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Identifying associations among site properties and weed species abundance. I. Multivariate analysis

Published online by Cambridge University Press:  20 January 2017

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
Cynthia A. Cambardella
Affiliation:
U.S. Department of Agriculture, Agricultural Research Service, National Soil Tilth Laboratory, Ames, IA 50011
Thomas B. Moorman
Affiliation:
U.S. Department of Agriculture, Agricultural Research Service, National Soil Tilth Laboratory, Ames, IA 50011

Abstract

Site properties and weed species abundance are known to vary spatially across fields. The extent to which they covary is not well understood. The objective of this research was to assess 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 Zea mays and Glycine max in Boone County, IA, was grid-sampled 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. Site properties such as total nitrogen, Bray-1 P, percent organic carbon, and texture were spatially variable. Weed species abundance was also spatially variable such that most weeds were found in patches and much of the field was weed-free. Canonical correlation analysis identified one to four significant correlations between linear combinations of site properties and weed species abundance. The first and second pairs of linear combinations explained the majority of variation in the data and were used to identify associations among site properties and weed species abundance. In years with Z. mays, the first pair of linear combinations described an association between herbicide activity and weed presence, and the second described topography and soil texture associations with weed presence. In years with G. max, the single observed association described a link between soil texture and presence of Setaria species and Polygonum coccineum. Several consistent associations were identified across years, indicating that site properties can influence weed abundance. However, annual variation in the associations may be attributed to differences in agronomic and weed management practices for each crop, as well as temporal weather variation influencing weed abundance from year to year. This multivariate technique is an important tool to identify associations between site properties and weed abundance that could help explain observed patchy patterns of weed abundance. These associations are an important first step in the generation of hypotheses to be tested at the whole field scale.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

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