Search tips
Search criteria 


Logo of procbhomepageaboutsubmitalertseditorial board
Proc Biol Sci. 2007 November 22; 274(1627): 2819–2828.
Published online 2007 September 4. doi:  10.1098/rspb.2007.0906
PMCID: PMC2288692

Computer simulation of feeding behaviour in the thylacine and dingo as a novel test for convergence and niche overlap


The extinct marsupial thylacine (Thylacinus cynocephalus) and placental grey wolf (Canis lupus) are commonly presented as an iconic example of convergence. However, various analyses suggest distinctly different behaviours and specialization towards either relatively small or large prey in the thylacine, bringing the degree of apparent convergence into question. Here we apply a powerful engineering tool, three-dimensional finite element analysis incorporating multiple material properties for bone, to examine mechanical similarity and niche overlap in the thylacine and the wolf subspecies implicated in its extinction from mainland Australia, Canis lupus dingo. Comparisons of stress distributions not only reveal considerable similarity, but also informative differences. The thylacine's mandible performs relatively poorly where only the actions of the jaw muscles are considered, although this must be considered in the light of relatively high bite forces. Stresses are high in the posterior of the thylacine's cranium under loads that simulate struggling prey. We conclude that relative prey size may have been comparable where both species acted as solitary predators, but that the dingo is better adapted to withstand the high extrinsic loads likely to accompany social hunting of relatively large prey. It is probable that there was considerable ecological overlap. As a large mammalian hypercarnivore adapted to taking small-medium sized prey, the thylacine may have been particularly vulnerable to disturbance.

Keywords: convergence, finite element analysis, Thylacinus, Canis

1. Introduction

Convergence remains central to the development and understanding of evolutionary theory (de Winter & Oxnard 2001; Madsen et al. 2001). Historically, various placentals of the order Carnivora and carnivorous marsupials have been offered as textbook supporting examples. Among these, few are more commonly cited than that of the marsupial ‘wolf’ or thylacine (Thylacinus cynocephalus) and its proposed placental counterpart the grey wolf, Canis lupus (Werdelin 1986; Wroe & Milne 2007) a subspecies of which (Canis lupus dingo) has been widely implicated in the disappearance of the thylacine from mainland Australia ca 3000 years ago. However, despite obvious resemblance between the two, many questions remain regarding apparent similarity in form and how this might reflect similarity in function (Werdelin 1986; Jones & Stoddart 1998; Johnson & Wroe 2003; Wroe et al. 2005).

Feeding ecology in most larger canids, including Canis lupus lupus and C. l. dingo is reasonably well understood (Corbett 1995; Stahler et al. 2006). The dingo in particular is a highly adaptable predator that deploys solitary, pair or pack hunting techniques to access a wide range of prey, from small vertebrates and invertebrates through to large kangaroos that considerably exceed its own body size (Thompson 1992; Corbett 1995). Carrion may provide a critical food source during periods of seasonal scarcity (Corbett 1995).

For the extinct thylacine, data on prey type and size are limited. Its reputation as a sheep killer was almost certainly exaggerated, but anecdotal evidence suggests that prey up to approximately 30 kg, including large kangaroos and emu may have been taken (Paddle 2002). Analyses of various character systems have often led to contradictory conclusions with respect to feeding habits. Canine tooth fracture rates are suggestive of reliance on small prey (1–5 kg) and the presence of a relatively long and gracile rostrum has been considered consistent with this interpretation (Werdelin 1986; Jones & Stoddart 1998). Similarly, three-dimensional geometric morphometric analyses demonstrate that skull shape in T. cynocephalus was most similar to that of medium- to small-prey specialists among canids (Wroe & Milne 2007). Alternatively, canine shape and a wide gape is suggestive of a capacity to take larger prey (Jones & Stoddart 1998; Johnson & Wroe 2003) and this is supported by high bite force estimates, which have been shown to correlate with increased prey size (Wroe et al. 2005). However, the relatively circular cross section of the canine is not consistent with the regular deployment of a dog-like slashing bite, wherein forces are largely directed along the anteroposterior axis (Jones 2003).

Moreover, relative to placental carnivores, in dasyuromorphians like T. cynocephalus, the masseteric is well developed and the temporalis is less so (Turnbull 1970). Precisely how differences in muscle organization between the two taxa might influence biomechanical performance remains unclear.

