Abstract

A multivariate selection analysis has been used to test the adaptiveness of several Iris pumila leaf traits that display plasticity to natural light conditions. Siblings of a synthetic population comprising 31 families of two populations from contrasting light habitats were grown at an open dune site and in the understory of a Pinus nigra stand in order to score variation in phenotypic expression of six leaf traits: number of senescent leaves, number of live leaves, leaf length, leaf width, leaf angle, and specific leaf area. The ambient light conditions affected the values of all traits studied except for specific leaf area. In accordance to ecophysiological expectations for an adaptive response to light, both leaf length and width were significantly greater while the angle between sequential leaves was significantly smaller in the woodland understory than at the exposed dune site. The relationship between leaf traits and vegetative fitness (total leaf area) differed across light habitats as predicted by functional hypotheses. The standardized linear selection gradient (β′) for leaf length and width were positive in sign in both environments, but their magnitude for leaf length was higher in the shade than under full sunlight. Since plasticity of leaf length in the woodland shade has been recognized as adaptive, fitness cost of producing plastic change in leaf length was assessed. In both of the available methods used, the two-step and the multivariate regression procedures, a rather high negative association between the fitness value and the plasticity of leaf length was obtained, indicating a cost of plasticity. The selection gradient for leaf angle was weak and significant only in the woodland understory. Genetic correlations between trait expressions in contrasting light environments were negative in sign and low in magnitude, implying a significant genetic variation for plasticity in these leaf traits. Furthermore, leaf length and leaf width were found to be genetically positively coupled, which indicates that there is a potential for these two traits to evolve toward their optimal phenotypic values even faster than would be expected if they were genetically independent.

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