Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T06:53:46.690Z Has data issue: false hasContentIssue false
  • English
  • Français

Identifying associations among site properties and weed species abundance. II. Hypothesis generation

Published online by Cambridge University Press:  20 January 2017

J. Anita Dieleman ,
David A. Mortensen ,
Douglas D. Buhler  and
Richard B. Ferguson
David A. Mortensen
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583
Douglas D. Buhler
Affiliation:
U.S. Department of Agriculture, Agricultural Research Service, National Soil Tilth Laboratory, Ames, IA 50011
Richard B. Ferguson
Affiliation:
South Central Research and Extension Center, Clay Center, NE 68933
Get access Rights & Permissions [Opens in a new window]

Abstract

Identification of associations between site properties and weed species abundance led to the generation of hypotheses as to why weed populations occur where they do, or do not, in agricultural fields. The objective of this research was to use a multivariate statistical technique, canonical correlation analysis, to identify the associations. Two continuous Zea mays production fields under center-pivot irrigation in the central Platte River Valley of Nebraska were grid-sampled between 1994 and 1997 for nine site properties and six to seven weed species. Weed species were identified and counted just prior to postemergence weed control in two adjacent quadrats (1 by 0.38 m) at each grid sampling point. These quadrats represented untreated weed populations emerging between crop rows and treated populations that survived preemergence herbicide banded within the crop row. Canonical correlation analysis identified one to five significant correlations between linear combinations of site properties and weed species abundance depending on field site, years, and between- vs. on-crop row weed populations. The first pair of linear combinations consistently described an association that separated weed species across a gradient of topography and soil type. The second pair of linear combinations described associations between weed species and soil fertility. In all cases, it was hypothesized that management practices strongly interacted with site properties to create the observed associations with weed populations. Other hypothesized mechanisms for weed patchiness include patchiness in available soil moisture that would influence weed seed germination, emergence, and seedling growth. Additional variation in plant-available preemergence herbicide concentration across the field site would vary weed control efficacy. Another mechanism would be variation in soil fertility that affects the growth, reproduction, and competitive ability of both the crop and the weed.

