Introduction

The body mass of mammals is affected by the interaction of genetic and environmental factors, with a series of genes and complex signal pathways in the body regulating the size and proliferation of cells, affecting the size of organs and tissues and thus influencing body mass (Galloni & Edgar 1999, Longo et al. 2004). The study of phenotypic differentiation effectively describes phylogenetic and taxonomic patterns (Boussange & Pellissier 2022). Morphological characteristics are closely related to habitat characteristics; habitat differences drive morphological differentiation, and this differentiation underpins intraspecific and interspecific differences (Cardini 2016, Shakya et al. 2022). The Hengduan Mountain region is a typical north-south oriented mountain range in China, with distinctive geological landforms and rich biodiversity (Wang et al. 2022). Due to its topology and geographical location, it has great significance in many disciplines, such as biology, geography, geology and hydrology, and represents one of the biodiversity hotspots of the world (Rana et al. 2022). The Yunnan red-backed vole, Eothenomys miletus, is an endemic species in the Hengduan Mountain region, where it lives in shallow tunnels. The Hengduan Mountain region has a changeable climate, rich vegetation and complex terrain, which provides conditions for the phenotypic differentiation and variation in body mass of E. miletus (Zhu et al. 2008). Previous studies showed that E. miletus inhabiting different regions of Hengduan Mountain were adapted to the different environmental conditions in the region through variation in body mass, liver mass, digestive tract mass and morphology (Zhang et al. 2018).

Fig. 1.

Chord diagram of body mass, body length and bone length.

Bergmann's and Allen's Laws explain the phenotypic differentiation of thermoregulating animals in adapting to cold and hot environments. Bergmann's Law predicts that thermoregulating animals at high latitudes and in low-temperature environments will have larger body sizes and a reduced surface area, which is conducive to cold resistance. In contrast, thermoregulating animals at low latitudes and in high-temperature environments are predicted to have smaller body sizes and a relatively larger surface area conducive to heat dissipation (Bergmann 1847). Furthermore, as a derivation of Bergmann's Law, Allen's Law predicts that the limbs, tails or ears of thermoregulating animals will be larger as an additional adaptation to temperature regulation in warm climates (Allen 1877). Previous studies showed phenotypic differences in body indices and skull morphology in E. miletus from five regions in the Hengduan Mountain region. Variation in body size and skull characteristics in E. miletus was not consistent with Bergmann's Law, but the variation in its appendages conformed to Allen's Law (Ren et al. 2020a, b). However, the phenotypic differentiation in E. miletus mainly focused on the study of its skull morphology. At the same time, the morphological differentiation of the whole body skeleton will also affect the body mass of the entire organism. Some studies have shown that the bone morphology of Australian marsupials was significantly related to body mass, reflecting allometric growth (Martin et al. 2019). In general, with relatively long bones, the insertion area of muscles was relatively large, both bone weight and muscle volume affected the weight of individuals, and stronger individuals had stronger limbs (Etienne et al. 2020, Zhou & Lui 2020). On this basis, the present study measured and analysed the whole-body bone indices in E. miletus to explore the influence of bone morphology on body shape and to test whether bone morphology indices conformed with Bergmann's Law in E. miletus.

Fig. 2.

Principal Component Analysis of body mass, body length and bone length.

Material and Methods

Bone data measurement and calculation

Measurements were taken of cranial length (CL), spinal length (SL), cervical vertebra length (CVL), thoracic vertebra length (TVL), lumbar vertebra length (LL), sacral vertebra length (SVL), caudal vertebra length (CaVL), sternal length (StL), scapula length (ScL), scapula width (SW), pelvic girdle length (PGL), pelvic girdle width (PGW), humeral length (HL), radial length (RL), ulnar length (UL), femoral length (FL), tibial length (TL), fibular length (FiL), and ulnar olecranon length (UOL) (accurate to 0.01 cm); radial and ulnar middle width (URMW), humeral middle width (HMW), femoral middle width (FMW) and tibial and fibular middle width (TFMW) (Wi, accurate to 0.01 cm); ulnar and radial length (URL), humeral length, femoral length, tibial and fibular length (TFL) (Li, accurate to 0.01 cm); ulnar and radial mass, humeral mass, femoral mass, tibial and fibular mass (mi, accurate to 0.0001 g). Because the epiphysis of the two segments of the radius and ulna is conglutinated, when measuring the middle width, mass and length, it is treated as a single bone. The shape of the upper part of the tibia and fibula changes irregularly. Therefore, when measuring the thickness of the middle part, the two bone unions at the lower end are taken. Also, the shape of the upper part of the tibia and fibula changes irregularly. Therefore when measuring the middle width, the two bone unions at the lower end are taken. Based on these measurements, the following indices were calculated: 1) olecranon index: OI = ulnar olecranon length/ulna length (the olecranon is the insertion area of the triceps brachii, and the triceps brachii is the extensor of the upper arm. A high olecranon index means a strong stretching force of the forelimbs); 2) robust index: RI = W_i/L_i (the robust index represents the climbing and running ability of animals to a certain extent); 3) Weight percentage: D_i = m_i/∑⁴ _i = ₁ m_i × 100% (Lin et al. 2007).