Conflicts and uncertainties aside, on the basis of molar anatomy, all authors concur that like C. lupus and other pack hunting canids, but unlike less social members of the dog family, T. cynocephalus was a hypercarnivore that derived the great bulk of its sustenance from meat (Jones 2003; Wroe et al. 2004). It is also clear that its dental anatomy is poorly adapted to a scavenging role (Johnson & Wroe 2003; Wroe 2003). Yet consensus on these points invites further contradiction. Cooperative hunting effectively increases the upper limits of prey size for social canids, but while there is some anecdotal evidence for limited social hunting in the thylacine (Paddle 2000), it is unlikely that the thylacine deployed comparable cooperative strategies (Corbett 1995). On the other hand, energetic constraints typically drive reliance on relatively large prey in terrestrial mammalian carnivores (Carbone et al. 1999) and at approximately 30 kg (Paddle 2000), the thylacine exceeds the body mass at which reliance on large prey would be predicted (i.e. 21.5 kg). Therefore, on energetic grounds and given an inability to efficiently resource carrion, non-vertebrate fauna or plant material, it might be expected that T. cynocephalus took relatively large prey. This holds even after allowing for a basal metabolic rate in marsupials that is 20% lower than for placentals (Burness et al. 2001; Johnson & Wroe 2003), although at least some marsupials present relatively high rates for field metabolism (Nagy et al. 1995).

Further investigation into convergence between T. cynocephalus and C. lupus is of interest, not only owing to its incisive pertinence to the understanding of evolutionary processes, but also because the degree of ecological overlap between these taxa impacts on the veracity of competing extinction hypotheses for mainland populations of the thylacine. While many have argued that competition with the dingo was the primary driver, others have suggested that differences in their ecology may have restricted competition and that Mid-Holocene intensification of human land use may have played a primary role (Johnson & Wroe 2003).

Here we apply a novel approach, finite element (FE) analysis, to the question of convergence between T. cynocephalus and C. l. dingo. FE analysis is a powerful engineering tool long used to predict the mechanical behaviour of man-made structures. However, despite great potential (Thomason 1995) and notable advances (Rayfield et al. 2001; Rayfield 2004; Tizzard et al. 2005; McHenry et al. 2006), the role of FE analysis in biology has been restricted by a number of limitations, perhaps most notably the time-consuming nature of model generation and difficulty in incorporating the variable material properties of bone (Rayfield 2007).

Most previous cranial models for vertebrates have assumed a single property for all bone, i.e. cortical. However, it has been argued on theoretical grounds that the presence of cancellous bone, which typically comprises much of the skull in large vertebrates, can greatly influence mechanical behaviour (Thomason 1995). FE modelling of the cranium of Macaca fascicularis has shown that allowance for differences in bone properties will impact on the accuracy of results (Strait et al. 2005). However, in this instance, properties were assigned manually to selected regions and distinctions between regional boundaries may not have been realistic (Strait et al. 2005). Most recently, Wroe et al. (in press) used a largely automated method to incorporate multiple material properties ranging from low-density cortical bone to enamel in FE modelling of a common chimpanzee skull. These authors found that distributions of stress and strain were broadly similar in single and multiproperty models, but allowance for variable properties resulted in lower stress and higher strain, as well as influencing relationships between internal and external gradients.

Additionally, to date, FE simulations of vertebrate skulls have been conducted on separate cranial and mandibular models that do not treat the skull as an articulated unit and muscle forces have typically been reduced to single vectors for major muscles. This can introduce high, artefactual point loads and stresses which may complicate the interpretation of results (Dumont et al. 2005).

The FE techniques we apply in the present study, which follow those of Wroe et al. (in press), represent a number of advances over previous simulations of the vertebrate skull in that they (i) incorporate multiple material properties for bone, (ii) treat the mandible and skull as a single articulated unit, and (iii) more accurately describe the three-dimensional architecture of jaw adducting musculature, with the additional benefit of minimizing the confounding influence of point loads (figure 1).

Figure 1
1 382 216 brick element heterogeneous model of Thylacinus cynocephalus. Comparison of (a) CT slice with (b) slice through same region of FE model. (c) Surface wire frame of model prior to the addition of musculature showing the level of geometric internal ...

2. Material and methods

We designed loads and restraints in our FE simulations to model a range of feeding behaviours. Our objective was to address levels of convergence in biomechanical performance, respective limitations on potential feeding behaviour and the potential for niche overlap in T. cynocephalus and C. l. dingo.

