Evolutionary trends in the vertebral morphology of extant Delphinidae

doi:10.21203/rs.3.rs-7420200/v1

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Evolutionary trends in the vertebral morphology of extant Delphinidae

https://doi.org/10.21203/rs.3.rs-7420200/v1

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published 17 Nov, 2025

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Background

Vertebral morphology in cetaceans is linked to various functional abilities that promote ecological diversity and adaptive radiation. While morphometric studies have examined vertebral shape evolution, few have quantified evolutionary trends in a phylogenetic framework. Here, we used three-dimensional landmark configurations and phylogenetic comparative methods to investigate how the vertebral morphology of Delphinidae is influenced by phylogenetic constraints, ecological adaptation, and allometric effects and how these influences vary along the vertebral column.

Results

Phylogenetic ordination methods revealed that species with particular habitat requirements differ greatly from their closest relatives, exhibiting biomechanically advantageous vertebral shapes. A comparison of the orientations of these ordination methods, phylogenetic ANOVAs and phylogenetic signal tests revealed that vertebral morphology is affected by overlapping allometric, ecologic, and phylogenetic signals, with their relative importance differing across regions, phylogenetic levels, and dimensions of shape. In the anterior thorax, the posterior thorax, and the synclinal point, diversification was associated primarily with size and habitat, resulting in low phylogenetic signals. Conversely, the mid-torso and tail stock retain strong phylogenetic signals, reflecting subfamily level conservatism. Notably, in the Tm region, the ecological demands for fast swimming remain highly relevant to vertebral morphology, emphasising the functional significance of this region.

Conclusion

Vertebral morphology in Delphinidae may reflect a complex interplay of ecological, allometric and phylogenetic influences, with distinct regions evolving under different combinations of selective and historical constraints. These region-specific patterns highlight the modularity of the vertebral column and provide new insights into the adaptive radiation of oceanic dolphins. Further studies, including evolutionary modelling and consideration of intraspecific variation, will be essential to fully understand macroevolutionary trends in vertebral morphology and their implications for axial locomotion.

adaptation

Delphinidae

ecomorphology

evolutionary constraints

geometric morphometrics

vertebral column

The cetacean clade Odontoceti includes approximately 75 species across 10 families and represents a remarkable example of both morphological and ecological diversity, with the Delphinidae family comprising 38 species (Committee on Taxonomy 2025). This family exemplifies explosive radiation, as it accounts for almost 50% of all odontocete species. Its high diversity has been attributed to rapid lineage diversifications during the last 10–15 my, driven by both vicariant events and adaptations to changing oceanic environments in the middle–late Miocene and early Pliocene (Banguera-Hinestroza et al., 2014; do Amaral et al., 2018; Steeman et al., 2009).

Given the ecological diversity within odontocetes, the vertebral column is integral to key behaviours such as locomotion, prey capture, and predator evasion. The biomechanics of the axial skeleton influence the ability of these species to exploit different ecological niches, contributing to their evolutionary success (Buchholtz, 2001; Gillet et al., 2019; Marchesi et al., 2020). Consequently, differences in vertebral morphology may translate into flexible and stable areas along the column that confer distinct swimming patterns, enabling these marine mammals to fulfil diverse ecological roles (Buchholtz, 2001; Gillet et al., 2022; Marchesi, 2025).

Vertebral modifications may have been key innovations in the diversification of cetaceans, likely playing a central role in the transition from terrestrial to aquatic life and in subsequent changes during odontocete radiation (Buchholtz & Gee, 2017; Gillet et al., 2019). Moreover, increases in total vertebral counts in cetaceans have been associated with greater regionalisation of the column and reduced vertebral shape disparity in offshore environments, whereas the opposite is observed for early diverging delphinoids (Buchholtz & Cleary, 2005; Gillet et al., 2024). The vertebral column of cetaceans therefore appears to display developmental and morphological features that confer biomechanical advantages for exploiting particular habitats and has been the focus of several ecomorphological studies (Buchholtz & Schur, 2004; Gillet et al., 2022; Marchesi et al., 2020; Viglino et al., 2014).