Table 1.

Main condition for five populations of Eothenomys miletus.

Statistical analysis

Differences in body mass and morphological indicators between the different sexes of E. miletus in the same region were not significant, so all data were pooled for analysis. The SPSS software package (ver. 26.0) was used to conduct ANOVA for body mass and body length, and one-way ANCOVA was conducted for 18 bone morphological indices, including cranial length and spine length, with body length as the covariate. Principal Component Analysis (PCA) and cluster analysis based on 20 groups of sample data were undertaken. Spearman's correlation was used to test the correlation of environmental variables with skeletal morphological indices, based on predictions of Bergmann's Law. Linear regression was used to calculate the relationship between spine length and 16 bone morphological indices, including the length of cervical vertebra and thoracic vertebra, as well as the relationship between total bone mass and body mass. Multiple linear regressions were used to examine the relationship of altitude, annual average temperature and temperature to bone morphological indices. Finally, regression coefficients were used to measure the influence of environmental factors on bone morphological indices. Kruskal-Wallis rank sum test and Dunn's test were used as post-hoc tests to identify differences in URMW, HMW, FMW, TTMW, URL, TFL, ulnar and radial sturdiness (URI), humeral sturdiness (HRI), femoral sturdiness (FRI), tibia and fibula sturdiness (TFRI), UOL, OI.

Fig. 3.

Cluster analysis of body mass, body length and bone length.

Fig. 4.

Linear regression analysis of spine length and A) cervical vertebra length; B) thoracic vertebra length; C) lumbar length; D) sacral vertebrae length; E) caudal vertebra length; F) sternal length; G) scapular length; H) scapular width; I) pelvic girdle length; J) pelvic girdle width; K) humeral length; L) radial length; M) ulnar length; N) femoral length; O) tibial length; P) fibular length.

Fig. 5.

Linear regression analysis of total bone mass and body mass.

Results

Cluster analysis

Although there were LJ individuals between DQ and XGLL, and XGLL individuals between DL and LJ, it may be due to the differences in wild individuals. In general, E. miletus from DL, JC and LJ at low latitude and high temperature clustered together, while E. miletus from XGLL and DQ at high latitudes and low temperatures clustered together (Fig. 3).

Fig. 6.

Correlation analysis between body mass, body length, bone length and climate (*P < 0.05, **P < 0.01).

Linear regression analysis of spine length and other bone morphological indices

The length of the spine was highly significantly and positively correlated with the length of the cervical vertebra (Fig. 4A), thoracic vertebra (Fig. 4B), lumbar vertebra (Fig. 4C), sacral vertebra (Fig. 4D), caudal vertebrae (Fig. 4E), sternum (Fig. 4F), scapular (Fig. 4G), pelvic girdle (Fig. 4I), humerus (Fig. 4K), radius (Fig. 4L), ulna (Fig. 4M), femur (Fig. 4N), tibia (Fig. 4O), fibula (Fig. 4P) and scapular width (Fig. 4H), pelvic girdle width (Fig. 4J), respectively.

Fig. 7.

Boxplots of limb bone indices (*P < 0.05, **P < 0.01).

Discussion

Species living in a specific habitat will adapt to the environment through the differentiation of morphological traits, thereby maximising reproductive success and survival (Zhu et al. 2010). Body mass is a fundamental index of animal body size but is affected by seasonal patterns and food availability and can vary widely. In contrast, bone is a more fixed character than body mass (Daniel et al. 2019). Presently, research on the morphological differentiation of small mammals mainly focuses on the phylogeny and classification of species through the characteristics of skulls (Zhu et al. 2015, Li et al. 2020, Fan et al. 2022). For example, it was shown that the skull morphology of Myospalax baileyi in different regions had apparent geographical differentiation, which was affected by habitat isolation and altitude factors (Su et al. 2018). There were significant differences in the size and shape of skulls among different geographic populations of the Hipposideros armiger, and regression analysis showed that the geographic changes in the shape of skulls were related to climate factors (Hou et al. 2017). Population differentiation of the skull morphology of Shaanxi Lepus capensis may be related to different selection pressures resulting from environmental differences in different regions (Li et al. 2011). In the present study, the body mass and body length of E. miletus in DL, JC and LJ were larger than those in XGLL and DQ. PCA and cluster analysis showed that E. miletus in DL, JC and LJ clustered together similarly in XGLL and DQ. Compared with XGLL and DQ, DL, JC, and LJ are at a lower latitude, higher temperature and with more abundant food resources, which may be one of the reasons for the body mass gain of E. miletus in the three regions. Competition with other species may also play a role. During sampling in DL, JC and LJ, many Apodemus were encountered. Both E. miletus and Apodemus eat plant buds, plant stems and seeds with high water content (Luo et al. 2000), and E. miletus may experience selection for a larger body size to enhance its competitiveness with Apodemus. An increase in body size might also enhance running speed and predator avoidance.

