SITE-TO-SITE AND YEAR-TO-YEAR VARIATION IN TRITICUM AESTIVUM-AEGILOPS CYLINDRICA INTERFERENCE RELATIONSHIPS

Marie Jasieniuk,1 Bruce D. Maxwell,2 Randy L. Anderson,3 John 0. Evans,4 Drew J. Lyon,5 Stephen D. Miller,6 Don W Morishita,7 Aex G. Ogg, Jr.,8 Steven Seefeldt,9 Phillip W.XT Stahlman,10 Francis E. Northam,'0 Philip Westra, 1 Zewdu Kebede, Gail A. Wicks'2 I Corresponding author. Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717; mariej@montana.edu; 2 Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717; 3 Central Plains Research Center, USDA-ARS, Akron, CO 80720; 4 Department of Plant, Soils, and Biometeorology, Utah State University, Logan, UT 84322; 5 Panhandle Research and Extension Center, University of Nebraska, Scotsbluff, NE 69361; 6 Department of Plant, Soil, and Insect Sciences, University of Wyoming, Laramie, WY 82071; 7 Twin Falls Research and Extension Center, University of Idaho, Twin Falls, ID 83303; 8 National A. cylindrica Research Program, P.O. Box 53, Ten Sleep, WY 82442; 9 USDA-ARS, Washington State University, Pullman, WA 99164; 10 Agricultural Research Center, Kansas State University, Hays, KS 67601; l1 Department of Bioagricultural Science and Pest Management, Colorado State University, Fort Collins, CO 80523; 12 West Central Research and Extension Center, University of Nebraska, North Platte, NE 69101 Crop yield loss-weed density relationships critically influence calculation of economic thresholds and the resulting management recommendations made by a bioeconomic model. To examine site-to-site and year-to-year variation in winter Triticum aestivum L. (winter wheat)-Aegilops cylindrica Host. (jointed goatgrass) interference relationships, the rectangular hyperbolic yield loss function was fit to data sets from multiyear field experiments conducted at Colorado, Idaho, Kansas, Montana, Nebraska, Utah, Washington, and Wyoming. The model was fit to three measures of A. cylindrica density: fall seedling, spring seedling, and reproductive tiller densities. Two parameters: i, the slope of the yield loss curve as A. cylindrica density approaches zero, and a, the maximum percentage yield loss as A. cylindrica density becomes very large, were estimated for each data set using nonlinear regression. Fit of the model to the data was better using spring seedling densities than fall seedling densities, but it was similar for spring seedling and reproductive tiller densities based on the residual mean square (RMS) values. Yield loss finctions were less variable among years within a site than among sites for all measures of weed density. For the one site where year-to-year variation was observed (Archer, WY), parameter a varied significantly among years, but parameter i did not. Yield loss functions differed significantly among sites for 7 of 10 comparisons. Site-to-site statistical differences were generally due to variation in estimates of parameter i. Site-to-site and year-to-year variation in winter T aestivum-A. cylindrica yield loss parameter estimates indicated that management recommendations made by a bioeconomic model cannot be based on a single yield loss function with the same parameter values for the winter T aestivumproducing region. The predictive ability of a bioeconomic model is likely to be improved when yield loss functions incorporating time of emergence and crop density are built into the model's structure.