Eco-morphology explores the relationships between morphological and environmental features, often attributed to natural selection and adaptive evolution (Klingenberg & Gidaszewski, 2010). Central to this paradigm is the idea that current morphological traits reflect both evolutionary adaptations and phylogenetic history. Many studies have investigated the covariation between morphology and phylogeny to understand shape evolution, often revealing that specific traits—such as vertebral shape—carry varying phylogenetic signals (Kamilar & Cooper, 2013). A high phylogenetic signal suggests that closely related species share similar morphological features, whereas lower signals indicate greater divergence due to environmental pressures or adaptive evolution (Kamilar & Cooper, 2013).

In cetaceans, shape analysis has played a crucial role in elucidating evolutionary patterns and morphological differences, both in the skull and the vertebral column, often in relation to accepted phylogenies (Coombs et al., 2022; Galatius et al., 2020; Gillet et al., 2019, 2022, 2024; Marchesi et al., 2021; Vicari et al., 2023, 2024). To date, many studies on vertebral morphology have relied on traditional morphometrics (Buchholtz, 2001; Buchholtz & Schur, 2004; Gillet et al., 2019, 2022; Marchesi et al., 2017; Viglino et al., 2014). Only one study has examined the presence of phylogenetic signals in porpoise vertebral shape via geometric morphometrics (Marchesi et al., 2021). A recent paper described vertebral shape variation in delphinids in light of their biomechanical requirements (Marchesi, 2025). However, little is known about the evolutionary roles of phylogenetic history, allometry and habitat in shaping vertebral morphology within Delphinidae. In the present study, we employ a three-dimensional dataset and phylogenetic comparative methods to investigate evolutionary trends in delphinid vertebral morphology.

Dataset, classification into habitats, and phylogenetic hypotheses

We aimed to assess the presence of phylogenetic signals and the influence of other factors, such as size and habitat, on delphinid vertebral morphology. To this end, we employed a morphometric dataset comprising three-dimensional landmarks for five different regions of the vertebral column: the anterior thorax (Th), the limit between the thorax and torso (ThTo), the torso (Tm), the synclinal point (SP) and the tailstock (TS; see Marchesi et al., 2021; Marchesi, 2025). To facilitate comparisons with recent work on the vertebral column (Gillet et al., 2024), our regions correspond to the anterior thorax (Th), the thoracolumbar area (ThTo), and three areas of the caudal region (Tm, SP, and TS). Owing to the varying morphology of vertebrae along the skeleton, the resulting landmark configurations comprised 35 (Th), 41 (ThTo, Tm, SP), and 28 (TS) landmarks (see Marchesi et al., 2021; Marchesi, 2025). We examined 524 vertebrae from 128 specimens representing 24 dolphin species, covering the same five vertebral regions analysed by Marchesi (2025). To ensure consistency with previous studies (Gillet et al., 2024; Marchesi, 2025), we classified species into five habitat categories according to the literature: coastal, deep-diving, mixed-habitat, offshore, and rivers and bays (Fig. 1; see Marchesi, 2025).

All phylogenetic analyses were based on a calibrated phylogenetic tree (Fig. 1) obtained by pruning the one published by McGowen et al. (2020; Supplementary Information 1). Because data for the TS of Lagenorhynchus australis were unavailable, the tree for this region comprised 23 species.

Analyses

All analyses were conducted in the open-source software R v4.4.1 (R Core Team, 2024). Example scripts are provided in Supplementary Materials 1.

For each region, landmark configurations were superimposed via generalised least-squares Procrustes analysis (GPA), accounting for semilandmarks (e.g., Mitteroecker and Gunz, 2009; Zelditch et al., 2012), implemented via the function gpagen in the Geomorph v4.0.8 package (Adams et al., 2024; Baken et al., 2021). This procedure computes the centroid size (CS), which is the square root of the summed squared distance of each landmark from the centroid of the configuration and can be used as a size variable (Zelditch et al., 2012). Species mean shapes were computed for use in evolutionary analyses.

To visualise shape‒space patterns and evolutionary trends under a Brownian motion (BM) model, we performed three-component analyses via the function gm.prcomp of the Geomorph package: phylomorphospace analysis (PA), phylogenetic principal component analysis (PhyPCA) and phylogenetically aligned component analysis (PACA) for each region (Collyer & Adams, 2021). The internal node positions in the morphospace were estimated in R via the squared change parsimony method and the given tree (Klingenberg & Gidaszewski, 2010).

