Competition between genotypes within a plant population can result in the displacement of the least competitive by more competitive genotypes. Although evolutionary processes in plants may occur over thousands and millions of years, it has been suggested that changes in key fitness traits could occur in as little as decades being herbicide resistance a common example. However, the rapid evolution of complex traits has not been proven in weeds. We hypothesized that changes in weed growth and competitive ability can occur in just a few years because of selection in agroecosystems. Seed of multiple generations of a single natural population of the grassy weed giant foxtail (Setaria faberi Herrm.) were collected during 34 years (i.e., 1983 to 2017). Using a “resurrection” approach, we characterized life-history traits of the different year-lines under non-competitive and competitive conditions. Replacement-series experiments comparing the growth of the oldest year-line (1983) vs. newer year-lines (1991, 1996, 1998, 2009, and 2017) showed that plant competitive ability decreased and then increased progressively in accordance with oscillating selection. The adaptations in competitive ability were reflected in dynamic changes in leaf area and biomass when plants were in competition. The onset of increased competitive ability coincided with the introduction of herbicide-resistant crops in the landscape in 1996. We also conducted a genome-wide association study (GWAS) and identified four loci that were associated with increased competitive ability over time, confirming that this trait changed in response to directional selection. Putative transcription factors and cell wall-associated enzymes were linked to those loci. This is the first study providing direct in situ evidence of rapid directional evolution of competitive ability in a plant species. The results suggest that agricultural systems can exert enough pressure to cause evolutionary adaptations of complex life-history traits potentially increasing weediness and invasiveness.

Field experiments were conducted from 2017 to 2019 to determine the tolerance of carinata to several preemergence and postemergence herbicides. Preliminary screenings identified herbicides which caused large variation on carinata injury, indicating the potential for selectivity. Dose-response field studies were conducted to quantify the tolerance of carinata to select herbicides. Diuron applied preemergence at rates of 280 g ai ha−1 or above reduced carinata population density 54% to 84% compared to the nontreated control. In certain locations, clomazone applied preemergence caused minor injury with an acceptable level of carinata tolerance and only doses above 105 g ai ha−1 caused yield reductions. Napropamide doses of 2,856 g ai ha−1 or higher applied preemergence caused at least 25% injury to carinata; however, the damage was not severe enough to reduce yields. Simazine applied postemergence at rates above 1,594 g ai ha−1 caused 50% or more injury, resulting in yield losses ranging from 0 to 95% depending on location. Clopyralid applied postemergence at 2,512 g ai ha−1 caused 25% injury with relative yield reductions which varied across locations. The present study identified clomazone and napropamide applied preemergence, and clopyralid applied postemergence as potential herbicides for weed control in carinata. In contrast, diuron, simazine, metribuzin, imazethapyr, and chlorimuron caused high levels of carinata mortality and can be used to control volunteer carinata plants in rotational crops.

BACKGROUNDThe potential of weed species to respond to selection forces affecting the evolution of weedy traits such as competitive ability is poorly understood. This research characterized evolutionary growth changes in a single Abutilon theophrasti Medik. population comparing multiple generations collected from 1988 to 2016. A competition study was performed to understand changes in competitive ability, and a herbicide dose–response study was carried out to assess changes in sensitivity to acetolactate synthase‐inhibiting herbicides and glyphosate over time.RESULTSWhen grown in monoculture, A. theophrasti biomass production per plant increased steadily across year‐lines while leaf number decreased. In replacement experiments, A. theophrasti plants from newer year‐lines were more competitive and produced more biomass and leaf area than the oldest year‐line. No clear differences in sensitivity to imazamox were observed among year‐lines. However, starting in 1995, this A. theophrasti population exhibited a progressive increase in growth in response to a sublethal dose of glyphosate (52 g a.e. ha−1), with the 2009 and 2016 year‐lines having more than 50% higher biomass than the nontreated control.CONCLUSIONThis study demonstrates that weeds can rapidly evolve increased competitive ability. Furthermore, the results indicate the possibility of changes in glyphosate hormesis over time. These results highlight the importance of the role that rapid (i.e., subdecadal) evolution of growth traits might have on the sustainability of weed management strategies. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Public concern regarding the use of herbicides in urban areas (e.g., golf courses, parks, lawns) is increasing. Thus, there is a need for alternative methods for weed control that are safe for the public, effective against weeds, and yet selective to turfgrass and other desirable species. New molecular tools such as RNAi have a potential to meet all those requirements, but before these technologies can be implemented, it is critical to understand the perceptions of key stakeholders to facilitate adoption as well as regulatory processes. With this in mind, turfgrass system managers, such as golf course superintendents and lawn care providers, were surveyed to gain insight to the perception and potential adoption of RNAi technology for weed management. Based on survey results, turfgrass managers believe that cost of weed management and time spent managing weeds are the main challenges faced in their fields. When considering new weed management tools, survey respondents were most concerned about cost, efficacy, and efficiency of a new product. Survey respondents were also optimistic toward RNAi for weed management and would either use this technology in their own fields or be willing to conduct research to develop RNAi herbicides. Although respondents believed that the general public would have some concerns about this technology, they did not believe this to be the most important factor for them when choosing new weed management tools. The need for new herbicides to balance weed control challenges and public demands is a central factor for turfgrass managers’ willingness to use RNAi-based weed control in turfgrass systems. They believe their clientele will be accepting of RNAi tools, although further research is needed to investigate how a wider range of stakeholders perceive RNAi tools for turfgrass management more broadly.

High crop densities are valuable to increase weed suppression, but growers might be reluctant to implement this practice due to increased seed cost. Because it is also possible to lower planting densities in areas with no or low weed interference risk, the area allocated to each planting density must be optimized considering seed cost and productivity per plant. In this study, the growth and yield of maize (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.] were characterized in response to low planting densities and arrangements. The results were used to develop a bioeconomic model to optimize the area devoted to high- and low-density plantings to increase weed suppression without increasing seed cost. Physiological differences seen in each crop varied with the densities tested; however, maize was the only crop that had differences in yield (per area) between densities. When using a model to optimize low- and high-planting densities, maize and cotton showed the most plasticity in yield per planted seed (g seed-1) and area of low-density to compensate for high-density area unit. Maize grown at 75% planting density compared to the high-planting density (200%) increased yield (g seed-1) by 229%, return by 43%, and profit by 79% while decreasing the low-density area needed to compensate for high-density area. Cotton planted at 25% planting density compared to the 200% planting density increased yield (g seed-1) by 1099%, return by 46%, and profit by 62% while decreasing the low-density area needed to compensate for high-density area. Alternatively, the high morphological plasticity of soybean did not translate into changes in area optimization, as soybean maintained return, profit, and a 1:1 ratio for area compensation. This optimization model could allow for the use variable planting at large scales to increase weed suppression while minimizing costs to producers.