You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Predictable Patterns of Disruptive Selection in Stickleback in Postglacial Lakes
Daniel I. Bolnick and On Lee Lau
The American Naturalist
Vol. 172, No. 1 (July 2008), pp. 1-11
Stable URL: http://www.jstor.org/stable/10.1086/587805
Page Count: 11
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Abstract: Disruptive selection is often assumed to be relatively rare, because it is dynamically unstable and hence should be transient. However, frequency‐dependent interactions such as intraspecific competition may stabilize fitness minima and make disruptive selection more common. Such selection helps explain the maintenance of genetic variation and may even contribute to sympatric speciation. There is thus great interest in determining when and where disruptive selection is most likely. Here, we show that there is a general trend toward weak disruptive selection on trophic morphology in three‐spine stickleback (Gasterosteus aculeatus) in 14 lakes on Vancouver Island. Selection is inferred from the observation that, within a lake, fish with intermediate gill raker morphology exhibited slower growth than phenotypically extreme individuals. Such selection has previously been shown to arise from intraspecific competition for alternate resources. However, not all environments are equally conducive to disruptive selection, which was strongest in intermediate‐sized lakes where both littoral and pelagic prey are roughly balanced. Also, consistent with theory, we find that sexual dimorphism in trophic traits tends to mitigate disruptive selection. These results suggest that it may be possible to anticipate the kinds of environments and populations most likely to experience disruptive selection.
© 2008 by The University of Chicago.