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

Site properties and weed species abundance are known to vary spatially acro ss fields. The extent to which they covary is not well understood. The obje ctive of this research was to assess how canonical correlation analysis cou ld be used to identify associations among sire properties and weed species abundance within an agricultural field. A farmer-managed field rotated betw een 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. T welve site properties were considered in relation to five weed species that were identified and counted after all weed control operations were complet ed. Site properties such as total nitrogen, Bray-l P, percent organic carbo n, and texture were spatially variable. Weed species abundance was also spa tially 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 a ssociations among site properties and weed species abundance. In years with Z. mays, the first pair of linear combinations described an association be tween herbicide activity and weed presence, and the second described topogr aphy 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 as sociations were identified across years, indicating that site properties ca n influence weed abundance. However, annual variation in the associations m ay be attributed to differences in agronomic and weed management practices for each crop, as well as temporal weather variation influencing weed abund ance from year to year. This multivariate technique is an important tool to identify associations between site properties and weed abundance that coul d help explain observed patchy patterns of weed abundance. These associatio ns are an important first step in the generation of hypotheses to be tested at the whole field scale.