humeral and femoral CC are quantified in a wide mammalian sample, representing slow
63 arboreal clades and near relatives with diverging lifestyles. Results are interpreted in a phylogenetically
64 informed manner. In this way, slow arboreality convergences could be reconstructed and ecological effects on
65 CC are preponderantly taken into account. If a direct relationship with this extreme lifestyle is present, we
66 expect to find the convergent slow arboreal groups consistently showing lower CC in respect to close relatives.
67
68 2. Material and Methods
69
70 a. Sampled collections
71 Ten mammals collections were sampled: Museum für Naturkunde, Berlin (ZMB), Staatliches Museum
72 für Naturkunde, Stuttgart (SMNS), Zoologisches Forschungsmuseum Alexander Koenig, Bonn (ZFMK),
73 Zoologische Staatssammlung, Munich (ZSM), Germany; Naturhistorisches Museum, Wien (NMW), Austria;
74 Muséum national d'Histoire naturelle, Paris (MNHN), France; American Museum of Natural History, New
75 York, NY, (AMNH), Field Museum of Natural History, Chicago, IL, (FMNH), Yale Peabody Museum of
76 Natural History, New Haven, CT, (YPM-PU) and Division of Fossil Primates, Duke Lemur Center, Durham.
77 NC (DPC), USA. A total of 106 humeri and 106 femora, belonging to 47 taxa were sampled. Only non-
78 pathological, non-captive and adult individuals were included. Adulthood was established assessing the degree
79 of epiphyseal fusion, in general, and bone size for marsupials, given their incomplete epiphyseal fusion through
80 adulthood [25]. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
81
82 Figure 1. Time-calibrated tree of mammalian taxa here analysed. Six events of convergent acquisition of ‘Slow Arboreal’ 83 adaptations were reconstructed with Stochastic Character Mapping [26]. It is shown by light blue branches and rectangles. 84 Taxa not sampled for the cortical compactness analysis are indicated with *. The figure was built with the ‘geoscalePhylo’ 85 function (‘strap’ R 3.6.3. package, [27]) and modified in Inkscape [28].
86
87 b. Data acquisition
88 Bones were scanned using micro Computed-Tomography (µCT) (Phoenix | x-ray Nanotom, GE Sensing
89 and Inspection Technologies GmbH; XYLON FF35-CT-System, YXLON GmbH; Microtomograph RX
90 EasyTom 150; Nikon XTH 225 ST; GE v|tome|x). CC being acquired at mid-diaphysis (see below), the field
91 of CT-scan acquisition was focused on this region, in order to reach the highest possible resolution. The mid-
92 shaft was defined as 50% of the whole bone length (Figure S1). Image stacks (16-bit tifs) were acquired with
93 a resolution ranging from 0.0045 to 0.0662 mm (Table S2 and S3), from which the 50% slice was taken. This
94 resolution range typically allows capturing all vacuities except for the smaller lumen of osteons [12] and it is bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
95 here confirmed for lower resolutions as well. The resolution is unavoidably affected by interspecific
96 differences in bone gross anatomy. Indeed, the presence of bony processes at mid-diaphysis (e.g. third
97 trochanter in the femur of Cingulata) forces an acquisition with longer specimen to X-ray source distance, thus
98 with lower resolution. For one specimen (femur of Priodontes maximus ZSM 1931-293) the resolution was
99 purposely increased excluding the mid-diaphysis process from the acquired field of view (not needed to
100 compute CC, see below and Supplementary Materials Figures S2, S3 and S4). Since its CC falls within the
101 range of Cingulata (Table S3), we will assume that the associated bias is minor.
102
103 c. Data processing
104 Following Montañez-Rivera et al. [12], all mid-shaft cross-sections were imported into Fiji [29] and
105 automatically binarised (‘Optimize Threshold’ function, BoneJ plugin, [30]). It was effective for almost all
106 specimens. Manual correction was necessary for two specimens. For one humerus and one femur of
107 Palaeopropithecus, dense, non-osseous material was present (clearly identifiable before binarisation). The
108 corresponding area was selected (‘Threshold’ and ‘Create Selection’ Fiji functions) and deleted (i.e. grey
109 values set to 0), before running ‘Optimize Threshold’. Post-binarisation corrections were performed for about
110 15% and 25% of the humeri and femora, respectively (specimens with PostBinarCorr = ‘Yes’ in Tables S2 and
111 S3). In such cases, since non-osseous material was recognised as ‘bone’ by the thresholding, it was manually
112 deleted from the slices after having confirmed its nature observing images before thresholding and regions
113 contiguous to the mid-shaft.
114
115 d. Quantification of the Cortical Compactness (CC)
116 Following the criteria of Montañez-Rivera et al. [12], a Region Of Interest (ROI) was selected on each
117 cross-section, including cortices and excluding spongiosa and medullary cavity (‘Wand (tracing)’ Fiji tool;
118 Figure S1). In about 65% of the humeri and 60% of the femora, the cortex-spongiosa transition was not abrupt
119 (specimens with SpongManualSel = ‘Yes’ in Tables S2 and S3), which required a manual selection [12]. The
120 transition was unambiguously located connecting the most external holes considered as part of the medullary bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
121 cavity (‘Polygon selection’ Fiji tool). Bony processes at the mid-shaft level, found in about 35% and 30% of
122 the sampled humeri and femora, respectively (specimens with BoneProc= ‘Yes’ in Tables S2 and S3), were
123 excluded by identifying the level of first cortical thinning and spongious bone appearance and using straight
124 lines, perpendicular to the outer cortical surface. Cracks within the cortical region were not included in the
125 ROIs. See Figure S2 for a demonstration of ROI selection criteria. For each ROI, the percentage of bone pixels
126 relative to total area (ratio representing the cortical compactness, CC) and the cortical area (CA, reliable body
127 size predictor [31]) were computed (respectively ‘Area Fraction’ and ‘Area’ routines, ‘Measure’ function of
128 Fiji). All cross-sections with ROIs used for CC and CA computation are shown in Figures S3 and S4 while
129 raw CC and CA values are listed in Tables S2 and S3.