The PA calculates the ordinary least squares (OLS) mean of the data and rotates the configuration to align with the PCs, identifying the axis of greatest variation (Collyer & Adams, 2021). The PhyPCA instead computes a generalised least squares (GLS) mean, projecting residuals obliquely so that they are independently distributed with respect to phylogeny, thereby minimising the phylogenetic signal on the first axis. A lack of difference between PA and PhyPCA suggests little phylogenetic signal in the dataset, whereas differences in dispersion between the two indicate phylogenetic influence on trait variation (Collyer & Adams, 2021). In contrast, PACA maximises the phylogenetic signal on the first axis rather than overall variation. The similarity in orientation between PA and PACA suggests that phylogeny primarily drives the major axis of variation. In addition, the PACA provides the RVscore for each component, analogous to the explained variance in the PA and PhyPCA, but reflects the proportion of covariation between observed phylogeny-predicted shapes under a BM model. These ordination approaches facilitate the detection of evolutionary trends in multivariate phenotypes and help clarify whether phylogenetic or other signals dominate in datasets with multiple overlapping signals (Collyer & Adams, 2021).

In addition to qualitative plot inspection, we assessed the similarity in the direction of the first component across PA, PhyPCA, and PACA via angleTest (Li, 2011) in the MORPHO v2.12 package (Schlager, 2017). This test estimates the probability that the angle between two random vectors is smaller than or equal to the angle calculated from x and y; significant values signal orientation similarity (Li, 2011).

To quantify phylogenetic signals related to vertebral size and shape, we used the function physignal.z in Geomorph with RRPP v2.0.3 (Collyer & Adams, 2018, 2024). This approach computes effect and p values for a particular K_mult statistic (Adams, 2014; Adams & Felice, 2014; Blomberg et al., 2003). K_mult measures the phylogenetic signal as the ratio of observed to expected phenotypic variation when accounting for, versus ignoring, phylogenetic nonindependence and has a constant expected value (K_mult =1) under BM (Adams & Collyer, 2019). We applied this test independently to four datasets: centroid size, Procrustes coordinates of species mean shapes, and the n first PhyPCs and PACs explaining 90% of the variation (Supplementary Material 2). Comparing these datasets allowed us to examine how phylogenetic signals vary under methods that maximise phylogenetic signal (PACA), emphasise ecological signal (PhyPCA), or preserve overall shape variation (Procrustes coordinates).

Finally, we assessed the associations between shape variation, size, and habitat via phylogenetic generalised least squares (PGLS). Two models were run: one on Procrustes coordinates and one on the n first PhyPCs explaining 90% percent of the variation (dimensionality reduction accounting for phylogeny, Supplementary Information 2), with log-transformed centroid size and habitat as predictors. These analyses were performed with procD.pgls (Adams & Collyer, 2018) in Geomorph, which tests shape differences while accounting for BM expectations under the calibrated phylogeny.

Component Analyses: PA, PhyPCA and PACA

In the two principal component analyses (PA and PhyPCA), the percentage of variance explained by the first two components exceeded 50% in all regions. The highest values were observed for Tm and TS, reaching over 73% in PA and over 60% in PhyPCA (Fig. 2; Supplementary Information 2). For PA, the lowest explained variance was observed in Th, whereas SP had the lowest values in PhyPCA. The RV1 of PACA was relatively large for Tm and TS and smallest for Th and ThTo (Fig. 2; Supplementary Information 2).

Comparisons of PA and PhyPCA within regions revealed the greatest similarity for Th and TS. In the remaining regions (ThTo, Tm, SP), the PhyPCA plots appeared as if the PA had inverted along PC2. Analysis of the angles between the first axes yielded significant values across all the regions, indicating a low probability that the angle between two randomly drawn vectors would be smaller than or equal to the observed angle, reflecting similarity in orientation (Fig. 2; Table 1).

Table 1
Angles between the first components of the three ordination methods.
	1) PA vs PhyPC	2) PA vs PAC	3) PhyPC vs PAC
Th	9.96***	141.70	146.28
ThTo	19.72***	152.41	148.40
Tm	27.59***	31.42***	8.99***
SP	27.19***	132.79	114.94
TS	33.83***	34.92***	16.56***

Angles (expressed in degrees) between the first component of the phylomorphospace (PA) and that of the phylogenetic principal component analysis (PhyPCA, 1) or the phylogenetically aligned component analysis (PACA, 2) and between PhyPCA and PACA (3). Th: anterior thorax; ThTo: thorax–torso transition; Tm: mid torso; SP: synclinal point; TS: tailstock. Significance levels: p < 0.05 (*), p < 0.01 (**), p ≤ 0.001 (***). The p value indicates the probability that the angle between two random vectors is smaller than or equal to the observed value.

