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Title: IDENTIFYING ASSOCIATIONS AMONG SITE PROPERTIES AND WEED SPECIES ABUNDANCE. PART I. MULTIVARIATE ANALYSIS

Author
item DIELEMAN, J - UNIVERSITY OF NEBRASKA
item MORTENSEN, DAVID - UNIVERSITY OF NEBRASKA
item Buhler, Douglas - Doug
item Cambardella, Cynthia
item Moorman, Thomas

Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/19/2000
Publication Date: 9/1/2000
Citation: Dieleman, J.A., Mortensen, D.A., Buhler, D.D., Cambardella, C.A., Moorman, T.B. 2000. Identifying associations among site properties and weed species abundance. Part I. Multivariate analysis. Weed Science. 48:567-575.

Interpretive Summary: Weed populations within crop production fields are often very patchy. Patchiness in weed populations is not well understood, but appears to result from many factors. Many soil properties vary within fields and affect weed infestations through their influence on herbicide effectiveness and the population biology of weeds. Patchiness in weed populations has been largely ignored in designing management strategies. Most research on the interaction of weeds with other aspects of the cropping system has assumed that weeds are uniformly distributed in fields. On the contrary, recent studies show that weeds occur in patches that often contain several weed species. The objective of our research was to demonstrate how a statistical analysis procedure called canonical correlation analysis could be used to identify associations between soil properties and weed abundance within an agricultural field. This analysis identified several relationships between soil properties and weed abundance. For example, specific associations of topography and soil texture with weed presence were defined. Many of the associations were consistent over years, indicating that soil properties influence weed populations. While some consistent relationships were identified, differences in production practices and weather influenced the results from year to year. The ultimate result of this research will be a series of soil parameters that will predict the type of weed population that will occur on a particular soil. This will be useful to crop consultants and farmers as they design site-specific weed management systems. This knowledge will also provide a basis for future research on the impacts of soil properties on weed populations and for management systems that discourage weed development.

Technical Abstract: Site properties and weed species abundance are known to vary spatially across fields. The extent to which they co-vary is not well understood. The objective of this research was to demonstrate how canonical correlation analysis could be used to identify associations among site properties and weed species abundance within an agricultural field. A farmer-managed field rotated between corn and soybean in Boone County, IA was grid-sample for site properties in 1992 and for weed species abundance between 1994 and 1997. Twelve site properties were considered in relation to five weed species that were identified and counted after all weed control operations were completed. Weed species abundance was spatially variable such that most weeds were found in patches while much of the field was weed-free. Canonical correlation analysis identified one to four significant correlations between linear combinations of properties and weed species abundance. The first and second pairs of linear combinations explained th majority of variation in the data and were used to identify associations among site properties and weed species abundance. In years with corn, the first pair of linear combinations described an association between herbicide activity and weed presence while the second described topography and soil texture associations with weed presence. In years with soybean, the association described a link between soil texture and presence of annual grasses and swamp smartweed. Several consistent associations were identified across years indicating that site properties influence weed species abundance. However, variations in the associations were attributed to differences in agronomic and weed management practices for each crop, as well as stochastic environmental variation from year to year.