The dingo's skull was smaller than that of the thylacine (basal condylar length of 166 mm as opposed to 219 mm) and we estimate that body mass in the placental was approximately 60% that of the marsupial (see below). We did not rescale models to approximate equivalent dimensions in both. All our analyses were linear static, and increasing or decreasing model sizes will not affect stress distributions or magnitudes of stress for individual ‘brick’ elements, i.e. mechanical behaviour of these models will remain constant regardless of scale. In reality, there would be some allometric variation with size. For example, Wroe et al. (2005) found negative allometry regarding the estimated bite force and body mass among mammalian carnivores and allometry has also been demonstrated with respect to endocranial volume (Jerison 1973; Wroe & Milne 2007). In the absence of CT data from specimens of similar size, we do not control for allometry in this study. Given the gross geometric disparity between the marsupial and placental, we consider it probable that allometry will play a relatively minor role in explaining any differences in mechanical behaviour between these two specimens. It is also important to note that a lack of validated data for material properties dictates that our models cannot yet be used to deduce absolute performance limits and results of FE analyses were interpreted following a comparative approach (Dumont et al. 2005; McHenry et al. 2006).

We assessed mechanical behaviour on the basis of visual output of the post-processing software (figures 2–4) and mean brick element stress for selected regions (table 1). Mean stress was used rather than maximal stress following Dumont et al. (2005). Although maximal stress is potentially informative, the interpretation of maximal stress values is currently problematic in FE analyses of complex biological structures. This is because such FE models are likely to contain a number of irregular elements that register artefactually high values (Snively & Russell 2002).

Figure 2
Stress (Von Mises) distributions in lateral views of FE models of (a)–(d) C. l. dingo and (eh) T. cynocephalus under four load cases: (a,e) bilateral bite at canines, (b,f) bilateral bite at carnassials, (c, g) dorsoventral head depression ...
Figure 3
Stress (Von Mises) distributions in left and right lateral views of FE models of (ad) C. l. dingo and (eh)T. cynocephalus under two load cases: (a,e) unilateral bite at canines (left), (b,f) unilateral bite at canines (right), (c,g) ...
Figure 4
Stress (Von Mises) distributions in lateral views of FE models of (ac) C. l. dingo and (eg) T. cynocephalus under two load cases: (a,d) lateral shake (left), (b,e) lateral shake (right) and (c,f) axial twist. MPa, mega pascals.
Table 1
Mean brick element stresses (von Mises) for selected regions in solved FE models of C. l. dingo and T. cynocephalus under four load cases. (cran, cranium; rost, rostrum; ant o, anterior orbit; zygo, zygomatic arch; mand, mandible.)

Our heterogeneous models (eight material properties) were constructed using data from computer tomography (CT) for two skulls held in the Australian Museum: T. cynocephalus (AM 1821) and C. l. dingo (AM 38587). Scans comprised 293 and 228 transaxial slices, respectively. Slices were separated by 0.8 mm intervals. For surface meshes, maximum and minimum triangle edge lengths were kept at a 1 : 3 ratio (0.1 geometric error). Minimizing differences between dimensions of triangles within models reduces the probable incidence of artefacts. Solid meshing was performed with the Strand7 (v. 2.3) FE program.

Material properties were assigned on the basis of density values (Rho et al. 1995; Schneider et al. 1996; figure 1a,b). These ranged from Young's modulus of elasticity, E=1.5 GPa, Poisson's ratio, ν=0.4 and density, ρ=250 kg m−3 to E=32.7 GPa, ν=0.4 and ρ=2861 kg m−3. DICOM files include X-ray attenuation data as Hounsfield Units (HU). For each scan, the total range of HUs was divided to give the eight material property types. We used the mean HU value for each type to calculate its average density. The relationship between HU and density is nonlinear, and equations derived from data presented by Rho et al. (1995) and Schneider et al. (1996) were applied to convert HU values into average density values. Values for density were converted to Young's modulus (E) using data from Rho et al. (1995).

Very high resolution was required with respect to brick element number in order to produce simulations that realistically accommodated differences between bone densities. Models comprised 1 382 216 (T. cynocephalus) and 887 281 (C. l. dingo) three-dimensional four-noded tetrahedral brick elements.

Theoretically, models based on four-noded elements (tet4) produce less accurate results than those built from higher-order elements, however, with increasing brick element number models converge on identical results. Dumont et al. (2005) found differences of approximately 10% between tet4 and 10-noded (tet10) based models of less than 252 000 brick elements. Since our models contain at least 3.5 times as many brick elements, our results should be well within 10% of those that might be drawn from tet10 models of the same resolution.

We modelled the temporomandibular joint using a hinged beam connected to both upper and lower jaws by rigid links. The two pivot beams were released to allow rotation.

Eight loading cases were applied, four ‘intrinsic’ (bite transmitted) and four ‘extrinsic’ (neck transmitted). The four intrinsic cases simulated bites driven solely by skull musculature with maximal bite force assumed in each instance. These were: (i) a bilateral bite at the canines, (ii) a unilateral bite at the left canine, (iii) a bilateral bite at the carnassial notch, and (iv) a unilateral bite at the left carnassial notch. Rigid links connecting the four canine teeth were arranged in an H-shaped configuration with forces or moment applied to a central node in the two cross links. Loads comprised: (i) a lateral ‘shake’, (ii) an axial twist wherein moment was applied around the long axis of the skull, (iii) a dorsoventral force, and (iv) a pull back/simulating prey pulling away from the predator.