The graphical differences were generally most pronounced when comparing the PACA and PA plots, except for Tm, where the plots were similar (Fig. 2). A comparison of the PACA and PhyPCA plots revealed visual differences in all regions; particularly at the Tm, the PACA plots appeared as if PhyPCA had inverted along PC2. Angles between the first component of PA or PhyPCA and PACA were significant only for Tm and TS (Table 1), indicating small angles between axes in these regions.

Species distribution along the first two PhyPCs showed region-dependent patterns (for a full description of species vertebral morphology, see Marchesi, 2025). In Th, Delphininae and Globicephalinae were widely dispersed in the morphospace, whereas Lissodelphininae occupied a more restricted morphospace despite their different habitats (Fig. 2A). The coastal species clustered in neighboring areas without clear subfamily differentiation (Fig. 2B). Coastal Lissodelphininae differed from their shelf and oceanic fast-swimming relatives and were located near the only coastal Delphininae species in the sample (T. truncatus) and other offshore dolphins. Offshore species were widely dispersed, with some Delphininae and Lissodelphininae diverging considerably from their closest relatives. Moreover, species with particular requirements (deep-diving, rivers and bays) also clearly diverged from their closest relatives. At Tm, species are grouped by habitat irrespective of subfamily. Within Delphininae and Lissodelphininae, species with particular habitat requirements (coastal, rivers and bays) differed markedly from offshore and mixed-habitat relatives (Fig. 2C). The extremely pelagic Lissodelphis peronii differed crearly from all other dolphins. At SP, PhyPCA indicated a grouping dominated by subfamilies, although some species with particular habitat requirements diverged from their closest relatives, with the riverine species diverging from the rest of Delphininae and an offshore Globicephanae species clustered with Lissodelphininae species (Fig. 2D). At TS, no clear grouping by habitat or subfamily was observed. The species varied mainly in terms of PC1 values, with most Globicephalinae overlapping with Delphininae, whereas the riverine Delphininae species differed greatly (Fig. 2E). Two coastal Lissodelphininae species differed from the rest of the clade, and an offshore Globicephalinae was located near fast-swimming Lissodelphininae (Fig. 2E).

Phylogeny, habitat and size as factors

A phylogenetic signal of centroid size was detected only in the three posterior regions (Tm, SP, and TS), with low K_mult and Z values (Fig. 3, Table S1). For shape, the highest K_mult values occurred in Tm and TS, which were close to one in the datasets, especially in TS. Effect size analysis (Z) for the phylogenetic signal was statistically significant for all regions and types of data, except for the selected PhyPCs of ThTo (Fig. 3). Despite this, the Z values were small in all the cases,, with relatively large values of Tm, SP, and TSfor the for PhyPCs and PACs; however, the Z values did not exceed 4.4 in any case (Fig. 3, Table S1).

Results for the PGLS done on Procrustes coordinates showed no significant effect of size or habitat on shape. After dimensionality reduction with minimised phylogenetic effect (PhyPCA), size was significant for ThTo and SP, although Z and R² were relatively low (Fig. 4, Table S2). Additionally, habitat was a significant factor in three regions, ThTo, Tm, and SP, with Z values over 3.2 and R² values ranging from 0.31 (SP) to 0.43 (Tm). Pairwise comparisons were performed only for regions where the habitat was significant. In general, offshore and mixed-habitat species differed from each other but not from each other, especially in the Tm (Table S3).

Disentangling the processes that drive the evolution of complex biological structures is a major aim of evolutionary biology. Multivariate data in comparative studies can reflect various signals (e.g., ecological, allometric, phylogenetic, or combinations thereof; Collyer & Adams, 2021). In this study, we employed 3D landmark configurations, a functional subdivision of the vertebral column in 24 dolphin species (Family Delphinidae), and phylogenetic comparative methods to test the effects of phylogenetic, ecological and allometric signals along the vertebral column of the most diverse cetacean family.