Fig. 8.

Weight percentage of forelimb bone and hindlimb bone.

Previous studies found that in the Hengduan Mountain region, E. miletus had phenotypic differentiation in body indices and skull morphology, which may be affected by altitude, temperature and food (Ren et al. 2020b). The current study showed that the cervical vertebra length and scapular length differed significantly, as did the scapular width, humeral length, radial length, ulnar length, and femoral length. Sternal length in JC was smaller than that in XGLL, and the lumbar length was smaller than that in XGLL and DQ, the length of the other trunk bones and limb bones were larger in DL, JC and LJ than that in XGLL and DQ. The length of the spine is directly related to body length of the animals. Although there was no difference in the length of the spine, cervical vertebra length, thoracic vertebra length, lumbar length, sacral vertebrae length and caudal vertebra length in DL, JC and LJ were larger than those in XGLL and DQ. A longer spine means a larger muscle insertion area, resulting in greater body length and bone mass (Amson & Bibi 2021), which corresponds to the body mass of E. miletus in the five regions. Linear regression of E. miletus in the five regions showed that the total bone mass and body mass had a significant positive correlation; greater body mass is related to greater total bone mass. The longer the spine, the larger the chest cavity formed with the ribs and sternum, the larger the body size, and the higher the upper limit of body mass (Amson & Bibi 2021). Notably, the length and width of the scapula in DL, JC and LJ were larger than those in XGLL and DQ. The scapula provides a larger attachment surface for the muscles involved in the forelimb movement; a larger attachment surface means more muscles, which also affects body mass (Young et al. 2019).

Fig. 9.

Correlation analysis between robustness index of limb bone and climate (**P < 0.01).

Correlation analysis showed that the body mass, body length and bone morphological indices were significantly negatively correlated with altitude and latitude and were significantly positively correlated with the annual average temperature, which means that E. miletus in the Hengduan Mountain region has greater body mass and body length at low latitudes and in a high-temperature environment, which was not consistent with the Bergman's Law.

Fig. 10.

The standard coefficients of multiple linear regression analysis between body mass, body length, bone morphology indices and latitude, altitude, annual average temperature.

The appearance and structure of organs are closely related to body proportions and functional differences, especially concerning locomotor behaviour (Maher et al. 2022). The robustness index of limb bones is an index of the ability of animals to climb, run, dig and forage (Assif & ChirChir 2022). The present results showed significant differences between the five regions in the robustness index of the humerus and the robustness index of the femur; XGLL and DQ were greater than those in DL, JC and LJ. From the point of view of sampling sites, those in DL, JC and LJ comprised almost flat farmland and dams, so the process of obtaining food for E. miletus may not involve climbing. However, the two sampling sites in XGLL and DQ were mostly steep hillsides, and the E. miletus living in these two regions may be required to actively climb to forage and avoid natural enemies, resulting in a stronger humerus and femur.

Weible's symmetrical morphological formation hypothesis states that the structure of organs and tissues to enable animals to complete specific functions is optimised, such that investment in the distribution of limb bone material reflects adaptive function (Weibel 1991). The relative weight of the hindlimb bone in E. miletus in the five regions was greater than that of the forelimb bone. Eothenomys miletus lives in shallow tunnels and is better at running and jumping than digging, which requires more robust hindlimb development. In contrast, the activities of M. baileyi, which are typical of subterranean rodents, and include foraging, migration and mate finding, are associated with active burrowing activity (Zhang et al. 2020). A previous study showed that the weight percentage of the forelimb of M. baileyi was 55.2% (Lin et al. 2007). Linear regression also showed that the length of each part of the trunk and limb bones was positively associated with the length of the spine, and spine length inevitably leads to increased body mass. Therefore, we speculated that the different habitat preferences and activities of E. miletus and M. baileyi would be reflected by their contrasting bone morphology. Notably, standard coefficients of multiple linear regression analysis showed that, compared with altitude, the body mass, body length, trunk bones length, limb bones length and robustness index of the E. miletus were more significantly affected by the annual average temperature and latitude, which may be related to adaptations to the harsh conditions associated with the high altitude and temperature changes in the Hengduan Mountain region.

In conclusion, the present study showed that the body mass and body length of E. miletus in the five regions of the Hengduan Mountains varied, with clear differentiation in bone morphological indices. Greater bone length and mass resulted in an increased body mass in E. miletus. The change in bone length does not conform to Bergmann's Law and is associated with altitude, average annual temperature and latitude. Differences in diet and habitat appear to be the drivers of bone morphology variation in E. miletus.