The whole tooth: changes in tooth size and shape associated with ontogenetic changes in prey consumption by white sharks (Carcharodon carcharias) in Australia.

The whole tooth: changes in tooth size and shape associated with ontogenetic changes in prey consumption by white sharks (Carcharodon carcharias) in Australia. | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecology and Evolution This is a preprint and has not been peer reviewed. Data may be preliminary. 10 September 2025 V1 Latest version Share on The whole tooth: changes in tooth size and shape associated with ontogenetic changes in prey consumption by white sharks (Carcharodon carcharias) in Australia. Authors : Emily Hunt 0009-0000-0245-1022 [email protected] , Yuri Niella 0000-0003-1878-6091 , Amy Smoothey , Ezequiel Marzinelli 0000-0002-3762-3389 , David Raubenheimer , Russell Bradford 0000-0003-0291-3180 , David Booth , and Victor Peddermors Authors Info & Affiliations https://doi.org/10.22541/au.175748673.32795363/v1 562 views 308 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract White sharks undergo pronounced ecological and dietary shifts across ontogeny, and their teeth play a central role in mediating these changes. Understanding fine-scale tooth morphology can provide insights into how feeding strategies and, hence, dietary niches and ecological function evolve with age and size. These morphological changes underpin ontogenetic niche shifts, revealing how functional adaptations in dentition enable white sharks to exploit different prey resources throughout development. This study provides novel insights into the ontogenetic and positional variation in C. carcharias dentition, integrating both Elliptic Fourier Analysis (EFA) and traditional morphometric approaches. We reveal significant patterns of tooth morphology that vary with jaw position and ontogenetic stage, reflecting functional adaptations to changing dietary and biomechanical demands. A key ontogenetic shift was identified as teeth transitioned from narrow, cuspidate forms with accessory cusplets in juveniles to broader, serrated teeth in larger individuals. We found no significant differences in tooth morphology between sexes, aligning with known similarities in diet and body shape in the eastern Australian white shark population. Significant anterior-to-posterior variation in tooth form was observed within the jaw, with lateral teeth becoming more compressed and recurved, suggesting functional transitions in prey handling throughout the jaw. Additionally, we documented structural changes in jaw morphology at approximately 210 cm PCL, corresponding to broader teeth and increased bite capacity. These shifts likely reflect developmental milestones in feeding capability, supporting the transition from a solely piscivorous diet to the inclusion of marine mammal prey. The whole tooth: changes in tooth size and shape associated with ontogenetic changes in prey consumption by white sharks ( Carcharodon carcharias ) in Australia. Emily Hunt 1 *, Yuri Niella 2 , Amy F. Smoothey 3 , Ezequiel M. Marzinelli 4 , David Raubenheimer 1 , Russell Bradford 5 , David J. Booth 6 , Victor M. Peddemors 3 1 School of Life and Environmental Sciences & Charles Perkins Centre, The University of Sydney, Sydney, NSW. 2 IMOS Animal Tracking Facility, Sydney Institute of Marine Science, Mosman, NSW 2088. 3 New South Wales Department of Primary Industries and Regional Development, Sydney Institute of Marine Science, Mosman, NSW 2088. 4 School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW. 5 CSIRO Environment, GPO Box 1538, Hobart, Tasmania 7001, Australia. 6 School of the Life Sciences, University of Technology Sydney, Ultimo, NSW 2007. *Corresponding author email: [email protected] Keywords: Elliptical Fourier Analysis; Feeding ecology; Functional morphology; Ontogenetic niche shift; Shark dentition; Tooth Morphology Abstract White sharks undergo pronounced ecological and dietary shifts across ontogeny, and their teeth play a central role in mediating these changes. Understanding fine-scale tooth morphology can provide insights into how feeding strategies and, hence, dietary niches and ecological function evolve with age and size. These morphological changes underpin ontogenetic niche shifts, revealing how functional adaptations in dentition enable white sharks to exploit different prey resources throughout development. This study provides novel insights into the ontogenetic and positional variation in C. carcharias dentition, integrating both Elliptic Fourier Analysis (EFA) and traditional morphometric approaches. We reveal significant patterns of tooth morphology that vary with jaw position and ontogenetic stage, reflecting functional adaptations to changing dietary and biomechanical demands. A key ontogenetic shift was identified as teeth transitioned from narrow, cuspidate forms with accessory cusplets in juveniles to broader, serrated teeth in larger individuals. We found no significant differences in tooth morphology between sexes, aligning with known similarities in diet and body shape in the eastern Australian white shark population. Significant anterior-to-posterior variation in tooth form was observed within the jaw, with lateral teeth becoming more compressed and recurved, suggesting functional transitions in prey handling throughout the jaw. Additionally, we documented structural changes in jaw morphology at approximately 210 cm PCL, corresponding to broader teeth and increased bite capacity. These shifts likely reflect developmental milestones in feeding capability, supporting the transition from a solely piscivorous diet to the inclusion of marine mammal prey. Keywords: Elliptical Fourier Analysis; Feeding ecology; Functional morphology; Ontogenetic niche shift; Shark dentition; Tooth Morphology INTRODUCTION Many organisms undergo distinct functional transitions that shape their dietary specialisation and other ecological interactions (Turner Tomaszewicz et al., 2017; Werner & Gilliam, 1984; Zelditch et al., 2004), known as ontogenetic niche shifts (Werner and Gilliam 1984). Ontogenetic niche shifts are adaptively important, often representing changes in resource use with an increasing body size (Wilson, 1975) or across life-history stages, for example, from prioritising growth and survival to reproduction (Bolnick et al. 2003; Tinker et al., 2007). Niche shifts also have significant implications for community ecology, which traditionally has assumed that species are composed of identical individuals (Nakazawa, 2015). It is thus important to understand and establish reliable markers of ontological niche shifts, especially in ecologically important keystone species that are difficult to observe directly, such as marine predators (e.g. sharks). Individual differences in diet and other factors related to foraging ecology, such as habitat use, are becoming increasingly evident in several species of sharks, which show notable differences in the allometric scaling of morphological features throughout development (Matich & Heithaus, 2015). For example, in tiger sharks, Galeocerdo cuvier , the frequency of predation on turtles, mammals and crustaceans increases with body size (Aines et al., 2017; Dicken et al., 2017; Lowe et al., 1996). This ontogenetic variation in diet is also displayed in lemon sharks, Negaprion brevirostris (Newman et al., 2011) , and the sevengill shark, Notorynchus cepedianus (Ebert, 2002), revealing a shift from predominantly opportunistic benthic foraging to a more selective diet of