On the validity of habitat as a predictor of genetic structure in aquatic systems: a comparative study using California water beetles

Authors

  • A. E. Z SHORT,

    1. Division of Entomology, 1501 Crestline Drive, Suite 140, Natural History Museum, University of Kansas, Lawrence, KS 66049, USA
    2. Department of Ecology & Evolutionary Biology, University of Kansas, Lawrence, KS 66049, USA
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  • M. S. CATERINO

    1. Department of Invertebrate Zoology, Santa Barbara Museum of Natural History, Santa Barbara, CA 93105, USA
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Andrew Short, Tel: +1 785 864 2323; E-mail: aezshort@ku.edu

Abstract

Among freshwater organisms, water flow is frequently considered to be one of the most important environmental variables affecting life-history traits such as dispersal abilities and therefore genetic structure. Recent studies have suggested that habitat type alone as defined by water flow is predictive of genetic population differentiation, while others have advocated against broad generalizations in favour of more conservative, species-specific conclusions. If aquatic habitat type is predictive of population differentiation, then one would expect sympatric taxa that occupy the same aquatic habitat to converge on a similar genetic structure. We tested this prediction by examining the haplotype diversity, phylogeographical concordance, population connectivity and population isolation of three lotic water beetle species in southern California: Anacaena signaticollis, Eubrianax edwardsii and Stictotarsus striatellus. In addition to coarse habitat and geography, we also controlled for the potentially confounding factors of range size, method of dispersal and clade independence. Together, the species spanned extremes of genetic and phylogeographical structure in all measures examined, suggesting that a coarse dichotomy of aquatic habitat type is not predictive of genetic structure. While there is little question that water flow plays a major role in shaping the life-history traits of freshwater organisms, it is perilous to confer predictive properties to an artificially simplistic dichotomy or use it as a surrogate for other unmeasured variables.

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