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Seedbank and Emerged Annual Weed Populations in Cornfields (Zea mays) in Colorado

Published online by Cambridge University Press:  12 June 2017

Edward E. Schweizer*
Affiliation:
U.S. Department of Agriculture, Agricultural Research Service, AERC, Colorado State University, Fort Collins, CO 80523
Philip Westra
Affiliation:
Department of Bioagricultural Sciences and Pest Management
Donald W. Lybecker
Affiliation:
Department of Agricultural and Resource Economics, Colorado State University, Fort Collins, CO 80523
*
Corresponding author e-mail: edwardes@frii.com

Abstract

Fifty irrigated cornfields in five eastern Colorado counties were sampled for their seedbanks and annual weed seedlings and mature populations between 1988 and 1992. Fourteen annual broadleaf species and seven annual grass species were identified in the 50 seedbanks sampled after the fields were tilled in the fall. Redroot pigweed and a mixture of green and yellow foxtail were the weed species encountered most, occurring in 90 and 54% of the fields, respectively. The single-plant populations of broadleaf and grass species in June and September were similar to those observed in the seedbanks. The number of weed species as seeds in the seedbank, June seedlings, and September plants per field ranged from zero to five grass species and zero to eight broadleaf species.

Type
Research
Copyright
Copyright © 1998 by the Weed Science Society of America 

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References

Literature Cited

Benoit, D. L., Kenkel, N. C., and Cavers, P. B. 1989. Factors influencing the precision of soil seed bank estimates. Can. J. Bot. 67:28332840.CrossRefGoogle Scholar
Bigwood, D. W. and Inouye, D. W. 1988. Spatial pattern analysis of seed banks: an improved method and optimized sampling. Ecology 69:497507.Google Scholar
Cardina, J., Regnier, E., and Harrison, K. 1991. Long-term tillage effects on seed banks in three Ohio soils. Weed Sci. 39:186194.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. L. 1995. Analysis of spatial distribution of common lambsquarters (Chenopodium album) in no-till soybean (Glycine max). Weed Sci. 43:258268.CrossRefGoogle Scholar
Cavers, P. B. and Benoit, D. L. 1989. Seed banks in arable land. In Leck, M. A., Parker, V. T., and Simpson, R. L., eds. Ecology of Soil Seed Banks. San Diego, CA: Academic Press, Inc., pp. 309328.Google Scholar
Chauvel, B., Gasquez, J., and Darmency, H. 1989. Changes of weed seed bank parameters according to species, time and environment. Weed Res. 29:213219.Google Scholar
Delorit, R. J. 1970. An illustrated taxonomy manual of weed seeds. Riverfalls, WI: Agronomy Publications. 175 p.Google Scholar
Dessaint, F., Chadoeuf, R., and Barralis, G. 1991. Spatial pattern analysis of weed seeds in the cultivated seed bank. J. Appl. Ecol. 28:721730.Google Scholar
Forcella, F., Wilson, R. G., Renner, K. A., Dekker, J., Harvey, R. G., Alm, D. A., Buhler, D. D., and Cardina, J. 1992. Weed seedbanks of the U.S. corn belt: magnitude, variation, emergence, and application. Weed Sci. 40:636644.Google Scholar
Frick, B. and Thomas, A. G. 1992. Weed surveys in different tillage systems in southwestern Ontario field crops. Can. J. Plant Sci. 72:13371347.CrossRefGoogle Scholar
Johnson, G. A., Mortensen, D. A., Young, L. J., and Martin, A. R. 1995. The stability of weed seedling population models and parameters in eastern Nebraska corn (Zea mays) and soybean (Glycine max) fields. Weed Sci. 43:604611.CrossRefGoogle Scholar
Ludwig, J. A. and Reynolds, J. F. 1988. Diversity indices. In Ludwig, J. A. and Reynolds, J. R. Statistical Ecology, New York, NY: John Wiley & Sons. pp. 85103.Google Scholar
Lybecker, D. W., Schweizer, E. E., and King, R. P. 1991. Weed management decisions in corn based on bioeconomic modeling. Weed Sci. 39:124129.Google Scholar
Lybecker, D. W., Schweizer, E. E., and Westra, P. 1993. Computer decision aid for managing weeds in irrigated corn. Proc. Agric. Res. Prot. Water Quality, Soil Water Conserv. Soc. 1:295297.Google Scholar
Mortensen, D. A., Johnson, G. A., and Young, L. J. 1993. Weed distribution in agricultural fields. In Robert, P. C., Rust, R. H., and Larson, W. E., eds. Soil Specific Crop Management. Madison, WI: ASA, CSSA, and SSSA. pp. 113124.Google Scholar
Schweizer, E. E., Lybecker, D. W., Wiles, L. J., and Westra, P. 1993. Bioeconomic models in crop production. Int. Crop Sci. I, Chap. 15. pp. 103107.Google Scholar
Thomas, A. G. 1985. Weed survey system used in Saskatchewan for cereal and oilseed crops. Weed Sci. 33:3443.CrossRefGoogle Scholar
Thomas, A. G. 1991. Floristic composition and relative abundance of weeds in annual crops of Manitoba. Can. J. Plant Sci. 71:831839.Google Scholar
Wiles, L. J., Oliver, G. W., York, A. C., Gold, H. J., and Wilkerson, G. G. 1992. Spatial distribution of broadleaf weeds in North Carolina soybean (Glycine max) fields. Weed Sci. 40:554557.Google Scholar
Wilson, R. G. 1988. Biology of weed seeds in soil. In Altieri, M. A. and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. Boca Raton, FL: CRC Press, Inc. pp. 2539.Google Scholar
Wilson, R. G., Kerr, E. D., and Nelson, L. A. 1985. Potential for using weed seed content in the soil to predict future weed problems. Weed Sci. 33:171175.Google Scholar