fish and mammals as they grow. Furthermore, these dietary shifts are usually accompanied by morphological changes in the shape and size of the body, and the documentation of these changes has been used to highlight shifts in resource availability (Tyler-Bonner & Horn, 2000; Zelditch et al., 2004). These morphological variations in body shape are often manifested through the allometric changes of the head shape and surrounding musculature linked to dietary shifts with age (Fu et al., 2016; Habegger et al., 2012; Huber et al., 2006). Additionally, ontogenetic changes contributing to dietary change have also been shown through the allometric scaling of the caudal fin. Increases in the surface area of the caudal fin in multiple shark species can lead to increased propulsion through the water, in turn allowing capture of fast-moving, larger pelagic prey (Hunt et al., 2024; Irschick & Hammerschlag, 2014; Lingham-Soliar, 2005). As cosmopolitan apex predators and a species frequently involved in shark bite incidents, the white shark, Carcharodon carcharias, is a species of ecological, conservation and public safety importance. The white shark generally consumes a diet consisting of cephalopods, elasmobranchs and teleosts (Grainger et al., 2020; Lipscombe et al., 2024). However, throughout ontogeny, the inclusion of marine mammals increases as they transition from juveniles (3m TL) (Bruce & Bradford, 2012). This ontogenetic shift in diet is also accompanied by changes in habitat use, whereby young-of-the-year (YOY) individuals are typically restricted to warmer, coastal nursery areas. As they grow, they become increasingly thermally tolerant and expand their range, utilising a broader spectrum of habitats, including both coastal and offshore environments (Lee et al., 2021; Spaet et al., 2020), ranging in temperatures between 2-30\({{}^{\circ}}C\ \) (Skomal et al., 2017). Marine predators, including white sharks, show distinct biomechanical adaptations of the mouth and its associated features, including gape, bite force and tooth shape, for grabbing, gripping and dismembering prey (Cullen & Marshall, 2019; Davit-Beal et al., 2007; Ferrara et al., 2011; Riverón et al., 2025). The teeth allow an individual to distribute prey into manageable portions and remove inedible segments of the body (Jones, 2009; Whitenack et al., 2010). To date, however, much of the functional analysis conducted on the feeding apparatus in sharks is largely focused on muscle and cranial movement (Huber et al., 2005; Motta et al., 2008). Furthermore, tooth morphology can provide insight into both dietary preferences and biomechanical function. Broadly, species with dietary preferences of ‘softer’ prey, such as cephalopods, typically have cuspid teeth, while molariform teeth are usually present in species that forage on ‘harder’ prey like crustaceans (Corn et al., 2016; Powter et al., 2010;). Beyond these general categories, variation in tooth shape can further reflect functional adaptations to feeding. For example, slim, smooth teeth demonstrate a better ability for piercing and puncturing through skin, while wider, serrated teeth are better at slicing and cutting (Frazzetta et al., 1988; Riverón et al., 2025). Previous studies have investigated tooth height in sharks to examine changes in feeding ecology (French et al., 2017; Mollet et al., 1996; Whitenack et al., 2010). However, focusing solely on tooth height overlooks important variations in shape that are closely tied to function and prey handling. A more detailed analysis of tooth morphology can reveal shifts in biomechanical adaptation and dietary specialisation that are not captured by linear measurements alone, as previously demonstrated in bull sharks, Carcharhinus leucas (Goodman et al., 2020). Given their broad thermal tolerance, complex ontogeny and well-documented dietary shifts, white sharks represent an ideal species to explore how tooth morphology changes with ecological and functional pressures across life stages. Not only do these shifts reflect internal development but, as apex predators, their ontogenetic transitions also have direct and indirect effects on prey populations and, in turn, community structure (Kim et al., 2012; Nakazawa, 2015; Papastamatiou et al., 2023). Understanding how tooth morphology changes across life stages can provide a mechanistic link between form and ecological function, offering insights into how morphological traits may influence trophic roles in complex ecosystems. In this study, we therefore examined the ontogenetic changes in the tooth shape of white sharks and the potential influence it has on their foraging ecology. By investigating how tooth shape changes across jaw positions and throughout life stages, we aimed to examine where these morphological alterations occur and their relative importance on feeding ecology. Based on previous studies outlining the biomechanics of teeth (Alber, 1992; Frazzetta, 1988; Whitenack & Motta, 2010), we predicted that the teeth will transition from a more cuspidate shape with cusplets, suitable for a diet predominantly composed of fish, to wider and thicker shape teeth with large serrations for hunting mammals. MATERIALS AND METHODS 2.1 Sample collection We analysed the jaws of 97 deceased white sharks encompassing the various life stages outlined by Bruce & Bradford (2012). These stages include young-of-the-year (YOY, n= 11), juveniles (JWS, n= 62), subadult (SUB, n= 6) and adults (MAT, n= 10), however, some jaws were from sharks of unknown body length ( n= 6). The majority (76%) of samples were from white sharks caught between 1999 to 2024 in the New South Wales Shark Meshing Program (SMP) (Reid et al., 2011). The remaining samples were collected by other means, including commercial fishing operations, law enforcement confiscations, and museum specimens (Table 1). Table 1 : Source and Acquisition of Carcharodon carcharias jaws included in this study. Organisation Number of Jaws Method NSW DPIRD Fisheries 74 SMP CSIRO 10 Commercial fishing operations/Confiscated WA DPI Fisheries 6 Strandings/Confiscated WA Museum 4 Donated Rodney Fox Museum 2 Fisherman caught pre-protection Flinders University 1 Confiscated Fig. 1 Cross-section of the lower jaw showing the functional row of teeth, and subsequent replacement teeth within the tooth file. This diagram has been adapted from Becker et al. (2000). 2.2 Morphometric measurements Morphometric data on teeth were collected from the jaws, using standard protocols established by NSW DPIRD. The functional row (first row) of teeth was measured for the upper and lower jaw, using the secondary tooth within the same tooth file if a functional tooth was absent or damaged (Fig. 1). The first two teeth within a tooth file were assumed to be equivalent, ascribing to the fast tooth turnover rate outlined by Grainger et al. (2020). For the following measurements, jaws were divided into the upper and lower hemispheres and left and right sides (Fig. 2a). The individual teeth were numbered following Moyer et al. (2015), starting from the centre of the jaw and ascending to the outer edge. The morphometric measurements collected included a) tooth (crown) height (TH), b) tooth width (TW), c) the thickness at the base of the first 4 teeth on each side of the jaw (BT), d) the interdental distance between the tips of the teeth (IDD), e) the basal gap between the base of the teeth (BG), f) and the width at the midpoint of the tooth (MTW) (Fig. 2b). The root height (CH) and root width (CW) were also collected for the first two teeth on the right side of the mouth for the upper and lower jaw (Fig. 2b). Additional measurements were also taken for the jaw including a) the upper jaw circumference (UC), b) the lower jaw circumference (LC), c) and the jaw width (JW). To examine if there is a distinct size when the juvenile sharks discontinue developing tooth cusplets, their presence or absence was also recorded for a random subsample of 37 jaws. Necropsies of 91 individuals allowed for body length measurements to be made available for each animal to the nearest millimetre. Due to the increased margin of error with total length measurements of white sharks (Hunt et al., 2024), the more accurate precaudal length (PCL) was used as the ‘standard’ metric of length for the subsequent analysis. Fig. 2 C. carcharias a) jaw structure, showing the functional row of teeth measured for analysis and tooth numbering and b) Tooth structure adapted from Ebert & Stehmann (2013). 