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DIFFERING SELECTION ON PLANT PHYSIOLOGICAL TRAITS IN RESPONSE TO ENVIRONMENTAL WATER AVAILABILITY: A TEST OF ADAPTIVE HYPOTHESES
Author(s) -
Dudley Susan A.
Publication year - 1996
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.1996.tb04475.x
Subject(s) - biology , selection (genetic algorithm) , biomass (ecology) , water use efficiency , leaf size , ecology , field experiment , agronomy , botany , photosynthesis , artificial intelligence , computer science
I used phenotypic selection analysis to test the prediction from functional and comparative studies of plants that smaller leaves and more efficient water use are adaptive in drier environments. I measured selection gradients on leaf size and instantaneous water‐use efficiency (a measure of carbon gain per unit water loss) in experimental populations of Cakile edentula var. lacustris placed into wet and dry environments in the field. Linear and nonlinear selection differed significantly between the two environments as predicted. Water‐use efficiency was selected to be higher, and leaf area was selected toward a small intermediate optimum, in the dry environment. There was also significant positive correlational selection on water‐use efficiency and leaf size, suggesting that the optimum leaf size in the dry environment is greater for plants with higher water‐use efficiency. In contrast, neither leaf size nor water‐use efficiency were selected in the wet environment, though larger leaves resulted in greater vegetative biomass. Path analysis of the linear selection gradients found that water‐use efficiency affected plant fitness primarily because it increased vegetative biomass, as suggested by the hypotheses about the function of physiological traits. These results were not only consistent with the functional hypotheses but also with the observed genetic differentiation in water‐use efficiency and leaf size between wet and dry site populations.