To prevent free body motion, FE models must be sufficiently restrained. Inappropriate point constraints (restricted to single nodes) can produce pronounced artefacts and inaccurate results (McHenry et al. 2006). Here we have applied more realistic constraints using frameworks of rigid links at the occipital condyle as well as at tooth bite points to more broadly distribute forces.

Mean brick element stresses were compared in six regions of interest for loading cases that produced symmetrical stress distributions, the whole skull, the cranium (i.e. here treated as that part of the skull inclusive of the facial skeleton excluding the mandible), the rostrum (from the antorbital fenestra to the anteriormost tip of the cranium), anterior orbit (from anterior margin of the orbit to antorbital fenestra), zygomatic arch and mandible (table 1). For simulations that produced asymmetrical loadings, these regions were further divided into left and right volumes.

All data were calculated in terms of von Mises stress. Von Mises is a uniaxial tensile stress which is a good predictor of failure in relatively ductile materials such as bone and proportional to the strain energy of distortion (Dumont et al. 2005). For statistical analyses, element number was too great to be accommodated by standard software packages and comparison of these large datasets was facilitated using a program written in RGui (by K. Moreno).

We calculated unilateral maximal contractile muscle forces using estimates for cross-sectional area (see Thomason (1991) and Wroe et al. (2005) for details). Muscle forces were 1320.1 N for T. cynocephalus and 895.9 N for the smaller Canis l. dingo. The three-dimensional architectures of the muscles were approximated using pre-tensioned trusses, beam elements that carry axial loads only (see Wroe et al. in press).

The number of truss elements and their diameters with respect to each major muscle subdivision were determined assuming that their force contributions were relative to muscle mass. Relative masses of muscle subdivisions for our dingo and thylacine models were taken from published data for C. l. dingo (Turnbull 1970) and Didelphis virginiana (Turnbull 1970). While overall forces for each muscle subdivision were computed on the basis of muscle mass, the number of trusses was calculated on the basis of muscle origin and insertion areas in order to spread forces appropriately. Pretension values for each truss were then calculated by dividing total force for the muscle subdivision by the number of trusses for that division.

In the T. cynocephalus model, the number of beams and their pretension values as applied to each muscle subdivision were: 42×22.7 N (temporalis profunda); 24×22.8 N (temporalis superficialis); 12×21.5 N (masseter profunda); 18×22.1 N (masseter superficialis); 10×24.7 N (zygomaticomandibularis); and 8×21.5 N (pterygoideus internus).

In our model of C. l. dingo, the number of beams and pretension values were: 38×16 N (temporalis profunda); 18×14.8 N (temporalis superficialis); 8×16 N (masseter profunda); 12×16.5 N (masseter superficialis); 8×15.9 N (masseter profunda); 8×14.2 N (zygomaticomandibularis); and 8×14.2 N (pterygoideus internus). The effect of the pterygoideus externus is negligible with respect to the power stroke, but additional unloaded beams were inserted in both models to simulate its potential stabilizing influence.

Four extrinsic loading cases simulated the influence of unrestrained prey (or cervically generated forces by the predator itself). These were calculated as directly proportional to body mass for both models. On the basis of predictive equations for craniodental dimensions in dasyuromorphian marsupials (Myers 2001) and canids (Van Valkenburgh 1990), estimated body masses were 23.5 and 13.8 kg for the T. cynocephalus and C. l. lupus, respectively. Forces for most extrinsic loadings were 500 N (T. cynocephalus) and 295 N (dingo). The exception here was for the axial loading case, which was applied as a moment (5000 and 295 Nmm).

As demonstrated by Preuschoft & Witzel (2004), extrinsic forces developed in the handling of even relatively small prey by a domestic dog are within the same order of magnitude as intrinsic bite forces. Thus, in shaking a 2 kg rabbit, accelerating the rostrum and overcoming mass moment of inertia will require an extrinsic muscle force of approximately 284 N and allowing for head and prey weight will bring total condylar force to 485 N. The extrinsic forces used in the present study are somewhat arbitrary, but are not unreasonable estimates for what might be expected in the dispatch and processing of relatively small prey in light of the findings of Preuschoft & Witzel (2004).