2.3 Elliptical Fourier Analysis (EFA) Photographs of the jaws were taken in situ from the labial side of the jaw using an Apple iPhone 14 (Version iOS 16.3.1). To minimise parallax error, the phone was mounted in a rig positioned approximately 7 cm away from the tooth. Images were then edited using the Adobe Photoshop 2024 software (version 25.12.3) to generate silhouettes of the individual teeth. The silhouettes were standardised to a 3024 x 3024 px format at 300 dpi resolution before being used for EFA. EFA was used to examine the change in tooth shape across jaw positions and throughout ontogeny. EFA describes the shape of an object by fitting a function consisting of a series of harmonics (trigonometric curves), to a set of four coordinates on the Cartesian plane (two x and y components, respectively) (Cullen & Marshall, 2019). This nearest pixel approach minimises intra-observer bias by converting the tooth outlines into a series of complex Fourier descriptors, which enables the quantification of morphological variations (Goodman et al., 2020). A greater proportion of an object’s shape is described with increasing harmonics. Only seven harmonics are required to account for 99.9% of the variation in tooth shape, as these coefficients characterise the size, shape, and orientation of each harmonic ellipse (Cullen & Marshall, 2019). The EFA was performed following the methods outlined by Goodman et al. (2020), using the Momocs package (Bonhomme et al., 2014). The root structure was not examined in this analysis as it was obstructed by the gums. 2.4 Data analysis To investigate variation in white shark tooth morphology with ontogeny and tooth position in the jaw, two comparative methods were used: one derived from outline-based morphometrics using Elliptic Fourier Analysis (EFA), and the other from classic morphometric measurements. All data analysis was conducted in the R Statistical Environment (RStudio Team, 2021). A paired t-test was used to examine the bilateral symmetry of the upper and lower jaw by comparing left and right tooth counts. A two-factor analysis of variance (ANOVA) was then applied to examine the effect of life stage and sex on tooth counts. Both datasets were subjected to principal component analysis (PCA) to reduce dimensionality and extract the primary axes (coefficients) of variation in tooth shape (Fig. S1). These coefficients were processed using PCA, and the first two principal components were extracted to capture the majority of morphological variance. This was subsequently repeated for the classic morphometrics, using five measurements per tooth to quantify the shape (excluding BT, as it was only taken for the first four teeth). To ensure the variables were normally distributed, histograms were used to visually assess their distribution and check for any deviation (Fig. S2). To evaluate the best model structure, both linear and non-linear models were compared. The Akaike information criterion (AIC) values confirmed that the Generalised Linear Mixed Model (GLMM) was more appropriate for the data. Final models using the mgcv package (Wood, 2017) incorporated tooth position (UR, UL, LR, LL), tooth number and precaudal length (PCL) as fixed effects, with individual shark ID included as a random effect. The standardized partial residuals of the PCA coefficients were plotted against tooth number and PCL to examine points where statistically significant changes occur in the tooth shape for both the classic morphometric and EFA datasets. After identifying points of statistically significant change for both the tooth number and PCL, we used coefficient (coo) plots to visualise the shape variation using reconstructed shapes from the individual EFA coefficients, dividing the plots into the four jaw positions for each identified group. Standardized partial residuals were also used to examine additional classic morphometric variables that were not included in the multivariate analysis. These included the base thickness, measured for the first four teeth on each side of the jaw, as these are assumed to play a key role in the initial prey capture. The root surface area (CH * CW) of tooth UR1, to evaluate structural stability and the jaw circumference and width to explore broader patterns in jaw morphology. Additionally, the TH was also examined individually using a generalised additive mixed model (GAMM) with a k value of 10, to highlight variation in the upper jaw that may be overlooked in the multivariate analysis. All models were initially run separately by sex and showed consistent trends in tooth shape changes in response to PCL and tooth number. As no difference were found between males and females in either the PCA or EFA dataset, they were therefore combined in the following analyses. RESULTS 3.1 Bilateral symmetry The 97 animals analysed (43 females, 38 males and 16 sex was undetermined) ranged in size from 90.85 cm PCL to 491.3 cm PCL. No significant difference was found in bilateral symmetry between the upper (mean difference= 0.11 ± 0.71 SD) and lower (mean difference= -0.14 ± 0.67 SD) left and right sides in terms of tooth counts (t(86)= 1.52, p > 0.05 and t(85)= -1.93, p> 0.05, respectively), with both hemispheres differing by a maximum of 2 teeth. Neither sex nor body length were significantly associated with tooth counts (ANOVA F 2,75 = 1.56, p> 0.05 and F 3,75 = 0.66, p> 0.05 , respectively). Cusplets were observed in individuals up to 235 cm PCL, however, the size at which they discontinue developing varied widely, with the smallest individual lacking cusplets measuring 180 cm PCL. 3.2 Classic Morphometric vs. EFA method comparison The PCAs conducted separately for the EFA coefficients, and the classic morphometric variables displayed consistent patterns of shape variation, with clear separation of teeth based on jaw position and a strong primary axis of morphological differentiation (Fig. S1). For the EFA dataset, 55.62% of the total variation was explained by the first two principal component scores, with PC1 explaining 36.38% of the variance and PC2 explaining 19.24% (Fig. S1a). The differences in shape between the upper and lower jaw hemispheres occurred primarily on the vertical plane through the ao and co coefficients, with the remaining coefficients predominantly driving the horizontal variation in the PCA scores. Conversely, 96.60% of the total shape variation was explained by the first two principal component scores in the classic morphometric dataset (Fig. S1b). Within this, PC1 alone explained 83.15% of the variance, and PC2 accounted for an additional 13.45%. Similar to the EFA model, the differences in shape between the upper and lower hemispheres also occurred along the vertical axis, primarily driven by the MTW and BG. Both models showed substantial similarity between the left and right sides. The GLMMs used to assess the influence of jaw position, tooth number and PCL on tooth shape differed between the two datasets (Tables 2 & 3). For both models, tooth number and PCL were significant predictors of variation in tooth shape (Table 2). The random effect for shark ID was also highly significant (Table 2), indicating considerable individual-level variation. Despite these significant effects, the EFA model only explained 4.3% of the deviance, suggesting limited overall explanatory power. In contrast, the classic morphometric model showed a much stronger fit, explaining 19.8% of the deviance. Overall, the classic morphometrics captured a larger proportion of the shape variation in relation to biological and positional factors compared to the EFA coefficients. 