Linking Phenotypic Modularity to Directional Selection on Multiple Functional Performances


Meeting Abstract

105-3  Monday, Jan. 6 14:00 – 14:15  Linking Phenotypic Modularity to Directional Selection on Multiple Functional Performances SIMON, MN*; BRANDT, R; KOHLSDORF, T; MARROIG, G; University of Sao Paulo; University of Sao Paulo; University of Sao Paulo; University of Sao Paulo monique.simon@usp.br

A better comprehension of the evolution of complex multivariate phenotypes can be achieved by unravelling the factors that shape trait correlations and modularity. An underexplored question is how directional selection on multiple functions contributes to phenotypic modularity. We hypothesized that combinations of traits describing the pattern of trait modularity would be under directional selection associated with performance, reflecting potential functional trade-offs. We tested this hypothesis using the lizard Tropidurus catalanensis, for which four locomotor performances were measured – climbing, grasping, sprinting and exertion – and a trade-off between grasping and exertion was found. We estimated selection as linear performance gradients of hindlimb traits (bones and muscles) on the four performances, using original traits and eigenvectors of the phenotypic correlation matrix (P-matrix). We expected the same eigenvector to show significant performance gradients for grasping and exertion, but with opposing signs. We found that two eigenvectors of the P-matrix, allometric size and a contrast involving the thigh muscle, are under significant directional selection associated with grasping, sprinting and exertion. Also, allometric size shows opposing signs of performance gradient associated with grasping and exertion, indicating conflicting selection. However, the most apparent modular signal (bone x muscle contrast) was not under significant directional selection, but instead seems to match developmental processes. Our results indicate that directional selection on different performances can reduce or increase phenotypic modularity depending on which combinations of traits affects each performance.

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