Our results indicate that vertebral morphology in dolphins is shaped by distinct but overlapping signals: strong ecological effects on ThTo, Tm, and SP; size effects, particularly ThTo and SP; and phylogenetic constraints on Tm, SP, and TS. These findings suggest that different regions of the column evolve under varying combinations of ecological, allometric, and phylogenetic influences.

Ecological signal

Previous studies on cetacean vertebral morphology have mainly focused on ecological signal (Buchholtz & Schur, 2004; Gillet et al., 2019, 2022, 2024; Marchesi et al. 2017, 2020). Based on vertebral morphology, it has been proposed that the most recent common ancestor (MRCA) of crown delphinids, as well as those of each subfamily (Lissodelphininae, Globicephalinae, and Delphininae), likely inhabited offshore environments, showing morphologies associated with oceanic non-fast-swimming species, with subsequent shape diversification linked to the biomechanical demands of different habitats and habits (Gillet et al., 2022; Marchesi, 2025). Our results revealed ecological signal in three regions critical for swimming efficiency: ThTo, Tm, and SP.

Both the anterior and middle torso (ThTo and Tm) are especially important regions, as they are where the longissimus muscle generates the greatest forces that are transferred to the flukes (Pabst, 1993). In these regions, habitat explained more than 37% of total variation, with relatively high Z values. The synclinal point marks the transition between the stable torso and the flexible tailstock, representing the area where muscle forces that affect the fluke’s angle of attack are produced (Buchholtz & Schur, 2004; Marchesi et al., 2017; Pabst, 1990; Slijper, 1936). Here, the effect of habitat was smaller than in the first two regions, with relatively low R² but high Z values. The associations between shape and habitat in these three areas suggest a particular influence of biomechanical constraints on the vertebral morphology imposed by habitat differences. Similarly, the distribution of shape in phylomorphospace when the ecological signal was maximised resembled the patterns described by Marchesi (2025), with closely related species showing, distinct morphologies associated with particular habitats. Species with specific habitat requirements (e.g., deep diving, rivers and bays, or extremely fast-swimming species) showed marked divergence from their closest ancestors (see also Marchesi 2025).

Importantly, the classification of habitats into discrete categories is inherently subjective and does not reflect the continuum of delphinid habitats. Other ecological factors (feeding mechanism, migration, prey size, etc.) may also influence vertebral morphology. For example, burst swimming speed in cetaceans has been linked to vertebral morphology and the vertebral count, with consequences for vertebral regionalisation (Gillet et al., 2024). In our study, differences in phylomorphospace occupation among species with similar habitats may reflect fine-scale ecological partitioning between sympatric species, as morphology could be linked to differences in prey size or spatial distribution (Bearzi, 2005; Smith et al., 2008; Spitz et al., 2006). While ecological drivers explained much of the shape variation in these regions, size effects also contributed, as discussed below.

Allometric effects

Evolutionary allometry has been shown for the skulls, mandibles, and vertebrae of cetaceans (Galatius et al., 2020; Marchesi et al., 2021; Vicari et al. 2023, 2024). For the odontocete skull, Vicari et al. (2023) reported that families occupy distinct positions via allometric regression, with 9% of skull shape variation explained by size. With respect to vertebral morphology, Marchesi et al. (2021) reported strong size-shaped associations across most regions of the column in Lissodelphininae dolphins, suggesting that size changes may have facilitated rapid morphological diversification within a short evolutionary timeframe.

In our study, size significantly influenced vertebral shape after accounting for phylogeny in ThTo and, to a lesser degree, in SP, possibly reflecting rapid evolutionary changes mediated by size in biomechanically critical regions. This was particularly evident in species with habitat requirements differing from those of the delphinid common ancestor, such as the large deep diver Globicephala macrorhynchus, the large riverine Sousa plumbea, and the small coastal Cephalorhynchus (within Lissodelphinidae), for which a reduction in size has already been proposed as a driver of morphological change (Galatius et al., 2010, Marchesi, 2025). Importantly, the influence of size on vertebral shape may differ across regions and have different biomechanical implications (Marchesi et al., 2021). These results should be interpreted with caution, as our sample may be biased regarding sex, and sexual size dimorphism is known in delphinids (Mesnick & Ralls, 2019).