3.3 Tooth shape throughout the jaw The GLMM models for both the EFA and classic morphometric datasets both exhibited a consistent inflection point at the 6th tooth across all jaw positions, indicating a distinct morphological transition in tooth shape around this location (Fig. 3). Further investigation using overlaid elliptic fourier tooth outline reconstructions highlight the gradual transition in tooth morphology across the jaw arcade, with teeth 1-6 presenting a more symmetrical shape and teeth 7-12 exhibiting a distally curved shape (Fig. 4). 3.4 Tooth shape throughout ontogeny Ontogenetic changes in tooth shape were suggested by the GLMMs, with divergence occurring at different PCL depending on the morphometric method. In the classic morphometric model, residuals indicated a significant shift in shape beginning at approximately 210 cm PCL, whereas the EFA model identified this transition at a larger body size, around 250 cm PCL (Fig.3). When grouped by body size, EFA outlines from smaller sharks (PCL ≤250 cm) tended to show more slender and curved forms, particularly in anterior teeth. In contrast, teeth from larger sharks (PCL >250 cm) appeared broader and more triangular (Fig. 4). This trend was most pronounced in the lower jaw, with the first 6 teeth exhibiting a broader shape at PCL >250. 3.5 Additional measures The standardized partial residuals from the additional linear models examined similarly revealed clear ontogenetic shifts in the classic morphometric variables not included in the primary multivariate PCA. The residuals for the BT displayed a significant shift at approximately 210 cm PCL (Fig. 5b). However, the distinct change in BT occurred after the second tooth, suggesting structural reinforcement in anterior teeth, possibly during the transition to larger prey (Fig. 5a). Similarly, the root surface area of tooth UR1 also exhibited a distinct increase at 210 cm PCL (Fig. 7), likely reflecting the need for enhanced tooth stability in larger individuals. The broader jaw metrics followed comparable patterns to the changes in tooth shape. Jaw circumference showed a significant increase relative to body length at approximately 205 cm PCL (Fig. 8a), while jaw width increased more gradually, with a similar inflection point at around 210 cm PCL (Fig. 8b). However, there was greater variability observed in the jaw width at larger PCL, as shown by the broader confidence intervals in the residuals. Finally, an analysis of the TH alone revealed that upper hemisphere teeth three and four are relatively shorter than their neighbouring teeth (Fig. 6). Table 2: GLMM of C. carcharias tooth shape for the EFA analysis, including the effects of PCL and interactions between jaw position and tooth number. Variable Estimate SE t-Value p-Value Intercept -1.84e-01 1.60e-02 -11.48 <0.001 PCL 3.50e-04 5.50e-05 6.36 <0.001 LL: Tooth number 5.44e-02 9.97e04 54.52 <0.001 LR: Tooth number 5.16e-02 9.81e-04 52.60 <0.001 UL: Tooth number -1.34e-02 8.73e-04 -15.34 <0.001 UR: Tooth number -1.34e-02 8.84e-04 -15.81 <0.001 Table 3: GLMM of C. carcharias tooth shape for the classic morphometric analysis, including the effects of PCL and interactions between jaw position and tooth number. Variable Estimate SE t-Value p-Value Intercept -9.64e-02 2.81e-02 -3.43 <0.001 PCL -3.16e-03 1.19e-04 -26.59 <0.001 LL: Tooth number 1.32e-01 1.68e-03 79.19 <0.001 LR: Tooth number 1.31e-01 1.60e-03 81.74 <0.001 UL: Tooth number 1.23e-01 1.40e-03 87.79 <0.001 UR: Tooth number 1.23e-01 1.41e-03 86.76 <0.001 Fig. 3 GLMM of the standardized partial residuals for a) EFA coefficients describing tooth shape across tooth number and body length (PCL), and (b) classic morphometric coefficients describing tooth shape across tooth number and body length (PCL). Shaded bands and dashed lines indicate the 95% confidence intervals and null effects, respectively. The red dashed lines indicate the inflection points where there is a significant shift in tooth shape. Fig. 4 Overlaid Elliptic Fourier tooth outline reconstructions for C. carcharias with (a) PCL 250 cm. Each panel includes a sequence of six adjacent teeth per jaw quadrant. Colour-coded overlays represent tooth position within the sequence, with lighter hues corresponding to the most mesial (central) tooth (tooth 1 or 7) and progressively darker hues indicating more distal (lateral) teeth (tooth 6 or 12). Fig. 5 The standardized partial residuals for the BT in a) tooth number and b) PCL. Shaded bands and dashed lines indicate the 95% confidence intervals and null effects, respectively. The red dashed lines indicate the inflection points where there is a significant shift in tooth shape. Fig. 6 The standardized partial residuals for the TH across tooth number for the upper jaw hemisphere to highlight the relative difference in tooth 3 and 4. Shaded bands indicate the 95% confidence intervals, respectively. Fig. 7 The standardized partial residuals for the root surface area using tooth UR1. Shaded bands indicate the 95% confidence intervals, respectively. The red dashed line indicates the inflection points where there is a significant shift in tooth shape. Fig. 8 The standardized partial residuals for a) jaw circumference and b) jaw width with PCL for C. carcharias jaws. Shaded bands indicate the 95% confidence intervals, respectively. The red dashed lines indicate the inflection points where there is a significant shift in tooth shape. DISCUSSION This study provides the most comprehensive morphometric analysis to date of tooth shape variation in white sharks, revealing significant patterns associated with tooth position within the jaw and throughout ontogeny. By using both EFA and traditional morphometrics, our results highlight the complex interplay of biological, developmental, and ecological factors that shape tooth morphology in this apex predator, offering insights into the functional implications of these variations (Wainwright et al., 2004). We observed a strong bilateral symmetry in tooth counts and tooth shape between the left and right sides of the jaw. This symmetrical structure likely promotes an even distribution of mechanical forces during feeding, reducing stress on the jaw and improving prey handling efficiency (Dean et al., 2005; Gomes et al., 2011). The discontinued development of cusplets in animals >235 cm PCL highlights the functional role cusplets play in juveniles to enhance grasping ability and prey retention when feeding on smaller, mucilaginous prey, and provide an adaptive advantage during early life