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Influence of velvetleaf (Abutilon theophrasti) and common sunflower (Helianthus annuus) density variation on weed management outcomes

Published online by Cambridge University Press:  12 June 2017

J. Anita Dieleman
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583–0915
Alex R. Martin
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583–0915

Abstract

Interactions between initial weed seedling density and postemergence herbicide and mechanical weed control were studied in two field experiments conducted between 1994 and 1996. Increasing seedbank densities of velvetleaf (0 to 500 seed m–2) in soybean or common sunflower (250 to 2,500 seed 1.3 m–2) in corn or soybean were established at Lincoln and Mead, NE, respectively. Emerged seedlings were treated with increasing intensities of weed control from none to bentazon alone or with interrow cultivation. A positive linear relationship between initial seedling density and density of surviving seedlings was consistently observed. As initial seedling density increased, more survivors were present after treatment. As intensity of weed control increased, the number of seedling survivors decreased. Resulting reproductive fitness decreased with increasing management intensity but remained positive when regressed against surviving seedling densities. Weed management outcomes were dependent on initial seedling density, such that the absolute number of survivors increased, while proportion of survivors appeared constant within the density ranges studied. These research findings emphasize the need to account for weed infestation level when assessing efficacy of weed management systems and provide evidence that patchy weed distributions may persist in part because of the need for considerably higher management intensities in high density patch centers.

Type
Weed Biology and Ecology
Copyright
Copyright © 1999 by the Weed Science Society of America 

