Kochia (Bassia Scoparia) Growth and Fecundity As Inuenced By Crop Competition and Weed Density

Kochia [Bassia scoparia (L.) A. J. Scott] represents one the most troublesome weeds in crop production systems in the North American Great Plains. The development of herbicide-resistant B. scoparia populations further exacerbated this problem. More ecologically driven approaches to its control are necessary. This study examined the competitive effects of four crops (sugar beet, soybean, barley, and corn) in combination with B. scoparia densities (3, 13, 24, 47, 94, and 188 plants m -2 ) on B. scoparia development and seed production across 2 years. Corn and barley had the greatest impact on B. scoparia growth and fecundity. B. scoparia biomass was 87 and 82% lower and seed production was 98 and 96% lower (p<0.001) in corn and barley, respectively, relative to fallow. Corn had greatest effect in reducing B. scoparia biomass and seed production. Barley had greatest effect in delaying B. scoparia owering which occurred 113 days after B. scoparia emergence (p<0.001). Soybean and sugar beet had the least effect reducing B. scoparia biomass by 70 and 65% and seed production by 84 and 80% (p<0.001), respectively, relative to fallow. Increasing B. scoparia densities resulted in reductions in B. scoparia width, number of primary branches, biomass plant -1 , and seeds plant -1 but increased B. scoparia height, biomass m -2 , and seeds m -2 (p<0.001) under all cropping treatments except corn. Barley represents the greatest opportunity to impact B. scoparia through reduced fecundity and delayed owering, with the latter providing a window of opportunity for post-harvest control. The effects observed here were isolated from differences in herbicide practices that are associated with each of these crops, differences that have a dramatic effect on B. scoparia in their own right. 2016. The trials used split plots deployed within a randomized complete block design with four replications. Whole plots were the cropping treatments, while sub-plots were the six B. scoparia density treatments randomly placed within each whole plot.

The unique features and competitive nature of B. scoparia have made it problematic in diverse cropping systems. A monoecious diploid (2n = 18) with C4 carbon xation, B. scoparia exhibits protogynous owering that forces high levels of outcrossing and promotes high genetic diversity within and among populations [20][21][22] . Among the reasons for its widespread distribution and its troublesome nature, are its ability to rapidly emerge early in the growing season, low seed dormancy, high environmental stress tolerance, high seed production, and the tumble mechanism for effective seed dispersal across long distances 2,6,16,23−28 . While its small seeds cannot emerge from more than 80 mm of soil cover and won't persist in the soil for more than 2 years 26 , B. scoparia is strongly nitrogen responsive and capable of ourishing under many different tillage and crop rotation systems [29][30][31][32] . Moreover, B. scoparia populations rapidly shift from early-emerging to late-emerging cohorts in response to early-season chemical control tactics that rapidly select for biotypes with elevated levels of seed dormancy and higher thermal requirements for seed germination 33 .
Increased herbicide use, due in part to the decline in herbicide prices, has led to the development of eldevolved herbicide-resistant B. scoparia populations that pose great challenges for their control and management 24,29,33−36 . Herbicide-resistant B. scoparia is now widespread in the Great Plains, Paci c Northwest, Rocky Mountains, and Midwestern USA 24 . These herbicide-resistances include resistance to acetolactate synthase (ALS) inhibitors, synthetic auxins, photosystem II (PSII) inhibitors, and 5enolpyruvylshikimate-3-phosphate synthase (EPSPS) inhibitors 24,37 . To make matters worse, several states have B. scoparia populations con rmed resistant to multiple herbicide sites of action, among of these are B. scoparia populations from Illinois with resistance to both PSII and ALS inhibitors, and more recent B. scoparia populations from Kansas with resistances to glyphosate, ALS inhibitors, PSII inhibitors, and dicamba 38, 39 . Even more troubling, some of these herbicide resistances have been shown to neither reduce the vegetative growth nor affect the reproductive success of the herbicide-resistant population in the absence of herbicide selection 95 . This suggests that herbicide resistant phenotypes of B. scoparia will likely persist in elds long after herbicide use has ceased 40,41,95 .
