Tail length evolution in deer mice: linking morphology, behavior and function

Determining how variation in morphology affects animal performance (and ultimately fitness) is key to understanding the complete process of evolutionary adaptation. Long tails have evolved many times in arboreal and semi-arboreal rodents; in deer mice, long tails have evolved repeatedly in populations occupying forested habit even within a single species (Peromyscus maniculatus). Here we use a combination of functional modeling, laboratory studies, and museum records to test hypotheses about the function of tail-length variation in deer mice. First, we use computational models, informed by museum records documenting natural variation in tail length, to test whether differences in tail morphology between forest and prairie subspecies can influence performance in behavioral contexts relevant for tail use. We find that the deer mouse tail plays little role in statically adjusting center of mass or in correcting body pitch and yaw, but rather it can affect body roll during arboreal locomotion. In this context, we find that even intraspecific tail-length variation could result in substantial differences in how much body rotation results from equivalent tail motions (i.e., tail effectiveness), but the relationship between commonly-used metrics of tail-length variation and effectiveness is non-linear. We further test whether caudal vertebra length, number, and shape are associated with differences in how much the tail can bend to curve around narrow substrates (i.e., tail curvature) and find that, as predicted, the shape of the caudal vertebrae is associated with intervertebral bending angle across taxa. However, although forest and prairie mice typically differ in both the length and number of caudal vertebrae, we do not find evidence that this pattern is the result of a functional trade-off related to tail curvature. Together, these results highlight how even simple models can both generate and exclude hypotheses about the functional consequences of trait variation for organismal-level performance.