130
131 e. Time-tree for phylogenetic comparative methods
132 To take into account non-independence of observations due to phylogenetic relationships, a time-tree of
133 the studied species was used to phylogenetically inform the statistical analysis (Figure 1). We used a Maximum
134 Clade Credibility (MCC) DNA-only node-dated mammals phylogeny taken from the related posterior
135 distribution of the work of Upham et al. [32] and representing 4098 species. In doing so, polytomies and
136 unresolved nodes were avoided [32]. However, several adjustments to fit our sample were performed in
137 Mesquite [33]. Two extant species (Dasypus septemcinctus and Tamandua mexicana) were added following
138 recently published phylogenetic positioning and divergence times [34,35]. Moreover, extinct taxa were
139 subsequently added based on previously published morphological phylogenies and/or analyses of recovered
140 genetic information [36–38]. Santacrucian sloths’ families position in respect to Choloepus and Bradypus and
141 all node ages of Folivora (extinct + extant sloths) were constrained on the tree provided by Delsuc et al. [36].
142 However, since none of the extinct sloths we studied were present in this tree, infra-familiar relationships
143 followed the morphological phylogeny built by Varela et al. [37]. First Appearance Datum (FAD) and Last
144 Appearance Datum (LAD) are respectively 17.5 and 16.3 Mya for the analysed extinct sloths, which all come
145 from the Santa Cruz Formation [39]. Divergence times between Hapalops and Eucholoeops and between
146 Analcitherium and Nematherium could only be placed in a period ranging from the previous node to the FAD.
147 In such cases, the divergence time was arbitrarily set halfway between these two corresponding ages. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
148 Mesopropithecus and Babakotia, not present in the tree from Upham et al. [32], were added following the
149 phylogeny of Herrera and Dávalos [38]. This phylogeny was used to set topology and date nodes for the
150 (‘Indriidae’+Palaeopropithecidae) clade, with ‘Indriidae’ being paraphyletic [38]. Indeed, constraining ages
151 only for palaeopropithecids would have resulted in a lack of consistency with the tree from Upham et al. [32],
152 concerning their temporal relationships with ‘Indriidae’. It is noteworthy that the MCC tree used here involves
153 that ‘Lorisidae’ are paraphyletic. Monophyly of the group is debated, with several phylogenies yielding
154 disagreeing results (e.g. [40–42]).
155
156 f. Ancestral Lifestyle Reconstruction
157 All statistical analyses were performed in R 3.6.3 [43]. Independent acquisitions of slow arboreal lifestyle
158 were reconstructed with Stochastic Character Mapping (SCM; [26]). SCM was performed using the sampled
159 taxa and an additional set of species (n=12) included to have a wider and more representative taxonomic sample
160 of mammalian lifestyles (3 Monotremata, 8 Marsupialia and Daubentonia madagascariensis; Figure 1). We
161 assigned a binary state Slow Arboreal/Non-Slow Arboreal to each terminal taxon, and applied the
162 ‘make.simmap’ R function for SCM (Equal Rate model, 1000 simulations, ‘phytools’ package; [44]).
163
164 g. Relationship between Cortical Compactness (CC) and lifestyle
165 The relationship between humeral/femoral CC and lifestyle (binary categorical variable: Non-Slow
166 Arboreal or Slow Arboreal) was tested through Phylogenetic Generalized Least Square (PGLS) regressions.
167 For both the humerus and the femur we performed a phylogenetic ANCOVA, controlling body mass effects
168 adding CA as covariate (‘gls’ function; method “ML”, ‘nlme’ R package; [45]). We used mean species CC
169 and CA values, both log-transformed. Individuals of extant species catalogued only at the generic level were
170 here excluded and the regressions were phylogenetically informed using Pagel’s lambda (‘corPagel’ function,
171 ‘ape’ R package, [46]). No significant relationship was found between CC and body mass (p-valuehumerus=0.45
172 and p-valuefemur=0.37). Humeral and femoral CC were visualised through boxplots (‘ggplot’ function,
173 ‘ggplot2’ R package; [47]) and mean CC values mapped on the phylogeny (‘contMap’ function, ‘phytools’ R bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
174 package; [44]), with graphs modified in Inkscape [28] for visualization (Figure 2). Supporting material and
175 dataset are available from Figshare Digital Repository (https://doi.org/10.6084/m9.figshare.12896249.v4)
176 [48].
177
178 3. Results
179 From SCM arose a highly probable ancestral Non-Slow Arboreal condition and the convergent acquisition
180 of slow arboreality in ‘Lorisidae’, Megaladapis, Palaeopropithecidae, Choloepus, Bradypus and P. cinereus,
181 which will be referred hereafter as slow arboreal clades. The aforementioned paraphyly for ‘Lorisidae’
182 involves that Asian ‘Lorisidae’ (Nycticebus and Loris) are more closely related to Galagidae than to African
183 ‘Lorisidae’ (Arctocebus and Perodicticus). Accordingly, a result of SCM is the ancestral slow arboreal
184 condition for Lorisiformes (‘Lorisidae’ + Galagidae) with subsequent reversion in active leaping Galagidae
185 (Figure 1).
186 CC values are significantly correlated with lifestyle (p-valuehumerus = 0.4e-05; p-valuefemur = 28e-05).
187 However, it is obvious that not all slow arboreal clades contribute to the difference and residuals of both
188 humeral and femoral regressions significantly deviate from normality (Shapiro-Wilk test, p-valuehumerus=2.8e-
189 05 and p-valuefemur=50e-05).
190
191 a. CC of ‘tree sloths’ vs. other xenarthrans
192 In both the humerus and the femur, ‘tree sloths’ represent the clades with the lowest CC in the entire
193 therian sample (especially Choloepus, with minima of CChumerus = 96.08% and CCfemur= 96.87%; Figure 2).
194 Their diaphyseal microstructure is characterised by numerous and large cavities, widespread in the cortex
195 (Figures S3 and S4). ‘Tree sloths’ sharply contrast other extant (Vermilingua and Cingulata) and extinct
196 (Nematherium, Analcitherium, Hapalops, Eucholoeops, Prepotherium) xenarthrans, conversely characterised
197 by higher CC. Moreover, ‘tree sloths’ are also distinct from other xenarthrans in exhibiting a wider CC range bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
A B
C D
Figure 2. Box-and-whisker plots of humeral (A) and femoral (B) cortical compactness (CC), with specimens grouped
by taxon. Black triangles and vertical bars indicate mean and median CC, respectively. B. Phylogenetic maps of the
humeral (left) and femoral (right) CC averaged for each species (or genus for extinct taxa).