Phylogenetic signal

Studies on phylogenetic signals in cetaceans remain scarce. Vicari et al. (2023) reported phylogenetic signals for both skull size and shape, which were stronger for size (K_mult = 0.653) than for shape (K_mult = 0.565), with size linked to ecological traits but shape showing no association. Conversely, Galatius et al. (2020) reported strong phylogenetic signals in delphinid skull shapes, with subfamilies displaying distinct morphologies. For vertebrae, Viglino et al. (2014) detected phylogenetic signals in traits related to swimming muscle architecture across delphinids and Pontoporia blainvillei, but this signal disappeared when Pontoporia was excluded, suggesting a strong effect of this distantly related species and highlighting the importance of considering several species in this type of study. Marchesi et al. (2021) reported no significant phylogenetic signal within porpoises, likely due to parallel convergence, but strong signals were recovered across delphinoids, particularly in Tm, suggesting suprafamily constraints during delphinoid diversification (~ 20 Mya; Marchesi et al., 2021).

Our results parallel these findings: a phylogenetic signal was detected along the dolphin vertebral column in centroid size (CS), shape (Procrustes coordinates), and ordination methods maximising ecological (PhyPCA) or phylogenetic (PACA) signals. Size exhibited a weak but significant phylogenetic signal (K_mult < 0.62, Z < 2.07) in the three most posterior regions, which are considered subregions within the caudal region (Gillet et al., 2024), suggesting that partial phylogenetic constraints on vertebral size in these areas are responsible for differences in swimming performance. With respect to shape (Procrustes coordinates, PhyPCA, and PACA), the phylogenetic signal was evident to varying degrees in all regions except ThTo (in PhyPCA). Disregarding the dataset,, with the lowest K_mult values occurred in the anterior regions, while higher values were found for Tm (K_mult ≅ 0.8) and TS (K_mult ≅ 0.9). The values for SP were intermediate, although the z values were the highest for this region. This pattern suggests that shape diversification may have contributed significantly to delphinid radiation, with phylogeny constraining shape in biomechanically relevant regions.

Consistent with earlier studies (Marchesi et al., 2021; Viglino et al., 2014), phylogenetic signals in these regions may be stronger with broader taxonomic sampling, implying constraints at the family level that were weakened during subfamily radiation. The strong phylogenetic signal in Tm and TS supports the idea that subfamily level constraints shape vertebral morphology during early delphinid diversification (12–6 Mya; McGowen et al., 2020).

Interaction of signals

A low phylogenetic signal in Th and ThTo for which habitat and size showed significant effects with an important percentage of shape variance explained by each factor suggest the combination of multiple signals at various degrees along the vertebral column. Importantly, the coexistence of strong phylogenetic and ecological signals in Tm and SP, with marked shape differences among closely related species in contrasting habitats, suggests that multiple interacting factors shape vertebral morphology to varying degrees depending on the level of the analysis (family or subfamily). In this way, within each subfamily, we observed highly divergent shapes that were related to the biomechanical demands of each habitat and may have been involved in the explosive radiation within subfamilies in the late Miocene–Pliocene (5–2 Mya; Banguera–Hinestroza et al., 2014; do Amaral et al., 2018; McGowen et al., 2020). Similarly, Vicari et al. (2024) reported a strong phylogenetic signal with a jaw shape (K_mult ≅ 1.1) alongside a significant association with the biosonar mode and diet, indicating an ecological signal in conjunction with a phylogenetic signal in an ecologically relevant structure.

Dimensionality and hierarchical processes

Phenotypic evolution is widely recognised as a multivariate process (Adams & Collyer, 2018, 2019; Blows, 2007; Collyer et al., 2015), where complex traits such as shape evolve in correlated dimensions. In this sense, phylogenetic signals may also be separated into multiple dimensions in the data (Adams & Collyer, 2019; Collyer & Adams, 2021). Here, K_mult values below 1 in all cases, the presence of both ecological and phylogenetic signals, and the results of the ordination analyses collectively suggest that multiple signals (ecologic, allometric, and phylogenetic) influence vertebral morphology. Nevertheless, our models assumed Brownian motion, which may be inadequate for clades with rapid diversification (Harmon, 2019). Within this evolutionary framework, vertebral morphology modification patterns seem to play a key role, suggesting continuity between evolutionary processes occurring at different phylogenetic levels and rapid ecomorphological changes at the macroevolutionary level (Gillet et al., 2022). Our results suggest that the morphology of Tm and TS, and to a lesser extent SP, was constrained by subfamily level divergence, whereas the morphology of Th and ThTo diverged from that of the MRCA, possibly due to ecological factors.

