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Data from: Selective regimes and functional anatomy in the mustelid forelimb: diversification toward specializations for climbing, digging, and swimming

Anatomical traits associated with locomotion often exhibit specializations for ecological niche, suggesting that locomotor specializations may constitute selective regimes acting on limb skeletal traits. To test this, I sampled 42 species of Mustelidae, encompassing climbing, digging, and swimming specialists, and determined whether trait variation reflects locomotor specialization by performing a principal components analysis on 14 forelimb traits. In addition to Brownian motion models, three Ornstein–Uhlenbeck models of selective regimes were applied to PC scores describing trait variation among mustelids: one without a priori defined phenotypic optima, one with optima based upon locomotor habit, and one with a single phenotypic optimum. PC1, which explained 43.8% of trait variance, represented a trade-off in long bone gracility and deltoid ridge length vs. long robustness and olecranon process length and distinguished between climbing specialists and remaining mustelids. PC2, which explained 17.4% of trait variance, primarily distinguished the sea otter from other mustelids. Best fitting trait diversification models are selective regimes differentiating between scansorial and nonscansorial mustelids (PC1) and selective regimes distinguishing the sea otter and steppe polecat from remaining mustelids (PC2). Phylogenetic half-life values relative to branch lengths suggest that, in spite of a strong rate of adaptation, there is still the influence of past trait values. However, simulations of likelihood ratios suggest that the best fitting models are not fully adequate to explain morphological diversification within extant mustelids.

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
8
Access
12
Reuse readiness
0
Engagement
4

Topics

Dataset details

Repository
dryad
Published
December 31, 2016
License
cc-zero
DOI
10.5061/dryad.87pg9

Scored with release 0.9.0

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