Wild oat is a problematic weed species that requires new management techniques in the face of herbicide resistance; harvest weed-seed control (HWSC) may be an option. Wild oat demographic information was collected in long-term, rotational field studies in Lacombe, AB, Canada, in 2006 and 2007, and a periodic matrix model was parameterized using management extremes (no IPM, no herbicide to high IPM, and full herbicide). Population growth rates were calculated for each treatment and year. Prospective (elasticity) and retrospective (LTRE) analyses were conducted alongside a rearrangement of the model equation in which population growth rates were designated and the required proportion of newly shed seed survival that gives that growth rate was solved for. All populations had λ > 1 or increasing populations. Elasticity analyses indicated that λ was most-highly elastic to the overwinter seedbank (Esw = 1), followed by seedling survival, fecundity, and survival of newly shed seed (0.63 to 0.86 across treatments). The latter may be the most-accessible vital rate for management of herbicide resistant populations. LTRE exposed the stochasticity of wild oat population growth rates between years and their ability to take advantage of lapses in control. Decreasing the proportion of newly shed seeds (snew) that survives was the most-effective and available control strategy until reduced to 0.1 to 0.3 when the summer seedbank becomes more critical. When averaged across treatments, > 80% of newly shed seed must be eliminated to stop the population from growing, resulting in a stable population, but not a decline. Because of preharvest shattering, HWSC will likely not be effective enough alone to cause wild oat populations to decline. New management techniques for wild oat control that can be used in combination with HWSC and integrated weed management strategies are needed.

Cropping system characteristics affect weed management by altering key demographic rates of weeds, including recruitment, seedling survival, fecundity, and seed survival. To facilitate the design and improvement of cropping systems that limit weed population growth, analytical methods are needed to identify weed management “choke points” (weed life stages that vary in response to management and whose variation strongly affects weed population growth rate). The objectives of this study were to (1) determine whether wheat–red clover green manure can limit giant foxtail population growth rate (λ) in a wheat–corn–soybean crop sequence and (2) identify choke points in the giant foxtail life cycle with respect to the green manure treatment. Demographic data were used to construct a periodic matrix model of giant foxtail population growth in a wheat–corn–soybean crop sequence, with either a wheat sole crop (W) or a wheat–red clover intercrop (R) in the wheat phase. Identification of choke points was accomplished by adapting the life-table response experiment (LTRE) design for retrospective perturbation analysis of the periodic matrix model. The difference in λ (Δλ) between the two treatments was decomposed into contributions from each parameter in each rotation phase of the periodic model. Each LTRE contribution was equal to the product of the sensitivity of λ to changes in a given parameter by the treatment difference in that parameter. Those parameters making large contributions to Δλ represented weed management choke points. Giant foxtail population growth rate in the simulation was more than twice as great in the W treatment (λ = 2.54) than in the R treatment (λ = 1.16). Retrospective perturbation analysis indicated that the proportion of seeds surviving predation in the wheat phase made the largest LTRE contribution (0.55) to Δλ, followed by seedling recruitment in the soybean (0.41) and corn (0.20) phases. By identifying weed management choke points within a given system, retrospective perturbation analysis can target research and management efforts for greater reductions in weed population growth.