stages (Bemis et al., 2015; Herman et al., 1991; Perez et al., 2018) when the Australasian white shark diet predominantly comprises smaller teleost prey (Grainger et al., 2020). However, there is considerable inter-individual variability, as the smallest individual lacking cusplets was only 180 cm PCL. This size corresponds with the findings of Hussey et al. (2012), who observed the initial appearance of marine mammals in the diet of South African white sharks at 194 cm PCL, potentially suggesting that early reductions in cusplet expression may coincide with the onset of a dietary transition towards including larger, more robust prey. Previous research has documented sexual dimorphism in white shark tooth shape, with males exhibiting broader upper first teeth and greater distal inclination in the upper third teeth during growth (French et al., 2017). In contrast, our data showed no significant differences in tooth shape between sexes. This aligns with the findings of Grainger et al. (2020), who found no dietary differences between female and male eastern-Australian white sharks, and suggests that the sex of an individual is unlikely to influence tooth morphology in this species. Similarly, Hunt et al. (2024) found no significant sexual dimorphism in the body shape of Australasian white sharks, further supporting our lack of sexual differences in this study of white shark teeth. Interestingly, our findings differed from those of French et al. (2017), who relied on two-dimensional photographs, whereas our study used outline-based morphometrics and multiple classic morphometric measurements of actual teeth throughout the entire jaws of white sharks to quantify the shape. Our findings confirm that white shark dentition is invariant across the jaw. The tooth shape varied significantly by tooth number, with a clear anterior-to-posterior gradient in both the upper and lower jaw. Upper teeth exhibited broader, more triangular crowns with greater curvature compared to the slender, piercing-shaped teeth, observed in the lower jaw, especially in juvenile sharks. The consistent differences observed between the upper and lower jaw hemispheres align with the known feeding behaviour of white sharks, whereby lower teeth are primarily used for prey capture and retention and upper teeth for sawing and dismemberment (Compagno, 2001; Frazzetta, 1988; Purdy, 1996; Whitenack et al., 2011). The overlaid elliptic Fourier tooth outline reconstructions displayed a clear pattern of mediolateral heterodonty evident across the functional tooth row. This was further examined through the standardized partial residuals in the GLMM, highlighting a pronounced shift in morphology at the sixth tooth. This represents a major inflection point along the jaw, beyond which teeth become considerably more laterally compressed and recurved. This gradation may be indicative of a transition from an impaling or cutting function in anterior teeth to a shape better suited for shearing or tearing in more lateral teeth (Herman et al., 1991; Shimada, 2002). These patterns reflect a high degree of within-row (sequential monognathic) heterodonty, a condition where adjacent teeth differ significantly in form, as described by Zimm et al. (2024). While some shark species display considerable variation between upper and lower jaws without pronounced differences between adjacent teeth, white sharks exhibit both (Zimm et al., 2024), supporting the notion that heterodonty may be functionally adaptive. The individual analysis of the tooth height in the upper jaw revealed the distinctive morphology of the third and fourth teeth, in particular their smaller size and slight angling toward the second tooth. Although these subtle features were not fully captured in the PCA, they warrant further investigation as they may offer greater insight into functional adaptations within the jaw. For example, the slight angling of the teeth may indicate a specific role in prey retention, potentially used as a specialised tool in hunting pinnipeds (French et al., 2017; Martin et al., 2005). The relative size of the third and fourth tooth on the other hand, are likely influenced by the underlying cranial morphology, as these teeth align with a region of the upper jaw where key tendons associated with the olfactory system are anchored (Denton et al., 2018; Staggl et al., 2022; Yopak et al., 2015), potentially constraining tooth development in this area. Additionally, the individual analysis of the base thickness in the first four teeth revealed comparable results for body length, where a distinct change in thickness occurred at 210 cm PCL. Conversely, the major inflection point was observed after the second tooth, implying that this increased tooth thickness in the front two teeth may indicate they are the primary teeth involved in the initial bite, as they represent teeth with enhanced strength (Lucifora et al., 2001; Siversson, 1992). One key ontogenetic trend observed in this study is the overall transition from a more cuspidate shape tooth with accessory cusplets in smaller individuals to broader, more triangular teeth with serrations in larger individuals. This trend is particularly evident in the lower jaw, whereby the shape is considerably wider at the mid-point of the tooth in individuals >250 cm PCL. The standardized partial residuals in the GLMM further revealed a distinct shift in tooth shape at approximately 210 cm PCL in the classic morphometry method and 250 cm PCL in the EFA method. Our results further corroborate the findings of Tricas and McCosker. (1984), who found a change in tooth shape in white sharks at approximately 300 cm TL (~ 240 cm PCL, Hunt et al., 2024). These morphological changes demonstrate clear ontogenetic shifts in tooth shape that coincide with known changes in white shark diet and foraging behaviour. Previous studies have shown that juveniles rely primarily on a piscivorous diet (Grainger et al., 2020; Kerr et al., 2006), requiring teeth optimised for grasping and holding. While mature animals (>300 cm TL) increasingly consume marine mammals, requiring broader, serrated teeth capable of slicing through dense flesh and bone (Estrada et al., 2006; Tricas & McCosker, 1984). As larger prey pose a greater risk of injury during predation, successful attacks require the immobilisation of prey within 1 minute (Martin et al., 2005). As such, this shift in tooth shape to broader, serrated teeth in larger individuals may enhance the initial bite to incapacitate the prey quickly, reducing both the overall handling time and the risk of injury. The increasing complexity and surface area of the teeth in larger individuals likely enhance the efficiency of processing large-bodied, high-calorie prey such as marine mammals (Curtis et al., 2012). These ontogenetic changes in tooth morphology therefore appear to reflect adaptive responses to mechanical and dietary demands at different life stages (Grainger et al., 2020; Hussey et al., 2012). Moreover, our findings also highlight substantial ontogenetic changes in jaw structure that are closely linked to functional shifts in feeding capacity and biomechanics. Notably, the standardized partial residuals indicated a distinct change in the jaw circumference at 205 cm PCL, a size supported by a jaw width increase at 210 cm PCL. This suggests a developmental shift in jaw structure, enabling support for larger, broader teeth and facilitating the transition to larger, more robust prey. Jaw width, in particular, exhibited greater variation in individuals larger