Plant Systematics and Evolution

, Volume 239, Issue 1–2, pp 95–112 | Cite as

Genetic variation within and between populations of Potamogeton pusillus agg.

  • Z. Kaplan
  • J. Štěpánek


Patterns of isozyme variation were examined in 17 populations of P. pusillus and P. berchtoldii, together with one population of P. trichoides taken for comparison. Both P. pusillus and P. berchtoldii displayed low levels of variation within populations associated with high levels of interpopulation differentiation. This pattern of partitioning of genetic variation within and between populations is attributed to the founder effect, frequent vegetative propagation by turions, dominant self-fertilization and limited seedling recruitment. The mechanism of pollen transfer was investigated in cultivation. Effective pollination takes place in air above the water surface (autogamy, geitonogamy, anemogamy), on the water surface (epihydrogamy) or below water surface (hydroautogamy). The species are self-compatible. The low level of infra-population variation together with rare occurrence of heterozygotes suggest that selfing is the most frequent mode of pollination, although the protogynous flowers may occasionally permit some cross-pollination. Unique enzyme markers were found for P. pusillus and P. berchtoldii, and also for the single population of P. trichoides. All multienzyme phenotypes were species-specific. Isozyme data support the separate position of P. pusillus and P. berchtoldii. UPGMA dendogram based on enzyme data of 133 plant samples revealed three distinct main enzymatic entities perfectly corresponding to the three morphologically defined species.


Potamogeton pusillus Potamogeton berchtoldii isozymes genetic variation population structure reproductive systems clonal growth 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Wien 2003

Authors and Affiliations

  1. 1.Academy of SciencesInstitute of BotanyPrůhoniceCzech Republic

Personalised recommendations