The vertebral column is a modular structure subject to hierarchical developmental processes, producing phenotypic units capable of independent modification (Buchholtz, 2007). Our findings demonstrate that different evolutionary signals might differentially affect the vertebral morphology of dolphins depending on the region along the skeleton, phylogenetic level, and shape dimension. At the family level, the vertebral morphology of Th and ThTo is partially constrained by phylogeny but, more importantly, by other factors, such as ecology or size. In contrast, the vertebral morphology of Tm, SP and TS was mostly constrained by phylogeny. Nonetheless, ecological signals are also important in critical regions for the biomechanics of fast-swimming oceanic species (ThTo, Tm, and SP), highlighting the role of ecological factors at relatively fine scales (Marchesi et al., 2020; Marchesi et al., 2021, Marchesi, 2025).

Future directions

Further work applying evolutionary models to identify the best-fit evolutionary scenarios for delphinids is needed to characterise evolutionary rates, selection strengths, and constraints fully and to determine the extent to which additional signals may explain vertebral morphological diversification. Moreover, with recent methods With the incorporation of intraspecific variation into PGLS analyses (Adams & Collyer, 2024), future studies should explore how accounting for intraspecific variation might affect our results. In this study, however, we relied on species-mean shapes, as required by the PGLS implementation available at the time of analysis.

Our study revealed that dolphin vertebral morphology reflects a dynamic interplay of ecological adaptation and phylogenetic constraints, varying along the column. Th and ThTo are influenced mainly by size and habitat, resulting in low phylogenetic constraints, whereas Tm, Sp, and TS retain strong phylogenetic signals, reflecting subfamily level morphological conservatism. Notably, the morphological similarity of the Tm values of fast-swimming species, regardless of lineage, highlights their functional relevance. These findings demonstrate how vertebral modularity allows differential evolution along the column and provide new insights into the adaptive radiation of oceanic dolphins. Further work, including evolutionary modelling and incorporation of intraspecific variation, will clarify macroevolutionary trends in axial locomotor structures.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Funding

CONICET, Argentina: Postdoctoral Fellowship

Society for Marine Mammalogy: Small Grants in Aid of Research

Science and Technology Ministry (MINCyT), Argentina: PICT 2019–2160

Author Contribution

MCM, MAC, and RGJ conceptualised the study. MCM collected and curated the data, acquired funding, designed the methodology, analysed the data, created visual aids, and wrote the original draft. ES designed the methodology, analysed the data, created visual aids, and wrote the original draft. RGJ designed the methodology and provided resources. All the authors reviewed and edited the original draft and approved the final manuscript.

Acknowledgement

We would like to thank collection curators and museum staff for their assistance during specimen preparation and data collection: Dr. Darrin Lundee and John Ososky at the US National History Museum, Smithsonian Institution; Marisa Surovy at the AMNH; Sergio Lucero and Dr. Pablo Teta at MACN; and Nestor García from CESIMAR, Argentina. We would also like to express our appreciation to the Society for Marine Mammalogy (Small Grants in Aid of Research, 2018), which made data collection for this work possible. Finally, MCM would like to dedicate this paper to the memory of Dr. Natalie R. Prosser Goodall, a great leader and mentor. Finally, we would like to highlight the importance of publishing morphological studies while facing a severe lack of funding in scientific institutions and universities in Argentina, which critically hampers the advancement and quality of scientific research in our country

Data Availability

The datasets employed in this study can be found in online repositories: https://doi.org/10.6084/m9.figshare.29954441

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Evolutionary trends in the vertebral morphology of extant Delphinidae

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Abstract

Background

Results

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BACKGROUND

METHODS

Dataset, classification into habitats, and phylogenetic hypotheses

RESULTS

Component Analyses: PA, PhyPCA and PACA

Phylogeny, habitat and size as factors

DISCUSSION

Ecological signal

Allometric effects

Phylogenetic signal

Interaction of signals

Dimensionality and hierarchical processes

Future directions

CONCLUSION

Declarations

Competing interests

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

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