The adoption of dicamba-resistant cotton (Gossypium hirsutum L.) cultivars allows using dicamba to reduce weed populations across growing seasons. However, the overuse of this tool risks selecting new herbicide-resistant biotypes. The objectives of this research were to determine the population trajectories of several weed species and track the frequency of glyphosate-resistant (GR) Palmer amaranth (Amaranthus palmeri S. Watson) over 8 yr in dicamba-resistant cotton. An experiment was established in North Carolina in 2011, and during the first 4 yr, different herbicide programs were applied. These programs included postemergence applications of glyphosate, alone or with dicamba, with or without residual herbicides. During the last 4 yr, all programs received glyphosate plus dicamba. Biennial rotations of postemergence applications of glyphosate only and glyphosate plus dicamba postemergence with and without preemergence herbicides were also included. Sequential applications of glyphosate plus dicamba were applied to the entire test area for the final 4 yr of the study. No herbicide program was entirely successful in controlling the weed community. Weed population trajectories were different according to species and herbicide program, creating all possible outcomes; some increased, others decreased, and others remained stable. Density of resistant A. palmeri increased during the first 4 yr with glyphosate-only programs (up to 11,739 plants m⁻²) and decreased a 96% during the final 4 yr, when glyphosate plus dicamba was implemented. This species had a strong influence on population levels of other weed species in the community. Goosegrass [Eleusine indica (L.) Gaertn.] was not affected by A. palmeri population levels and even increased its density in some herbicide programs, indicating that not only herbicide resistance but also reproductive rates and competitive dynamics are critical for determining weed population trajectories under intensive herbicide-based control programs. Frequency of glyphosate resistance reached a maximum of 62% after 4 yr, and those levels were maintained until the end of the experiment.

Crop–weed interactions are affected by environmental alterations resulting from a crop’s presence, such as modifications in temperature, light quality and quantity, and moisture conditions that could modify weed performance. The objectives of this work were to study (1) how soybean [Glycine max(L.) Merr.] crop structure modifies the environment under the canopy and large crabgrass [Digitaria sanguinalis(L.) Scop.] plant structure, biomass, and seed production and dormancy; and (2) the relative importance of these environmental changes on the weed’s characteristics. A field experiment in a completely randomized block design with five replicates was performed to evaluate narrow and wide interrow spacing and soybean maturity groups 3 and 4. Measured variables were intercepted solar radiation (RAD); red–far red (R-FR) ratio; humidity; minimum, maximum, and alternating temperatures; and weed biomass, tillers per plant, height, and seed dormancy. Crop canopy reduced solar radiation, R-FR ratio, and daily average maximum and alternating temperatures. Soybean presence reduced the weed biomass, tillers and seeds per plant, and seed dormancy. High solar radiation intercepted by the crop during the reproductive phase was the main environmental variable related to reductions in weed biomass, tillers per plant, and fecundity. The combination of low temperature and solar radiation received by developing seeds was more related to seed dormancy than the rest of the variables. Crop management decisions focused on the fact that keeping the crop canopy alive for a longer time at the end of the season would not only reduce the weed growth but also seed dormancy.

Russian thistle (Salsola tragusL.) is among the most troublesome weeds in cropland and ruderal semiarid areas of the Pacific Northwest (PNW). PredictingS. tragusemergence timing plays a critical role in scheduling weed management measures. The objective of this research was to develop and validate a predictive model of the seedling emergence pattern ofS. tragusunder field conditions in the PNW to increase the efficacy of control measures targeting this species. The relationship between cumulative seedling emergence and cumulative hydrothermal time under field conditions was modeled using the Weibull function. This model is the first to use hydrothermal time units (HTT) to predictS. tragusemergence and showed a very good fit to the experimental data. According to this model, seedling emergence starts at 5 HTT, and 50% and 90% emergence is completed at 56 HTT and 177 HTT, respectively. For model validation, independent field experiments were carried out. Cumulative seedling emergence was accurately predicted by the model, supporting the idea that this model is robust enough to be used as a predictive tool forS. tragusseedling emergence. Our model can serve as the basis for the development of decision support systems, helping farmers make the best decisions to controlS. traguspopulations in no-till fallow and spring wheat systems.