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Data from: Mechanosensation is evolutionarily tuned to locomotor mechanics

Cite this dataset

Aiello, Brett R.; Westneat, Mark W.; Hale, Melina E. (2018). Data from: Mechanosensation is evolutionarily tuned to locomotor mechanics [Dataset]. Dryad. https://doi.org/10.5061/dryad.0463n

Abstract

The biomechanics of animal limbs has evolved to meet the functional demands for movement associated with different behaviors and environments. Effective movement relies not only on limb mechanics but also on appropriate mechanosensory feedback. By comparing sensory ability and mechanics within a phylogenetic framework, we show that peripheral mechanosensation has evolved with limb biomechanics, evolutionarily tuning the neuromechanical system to its functional demands. We examined sensory physiology and mechanics of the pectoral fins, forelimb homologs, in the fish family Labridae. Labrid fishes exhibit extraordinary morphological and behavioral diversity and employ pectoral fin-based propulsion with fins ranging in shape from high aspect ratio (AR) wing-like fins to low AR paddle-like fins. Phylogenetic character analysis demonstrates that high AR fins evolved independently multiple times in this group. Four pairs of species were examined; each included a pleseiomorphic low AR and a high AR species. Within each species pair, the high AR species demonstrated significantly stiffer fin rays in comparison to the low AR species. Afferent sensory nerve activity was recorded during fin ray bending. In all cases, afferents of stiffer fins were more sensitive at lower displacement amplitudes demonstrating mechanosensory tuning to fin mechanics, and a consistent pattern of correlated evolution. We suggest that this is a clear example of parallel evolution in a complex neuromechanical system, with a strong link between multiple phenotypic characters: pectoral fin shape, swimming behavior, fin ray stiffness, and mechanosensory sensitivity.

Usage notes

Funding

National Science Foundation, Award: DGE-0903637, IOS-1425049, DEB-1541547, IOS-1257886