Covariation between forelimb muscle anatomy and bone shape in an Australian scratch‐digging marsupial: Comparison of morphometric methods

Abstract

The close association between muscle and bone is broadly intuitive; however, details of the covariation between the two has not been comprehensively studied. Without quantitative understanding of how muscle anatomy influences bone shape, it is difficult to draw conclusions of the significance of many morphological traits of the skeleton. In this study, we investigated these relationships in the Quenda (Isoodon fusciventer), a scratchdigging marsupial. We quantified the relationships between forelimb muscle anatomy and bone shape for animals representing a range of body masses (124-1,952 g) using two-block partial least square analyses. Muscle anatomy was quantified as muscle mass and physiological cross-sectional area (PCSA), and we used two morphometric methods to characterize bone shape: seven indices of linear bone proportions, and landmarks analysis. Bone shape was significantly correlated with body mass, reflecting allometric bone growth. Of the seven bone indices, only shoulder moment index (SMI) and ulna robustness index (URI) showed a significant covariation with muscle anatomy. Stronger relationships between muscle anatomy and forelimb bone shape were found using the landmark coordinates: muscle mass and PCSA were correlated with the geometric shape of the scapula, humerus, and third metacarpal, but to a lesser extent with shape of the ulna. Overall, our data show that landmark coordinates are more sensitive than bone indices to capturing shape changes evident throughout ontogeny, and is therefore a more appropriate method to investigate covariation with forelimb muscle anatomy.Single-species studies investigating ontogeny require refined methods to accurately develop understanding of the important relationships between muscle force generation and bone shape remodeling. Landmark analyses provide such a method. K E Y W O R D SBiopedturbation, humerus, scapula, third metacarpal, two-block partial least squares, ulna

How to build a dinosaur: Musculoskeletal modeling and simulation of locomotor biomechanics in extinct animals

“…Thus, we argue that the best data-driven method to muscle architecture estimation is a “total evidence” one. To this end, further research on extant species (archosaur and non-archosaur) will help refine general principles relating muscular anatomy to function, such as how muscle attachment size and morphology correlate to architecture (Martin et al 2019; Fahn-Lai et al 2020) or how long muscle fibers need to be to be able to effectively execute movement over a range of postures (Sellers et al 2013).…”

“…It was noted earlier how both m musc and ℓ o are crucial for better modeling muscle function, and therefore the more accurate determination of their values in extinct taxa represents a key challenge for future work. For instance, the study of how m musc relates to actual attachment area, type of osteological correlate, and muscle identity may reveal relationships that can be used to produce more anatomically grounded estimates in extinct taxa (Martin et al 2019; Fahn-Lai et al 2020). Similarly, the accurate estimation of ℓ o poses another key challenge.…”

Broad similarities in shoulder muscle architecture and organization across two amniotes: implications for reconstructing non-mammalian synapsids

“…Moreover, mm. infraspinatus and supraspinatus PCSAs have been shown to covary with the size of their areas of origin in the short-nosed bandicoot Isoodon fusciventer, a marsupial with pectoral skeletal anatomy comparable to Didelphis (Martin et al, 2019). Considering mm.…”

Effect of mass and habitat on the shape of limb long bones: A morpho‐functional investigation on Bovidae (Mammalia: Cetartiodactyla)

“…Additionally, muscle insertion areas will become larger, presumably accommodating for stronger muscles (see e.g. Doube et al, 2009; Mallet et al, 2019; Martin et al, 2019; Walmsley et al, 2012). This is of course also influenced by phylogenetical factors (Biewener & Patek, 2018).…”