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References

Literature Cited

Andersen, R. N. 1981. Increasing herbicide tolerance of soybeans (Glycine max) by increasing seeding rates. Weed Sci. 29: 336338.Google Scholar
Andreasen, C., Streibig, J. C., and Haas, H. 1991. Soil properties affecting the distribution of 37 weed species in Danish fields. Weed Res. 31: 181187.Google Scholar
Bell, G. and Lechowicz, M. J. 1991. The ecology and genetics of fitness in forest plants. I. Environmental heterogeneity measured by explant trials. J. Ecol. 79: 663685.Google Scholar
Buhler, D. D., Doll, J. D., Proost, R. T., and Visocky, M. R. 1995. Integrating mechanical weeding with reduced herbicide use in conservation tillage corn production systems. Agron. J. 87: 507512.CrossRefGoogle Scholar
Burrill, L. C. and Appleby, A. P. 1978. Influence of Italian ryegrass density on efficacy of diuron herbicide. Agron. J. 70: 505506.CrossRefGoogle 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.Google Scholar
Cousens, R. and Mortimer, M. 1995. Dynamics of Weed Populations. New York: Cambridge University Press. 332 p.Google Scholar
Defelice, M. S., Brown, W. B., Aldrich, R. J., Sims, B. D., Judy, D. T., and Guethle, D. R. 1989. Weed control in soybeans (Glycine max) with reduced rates of postemergence herbicides. Weed Sci. 37: 365374.CrossRefGoogle Scholar
Dieleman, J. A. and Mortensen, D. A. 1998a. Influence of weed biology and ecology on development of reduced dose strategies for integrated weed management systems. Pages 333362 in Hatfield, J. L., Buhler, D. D., and Stewart, B. A., eds. Integrated Weed and Soil Management. Chelsea, MI: Ann Arbor Press.Google Scholar
Dieleman, J. A. and Mortensen, D. A. 1998b. Velvetleaf (Abutilon theophrasti) patch attributes: whole-patch spatial patterns and within-patch dynamics. Proc. Weed Sci. Soc. Am. 38: 9.11.Google Scholar
Donald, W. W. 1994. Geostatistics for mapping weeds, with a Canada thistle (Cirsium arvense) patch as a case study. Weed Sci. 42: 648657.Google Scholar
Ellison, A. M. and Rabinowitz, D., 1989. Effects of plant morphology and emergence time on size hierarchy formation in experimental populations of two varieties of cultivated peas (Pisum sativum). Am. J. Bot. 76: 427436.Google Scholar
Gerhards, R., Wyse-Pester, D. Y., Mortensen, D. A., and Johnson, G. A. 1997. Characterizing spatial stability of weed populations using interpolated maps. Weed Sci. 45: 108119.Google Scholar
Gonzalez-Andujar, J. L. and Fernandez-Quintanilla, C. 1991. Modelling the population dynamics of Avena sterilis under dry-land cereal cropping systems. J. Appl. Ecol. 28: 1627.Google Scholar
Hanna, A. Y., Harlan, P. W., and Lewis, D. T. 1982. Soil available water as influenced by landscape position and aspect. Agron. J. 74: 9991004.Google Scholar
Hartzler, R. G. and Roth, G. W. 1993. Effect of prior year's weed control on herbicide effectiveness in corn (Zea mays). Weed Technol. 7: 611614.Google Scholar
Hartzler, R. G., van Kooten, B. D., Stoltenberg, D. E., Hall, E. M., and Fawcett, R. S. 1993. On-farm evaluation of mechanical and chemical weed management practices in corn (Zea mays). Weed Technol. 7: 10011004.CrossRefGoogle Scholar
Hoffman, D. W. and Lavy, T. L. 1978. Plant competition for atrazine. Weed Sci. 26: 9499.Google Scholar
Johnson, G. A. 1994. Model Parameterization, Parametric Sequential Sampling, and Geostatistical Analysis of Weed Seedling Populations. . University of Nebraska, Lincoln, NE. 193 p.Google Scholar
Johnson, G. A., Mortensen, D. A., and Gotway, C. A. 1996. Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci. 44: 704710.Google 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.Google Scholar
Khedir, K. D. and Roeth, F. W. 1981. Velvetleaf (Abutilon theophrasti) seed populations in six continuous-corn (Zea mays) fields. Weed Sci. 29: 485490.CrossRefGoogle Scholar
Martin, A. R., Mortensen, D. A., and Burchell, N. 1994. Visual and photographic assessment of herbicide efficacy trials for use in bioeconomic modeling. Proc. Weed Sci. Soc. Am. 34: 117.Google Scholar
Mortensen, D. A., Higley, L. G., Dieleman, J. A., Lindquist, J. L., and Holshouser, D. L. 1998. Ecological principles underlying integrated weed management systems. Proc. Weed Sci. Soc. Am. 38: 13.8.Google Scholar
Mortensen, D. A., Johnson, G. A., Wyse, D. Y., and Martin, A. R. 1995. Managing spatially variable weed populations. Pages 397415 in Site-Specific Management for Agricultural Systems. Madison, WI: ASA-CSSA-SSSA.Google Scholar
Mortensen, D. A., Johnson, G. A., and Young, L. J. 1993. Weed distribution in agricultural fields. Pages 113124 in Soil Specific Crop Management. Madison, WI: ASA-CSSA-SSSA.Google Scholar
Nagashima, H., Terashima, I., and Katoh, S. 1995. Effects of plant density on frequency distributions of plant height in Chenopodium album stands: analysis based on continuous monitoring of height-growth of individual plants. Ann. Bot. 75: 173180.Google Scholar
O'Sullivan, J. and Bouw, W. J. 1993. Reduced rates of postemergence herbicides for weed control in sweet corn (Zea mays). Weed Technol. 7: 9951000.Google Scholar
Pacala, S. W. and Silander, J. A. Jr. 1985. Neighborhood models of plant population dynamics. I. Single species models of annuals. Am. Nat. 125: 385411.Google Scholar
Pannell, D. J. 1990. Model of wheat yield response to application of diclofop-methyl to control rigid ryegrass (Lolium rigidum). Crop Prot. 9: 422428.CrossRefGoogle Scholar
Rasmussen, I. A. 1993. Seed production of Chenopodium album in spring barley sprayed with different herbicides in normal to very low doses. Pages 639646 in Proceedings of the 8th EWRS Symposium “Quantitative approaches to weed and herbicide research and their practical application.” Wageningen, Netherlands: EWRS.Google Scholar
Seefeldt, S. S., Jensen, J. E., and Fuerst, E. P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technol. 9: 218227.CrossRefGoogle Scholar
Swanton, C. J. and Weise, S. F. 1991. Integrated weed management: the rationale and approach. Weed Technol. 5: 657663.Google Scholar
Teo-Sherrell, C.P.A. 1996. The Fates of Weed Seeds. . University of Nebraska, Lincoln, NE. 173 p.Google Scholar
Thrall, P. H., Pacala, S. W., and Silander, J. A. Jr. 1989. Oscillatory dynamics in populations of an annual weed species Abutilon theopbrasti . J. Ecol. 77: 11351149.CrossRefGoogle Scholar
Weiner, J. and Thomas, S. C. 1986. Size variability and competition in plant monocultures. Oikos 47: 211222.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
Willson, M. F., Thomas, P. A., Hoppes, W. G., Katusic-Malmborg, P. L., Goldman, D. A., and Bothwell, J. L. 1987. Sibling competition in plants: an experimental study. Am. Nat. 129: 304311.Google Scholar
Wilson, B. J. and Lawson, H. M. 1992. Seedbank persistence and seedling emergence of seven weed species in autumn-sown crops following a single year's seeding. Ann. Appl. Biol. 120: 105116.CrossRefGoogle Scholar
Winkle, M. E., Leavitt, J.R.C., and Burnside, O. C. 1981. Effects of weed density on herbicide absorption and bioactivity. Weed Sci. 29: 405409.Google Scholar
Wyse, D. Y. 1996. Characterizing the Stability of Weed Seedling Populations. . University of Nebraska, Lincoln, NE. 122 p.Google Scholar