Tuesday, August 7, 2007

PS 30-84: Why new-fangled ecologists need old-fashioned taxonomy: An example from plant population ecology with reference to invasive species

Juliana C. Mulroy, Denison University and Thomas W. Mulroy, Science Applications International Corporation (SAIC), Carpinteria CA.

A number of “firsts” in plant population ecology have been reported for Draba verna L. (Brassicaceae), an Eurasian winter annual sporadically colonizing the temperate zones of both hemispheres.  (Known outside the U.S. as Erophila, recent molecular studies show no justification for the 1825 generic segregation from Draba.)  A seven-year study of population dynamics of E. verna in Poland yielded the first “long-term” study of an annual plant and continues to be highlighted in (especially European) textbooks.  Reanalysis of the Polish data yielded claims of over-compensating density dependence, chaotic population dynamics, and two-year “boom-bust” cycles, all significant concepts in ecology.  Despite the importance of these botanical “firsts,” an extensive and explanatory taxonomic-genetic literature was ignored in interpreting the data. Alexis Jordan’s 19th C work with E. verna, often used to illustrate taxonomic “splitting,” is explained by obligate self-fertilization in the bud, producing local aggregations of interacting individuals that are genetically similar/identical; most variation is found among sites, not within. The implications for population dynamics should be obvious; Jordan’s prominence should make the literature hard to miss.  Although  D. verna is NOT an invasive species, it provides a dramatic example of how relevant literature can be overlooked. Invasive species discussions are replete with examples of nomenclatural and identification problems; we suspect much relevant international literature is being ignored and argue that new online tools such as JSTOR and Babel, along with a solid understanding of traditional taxonomy, can provide even monolingual ecologists with ways to design and prioritize more efficient research.

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