than 300 cm PCL, though some of this variation may be influenced by the way specimens have been preserved. These morphological changes are accompanied by a significant increase in the surface area of the tooth root at 210 cm PCL, possibly reflecting the early stages of jaw mineralization and structural reinforcement (Ferrara et al., 2011). White sharks are unique among elasmobranchs in possessing up to five extra layers of mineralized cartilage in the jaw, a trait acquired as they mature (Dingerkus et al., 1991). This added mineralization reduces stress in the load-bearing outer layers of the jaw, thereby improving its mechanical resistance to bite forces (Ferrara et al., 2011). Ferrara et al. (2011) observed this mineralization of the jaw in the transitional stages in ontogeny (~150-300 cm TL). However, the full mineralization did not occur until sharks exceeded 300 cm TL, complementing our findings of tooth reinforcement in the surface area of the root at 210 cm PCL (~260 cm TL, Hunt et al., 2024). Biomechanical studies show that serrated teeth in larger individuals improve efficiency by reducing shear and tear stresses when feeding (Frazzetta et al., 1988; Riverón et al., 2025; Whitenack & Motta, 2010; Whitenack & Motta, 2011). However, this adaptation comes with trade-offs as serrations impede puncturing, limiting effectiveness on small or hard-bodied prey. One limitation in our dataset is that some functional teeth, particularly from large specimens, may show worn serrations due to feeding history, making serration morphology a less reliable metric for ontogenetic comparison. Although we did not quantify the serration morphology in this study, we recommend that it be included in future research to better understand its role in feeding biomechanics and ontogeny. Nevertheless, the coordination of jaw expansion, tooth reinforcement and mineralization of jaw cartilage collectively enhances bite performance and dietary breadth as sharks grow, supporting their shift from piscivory to macropredation. Our study provides strong evidence that white shark tooth shape is associated with both positional and ontogenetic factors, reflecting adaptations to changing dietary needs and jaw mechanics. Specifically, the slender, narrow teeth observed in juveniles likely facilitate grasping and holding of slippery teleost prey, while the broader, serrated teeth in adults are better suited for cutting and processing marine mammal tissue. The use of both elliptic Fourier descriptors and traditional linear measures provided complementary insights. While linear morphometrics effectively captured gross size and proportional changes, Fourier analysis revealed subtler, holistic shape differences that may be overlooked in traditional methods. The consistency in patterns across both datasets supports the robustness of our findings and highlights the utility of combining shape quantification techniques in studies of dental functional morphology. However, the classic morphometrics captured a larger proportion of the shape variation in relation to biological and positional factors compared to the EFA coefficients and presented a greater overall explanatory power. By linking form to function across multiple scales, this work contributes to a more nuanced understanding of the ecological and evolutionary forces shaping apex predator feeding morphology. Acknowledgements We would like to thank all those who assisted in collecting morphometric data and provided jaws for this study. Many institutions contributed to these data, including the New South Wales Department of Primary Industries and Regional Development via the collection of animals from the Shark Meshing Program, Commonwealth Scientific and Industrial Research Organisation, Western Australia Department of Primary Industries, Western Australian Museum, Flinders University, and Rodney Fox and Mark Tozer’s Museum and Research Centre. Declaration of Interests The authors declare no competing interests. Author Contributions Emily Hunt, Victor M. Peddemors, Amy Smoothey and David Raubenheimer conceived the original idea with subsequent input from all authors. Emily Hunt wrote the first draft of the manuscript with all authors contributing to edits. Shark jaws and associated data were collected by Emily Hunt, Victor M. Peddemors, Amy F. Smoothey and Russel Bradford. Data Analysis was conducted by Emily Hunt and Yuri Niella with input from all authors. Data Availability Statement The data supporting the findings of this study are publicly available via the Zenodo Digital Repository: https://doi.org/10.5281/zenodo.16741930. All data are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Funding Information No funding was received for this research. REFERENCES Adobe. (2024). Adobe Photoshop (Version 25.12.3). Adobe Inc. https://www.adobe.com/photoshop Aines, A. C., Carlson, J. K., Boustany, A., Mathers, A., & Kohler, N. E. (2017). Feeding habits of the tiger shark, Galeocerdo cuvier, in the northwest Atlantic Ocean and Gulf of Mexico. Environmental Biology of Fishes , 101 (3), 403–415. https://doi.org/10.1007/s10641-017-0706-y Becker, M.A., Chamberlain, J.A. Jr. & Stoffer, P.W. (2000) Pathologic tooth deformities in modern and fossil chondrichthians: a consequence of feeding-related injury. Lethaia 33 : 103-118. https://doi.org/10.1080//00241160050150249 Bemis, W. E., Moyer, J. K., & Riccio, M. L. (2015). Homology of lateral cusplets in the teeth of lamnid sharks (Lamniformes: Lamnidae). Copeia, 103(4), 961-972. https://doi.ord/10.1643/CG-14-109 Bolnick, Daniel I., Svanbäck, R., Fordyce, James A., Yang, Louie H., Davis, Jeremy M., Hulsey, C. Darrin, & Forister, Matthew L. (2003). The Ecology of Individuals: Incidence and Implications of Individual Specialization. The American Naturalist , 161 (1), 1–28. https://doi.org/10.1086/343878 Bonhomme, V., Sandrine Picq, Cédric Gaucherel, & Claude, J. (2014). Momocs: Outline Analysis Using R . Journal of Statistical Software , 56 (13). https://doi.org/10.18637/jss.v056.i13 Bruce, B. D., & Bradford, R. (2012). Habitat use and spatial dynamics of juvenile white sharks, Carcharodon carcharias, in eastern Australia. In Global perspectives on the biology and life history of the white shark (pp. 225–253). CRC Press. https://doi.org/10.1201/b11532-20 Compagno, L. J. V. (2001). Sharks of the world: An annotated and illustrated catalogue of shark species known to date. Volume 2. Bullhead, mackerel and carpet sharks (Heterodontiformes, Lamniformes and Orectolobiformes) . FAO. Corn, K. A., Farina, S. C., Brash, J., & Summers, A. P. (2016). Modelling tooth–prey interactions in sharks: the importance of dynamic testing. Royal Society Open Science , 3 (8), 160141. https://doi.org/10.1098/rsos.160141 Cullen, J. A., & Marshall, C. D. (2019). Do sharks exhibit heterodonty by tooth position and over ontogeny? A comparison using elliptic Fourier analysis. Journal of Morphology , 280 (5), 687–700. https://doi.org/10.1002/jmor.20975 Davit-Béal, T., Chisaka, H., Delgado, S., & Sire, J.-Y. (2007). Amphibian teeth: current knowledge, unanswered questions, and some directions for future research. Biological Reviews , 82 (1), 49–81. https://doi.org/10.1111/j.1469-185x.2006.00003.x Dean, M. N., Wilga, C. D., & Summers, A. P. (2005). Eating without hands or tongue: Specialization, elaboration and the evolution of prey processing mechanisms in cartilaginous fishes. Biology Letters , 1 (3), 357–361. https://doi.org/10.1098/rsbl.2005.0319. Denton, J. S., Maisey, J. G., Grace, M., Pradel, A., Doosey, M. H., Bart Jr, H. L., & Naylor, G. J. (2018). Cranial morphology in Mollisquama sp.