3. Results

The most broadly evident result was that mean brick stress distributions across selected regions followed similar patterns in all loading cases for T. cynocephalus and C. l. dingo simulations (figures 2–4). Generalities which hold for both specimens regarding intrinsic loadings are: (i) for all intrinsic loads (unilateral and bilateral bites at the canine and carnassial), mean brick stresses were highest in the mandible overall, and also in the zygomatic arches among cranial regions, (ii) mean brick stresses in both the cranium and mandible were higher in canine bites than carnassial bites, (iii) mean brick stresses were lowest in the rostral region for both bilateral and unilateral bites, and (iv) in unilateral biting, at both canine and carnassial, brick stresses were lower on the balancing side than the working side.

Mechanical behaviour common to both models with respect to extrinsic loads include: (i) in direct contrast to results from intrinsic loadings, for all four extrinsic loads the cranium records higher mean brick stress than for any other region and although not specifically selected, we can infer from this that the posterior of the cranium (i.e. that part exclusive of the rostral, antero-orbital and zygomatic regions) receives the highest mean stresses, (ii) for the cranium, the highest mean stresses are recorded under dorsoventral loading, and (iii) the lowest mean stresses for the skull and cranium occur under ‘pull back’ loading.

General similarities aside, clear differences were also evident between the two models. Regarding simulations of intrinsic bites these included: (i) maximal bite forces were considerably greater for the thylacine than dingo, i.e. respectively 679 and 299 N for a unilateral canine bite, and 1391 N compared with 635 N for a unilateral carnassial bite, (ii) under all intrinsic loads the marsupial wolf's mandible exhibited higher brick stress than the dingo's and this was particularly marked in the unilateral canine bite, (iii) the zygomatic arch received more stress in the dingo under all intrinsic loads except during a unilateral carnassial bite, and (iv) although low compared with the cranium as a whole in both simulations, mean brick stress in the rostrum was relatively still lower in the dingo than the thylacine under unilateral biting loads.

Performance differences between our two models under extrinsic loads were as follows: (i) under dorsoventral loading, overall mean brick stress was higher for the skull and cranium in T. cynocephalus, but this was concentrated in the posterior of the cranium because mean brick stresses were uniformly lower in facial regions of the marsupial, (ii) regarding overall mean brick stress, differences between the two are most extreme under pull back loading, however, again these differences are concentrated in the posterior of the cranium and mechanical performance in facial regions of T. cynocephalus is comparable or superior to that in C. l. lupus, (iii) similarly, during a lateral shake, mean cranial brick stress is clearly lower in the dingo, but differences are less marked in facial regions, and (iv) under axial loadings, the mean brick stress is consistently lower in the marsupial wolf in all regions. The finding of typically higher stress under extrinsic loadings in the thylacine is consistent with the observation of relatively smaller areas available for cervical muscle origins in the marsupial.

4. Discussion

Our data show that the zygomatic arches and mandible record relatively high stresses under all intrinsic loads for both models. This is concordant with previous suggestions that the mammalian skull may not be optimized solely to resist forces generated during feeding, based on analyses of feeding mechanics in primates and bats (Hylander et al. 1991; Dumont et al. 2005). However, in predators, particularly long-snouted ones, it has been argued that extrinsic forces may be important (Preuschoft & Witzel 2005). Consideration of extrinsic cases in the present study suggests that forces generated by the predator's cervical and other postcranial musculature, or by the resisting prey itself, can direct stresses to the posterior of the cranium that are comparable to those developed in the mandible and zygomatic arches under intrinsic loads. Moreover, the extrinsic forces applied to our models are designed to simulate interaction with relatively small prey and it is reasonable to assert that the handling of larger prey would introduce considerably greater stresses. Regarding mammalian predators, the skull may be more fully optimized for a range of loading regimes related to obtaining and processing food than that in omnivorous/herbivorous taxa. However, there can be little doubt that the need to fulfil other functions, such as housing neural and sensory organs, must introduce compromise (Preuschoft & Witzel 2004).

Nonetheless, although the specific extrinsic behaviours alluded to here are only directly applicable to predators, comparable postcranially generated forces might also be applied in cases of intra- and interspecific aggression/competition, which occurs in many largely non-predatory taxa including primates (Jones et al. 2006; Valero et al. 2006). We contend that, while unlikely to be as important in non-predators, the ability to adequately perform such less common, but nonetheless potentially critical behaviours involving extrinsic forces may influence skull morphology. We predict that FE analyses will further establish and expand on elective pressure to resist extrinsically generated forces as an influence on the evolution of skull shape, especially in predators, fossorial species and animals with agonistically adapted structures.

