Using path analysis to measure natural selection

We expand current methods for calculating selection coefficients using path analysis and demonstrate how to analyse nonlinear selection. While this in corporation is a straightforward extension of current procedures, the rules for combining these traits to calculate selection coefficients can be comp lex. We demonstrate our method with an analysis of selection in an experime ntal population of Arabidopsis thaliana consisting of 289 individuals. Mult iple regression analyses found positive directional selection and positive nonlinear selection only for inflorescence height. In contrast, the path an alyses also revealed positive directional selection for number of rosette l eaves and positive nonlinear selection for leaf number and time of inflores cence initiation. These changes in conclusions came about because indirect selection was converted into direct selection with the change in causal str ucture. Path analysis has great promise for improving our understanding of natural selection but must be used with caution since coefficient estimates depend on the assumed causal structure.