198 of variability. Choloepus stands out on that regard as well, with a CC range of 2.99% and 2.48% for the bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
199 humerus and femur, respectively (Table S1; Figure 2A, B). With high CC values and less variable CC, the
200 other xenarthrans mirror the generalised mammalian condition. Vermilinguans also show a relatively wide
201 range of CC variation (0.96% in the humerus and 1.05% in the femur). This is mainly due to the low values of
202 Cyclopes didactylus (4 individuals with means of CChumerus=99.3% and CCfemur=99.2%) and Tamandua
203 mexicana (only one humerus and one femur with CC of 99.11% and 98.95%, respectively). Similarly to
204 Bradypus and Choloepus, the vacuities of Cy. didactylus are widespread in the cortex and the spatial pattern is
205 reminiscent of that of ‘tree sloths’. On the other hand, porosities of T. mexicana appear to be mainly
206 concentrated toward the inner cortex, with few isolated vacuities in the outer regions (Figures S3, S4).
207
208 b. CC of subfossil lemurs vs. other lemurs
209 We found low humeral and femoral mean CC in Palaeopropithecidae (especially Palaeopropithecus) and
210 Megaladapis. It discriminates them from their closest relatives (‘Indriidae’ and Lemuridae, respectively) and
211 other strepsirrhines who, instead, follow the generalised mammalian condition (i.e. high CC). Moreover,
212 subfossil lemurs mirror ‘tree sloths’ also in showing a wide humeral and femoral CC variability. Although not
213 reaching the extreme condition of Choloepus, both palaeopropithecids and Megaladapis approach the CC
214 range of variation of Bradypus, with palaeopropithecids femoral CC range (1.67%) even exceeding Bradypus
215 femoral CC range (1.15%; Figure 2A, B). In one femur of Megaladapis (MNHN MAD 1567) the repartition
216 of the vacuities found throughout the cortex is reminiscent of that of the ‘tree sloths’ (Figure S4). Most of the
217 other subfossil lemurs’ specimens show a heterogeneous distribution of porosities with a concentration toward
218 the inner cortex and an almost complete absence from the periosteal region. On the other hand, Babakotia
219 yielded higher CC values (data only for the humerus, 99.65%), while Mesopropithecus shows contrasting CC
220 values between the humerus (lower CC, 99.2%) and the femur (higher CC, 99.77%; Figure 2C, D).
221
222 c. CC of ‘Lorisidae’ vs. Galagidae bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
223 ‘Lorisidae’ do not show evident differences in CC mean and variability in respect to Galagidae (Figure
224 2A, B). Moreover, no diverging patterns are identified by a closer inspection of different species mean CC
225 values (Figure 2C, D).
226
227 d. CC of koala vs. wombats
228 Mean CC do not clearly differ between koala (P. cinereus) and wombats’ (Vombatus ursinus and
229 Lasiorhinus latifrons). However, a clear difference is observed between humeral and femoral patterns (Figure
230 2). Humeral mean CC is higher than femoral mean CC in both koala (CChumerus=99.50%, CCfemur=99.04%) and
231 wombats (CChumerus=99.68%, CCfemur=98.82%). The femur of P. cinereus shows the widest range in the sample
232 (3.17%). The humerus of the latter show a moderately wide range (0.84%), while wombats exhibit narrower
233 CC ranges for both humerus (0.34%) and femur (0.59%). Specimens of P. cinereus with lower CC show a
234 preferential distribution of the porosity toward the endosteal margin. Conversely, more porous specimens of
235 wombats (for example, femur of V. ursinus SMNS 26510) show vacuities that are widespread in the whole
236 cortex (Figures S3 and S4).
237
238 4. Discussion
239
240 a. Humeral and femoral CC in ‘tree sloths’ and other xenarthrans
241 Our analysis of an extensive sampling of therian mammals, confirmed that ‘tree sloths’ exhibit lower CC
242 compared to other xenarthrans, as previously shown [12], and highlights their convergent humeral and femoral
243 CC decrease. Choloepus’ humerus and femur also exhibit the highest variability. None of the analysed taxa
244 reaches ‘tree sloths’ extreme mean levels of low CC (Figure 2; Table S1). Montañez-Rivera et al. [12] related
245 ‘tree sloths’ low CC to extensive bone remodeling, namely the continuous process involving the generation of
246 resorption cavities (through bone resorption) and the deposition, within such spaces, of secondary osteons
247 [49,50]. Vacuities on µCT cross-sections were identified as resorption cavities at various maturation stages
248 recognised on histological sections [12,51]. ‘Tree sloths’ sharply contrast the general condition of terrestrial bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
249 mammals in which the diaphyseal cortex shifts from highly porous and remodeled juvenile structures to lower
250 remodeling rates in adults [12]. The latter results in few resorption cavities [49,52] and causes the generalised
251 mammalian high CC. Conversely, low CC in adult ‘tree sloths’ suggests intense remodeling still active through
252 adulthood.
253 High CC of Santacrucian extinct sloths resembles Vermilingua (but see discussion on Cy. didactylus and
254 T. mexicana below) and Cingulata rather than more closely related ‘tree sloths’. Albeit with similar evidence,
255 Montañez-Rivera et al. [12] did not exclude the possibility that low CC could characterise some extinct sloths.
256 Conversely, specimens here analysed, which extend the sample of Montañez-Rivera et al. [12], coherently
257 point toward high CC in extinct sloths. This supports the convergent acquisition of the trait in the lineages
258 leading to Bradypus and Choloepus and it can be added to the phenotypical convergent traits shared by ‘tree
259 sloths’ [11]. While the extinct sloths sampled here belong to three families [37], they all come from one locality
260 (Patagonian Early Miocene Santa Cruz Formation, 17.5-16.3 Mya; [23,39]). Considering the taxonomical and
261 ecological diversity of extinct Folivora [53], studying taxa from other ages and geographical contexts may
262 elucidate the pattern of evolution of CC in the clade.
263 Low CC was found for the silky anteater, Cy. didactylus. Due to its elusive nocturnal habits, the ecology
264 of Cy. didactylus is poorly known. However, available information suggests that it is almost fully arboreal and
265 slow moving [54–56]. Postcranial similarities to ‘tree sloths’ have been already highlighted [57]. The
266 convergence of low CC in ‘tree sloths’, together with slightly lower CC in Cy. didactylus, suggests a
267 relationship between low CC and slow arboreality within xenarthrans. Long bone thin-sections of Cy.
268 didactylus are needed to confirm that porosities observed throughout the cortex (yielding slightly lowered CC)
269 are indeed resorption cavities or immature secondary osteons, as in ‘tree sloths’. The spatial distribution of
270 vacuities in Cy. didactylus is reminiscent of the ‘tree sloths’ pattern (Figures S3 and S4). Pending histological
271 confirmation, we tentatively propose ongoing bone remodeling in adult silky anteaters. The low CC values of
272 T. mexicana, contrasting Tamandua tetradactyla’ s more compact structure (Figures 2C, D), is puzzling. No
273 major ecological differences between the two (non-slow) semiarboreal Tamandua species are reported [58,59].