The general similarity to be inferred regarding mechanical behaviour in our thylacine and dingo models is perhaps the most striking result to emerge from our analyses. For both taxa, the same broadly proportional trends are evident with respect to differences in mean brick stress between regions in all intrinsic and three of the four extrinsic load cases (figures 2–4), the only clear exception being that the dingo's zygomatic arch receives higher stress than any other facial region under extrinsic axial loading. This suggests that differences in the relative sizes of primary jaw adductors between the marsupial and placental skulls do not produce greatly differing stress distributions. However, the notable differences between mean brick stress levels for individual regions under specific loads point to differing mechanical limits on behaviour. Relative to the dingo, the thylacine's mandible appears less well adapted to resist high intrinsic loads, especially regarding unilateral bites at the canine (table 1). Interestingly, snout morphology does not appear to be similarly limiting.

Maximal bite forces generated in our thylacine simulations are more than double those generated for the dingo. It is to be expected that much of this difference could be accounted for by differences in absolute size, with the thylacine being 70% heavier. However, on the basis of previously determined equations relating bite force to body mass in canids (Wroe et al. 2005), we estimate that a canid of equivalent body mass (23.5 kg) would develop a bite force at the canines of 424 N, still considerably less than that generated by our thylacine (679 N).

It is possible that cross-sectional muscle area may not be directly comparable as a predictor of jaw adductor force between marsupials and placentals (Wroe et al. 2005). If jaw adducting muscle forces in the thylacine were reduced to levels proportional to those of the dingo, the differences in stress distribution regarding the mandible under intrinsic loadings would diminish. This argument does not apply to extrinsic loadings, however, and the posterior part of the thylacine's cranium clearly receives higher stresses in response to simulated forces generated by the predator's cervical musculature or unrestrained prey, except under torsional loading at the canines. This is particularly true with respect to pull back loading, where stresses are 85% higher for the cranium as a whole in the thylacine, despite being very similar for all facial regions. Another assumption that we make here is that safety factors are comparable between marsupials and placentals. Final assessment will require in vivo as well as simulation-based data and is beyond the scope of the present study.

In the absence of securely validated data for material properties and forces generated in the despatch of large prey, actual mechanical limits on maximal prey size cannot be directly predicted. On the basis of comparative intrinsic results, we conclude that if prey were despatched by a largely cranially derived bite, then relative prey size for the thylacine was probably smaller or perhaps comparable with that of the dingo. However, in the despatch of relatively large prey, canids apply repeated slashing bites (Van Valkenburgh & Koepfli 1993) that are most closely approximated by our extrinsic pull back simulations, and the relatively poor performance of the thylacine's cranium under this extrinsic loading case suggests that its skull was not as well adapted to perform such a role. Brain size, typically around 2.4 times greater in placental carnivores (Wroe et al. 2003), could be a further confounding factor here. Structures required to house the larger brain of the placental might incidentally result in a cranium that can withstand relatively greater extrinsic loads. Nonetheless, on the basis of available data, the placental's theoretical performance limits remain greatly in excess of those evident in the thylacine and the most parsimonious conclusion is that this was related to function.

In summary, if only the results of our intrinsic loading cases are considered, then we would predict that relative prey size for the thylacine might have been comparable to that of the dingo if both taxa are considered as solitary predators. Given that mean body mass for the thylacine is approximately twice that of the placental's, it might also be reasonable to conclude on theses bases that actual mean prey size in the thylacine was considerably greater. However, we consider it probable that for long-snouted predators, killing behaviours in which intrinsic loads dominate are more likely confined to relatively small prey taken in a solitary context. The high extrinsic loadings, under which the thylacine performs poorly, are more likely to be encountered in the despatch of prey approaching or exceeding the predator's own body mass and we predict that relative maximal prey size was higher in the dingo, even if the thylacine did operate as pack hunter. We conclude that the thylacine concentrated on small- to medium-sized prey (i.e. smaller than its own body size) and that contra Johnson & Wroe (2003), actual overlap regarding prey size and hence the opportunity for competition was considerable. If as Carbone et al. (1999) suggest, the energetics of mammalian predation dictate that it is difficult for carnivores exceeding approximately 21.5 kg to obtain sufficient sustenance from prey smaller than themselves, then as a large hypercarnivorous species that specialized on small-medium sized prey, the thylacine, may have been particularly vulnerable to disturbance.


Work was funded by ARC Discovery, ARC QE2 Research Fellowship and UNSW Strategic Research Initiatives grants to S.W., and an Internal grant (University of Newcastle) to P.C. Special thanks to S. Ingleby (Australian Museum) and the Mater Hospital (Newcastle).


