Literature DB >> 28568619

SELECTION FOR NATIVE CHARACTERS IN HYBRIDS BETWEEN TWO LOCALLY ADAPTED PLANT SUBSPECIES.

Eric S Nagy1.   

Abstract

Gene exchange between locally adapted plant populations can have significant evolutionary consequences, including changes in genetic diversity, introduction of adaptive or maladaptive traits, disruptive of coadaptive gene complexes, and the creation of new ecotypes or even species. The potential for introgression between divergent populations will depend on the strength of selection against nonnative characters. Morphologically variable F2 hybrids of two Gilia capitata subspecies were used to evaluate the strength of phenotypic selection and the response to selection in the home habitats of each subspecies. At both sites, traits diagnostic of the subspecies were subject to significant phenotypic selection, probably mediated by direct selection on unmeasured correlated characters. Phenotypic selection favored native morphologies in all but a single case; leaf shape of one subspecies was favored in both habitats. The strength of selection varied between sites, with one site selecting more strongly against nonnative characters. Offspring of the F2 hybrids showed a significant evolutionary response to selection when grown in a common environment. Evolution was in the direction of similarity with the subspecies native to the site where selection was imposed. This result reveals that native character states are adaptive and suggests that selection will maintain native morphologies even after a substantial influx of genes from an ecologically and morphologically distinct, and locally adapted subspecies. © 1997 The Society for the Study of Evolution.

Entities:  

Keywords:  Evolution; Gilia; geographic divergence; hybridization; local adaptation; natural selection; phenotypic selection; reciprocal transplant; response

Year:  1997        PMID: 28568619     DOI: 10.1111/j.1558-5646.1997.tb01470.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


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