274 However, since CC values of T. mexicana come from a single individual (Table S2, S3), the possibility of
275 biases related to small sample size should be considered. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
276
277 b. Humeral and femoral CC in slow arboreal primates and marsupials
278 Similarly to ‘tree sloths’, Palaeopropithecidae (mainly Palaeopropithecus) and Megaladapis show
279 independent acquisition of humeral and femoral low CC with higher variability (Figure 2). Several postcranial
280 convergences between subfossil lemurs and ‘tree sloths’ are documented [18–20]. Due to the abundant
281 inferences of slow arboreal ecology for palaeopropithecids and megaladapids [17–21], low CC could be a
282 convergence driven by their similar purported lifestyle. However, the subfossil lemurs analysed here show a
283 CC that, despite being clearly lower than in other lemurs, is not comparable to the extreme levels of ‘tree
284 sloths’. Only Palaeopropithecus and Megaladapis show similarly low humeral and femoral CC, while
285 Babakotia and Mesopropithecus yielded higher CC and/or contrasting inter-limb patterns (Figure 2). One
286 should note that Palaeopropithecus and Megaladapis are the most represented subfossil lemurs in the sample
287 (Table S2, S3). In contrast, the femur of Babakotia was not analysed and the only available humerus is not
288 well preserved. Likewise, Mesopropithecus’ humeri are only preserved poorly (Figure S3). Biases deriving
289 from low number of analysed bones and specimens’ preservation should thus be taken into account. No osteo-
290 histological analyses are available for subfossil lemurs, which prevents the characterization of the cortical
291 vacuities responsible for low CC in Palaeopropithecus and Megaladapis. The concentration of porosities
292 toward the inner cortex in some of their specimens matches the distribution of secondary osteons in humeral
293 and femoral thin-sections of ‘Indriidae’ and Lemuridae [60]. This suggests that the cortical vacuities observed
294 in subfossil lemurs are resorption cavities (immature secondary osteons). This would imply relatively intense
295 and perennial bone remodeling being responsible for the low CC of Palaeopropithecus and Megaladapis.
296 Strikingly, humeral/femoral CC do not differ between ‘Lorisidae’ and Galagidae and both taxa do not
297 deviate from the mammal general condition of highly compact/little variable adult cortex. Indeed, their highly
298 diverging arboreal habits (slow arboreal in ‘Lorisidae’, [16] vs. active leaping in Galagidae, [61]) were
299 considered explanatory for postcranial differences in both external and internal anatomy [62]. Moreover,
300 several postcranial convergences between ‘Lorisidae’ and ‘tree sloths’ are reported [57,63].
301 Koala and wombats do not consistently differ in CC and we found differences between humeral and
302 femoral CC, with the latter lower than the former in both koalas and wombats. Moreover, koalas exhibit the bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
303 largest CC variability in our sample. Considering their ecological differences (slow arboreality of P. cinereus
304 [15] vs. terrestrial fossoriality in wombats, [64]) lifestyle alone can hardly explain the CC pattern and suggest
305 additional/alternative explanations. Differing from most marsupials, Vombatus ursinus’ cortex is intensely
306 remodeled [65,66] and it is reasonable to ascribe the vacuities in wombats’ cortex to immature secondary
307 osteons. Walker et al. [66] hypothesised that wombats’ humeral microstructure could be explained by
308 physiological and biomechanical adaptations to fossoriality. We propose that physiological effects,
309 systemically lowering CC through remodeling, may be locally attenuated by biomechanical needs for a
310 compact structure in the humerus related to wombats’ forelimb based scratch-digging [66]. This scenario
311 would be consistent with CC values lower in the femur than in the humerus, as found in Vombatus ursinus.
312 Secondary osteons are almost absent from the cortex of P. cinereus [65], contrasting with xenarthrans
313 [51] and other slow arboreal therians considered here. Large vascular canals are however present in P. cinereus,
314 especially in the endosteal region [65] We hence tentatively propose that the slightly higher humeral CC
315 variability and the extremely wide femoral CC range of P. cinereus could be explained by a more variable
316 extension of the observed primary vascularization in this species. In any case, the CC pattern of P. cinereus
317 seems to reflect different factors than those of the other mammals investigated here.
318
319 c. Relationship of low CC and bone remodeling with low metabolic rate
320 Several bone microstructural features and bone remodeling were linked to metabolic rates [67–69]. Low
321 CC was qualitatively observed in humerus, femur, and other postcranial elements of ‘tree sloths’ [12],
322 suggesting that a systemic phenomenon as low metabolism plays a role [12]. Indeed, ‘tree sloths’ exhibit a
323 strikingly low metabolic rate for their body size [70,71]. Moreover, low thyroid activity was reported for
324 Choloepus [72]. Thyroid hormones contribute to metabolism [73] and bone growth [74] regulation.
325 Accordingly, intense but balanced remodeling through adulthood, responsible for low CC, was inferred for
326 ‘tree sloths’ [12]. Cy. didactylus convergently appears to have acquired low CC. Beside evidence of slow
327 arboreal ecology [54–56], Cy. didactylus’ metabolism was reported as lower than expected for its mass (but
328 not as low as Bradypus; [56]). This suggests that slow arboreality/hypometabolism could be responsible for
329 low CC in 'tree sloths’ and Cy. didactylus. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
330 Moderately low CC was independently acquired in palaeopropithecids (especially Palaeopropithecus)
331 and Megaladapis. Despite the impossibility to directly measure metabolic activity in subfossil lemurs, several
332 clues point toward hypometabolism [17]. Energy saving strategy is generally related to folivory [75], and this
333 trophic adaptation was inferred for both palaeopropithecids and Megaladapis [17,19,76]. Moreover, tooth
334 enamel accretion periodicity (Retzius periodicity) suggests possibly low metabolic activity [18,67,77]. We
335 hypothesise that their hypometabolism is related to their actively remodeled cortex, which is in turn responsible
336 for the relatively low CC in these taxa.
337 ‘Lorisidae’ slow arboreal lifestyle is accompanied with low body mass-corrected metabolic activity [78].
338 It distinguishes them from other strepsirrhines, which are generally hypometabolic [79]. This condition mirrors
339 that of ‘tree sloths’ and their distinctively low metabolism within the generally hypometabolic Xenarthra [71].