  • Burness G.P, Diamond J, Flannery T. Dinosaurs, dragons, and dwarfs: the evolution of maximal body size. Proc. Natl Acad. Sci. USA. 2001;98:14 518–14 523. doi:10.1073/pnas.251548698 [PubMed]
  • Carbone C, Mace G.M, Roberts S.C, MacDonald D.W. Energetic constraints on the diet of terrestrial carnivores. Nature. 1999;402:286–288. doi:10.1038/46266 [PubMed]
  • Corbett L. University of New South Wales Press; Sydney, Australia: 1995. The dingo in Australia and Asia.
  • de Winter W, Oxnard C.E. Evolutionary radiations and convergences in the structural organization of mammalian brains. Nature. 2001;409:710–714. doi:10.1038/35055547 [PubMed]
  • Dumont E.R, Piccirillo J, Grosse I.R. Finite-element analysis of biting behavior and bone stress in the facial skeletons of bats. Anat. Rec. A. 2005;283:319–330. doi:10.1002/ar.a.20165 [PubMed]
  • Hylander W.L, Picq P.G, Johnson K.R. Masticatory-stress hypotheses and the supraorbital region of primates. Am. J. Phys. Anthropol. 1991;86:1–36. doi:10.1002/ajpa.1330860102 [PubMed]
  • Jerison H.J. Academic Press; New York, NY: 1973. Evolution of the brain and intelligence.
  • Johnson C.N, Wroe S. Causes of extinction of vertebrates during the Holocene of mainland Australia: arrival of the dingo, or human impact? Holocene. 2003;13:941–948. doi:10.1191/0959683603hl682fa
  • Jones M.E. Convergence in ecomorphology and guild structure among marsupial and placental carnivores. In: Jones M.E, Dickman C, Archer M, editors. Predators with pouches: the biology of carnivorous marsupials. CSIRO Publishing; Collingwood, Australia: 2003. pp. 269–285.
  • Jones M.E, Stoddart D.M. Reconstruction of the predatory behaviour of the extinct marsupial thylacine (Thylacinus cynocephalus) J. Zool. (Lond.) 1998;246:239–246.
  • Jones T, Laurent S, Mselewa F, Mtui A. Sanje mangabey Cercocebus sanjei kills an African crowned eagle Stephanoaetus coronatus. Folia Primatol. 2006;77:359–363. doi:10.1159/000093701 [PubMed]
  • Madsen O, et al. Parallel adaptive radiations in two major clades of placental mammals. Nature. 2001;409:614–620. doi:10.1038/35054544 [PubMed]
  • McHenry C.R, Clausen P.D, Daniel W.J.T, Meers M.B, Pendharkar A. The biomechanics of the rostrum in crocodilians: a comparative analysis using finite element modelling. Anat. Rec. A. 2006;288:827–849. doi:10.1002/ar.a.20360 [PubMed]
  • Myers T.J. Marsupial body mass prediction. Aust. J. Zool. 2001;49:99–118. doi:10.1071/ZO01009
  • Nagy K, Meienberger C, Bradshaw S.D, Wooller R.D. Field metabolic rate of a small marsupial mammal, the honey possum (Tarsipes rostratus) J. Mammal. 1995;76:862–866. doi:10.2307/1382755
  • Paddle R. Cambridge University Press; Cambridge, UK: 2000. The last Tasmanian tiger: the history and extinction of the thylacine.
  • Paddle R. Cambridge University Press; Cambridge, UK: 2002. The last Tasmanian tiger. The history and extinction of the thylacine.
  • Preuschoft H, Witzel U. A biomechanical approach to craniofacial shape in primates, using FESA. Ann. Anat. 2004;186:397–404. [PubMed]
  • Preuschoft H, Witzel U. Functional shape of the skull in vertebrates: which forces determine skull morphology in lower primates and ancestral synapsids? Anat. Rec. A. 2005;283:402–413. doi:10.1002/ar.a.20176 [PubMed]
  • Rayfield E.J. Cranial mechanics and feeding in Tyrannosaurus rex. Proc. R. Soc. B. 2004;271:1451–1459. doi:10.1098/rspb.2004.2755 [PMC free article] [PubMed]
  • Rayfield E.J. Finite element analysis and understanding the biomechanics and evolution of living and fossil organisms. Annu. Rev. Earth Planet. Sci. 2007;35:541–576. doi:10.1146/
  • Rayfield E.J, Norman D.B, Horner C.C, Horner J.R, Smith P.M, Thomason J.J, Upchurch P. Cranial design and function in a large theropod dinosaur. Nature. 2001;409:1033–1037. doi:10.1038/35059070 [PubMed]
  • Rho J.Y, Hobatho M.C, Ashman R.B. Relations of mechanical properties to density and CT numbers in human bone. Med. Eng. Physiol. 1995;17:347–355. doi:10.1016/1350-4533(95)97314-F [PubMed]
