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Living Boundaries: Tracking Weed Seed Movement With Nondormant Seed

Published online by Cambridge University Press:  20 January 2017

Adam S. Davis*
Affiliation:
United States Department of Agriculture, Agricultural Research Service, Invasive Weed Management Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
Edward C. Luschei
Affiliation:
Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI 53706
*
Corresponding author's E-mail: adam.davis@ars.usda.gov

Abstract

Synthetic seed banks are a useful tool for tracking how weed populations change over time. By sowing a known number of seeds of a given species within a quadrat with defined boundaries, an investigator can measure the number remaining and thereby calculate demographic rates (e.g., mortality). The alternative is to use in situ seeds and estimate their initial population density via sampling. To make a synthetic seed bank approach useful within an agricultural system subjected to soil disturbances such as tillage, one would need a way to account for seeds leaving the initial quadrat (i.e., a way to follow how the area encompassing the sown seeds changes over time). Without accounting for the change in location/extent of the synthetic seed bank, any field operation moving soil will create additional uncertainty in population size. Depending on the “aggressiveness” of specific field operations and the initial size of the quadrat, this effect might be negligible or so large as to be intractable. Here, we describe a method for following a synthetic seed bank over time using a “living boundary” of nondormant seeds, which effectively play the role of tracers used in the study of dynamics in other scientific disciplines. Study quadrats in East Lansing, MI, and Arlington, WI, were sown with giant foxtail and velvetleaf at a rate of 2,000 seeds m−2. The study quadrats were marked on the perimeter and diagonals using nondormant seeds of three marker species: kale, radish, and rye. The areas were then subjected to tillage and planting operations. Spatial coordinates of seedling locations for the marker and weed species were obtained through digital image processing. A nonparametric comparison of the spatial displacement of marker and weed species indicated that their empirical spatial distributions did not differ. The marker species quadrats described by the 50th, 90th, and 99th quantiles of movement contained all velvetleaf seedlings in Wisconsin, all velvetleaf seedlings in Michigan, and all giant foxtail seedlings in Michigan, respectively. The results suggest a simple rule for applying the method to field demography studies: after the original quadrat is deformed and seedlings have emerged, flag the polygon containing all marker seedlings to obtain the expanded quadrat containing the study weed population.

Type
Weed Biology and Ecology
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Ambrosio, L., Dorado, J., and del Monte, J. P. 1997. Assessment of the sample size to estimate the weed seedbank in soil. Weed Res. 37:129137.CrossRefGoogle Scholar
[AOSA] Association of Official Seed Analysts 2000. Tetrazolium Testing Handbook. Contribution No. 29 to the Handbook on Seed Testing. Stillwater, OK AOSA. 302.Google Scholar
Buhler, D. D. and Hoffman, M. L. 1999. Andersen's Guide to Practical Methods of Propagating Weeds and Other Plants. Lawrence, KS Allen Press. 248.Google Scholar
Cardina, J. and Sparrow, D. H. 1996. A comparison of methods to predict weed seedling populations from the soil seedbank. Weed Sci. 44:4651.Google Scholar
Conover, W. J. 1980. Practical Nonparametric Statistics. 2nd ed. New York John Wiley & Sons. 493.Google Scholar
Davis, A. S., Dixon, P. M., and Liebman, M. 2004. Using matrix models to determine cropping system effects on annual weed demography. Ecol. Appl. 14:655668.CrossRefGoogle Scholar
Gotelli, N. J. and Ellison, A. M. 2004. A Primer of Ecological Statistics. Sunderland, MA Sinauer Associates. 150.Google Scholar
Mohler, C. L., Frisch, J. C., and McCulloch, C. E. 2006. Vertical movement of weed seed surrogates by tillage implements and natural processes. Soil Tillage Res. 86:110122.Google Scholar
Telewski, F. W. and Zeevaart, J. A. D. 2002. The 120-yr period for Dr. Beal's seed viability experiment. Am. J. Bot. 89:12851288.CrossRefGoogle ScholarPubMed
Teo-Sherrell, C. P. A., Mortensen, D. A., and Keaton, M. E. 1996. Fates of weed seeds in soil: a seeded core method of study. J. Appl. Ecol. 33:11071113.CrossRefGoogle Scholar
Westerman, P. R., Liebman, M., Menalled, F. D., Heggenstaller, A. H., Hartzler, R. G., and Dixon, P. M. 2005. Are many little hammers effective? Velvetleaf population dynamics in two- and four-year crop rotation systems. Weed Sci. 53:382392.Google Scholar