340 Nevertheless, no low CC was found in ‘Lorisidae’ and they do not show differences in CC to Galagidae. Both
341 taxa follow the general therian condition. Differences from galagids in the pattern of intracortical remodeling
342 were identified on osteo-histological sections and ascribed to the slow arboreal locomotion of ‘Lorisidae [60].
343 Positional behaviour could thus preponderantly explain cortical microstructure and intracortical remodeling in
344 this clade, with metabolism considered a negligible factor [60].
345 CC in koala and wombats unlikely is explained in terms of lifestyle alone. P. cinereus belongs to a
346 generally hypometabolic clade, the marsupials, and its unusually low metabolism stands out [64]. Although
347 their terrestrial lifestyle is distinct from slow arboreal, wombats are known for their energy conserving
348 adaptations [80]. We found that Vombatiformes’ CC deviates from the general mammalian pattern, with higher
349 values in the humerus than in the femur in both taxa. To explain the relatively higher CC in the wombats’
350 humerus in respect to the femur, we propose that biomechanical demands for high CC related to their forelimb
351 dominated scratch-digging, could locally act on the humerus [66]. The CC discrepancy between humeral and
352 femoral mean CC remains unclarified in P. cinereus, especially when considering a systemic explanation.
353 However, its inter-limb difference in mean CC is less extreme than in wombats, and the most striking aspect
354 of koala’s CC is its variability. As shown by histology, P. cinereus is clearly distinct from other slow arboreal
355 therians with extremely low bone remodeling activity [65]. We hypothesise that the CC pattern of P. cinereus,
356 distinct from those of other slow arboreal mammals, does not reflect bone remodeling and metabolic factors. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
357 5. Conclusions
358 Adult ‘tree sloths’ are characterised by low humeral and femoral CC. The trait was previously linked to
359 highly active bone remodeling and low metabolism, related to their slow arboreal lifestyle. Extinct sloths
360 sampled here show high levels of CC, thus low CC likely represents a recent convergence in ‘tree sloths’,
361 reflecting their convergent lifestyle. Their extreme low CC are not paralleled by other slow
362 arboreal/hypometabolic mammals. Nevertheless, relatively low CC identified in Palaeopropithecus and
363 Megaladapis appears to be a convergent trait shared with ‘tree sloths’. This finding, together with the striking
364 evidence of low CC in the silky anteater (Cyclopes didactylus), supports a driving role of slow arboreality/low
365 metabolism on CC. However, the absence of a clear overall pattern in all analysed slow arboreal/hypometabolic
366 therians calls for additional or alternative explanations. Future studies, possibly including a more diverse
367 mammal sample and also non-arboreal hypometabolic mammal species, ideally complemented with
368 experimental physiological evidence, are required to shed light on the functional significance of low CC.
369 Data accessibility
370 The analysed dataset is available on Figshare Digital Repository
371 (https://doi.org/10.6084/m9.figshare.12896249.v4) [48]. The Museum für Naturkunde (Berlin, Germany)
372 stores raw CT data, making them available upon reasonable request.
373
374 Authors’ contribution 375 F.A. collected the sample, acquired, processed and analysed µCT data, performed statistical analysis
376 and drafted the manuscript. All authors designed the study, interpreted the data, and contributed to the
377 writing and editing of the manuscript.
378 Competing interests
379 Authors declare that no competing interests are involved.
380 Funding bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
381 The study was funded by Elsa-Neumann-Stipendium (Humboldt-Universität zu Berlin), the German
382 Research Council (Deutsche Forschungsgemeinschaft; grant number AM 517/1-1) and the Kickstarter
383 Program from RTNN (NC, USA).
384
385 Acknowledgements
386 We would like to thank curators and assistant curators who allowed visits to collections and specimens
387 access: Frieder Mayer, Christiane Funk and Anna Rosemann (ZMB), Eva Bärmann (ZFMK), Frank Zachos
388 and Alexander Bibl (NMW), Stefan Merker (SMNS), Anneke van Heteren (ZSM), Guillaume Billet (MNHN),
389 Neil Duncan (AMNH), Sara Ketelsen (AMNH), Vanessa Rhue (YPM-PU), Daniel Brinkman (YPM-PU),
390 Adam Ferguson (FMNH), William Simpson (FMNH), Matt Borths (DPC) and Catherine Riddle (DPC).
391 Moreover, we acknowledge Kristin Mahlow and Martin Kirchner (Museum für Naturkunde, Berlin), Renaud
392 Lebrun (MRI-ISEM, Montpellier), Justin Gladman (SMIF, Durham, NC, USA), April Isch Neander and Zhe-
393 Xi Luo (University of Chicago, IL, USA) for allowing access to Micro-CT scanners, providing precious
394 assistance. We acknowledge the MRI platform member of the national infrastructure France-BioImaging
395 supported by the French National Research Agency (ANR-10-INBS-04, «Investments for the future»), the
396 labex CEMEB (ANR-10-LABX-0004) and NUMEV (ANR-10-LABX-0020). This work was performed in
397 part at the Duke University Shared Materials Instrumentation Facility (SMIF), a member of the North Carolina
398 Research Triangle Nanotechnology Network (RTNN), which is supported by the National Science Foundation
399 (Grant ECCS-1542015) as part of the National Nanotechnology Coordinated Infrastructure (NNCI).
400
401 References 402 403 1. Ricqlès AJ de. 2011 Vertebrate palaeohistology: Past and future. Comptes Rendus Palevol 10, 509–515. 404 (doi:10.1016/j.crpv.2011.03.013)
405 2. Mitchell J. 2016 Cortical bone remodeling in Amniota. A functional, evolutionary and comparative 406 perspective of secondary osteons. PhD Dissertation, Bonn, Germany. See http://hss.ulb.uni- 407 bonn.de/2017/4704/4704.htm. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
408 3. Padian K. 2011 Vertebrate palaeohistology then and now: A retrospective in the light of the 409 contributions of Armand de Ricqlès. Comptes Rendus Palevol 10, 303–309. 410 (doi:10.1016/j.crpv.2011.02.001)
411 4. Germain D, Laurin M. 2005 Microanatomy of the radius and lifestyle in amniotes (Vertebrata, 412 Tetrapoda). Zool Scripta 34, 335–350. (doi:10.1111/j.1463-6409.2005.00198.x)
413 5. Canoville A, Laurin M. 2010 Evolution of humeral microanatomy and lifestyle in amniotes, and some 414 comments on palaeobiological inferences. Biol J Linn Soc 100, 384–406. (doi:10.1111/j.1095- 415 8312.2010.01431.x)
416 6. Arcucci A, Previtera E, Mancuso A. 2019 Ecomorphology and bone microstructure of Proterochampsia 417 from the Chañares Formation. APP 64, 157–170. (doi:10.4202/app.00536.2018)
418 7. Chinsamy A, Angst D, Canoville A, Göhlich UB. 2020 Bone histology yields insights into the biology of 419 the extinct elephant birds (Aepyornithidae) from Madagascar. Biological Journal of the Linnean Society 420 130, Issue 2, 268–295. (doi:10.1093/biolinnean/blaa013)
421 8. Ricqlès A de. 1992 Some remarks on palaeohistology from a comparative evolutionary point of view. In 422 Histology of Ancient Human Bone: Methods and Diagnosis., pp. 37–77. Berlin: Springer-Verlag: Grupe 423 G. and Garland AN. (doi: 10.1007/978-3-642-77001-2).
