Cranial biomechanics in squirrels: adaptation to feeding


In the last century, the population of red squirrels (Sciurus vulgaris) in the United Kingdom has reduced significantly due to the introduction of grey squirrels (Sciurus carolinensis)[1]. The increasing threat of extinction of red squirrels has been attributed to many factors, such as disease and starvation[2], with dietary competition between red and grey squirrels being important in some habitats[3,4]. Consequently, it is of interest to determine the extent to which red and grey squirrels can coexist in the same habitat, and how forest management can assist in red squirrel conservation[5].

Biomechanical analysis of the cranio-cervical system has the potential to assist in the conservation of red squirrel populations. For example, grey squirrels are known to have larger skulls (and thus larger masticatory muscles), so may be able to process foods with a higher mechanical advantage when compared to red squirrels. The computational methods of multibody dynamics and finite element analysis (FEA) are currently being employed to investigate the extent to which cranial morphology impacts feeding biomechanics in squirrels, therefore evaluating the role that diet plays in determining if red squirrels can persist in the presence of invasive grey squirrels.

Comparison between the feeding biomechanics of red and grey squirrels also raises an interest into whether the hard and soft material properties in the skull vary between the two species. Bone stiffness is often measured in skulls, and is known to vary throughout the structure[6]. This variation has been linked to numerous factors although mechanical loading, particularly that generated during feeding (i.e. joint, muscle and bite forces), is likely to be very important. Therefore, this PhD project aims to investigate the intra- and inter-specific variation in hard (bone) and soft (sutures) tissue stiffness between red and grey squirrels. In addition, this project will also examine how these material properties influence the ability of the skull to withstand the mechanical forces generated during feeding; for example, does a heterogeneous bone stiffness lower or produce a more even mechanical strain distribution across the skull? This will provide valuable information as to the whether the red and grey squirrel skull are adapted to similar mechanical forces.


This PhD will combine experimental measurements of hard (bone) and soft (suture) material properties with the computational technique of FEA:

  1. Use nano-indentation to measure the stiffness of bone (both cortical and trabecular), teeth and sutures in the red and grey squirrel. This will measure stiffness at various locations throughout the skull, and will test the stiffness in different directions.
  2. Use statistical methods to perform: i) intra-species comparison to determine the variation in stiffness to due location in the skull, direction, habitats (urban and rural); ii) inter-species variation in material stiffnesses.
  3. Use FEA to examine how the variation in material stiffness promotes an efficient force transfer throughout the skull, when simulating biting a range of foods (hard and soft). This will determine the ability of the skull to dissipate mechanical forces via comparing simulations with a homogenous stiffness throughout the whole skull (as is often the case with such modelling), to those which present a more heterogeneous stiffness (as measured in 1).

The outcome of this PhD project will provide quantitative data demonstrating the extent to which red and grey squirrel skulls are adapted to the mechanical forces generated during feeding, and if one species is more favourable in terms of structural optimisation. This will provide a valuable insight into the ability of both species to process a range of foods and thus help to inform conversation management of red squirrels. In addition, successful application of the computational modelling in this manner has use in palaeobiology to study fossil organisms, where the variation in material properties is unknown, therefore the development of FEA models is obviously extremely challenging.


  1. Gurnell J, Pepper H (1993) Mammal Rev 25 : 125-136 ; 2. LaRose JP et al. (2010) Vet Rec 167 : 297-302 ; 3. Wauters LA et al. (2002) Behv Evol Sociobiol 52 : 332-341 ; 4. Kenward RE, Holm JL (1993) Proc R Soc B 251 : 187-194. 5. Bryce J et al. (2002) J Appl Ecol 39 : 875-887 ; 6. Cox PG et al. (2011) J Anat 219 : 696-709.