(Squaliformes; Dalatiidae) and patterns of cranial evolution in dalatiid sharks. Journal of Anatomy, 233(1), 15-32. https://doi.org/10.1111/joa.12823 Dicken, M. L., Hussey, N. E., Christiansen, H. M., Smale, M. J., Nomfundo Nkabi, Cliff, G., & Wintner, S. P. (2017). Diet and trophic ecology of the tiger shark (Galeocerdo cuvier) from South African waters. PLoS ONE , 12 (6), e0177897–e0177897. https://doi.org/10.1371/journal.pone.0177897 Ebert, D. A. (2002). Ontogenetic changes in the diet of the sevengill shark (Notorynchus cepedianus). Marine and Freshwater Research , 53 (2), 517. https://doi.org/10.1071/mf01143 Ebert, D.A. & M.F. Stehmann. (2013). Sharks, batoids and chimaeras of the North Atlantic. FAO Species catalogue for Fishery Purposes No. 7. Rome, FAO. 523 pp Estrada, J. A., Rice, A. N., Natanson, L. J., & Skomal, G. B. (2006). Use of isotopic analysis of vertebrae in reconstructing ontogenetic feeding ecology in white sharks. Ecology , 87 (4), 829–834. https://doi.org/10.1890/0012-9658(2006)87[829:uoiaov]2.0.co;2 Frazzetta, T. H. (1988). The mechanics of cutting and the form of shark teeth (Chondrichthyes, Elasmobranchii). Zoomorphology , 108 (2), 93–107. https://doi.org/10.1007/bf00539785 French, G. C. A., Stürup, M., Rizzuto, S., van Wyk, J. H., Edwards, D., Dolan, R. W., Wintner, S. P., Towner, A. V., & Hughes, W. O. H. (2017). The tooth, the whole tooth and nothing but the tooth: tooth shape and ontogenetic shift dynamics in the white shark Carcharodon carcharias . Journal of Fish Biology , 91 (4), 1032–1047. https://doi.org/10.1111/jfb.13396 Fu, A. L., Hammerschlag, N., Lauder, G. V., Wilga, C. D., Kuo, C., & Irschick, D. J. (2016). Ontogeny of head and caudal fin shape of an apex marine predator: The tiger shark ( Galeocerdo cuvier) . Journal of Morphology , 277 (5), 556–564. https://doi.org/10.1002/jmor.20515 Gomes, S. G. F., Custodio, W., Faot, F., Cury, A. A. D. B., & Garcia, R. C. M. R. (2011). Chewing side, bite force symmetry, and occlusal contact area of subjects with different facial vertical patterns. Brazilian Oral Research, 25(5), 446–452. https://doi.org/10.1590/S1806-83242011005000014. Goodman, K., Niella, Y., Bliss‐Henaghan, T., Harcourt, R., Smoothey, A. F., & Peddemors, V. M. (2022). Ontogenetic changes in the tooth morphology of bull sharks ( Carcharhinus leucas ). Journal of Fish Biology , 101 (4), 1033–1046. https://doi.org/10.1111/jfb.15170 Grainger, R., Peddemors, V. M., Raubenheimer, D., & Machovsky-Capuska, G. E. (2020). Diet Composition and Nutritional Niche Breadth Variability in Juvenile White Sharks (Carcharodon carcharias). Frontiers in Marine Science , 7, 422 . https://doi.org/10.3389/fmars.2020.00422 Habegger, M. L., Motta, P. J., Huber, D. R., & Dean, M. N. (2012). Feeding biomechanics and theoretical calculations of bite force in bull sharks (Carcharhinus leucas) during ontogeny. Zoology , 115 (6), 354–364. https://doi.org/10.1016/j.zool.2012.04.007 Herman, J., Hovestadt-Euler, M., & Hovestadt, D. C. (1991). Contributions to the study of the comparative morphology of teeth and other relevant ichthyodorulites in living supraspecific taxa of chondrichthyan fishes. Part A: Selachii. No. 2c: Order: Carcharhiniformes, Families: Proscylliidae, Hemigaleidae, Pseudotriakidae, Leptochariidae and Carcharhinidae. Bull. Inst. R. Sci. Nat. Belg. Biol, 61, 73-120. Huber, D. R., Weggelaar, C. L., & Motta, P. J. (2006). Scaling of bite force in the blacktip shark Carcharhinus limbatus. Zoology , 109 (2), 109–119. https://doi.org/10.1016/j.zool.2005.12.002 Hunt, E., Bradford, R. W., Booth, D. J., Doak, C., Patterson, T. A., & Peddemors, V. M. (2024). Ontogenetic change in body shape for white sharks, Carcharodon carcharias , in Australian waters. Journal of Fish Biology . https://doi.org/10.1111/jfb.16016 Hussey, Nigel & Christiansen, Heather & Cliff, Geremy & Dudley, Sheldon & Wintner, S. & Fisk, Aaron. (2012). Size-based analysis of diet and trophic position of the white shark (Carcharodon carcharias) in South African waters. Global perspectives on the biology and life history of the white shark. 27-50. http://doi.org/10.1201/b11532-5 Hussey, N. E., MacNeil, M. A., McMeans, B. C., Olin, J. A., Dudley, S. F. J., Cliff, G., … & Fisk, A. T. (2012). Rescaling the trophic structure of marine food webs. Ecology Letters, 15 (1), 104–112. https://doi.org/10.1111/j.1461-0248.2011.01710.x Irschick, D. J., & Hammerschlag, N. (2014). Morphological scaling of body form in four shark species differing in ecology and life history. Biological Journal of the Linnean Society , 114 (1), 126–135. https://doi.org/10.1111/bij.12404 Jones, M. E. H. (2009). Dentary Tooth Shape in Sphenodon and Its Fossil Relatives (Diapsida: Lepidosauria: Rhynchocephalia). Frontiers of Oral Biology , 9–15. https://doi.org/10.1159/000242382 Kerr, L.A., Andrews, A.H., Cailliet, G.M. et al. Investigations of Δ 14C, δ 13C, and δ 15N in vertebrae of white shark (Carcharodon carcharias) from the eastern North Pacific Ocean. Environ Biol Fish 77, 337–353 (2006). https://doi.org/10.1007/s10641-006-9125-1 Kim, S. L., Tinker, M. T., Estes, J. A., & Koch, P. L. (2012). Ontogenetic and Among- Individual Variation in Foraging Strategies of Northeast Pacific White Sharks Based on Stable Isotope Analysis. PLoS ONE , 7 (9), e45068. https://doi.org/10.1371/journal.pone.0045068 Lee KA, Butcher PA, Harcourt RG, Patterson TA, Peddemors VM, Roughan M, Harasti D, Smoothey AF, Bradford RW. (2021). Oceanographic conditions associated with white shark (Carcharodon carcharias) habitat use along eastern Australia. Mar Ecol Prog Ser 659:143-159 https://doi.org/10.3354/meps13572 Lipscombe, R. S., Meyer, L., Butcherine, P., Morris, S., Huveneers, C., Scott, A., & Butcher, P. A. (2024). A taste of youth: Seasonal changes in the diet of immature white sharks in eastern Australia. Frontiers in Marine Science , 11 , 1359785. https://doi.org/10.3389/fmars.2024.1359785 Lingham-Soliar, T. (2005). Caudal fin allometry in the white shark Carcharodon carcharias: implications for locomotory performance and ecology. Naturwissenschaften , 92 (5), 231–236. https://doi.org/10.1007/s00114-005-0614-4 Lowe, C. G., Wetherbee, B. M., Crow, G. L., & Tester, A. L. (1996). Ontogenetic dietary shifts and feeding behavior of the tiger shark, Galeocerdo cuvier, in Hawaiian waters. Environmental Biology of Fishes , 47 (2), 203–211. https://doi.org/10.1007/bf00005044 Martin, & Aidan, R. & Hammerschlag, Neil & Collier, Ralph & Fallows, Chris. (2005). Predatory behaviour of white sharks (Carcharodon carcharias) at Seal Island, South Africa. Journal of the Marine Biological Association of the United Kingdom. 