424 9. Wall WP. 1983 The correlation between high limb-bone density and aquatic habits in recent mammals. 425 Journal of Paleontology 57, 197–207. (doi:10.2307/1304649)
426 10. Fish FE, Stein BR. 1991 Functional correlates of differences in bone density among terrestrial and 427 aquatic genera in the family Mustelidae (Mammalia). Zoomorphology 110, 339–345. 428 (doi:10.1007/BF01668024)
429 11. Nyakatura JA. 2012 The convergent evolution of suspensory posture and locomotion in tree sloths. J 430 Mammal Evol 19, 225–234. (doi:10.1007/s10914-011-9174-x)
431 12. Montañez‐Rivera I, Nyakatura JA, Amson E. 2018 Bone cortical compactness in ‘tree sloths’ reflects 432 convergent evolution. Journal of Anatomy 233, 580–591. (doi:10.1111/joa.12873)
433 13. Hua S, de Buffrénil V. 1996 Bone histology as a clue in the interpretation of functional adaptations in 434 the Thalattosuchia (Reptilia, Crocodylia). Journal of Vertebrate Paleontology 16, 703–717. 435 (doi:10.1080/02724634.1996.10011359)
436 14. Laurin M, Girondot M, Loth M-M. 2004 The evolution of long bone microstructure and lifestyle in 437 lissamphibians. Paleobiology 30, 589–613. (doi:10.1666/0094-8373(2004)030<0589:TEOLBM>2.0.CO;2)
438 15. Grand TI, Barboza PS. 2001 Anatomy and development of the koala, Phascolarctos cinereus: an 439 evolutionary perspective on the superfamily Vombatoidea. Anat Embryol 203, 211–223. 440 (doi:10.1007/s004290000153)
441 16. Jouffroy F, Petter A. 1990 Gravity-related kinematic changes in lorisine horizontal locomotion in 442 relation to position of the body. In Gravity, Posture and Locomotion in Primates., pp. 199–208. Firenze: 443 Il Sedicesimo: Jouffroy F., Stack M. and Niemitz C. (doi:10.1007/BF02547675).
444 17. Godfrey LR, Jungers WL, Schwartz GT. 2006 Ecology and Extinction of Madagascar’s Subfossil Lemurs. 445 In Lemurs: Ecology and Adaptation, pp. 41–64. Springer, New York.: Gould L., Sauther M.L. (doi: 446 10.1007/978-0-387-34586-4_3). bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
447 18. Godfrey LR, Granatosky MC, Jungers WL. 2016 The Hands of Subfossil Lemurs. In The Evolution of the 448 Primate Hand. Anatomical, Developmental, Functional, and Paleontological Evidence., pp. 421–453. 449 Springer, New York: Kivell T.L., Lemelin P., Richmond B.G., Schmitt D. (doi: 10.1007/978-1-4939-3646- 450 5_15).
451 19. Jungers WL, Godfrey LR, Simons EL, Wunderlich RE, Richmond BG, Chatrath PS. 2002 Ecomorphology 452 and Behavior of Giant Extinct Lemurs from Madagascar. In Reconstructing Behavior in the Primate 453 Fossil Record, pp. 371–411. Kluwer Academic/Plenum Publishers, New York.: Plavcan J.M., Kay R.F., 454 Jungers W.L., van Schaik C.P. (doi: https://doi.org/10.1007/978-1-4615-1343-8_10).
455 20. Marchi D, Ruff CB, Capobianco A, Rafferty KL, Habib MB, Patel BA. 2016 The locomotion of Babakotia 456 radofilai inferred from epiphyseal and diaphyseal morphology of the humerus and femur: Babakotia 457 Radofilai Postcranial Suspensory Adaptations. Journal of Morphology 277, 1199–1218. 458 (doi:10.1002/jmor.20569)
459 21. Walker A, Ryan TM, Silcox MT, Simons EL, Spoor F. 2008 The semicircular canal system and locomotion: 460 The case of extinct lemuroids and lorisoids. Evol. Anthropol. 17, 135–145. (doi:10.1002/evan.20165)
461 22. White JL. 1993 Indicators of locomotor habits in xenarthrans: evidence for locomotor heterogeneity 462 among fossil sloths. Journal of Vertebrate Paleontology 13, 230–242. 463 (doi:10.1080/02724634.1993.10011502)
464 23. Perkins ME, Fleagle JG, Heizler MT, Nash B, Bown TM, Tauber AA, Dozo MT. 2012 Tephrochronology of 465 the Miocene Santa Cruz and Pinturas Formations, Argentina. In Early Miocene Paleobiology in 466 Patagonia: high-latitude paleocommunities of the Santa Cruz Formation., pp. 23–40. Cambridge 467 University Press, Cambridge: Vizcaíno, R.F. Kay, and M.S. Bargo (doi: 468 10.1017/CBO9780511667381.003).
469 24. Toledo N. 2016 Paleobiological integration of Santacrucian Sloths (Early Miocene of Patagonia). 470 Ameghiniana 53, 100. (doi:10.5710/AMGH.07.10.2015.2891)
471 25. Werning S. 2013a Osteohistological differences between marsupials and placental mammals reflect 472 both growth rates and life history strategies. Integrative and Comparative Biology 53:E224.
473 26. Bollback JP. 2006 SIMMAP: Stochastic character mapping of discrete traits on phylogenies. BMC 474 Bioinformatics 7, 88. (doi:10.1186/1471-2105-7-88)
475 27. Bell MA, Lloyd GT. 2015 strap: an R package for plotting phylogenies against stratigraphy and assessing 476 their stratigraphic congruence. Palaeontology 58, 379–389. (doi:10.1111/pala.12142)
477 28. Harrington B, et al. 2004 Inkscape. http://www.inkscape.org.