  • Schneider U, Pedroni E, Lomax A. The calibration of CT Houndsfield units for radiotherapy treatment planning. Phys. Med. Biol. 1996;41:111–124. doi:10.1088/0031-9155/41/1/009 [PubMed]
  • Snively E, Russell A. The tyrannosaurid metatarsus: bone strain and inferred ligament function. Senckenbergiana Lethaea. 2002;82:35–42.
  • Stahler D.R, Smith D.W, Guernsey D.S. Foraging and feeding ecology of the gray wolf (Canis lupus): lessons from Yellowstone National Park, Wyoming, USA. J. Nutr. 2006;136(Suppl.):1923S–1926S. [PubMed]
  • Strait D.S, Wang Q, Dechow P.C, Ross C.F, Richmond B.G, Spencer M.A, Patel B.A. Modeling elastic properties in finite-element analysis: how much precision is needed to produce an accurate model? Anat. Rec. A. 2005;283:275–287. doi:10.1002/ar.a.20172 [PubMed]
  • Thomason J.J. Cranial strength in relation to estimated biting forces in some mammals. Can. J. Zool. 1991;69:2326–2333.
  • Thomason J.J. To what extent can the mechanical environment of a bone be inferred from its internal architecture. In: Thomason J.J, editor. Functional morphology in vertebrate paleontology. Cambridge University Press; Cambridge, UK: 1995. pp. 249–263.
  • Thompson P.C. The behavioral ecology of dingoes in north-western Australia IV: social and spatial organisation and movement. Wildl. Res. 1992;19:543–563. doi:10.1071/WR9920543
  • Tizzard A, Horesh L, Yerworth R.J, Holder D.S, Bayford R.H. Generating accurate finite element meshes for the forward model of the human head in EIT. Physiol. Measure. 2005;26:S251–S253. doi:10.1088/0967-3334/26/2/024 [PubMed]
  • Turnbull W.D. Mammalian masticatory apparatus. Fieldiana. Geol. 1970;18:149–356.
  • Valero A, Schaffner C.M, Vick L.G, Aureli F, Ramos-Fernandez G. Intragroup lethal aggression in wild spider monkeys. Am. J. Primatol. 2006;68:732–737. doi:10.1002/ajp.20263 [PubMed]
  • Van Valkenburgh B. Skeletal and dental predictors of body mass in carnivores. In: Damuth J, MacFadden B.J, editors. Body size in mammalian paleobiology: estimation and biological applications. Cambridge University Press; Cambridge, UK: 1990. pp. 181–205.
  • Van Valkenburgh B, Koepfli K.P. Cranial and dental adaptations to predation in canids. Symp. Zool. Soc. Lond. 1993;65:15–37.
  • Werdelin L. Comparison of skull shape in marsupial and placental carnivores. Aust. J. Zool. 1986;34:109–117. doi:10.1071/ZO9860109
  • Wroe S. Australian marsupial carnivores: an overview of recent advances in palaeontology. In: Jones M, Dickman C, Archer M, editors. Predators with pouches: the biology of carnivorous marsupials. CSIRO Publishing; Melbourne, Australia: 2003. pp. 102–123.
  • Wroe S, Milne N. Convergence and remarkable constraint in the evolution of mammalian carnivore skull shape. Evolution. 2007;61:1251–1260. doi:10.1111/j.1558-5646.2007.00101.x [PubMed]
  • Wroe S, Myers T, Seebacher F, Kear B, Gillespie A, Crowther M, Salisbury S. An alternative method for predicting body-mass: the case of the marsupial lion. Paleobiology. 2003;29:403–411. doi:10.1666/0094-8373(2003)029<0403:AAMFPB>2.0.CO;2
  • Wroe S, Argot C, Dickman C. On the rarity of big fierce carnivores and primacy of isolation and area: tracking large mammalian carnivore diversity on two isolated continents. Proc. R. Soc. B. 2004;271:1203–1211. doi:10.1098/rspb.2004.2694 [PMC free article] [PubMed]
  • Wroe S, McHenry C, Thomason J. Bite club: comparative bite force in big biting mammals and the prediction of predatory behaviour in fossil taxa. Proc. R. Soc. B. 2005;272:619–625. doi:10.1098/rspb.2004.2986 [PMC free article] [PubMed]
  • Wroe, S., Moreno, K., Clausen, P., McHenry, C. & Curnoe, D. In press. High resolution computer simulation of hominid cranial mechanics. Anat. Rec. A. [PubMed]

Articles from Proceedings of the Royal Society B: Biological Sciences are provided here courtesy of The Royal Society