Keywords

Abutilon theophrasti Medicus ABUTH, velvetleafAmaranthus spp., pigweedApocynum cannabinum L. APCCA, hemp dogbaneHelianthus annuus L. HELAN, common sunflowerPhysalis subglabrata Mack. et Bush. PHYSU, smooth groundcherrySetaria spp., foxtailSolanum ptycanthum Dun. ex DC. SOLPT, eastern black nightshadeStrophostyles leiosperma (T. et G.) Piper, smoothseed wildbeanZea mays L., cornCanonical correlation analysisgrid-samplingsoil propertiesspatial heterogeneityABUTHAMASSAPCCAHELANPHYSUSETSS
Type
Research Article
Information
Weed Science , Volume 48 , Issue 5 , October 2000 , pp. 576 - 587
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Almekinders, C.J.M., Fresco, L. O., and Struik, P. C. 1995. The need to study and manage variation in agro-ecosystems. Neth. J. Agric. Sci. 43:127–142.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. 31:181–187.CrossRefGoogle Scholar
Blackshaw, R. E., Moyer, J. R., and Kozub, G. C. 1994. Efficacy of downy brome herbicides as influenced by soil properties. Can. J. Plant Sci. 74:177–183.Google Scholar
Blumhorst, M. R., Weber, J. B., and Swain, L. R. 1990. Efficacy of selected herbicides as influenced by soil properties. Weed Technol. 4:279–283.CrossRefGoogle Scholar
Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Turco, R. F., and Konopka, A. E. 1994. Field-scale variability of soil properties in Central Iowa soils. Soil Sci. Soc. Am. J. 58:1501–1511.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. L. 1995. Analysis of spatial distribution of common lambsquarters (Chenopodium album) in notill soybean (Glycine max). Weed Sci. 43:258–269.CrossRefGoogle Scholar
Dale, H. M., Harrison, P. J., and Thomson, G. W. 1965. Weeds as indicators of physical site characteristics in abandoned pastures. Can. J. Bot. 43:1319–1327.Google Scholar
Dale, M.R.T., Thomas, A. G., and John, E. A. 1992. Environmental factors influencing management practices as correlates of weed community composition in spring seeded crops. Can. J. Bot. 70:1931–1939.CrossRefGoogle Scholar
Dieleman, J. A., Mortensen, D. A., Buhler, D. D., Cambardella, C. A., and Moorman, T. B. 2000. Identifying associations among site properties and weed species abundance. I. Multivariate analysis. Weed Sci. 48:567–575.Google Scholar
Dieleman, J. A., Mortensen, D. A., and Young, L. J. 1999. Predicting within-field weed species occurrence based on field-site attributes. Pages 517–528 In Stafford, J. V., ed. Second European Conference on Precision Agriculture, 11–15 July 1999, Odense, Denmark. Sheffield, UK: Sheffield Academic Press.Google Scholar
Firbank, L. G., Cousens, R., Mortimer, A. M., and Smith, R.G.R. 1990. Effects of soil type on crop yield-weed density relationships between winter wheat and Bromus sterilis . J. Appl. Ecol. 27:308–318.Google Scholar
Gittins, R. 1985. Canonical Analysis: A Review with Applications in Ecology. Berlin, Germany: Springer-Verlag, pp. 13–36.CrossRefGoogle Scholar
Gupta, S. C. and Larson, W. E. 1979. Estimating soil water retention characteristics from particle size distribution, organic matter percent, and bulk density. Water Resour. Res. 15:1633–1635.Google Scholar
Harper, J. L. 1977. Population Biology of Plants. New York: Academic Press, pp. 151–194, 305–345.Google Scholar
Hausler, A. and Nordmeyer, H. 1995. Impact of soil properties on weed distribution. Pages 186–189 In Olesen, S. E., ed. Proceedings of the Seminar on Site Specific Farming. Tjele: Danish Institute of Plant and Soil Science SP-report 26.Google Scholar
Hudson, B. D. 1994. Soil organic matter and available water capacity. J. Soil Water Conserv. 49:189–194.Google Scholar
Hume, L. 1982. The long-term effects of fertilizer application and three rotations on weed communities in wheat (after 21–22 years at Indian Head, Saskatchewan). Can. J. Plant Sci. 62:741–750.Google Scholar
Jamison, V. C. and Kroth, E. M. 1958. Available moisture storage capacity in relation to textural composition and organic matter content of several Missouri soils. Soil Sci. Soc. Am. J. 22:189–192.CrossRefGoogle Scholar
Johnson, G. A., Mortensen, D. A., and Gotway, C. A. 1996. Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci. 44:704–710.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. 43:604–611.Google Scholar
Johnson, R. A. and Wichern, D. W. 1992. Applied Multivariate Statistical Analysis. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, pp. 459–486.Google Scholar
Mortensen, D. A., Johnson, G. A., and Young, L. J. 1993. Weed distribution in agricultural fields. Pages 113–124 In Robert, P. C. and Rust, R. H., eds. Soil Specific Crop Management. Madison, WI: Agronomy Society of America.Google Scholar
Mulla, D. J. 1993. Mapping and managing spatial patterns in soil fertility and crop yield. Pages 15–26 In Robert, P. C. and Rust, R. H., eds. Soil Specific Crop Management. Madison, WI: Agronomy Society of America.Google Scholar
Novak, J. M., Moorman, T. B., and Cambardella, C. A. 1997. Atrazine sorption at the field scale in relation to soils and landscape position. J. Environ. Qual. 26:1271–1277.CrossRefGoogle Scholar
Pyšek, P. and Lepš, J. 1991. Response of a weed community to nitrogen fertilization: a multivariate analysis. J. Veg. Sci. 2:237–244.Google Scholar
Rao, P.S.C. and Wagenet, R. J. 1985. Spatial variability of pesticides in field soils: methods for data analysis and consequences. Weed Sci. 33 (suppl. 2): 18–24.Google Scholar
Salter, P. J., Berry, G., and Williams, J. B. 1966. The influence of texture on the moisture characteristics of soil. III. Quantitative relationships between particle size, composition, and available-water capacity. J. Soil Sci. 17:93–98.Google Scholar
Sampson, A. W. 1939. Plant indicators—concept and status. Bot. Rev. 5:155–206.Google Scholar
[SAS] Statistical Analysis Systems. 1990. SAS/STAT User's Guide. Version 6, 4th ed., Volume 1. Cary, NC: Statistical Analysis Systems Institute, pp. 367–385.Google Scholar
[USDA] U.S. Department of Agriculture. 1962. Soil Survey of Hall County, Nebraska. USDA-Soil Conservation Service, Washington, DC, and University of Nebraska—Conservation and Survey Division, Lincoln, NE.Google Scholar
[USDA] U.S. Department of Agriculture. 1974. Soil Survey of Buffalo County, Nebraska. USDA-Soil Conservation Service, Washington, DC, and University of Nebraska-Conservation and Survey Division, Lincoln, NE.Google Scholar
Weaver, S. E. and Hamill, A. S. 1985. Effects of soil pH on competitive ability and leaf nutrient content of corn (Zea mays L.) and three weed species. Weed Sci. 33:447–451.CrossRefGoogle Scholar
Wood, L. S., Scott, H. D., Marx, D. B., and Lavy, T. L. 1987. Variability in sorption coefficients of metolachlor on a Captina silt loam. J. Environ. Qual. 16:251–256.Google Scholar
Zimdahl, R. L. 1999. My view. Weed Sci. 47:1.Google Scholar