478 29. Schneider CA, Rasband WS, Eliceiri KW. 2012 NIH Image to ImageJ: 25 years of image analysis. Nat. 479 Methods 9, 671–675. (doi:10.1038/nmeth.2089)
480 30. Doube M, Kłosowski MM, Arganda-Carreras I, Cordelières FP, Dougherty RP, Jackson JS, Schmid B, 481 Hutchinson JR, Shefelbine SJ. 2010 BoneJ: Free and extensible bone image analysis in ImageJ. Bone 47, 482 1076–1079. (doi:10.1016/j.bone.2010.08.023)
483 31. Ruff CB. 2003 Long bone articular and diaphyseal structure in Old World monkeys and apes. II: 484 Estimation of body mass. Am. J. Phys. Anthropol. 120, 16–37. (doi:10.1002/ajpa.10118) bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
485 32. Upham NS, Esselstyn JA, Jetz W. 2019 Inferring the mammal tree: species-level sets of phylogenies for 486 questions in ecology, evolution, and conservation. PLoS Biol 17, e3000494. 487 (doi:10.1371/journal.pbio.3000494)
488 33. Maddison DR, Maddison WP. 2019 Mesquite: a modular system for evolutionary analysis. Version 3.61. 489 See https://www.mesquiteproject.org/.
490 34. Feijó A, Vilela JF, Cheng J, Schetino MAA, Coimbra RTF, Bonvicino CR, Santos FR, Patterson BD, 491 Cordeiro-Estrela P. 2019 Phylogeny and molecular species delimitation of long-nosed armadillos 492 (Dasypus: Cingulata) supports morphology-based taxonomy. Zoological Journal of the Linnean Society 493 186, 813–825. (doi:10.1093/zoolinnean/zly091)
494 35. Casali D de melo, Dos Santos Júnior JE, Miranda FR, Santos FR, Perini FA. 2020 Total-evidence 495 phylogeny and divergence times of Vermilingua (Mammalia: Pilosa). Systematics and Biodiversity 18, 496 216–227. (doi:10.1080/14772000.2020.1729894)
497 36. Delsuc F et al. 2019 Ancient mitogenomes reveal the evolutionary history and biogeography of sloths. 498 Current Biology 29, 2031-2042.e6. (doi:10.1016/j.cub.2019.05.043)
499 37. Varela L, Tambusso PS, McDonald HG, Fariña RA. 2019 Phylogeny, macroevolutionary trends and 500 historical biogeography of sloths: insights From a Bayesian morphological clock analysis. Systematic 501 Biology 68, 204–218. (doi:10.1093/sysbio/syy058)
502 38. Herrera JP, Dávalos LM. 2016 Phylogeny and divergence times of lemurs inferred with recent and 503 ancient fossils in the tree. Syst Biol 65, 772–791. (doi:10.1093/sysbio/syw035)
504 39. Bargo MS, Toledo N, Vizcaíno SF. 2012 Paleobiology of the Santacrucian soths and anteaters 505 (Xenarthra, Pilosa). In Early Miocene paleobiology in Patagonia. High latitude paleocommunities of the 506 Santa Cruz formation., pp. 216–242. Cambridge University Press, New York.: Vizcaíno S.F. Kay R.F., 507 Bargo M.S. (doi: 10.1017/CBO9780511667381.014).
508 40. Yoder AD, Irwin JA, Payseur BA. 2001 Failure of the ILD to determine data combinability for slow loris 509 phylogeny. Syst Biol 50, 408–424. (doi:10.1080/10635150116801)
510 41. Masters JC, Anthony NM, Wit MJ de, Mitchell A. 2005 Reconstructing the evolutionary history of the 511 Lorisidae using morphological, molecular, and geological data. American Journal of Physical 512 Anthropology 127, 465–480. (doi:10.1002/ajpa.20149)
513 42. Perelman P et al. 2011 A molecular phylogeny of living primates. PLOS Genetics 7, e1001342. 514 (doi:10.1371/journal.pgen.1001342)
515 43. R Core Team. 2020 R: A language and environment for statistical computing. R Foundation for 516 Statistical Computing, Vienna, Austria. See https://www.R-project.org/.
517 44. Revell LJ. 2012 phytools: an R package for phylogenetic comparative biology (and other things). 518 Methods in Ecology and Evolution 3, 217–223. (doi:10.1111/j.2041-210X.2011.00169.x)
519 45. Pinheiro J, Bates D, DebRoy S, Sarkar D. 2020 nlme: Linear and Nonlinear Mixed Effects Models. R 520 package version 3.1-147. See https://rdrr.io/cran/nlme/.
521 46. Paradis E, Claude J, Strimmer K. 2004 APE: Analyses of Phylogenetics and Evolution in R language. 522 Bioinformatics 20, 289–290. (doi:10.1093/bioinformatics/btg412) bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
523 47. Wickham H. 2016 ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. See 524 https://ggplot2.tidyverse.org.
525 48. Alfieri F, Nyakatura JA, Amson E. 2020 Data from: Evolution of bone cortical compactness in slow 526 arboreal mammals. Figshare Digital Repository. (https://doi.org/10.6084/m9.figshare.12896249.v4).
527 49. Francillon‐Vieillot H, Buffrénil V de, Castanet J, Géraudie J, Meunier FJ, Sire JY, Zylberberg L, Ricqlès A 528 de. 1990 Microstructure and Mineralization of Vertebrate Skeletal Tissues. In Skeletal 529 Biomineralization: Patterns, Processes and Evolutionary Trends, pp. 175–234. American Geophysical 530 Union (AGU) (doi:10.1029/SC005p0175).
531 50. Barak MM. 2020 Bone modeling or bone remodeling: That is the question. Am J Phys Anthropol 172, 532 153–155. (doi:10.1002/ajpa.23966)
533 51. Straehl FR, Scheyer TM, Forasiepi AM, MacPhee RD, Sánchez-Villagra MR. 2013 Evolutionary patterns 534 of bone histology and bone compactness in xenarthran mammal long bones. PLoS ONE 8, e69275. 535 (doi:10.1371/journal.pone.0069275)
536 52. Amprino R, Godina G. 1947 La struttura delle ossa nei vertebrati. Ricerche comparative negli Anfibi e 537 negli Amnioti. Commentationes Pontificae Academiae Scientiarum 11, 329–267.
