ANALYSIS OF SPATIAL-DISTRIBUTION OF COMMON LAMBSQUARTERS (CHENOPODIUM-ALBUM) IN NO-TILL SOYBEAN (GLYCINE-MAX)

The nonuniform spatial distribution of weeds complicates sampling, mod eling, and management of weed populations, Principles of a rational ap proach to analysis of weed spatial distribution, combining classical a nd spatial statistics, are presented using data for cumulative emergen ce of common lambsquarters in no-tillage soybean fields in 1990 and 19 93. Classical statistics, dispersion indices, mean/variance relationsh ips, and frequency histograms confirmed that raw and log(e)-transforme d data were not normally distributed, that populations were aggregated , and that large-scale trends in population means violated assumptions of spatial statistics. Detrending was accomplished by median polishin g log(e)-transformed data and confirmed by evaluation of standardized residuals and frequency histograms. Detrended residuals were used to c onstruct omni-directional and uni-directional semivariograms to descri be the spatial structure of the populations. A spherical model fit to the data was verified by cross validation, Semivariograms showed that common lambsquarters density was spatially autocorrelated at distances to 16 m, with more than 30% of the variance in density due to distanc e between field locations. Comparisons of kriged estimates and their s tandard deviations with and without detrending indicated that estimate s using detrended data were more appropriate and more precise. Kriged estimates of common lambsquarters density were used to draw contour ma ps of the populations.