85(5): 1121-1135. https://doi.org/10.1017/S002531540501218X Nakazawa, T. (2015). Ontogenetic niche shifts matter in community ecology: a review and future perspectives. Population Ecology , 57 (2), 347–354.https://doi.org/10.1007/s10144-014-0448-z Newman, S. P., Handy, R. D., & Gruber, S. H. (2011). Ontogenetic diet shifts and prey selection in nursery bound lemon sharks, Negaprion brevirostris, indicate a flexible foraging tactic. Environmental Biology of Fishes , 95 (1), 115–126. https://doi.org/10.1007/s10641-011-9828-9 Papastamatiou, Y. P., Binder, B. M., Boswell, K. M., Malone, M. A., Heithaus, M. R., Huveneers, C., Mourier, J., & Harborne, A. R. (2024). Dynamic energy landscapes of predators and the implications for modifying prey risk. Functional Ecology , 38 (2), 284-293. https://doi.org/10.1111/1365-2435.14478 Perez, V. J., Godfrey, S. J., Kent, B. W., Weems, R. E., & Nance, J. R. (2018). The transition between Carcharocles chubutensis and Carcharocles megalodon (Otodontidae, Chondrichthyes): lateral cusplet loss through time. Journal of Vertebrate Paleontology, 38(6). https://doi.org/10.1080/02724634.2018.1546732 Powter, D. M., Gladstone, W., & Platell, M. (2010). The influence of sex and maturity on the diet, mouth morphology and dentition of the Port Jackson shark, Heterodontus portusjacksoni. Marine and Freshwater Research , 61 (1), 74. https://doi.org/10.1071/mf09021 Purdy, R. (1996). Evolution of the white shark: A biochronological perspective. In: Kimley, A.P. and Ainley, D.G., Eds., Great White Sharks: The Biology of Carcharodon carcharias, Academic Press, San Diego, 67-78. http://dx.doi.org/10.1016/B978-012415031-7/50009-4 Riverón, S., Raoult, V., Slip, D. J., Mas, F., Laporta, M., Pereyra, I., Silveira, S., & Harcourt, R. G. (2025). Shearing Tooth Morphology May Allow Sharks to Access Higher Trophic Levels at Smaller Sizes. Ecology and Evolution , 15 (8). https://doi.org/10.1002/ece3.71722 Shimada, K. (2002). The relationship between the tooth morphology and body size of the lamniform shark, Cretalamna appendiculata . Journal of Fossil Research, 35(2), 45–53. Siversson, M. (1992). Biology, dental morphology and taxonomy of lamniform sharks from the Campanian of the Kristianstad Basin, Sweden. Palaeontology, 35, 519–554. https://www.biodiversitylibrary.org/part/174092 Skomal GB, Braun CD, Chisholm JH, Thorrold SR (2017) Movements of the white shark Carcharodon carcharias in the North Atlantic Ocean. Marine Ecology Progress Series 580:1-16 https://doi.org/10.3354/meps12306 Spaet, J., Patterson, T., Bradford, R. & Butcher, P. (2020). Spatiotemporal distribution patterns of immature Australasian white sharks (Carcharodon carcharias). Scientific Reports, 10:10169 . https://doi.org/10.1038/s41598-020-66876-z. Staggl, M. A., Abed-Navandi, D., & Jürgen Kriwet. (2022). Cranial morphology of the orectolobiform shark, Chiloscyllium punctatum Müller & Henle, 1838. Vertebrate Zoology , 72 , 311–370. https://doi.org/10.3897/vz.72.e84732 Tinker, M. T., Costa, D. P., Estes, J. A., & Wieringa, N. (2007). Individual dietary specialization and dive behaviour in the California sea otter: Using archival time–depth data to detect alternative foraging strategies. Deep Sea Research Part II: Topical Studies in Oceanography , 54 (3-4), 330–342. https://doi.org/10.1016/j.dsr2.2006.11.012 Tricas, T. C., & McCosker, J. E. (1984). Predatory behavior of the white shark ( Carcharodon carcharias ) with notes on its biology. Proceedings of the California Academy of Sciences, 43 , 221–238. Wainwright, P. C., Bellwood, D. R., Westneat, M. W., Grubich, J. R., & Hoey, A. S. (2004). A functional morphospace for the skull of labrid fishes: patterns of diversity in a complex biomechanical system. Biological Journal of the Linnean Society , 82 (1), 1–25. https://doi.org/10.1111/j.1095-8312.2004.00313.x Werner, E. E., & Gilliam, J. F. (1984). The Ontogenetic Niche and Species Interactions in Size-Structured Populations. Annual Review of Ecology and Systematics , 15 (1), 393–425. https://doi.org/10.1146/annurev.es.15.110184.002141 Whitenack, L. B., & Motta, P. J. (2010). Performance of shark teeth during puncture and draw: implications for the mechanics of cutting. Biological Journal of the Linnean Society , 100 (2), 271–286. https://doi.org/10.1111/j.1095-8312.2010.01421.xWhitenack, L. B., Simkins, D. C., Motta, P. J., Hirai, M., & Kumar, A. (2010). Young’s modulus and hardness of shark tooth biomaterials. Archives of Oral Biology , 55 (3), 203–209. https://doi.org/10.1016/j.archoralbio.2010.01.001 Wood SN (2017). Generalized Additive Models: An Introduction with R, 2 edition. Chapman and Hall/CRC. https://doi.org/10.1201/9781315370279 Yopak, K. E., Lisney, T. J., & Collin, S. P. (2015). Not all sharks are “swimming noses”: variation in olfactory bulb size in cartilaginous fishes. Brain Structure and Function, 220(2), 1127-1143. https://doi.org/10.1007/s00429-014-0705-0 Zelditch, M. L., Swiderski, D. L., Sheets, H. D., & Fink, W. L. (2004). Superimposition methods. Geometric Morphometrics for Biologists, 105-128. https://doi.org/10.1016/B978-012778460-1/50007-7 SUPPLEMENTARY DATA Table S1: Stepwise model selection procedure for the GLMM of biological traits influencing the classic morphometrics method of C. carcharias tooth morphology. Included are all candidate models, their AICc values, ΔAIC (difference from the best model), and AIC weights (wAIC). Also shown are p-values from ANOVA comparing each model to the previous one in the sequence. Model Description AICc ΔAIC wAIC p-Value Null 217124.2 10826.97 <0.0001 - + PCL 217117.8 10820.63 <0.0001 <0.01 + Tooth number 206368.0 70.77 <0.0001 <0.001 + Position 216753.7 10456.50 <0.0001 - + Tooth number + PCL 206361.1 63.88 <0.0001 - + Tooth number:Position 206304.2 7.00 0.029 <0.001 + Tooth number:Position + PCL * 206297.2 0.0 0.971 <0.01 * Final Model Table S2: Stepwise model selection procedure for the GLMM of biological traits influencing the EFA method of C. carcharias tooth morphology. Included are all candidate models, their AICc values, ΔAIC (difference from the best model), and AIC weights (wAIC). Also shown are p-values from ANOVA comparing each model to the previous one in the sequence. Model Description AICc ΔAIC wAIC p-Value Null 691802.8 9321.6 <0.0001 - + PCL 691802.9 9321.7 <0.0001 <0.001 + Tooth number 691627.4 9146.2 <0.0001 <0.0001 + Position 690592.3 8111.1 <0.0001 <0.0001 + Tooth number + PCL 691627.4 9146.2 <0.0001 <0.0001 + Tooth number:Position 682481.2 0.0 0.427 <0.0001 + Tooth number:Position + PCL * 682481.2 0.0 0.427 - * Final Model Fig. S1 PCA of a) EFA coefficients and (b) classic morphometric coefficients used to observe the primary axes (coefficients) of variation in tooth shape. Fig. S2 Histograms of the a) classic morphometric coefficients and (b) EFA coefficients. Information & Authors Information Version history V1 Version 1 10 September 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Ecology and Evolution Keywords behavioral ecology comparative marine statistical vertebrate Authors Affiliations Emily Hunt 0009-0000-0245-1022 [email protected] The University of Sydney View all articles by this author Yuri Niella 0000-0003-1878-6091 IMOS Animal Tracking Facility View all articles by this author Amy Smoothey NSW Department of Primary Industries View all articles by this author Ezequiel Marzinelli 0000-0002-3762-3389 The University of Sydney Faculty of Science View all articles by this author David Raubenheimer The University of Sydney View all articles by this author Russell Bradford 0000-0003-0291-3180 CSIRO View all articles by this author David Booth University of Technology Sydney View all articles by this author Victor Peddermors NSW Department of Wild Fisheries View all articles by this author Metrics & Citations Metrics Article Usage 562 views 308 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Emily Hunt, Yuri Niella, Amy Smoothey, et al. The whole tooth: changes in tooth size and shape associated with ontogenetic changes in prey consumption by white sharks (Carcharodon carcharias) in Australia.. Authorea . 10 September 2025. DOI: https://doi.org/10.22541/au.175748673.32795363/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.175748673.32795363/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9feccb7d486006f3',t:'MTc3OTI5NTM0OQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();