538 53. Pujos F, De Iuliis G, Cartelle C. 2017 A paleogeographic overview of tropical fossil sloths: towards an 539 understanding of the origin of extant suspensory sloths? J Mammal Evol 24, 19–38. 540 (doi:10.1007/s10914-016-9330-4)
541 54. van Tyne J. 1929 Notes on the habits of Cyclopes dorsalis. Journal of Mammalogy 10, 314. 542 (doi:10.2307/1374117)
543 55. Hayssen V, Miranda F, Pasch B. 2012 Cyclopes didactylus (Pilosa: Cyclopedidae). Mammalian Species 544 44, 51–58. (doi:10.1644/895.1)
545 56. Nagy KA, Montgomery GG. 2012 Field metabolic rate, water flux and food consumption by free-living 546 silky anteaters (Cyclopes didactylus) in Panama. Edentata 13, 61–65. (doi:10.5537/020.013.0106)
547 57. Lewton KL, Dingwall HL. 2016 Morphological convergence in the pubis of slow-moving primates and 548 xenarthrans: L EWTON AND D INGWALL. Am. J. Phys. Anthropol. 161, 381–397. (doi:10.1002/ajpa.23038)
549 58. Hayssen V. 2011 Tamandua tetradactyla (Pilosa: Myrmecophagidae). Mammalian Species 43, 64–74. 550 (doi:10.1644/875.1)
551 59. Navarrete D, Ortega J. 2011 Tamandua mexicana (Pilosa: Myrmecophagidae). Mammalian Species 43, 552 56–63. (doi:10.1644/874.1)
553 60. Warshaw, J. 2007 Primate bone microstructural variability: Relationships to life history, mechanical 554 adaptation and phylogeny. Ph.D thesis. City University of New York.
555 61. Walker A. 1979 Prosimian Locomotor Behavior. In The Study of Prosimian Behavior., pp. 543–565. 556 Academic Press, Inc.: Doyle GA. and Martin RD. (doi: 10.1016/B978-0-12-222150-7.X5001-6).
557 62. Ryan TM. 2002 The structure and function of trabecular bone in the femoral head of strepsirhine 558 primates. Ph.D. thesis. The University of Texas, Austin. bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
559 63. Amson E, Nyakatura JA. 2018 The postcranial musculoskeletal system of xenarthrans: insights from 560 over two centuries of research and future directions. J Mammal Evol 25, 459–484. 561 (doi:10.1007/s10914-017-9408-7)
562 64. Tyndale-Biscoe CH. 2005 Life of Marsupials. Csiro Publishing (doi: 10.1071/9780643092204).
563 65. Werning SA. 2013b Evolution of bone histological characters in amniotes, and the implications for the 564 evolution of growth and metabolism. Ph.D. Thesis. University of California, Berkeley, CA.
565 66. Walker MM, Louys J, Herries AIR, Price GJ, Miszkiewicz JJ. 2020 Humerus midshaft histology in a 566 modern and fossil wombat. Aust. Mammalogy (doi:10.1071/AM20005)
567 67. Bromage TG, Hogg RT, Lacruz RS, Hou C. 2012 Primate enamel evinces long period biological timing and 568 regulation of life history. J. Theor. Biol. 305, 131–144. (doi:10.1016/j.jtbi.2012.04.007)
569 68. Cubo J, Roy NL, Martinez-Maza C, Montes L. 2012 Paleohistological estimation of bone growth rate in 570 extinct archosaurs. Paleobiology 38, 335–349. (doi:10.1666/08093.1)
571 69. de Paula FJA, Rosen CJ. 2013 Bone remodeling and energy metabolism: new perspectives. Bone Res. 1, 572 72–84. (doi:10.4248/BR201301005)
573 70. Pauli JN, Peery MZ, Fountain ED, Karasov WH. 2016 Arboreal folivores limit their energetic output, all 574 the way to slothfulness. The American Naturalist 188, 196–204. (doi:10.1086/687032)
575 71. Vendl C, Frei S, Dittmann MT, Furrer S, Osmann C, Ortmann S, Munn A, Kreuzer M, Clauss M. 2016 576 Digestive physiology, metabolism and methane production of captive Linné’s two-toed sloths 577 (Choloepus didactylus). J Anim Physiol Anim Nutr (Berl) 100, 552–564. (doi:10.1111/jpn.12356)
578 72. Lemaire M, Goffart M, Closon J, Winand R. 1969 La fonction thyroidienne chez l’unau (Choloepus 579 hoffmanni Peters). General and Comparative Endocrinology 12, 181–199. (doi:10.1016/0016- 580 6480(69)90191-9)
581 73. Brent GA. 2012 Mechanisms of thyroid hormone action. J. Clin. Invest. 122, 3035–3043. 582 (doi:10.1172/JCI60047)
583 74. Gorka J, Taylor-Gjevre RM, Arnason T. 2013 Metabolic and clinical consequences of hyperthyroidism on 584 bone density. Int J Endocrinol 2013, 11. (doi:10.1155/2013/638727)
585 75. Anderson KJ, Jetz W. 2005 The broad-scale ecology of energy expenditure of endotherms. Ecology 586 Letters 8, 310–318. (doi:10.1111/j.1461-0248.2005.00723.x)
587 76. Godfrey LR, Semprebon GM, Jungers WL, Sutherland MR, Simons EL, Solounias N. 2004 Dental use 588 wear in extinct lemurs: evidence of diet and niche differentiation. J. Hum. Evol. 47, 145–169. 589 (doi:10.1016/j.jhevol.2004.06.003)
590 77. Hogg RT, Godfrey LR, Schwartz GT, Dirks W, Bromage TG. 2015 Lemur biorhythms and life history 591 evolution. PLoS ONE 10 (8), e0134210. (doi:10.1371/journal.pone.0134210)
592 78. Rasmussen DT, Izard MK. 1988 Scaling of growth and life history traits relative to body size, brain size, 593 and metabolic rate in Lorises and Galagos (Lorisidae, primates). Am. J. Phys. Anthropol. 75, 357–367. 594 (doi:10.1002/ajpa.1330750307)
595 79. Harcourt AH. 2008 Are lemurs’ low basal metabolic rates an adaptation to Madagascar’s unpredictable 596 climate? Primates 49 4, 292. (doi:10.1007/s10329-008-0102-5) bioRxiv preprint doi: https://doi.org/10.1101/2020.09.02.279836; this version posted September 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
597 80. Barboza PS. 1993 Digestive strategies of the wombats: feed intake, fiber digestion, and digesta passage 598 in two grazing marsupials with hindgut fermentation. Physiological Zoology 66, 983–999. 599 (doi:10.1086/physzool.66.6.30163750)
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