The great challenge for the continued control and management of herbicide-resistant B. scoparia will be the development of diverse approaches to weed management that reduce the reliance on chemical weed control. Mechanical and ecological approaches such as tillage, increased crop competition, cover crops, and diverse and improved crop rotations hold great potential for decreasing B. scoparia seedbanks and managing B. scoparia herbicide resistance 37,40,42−44 . Growing interests in ecological approaches to weed management that can be integrated into current herbicide weed control programs has become a renewed frontier in integrated weed management. One ecological approach is to take advantage of the natural competitive abilities of crops including their ability to tolerate weed competition (tolerance) thus maintaining yields while reducing weed tness (suppression) 45,46 . A strong suppressive crop can reduce weed seed production, which can have positive long-term effect on weed seed banks 47,48 . For instance, the early biomass production in wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) is one of the two traits responsible for signi cant suppression of perennial ryegrass (Lolium perenne L.) and volunteer oil rapeseed (Brassica napus L.) 49,50 . For B. scoparia, seed production was reduced in corn and wheat plots relative to a fallow control 51 . In comparison to other crops, corn has been shown to reduce B. scoparia seed banks compared to dry beans (Phaseolus vulgaris L.) and to a rotation of sugar beetsugar beet-corn 42 . For the latter, differences were suggested to be due to differing herbicide use for each crop in the cropping sequence and the more competitive nature of corn crop 42 . At this time, it is unclear the relative contribution of each of these factors on B. scoparia control. There is currently little information on the interactions between B. scoparia density and crop competition on B. scoparia growth and development. This study aims to address this de ciency as well as assess the relative competitiveness of viable rotational crops for B. scoparia management in Montana. Our objective is to determine the impact of corn, barley, soybean, and sugar beet and varying B. scoparia densities have on overall B. scoparia growth and fecundity. An effective integrated weed management strategy relies on accurate description of biological characteristics and prediction of ecological behaviors of weeds in agricultural situations 52,53 . As part of a diversi ed and ecological approach to weed control and management, taking advantage of competitive crops could be a viable approach to reduce herbicideresistant B. scoparia seedbanks.
Presence of a crop had a profound effect on B. scoparia growth and development compared to its absence (fallow) [ Figure 1]. Among the main effects, the crop treatment affected the width, number of primary branches, biomass plant −1 , biomass m −2 , seeds plant −1 , seeds m −2 , height, and days to owering (all p<0.001) as shown in Table 1. Averaged across B. scoparia densities, the crop treatments decreased the B. scoparia nal width, height, number of primary branches, biomass plant −1 , biomass m −2 , seeds plant −1 , and seeds m −2 compared to fallow treatment (Table 2). Corn and barley were the most suppressive on B. scoparia growth and fecundity. Soybean and sugar beet reduced B. scoparia growth and fecundity compared to fallow treatment but the effects were not as dramatic as compared to the effects of barley or corn (Table 2, Figure 3, Figure 4). B. scoparia width was narrowest in barley and corn at 0.26 and 0.37 m, respectively, followed in ascending order by B. scoparia in sugar beet and soybean at 0.53 and 0.60 m, respectively ( Table 2). B. scoparia was widest at 0.76 m in fallow plots. B. scoparia in barley had the least number of primary branches at 25.7, followed in ascending order by B. scoparia in sugar beet, corn, and soybean at 44.9, 49.9, and 50.3 primary branches, respectively ( Table 2). For fallow, B. scoparia had 53.3 primary branches (HSD=2.1). B. scoparia biomass plant −1 was least in corn and barley at 77 g and 107 g, respectively, followed in ascending order by B. scoparia biomass plant −1 in soybean and sugar beet at 177 g, and 212 g, respectively, and was greatest in fallow at 600 g (Table 2).
Thus, B. scoparia biomass plant −1 was reduced by 87, 82, 70, and 65% in corn, barley, soybean, and sugar beet, respectively, when compared to the fallow treatment. The same trend was observed with respect to biomass m −2 . B. scoparia in corn and barley had the lowest biomasses m −2 at 2,363 g, and 3,254 g, respectively, followed in ascending order by B. scoparia biomasses in soybean and sugar beet at 5,375 g, and 6,430 g m −2 , respectively, and was greatest in fallow at 18,211 g m −2 ( Table 2), which translate to 87, 82, 70, and 65% less biomass m −2 in corn, barley, soybean, and sugar beet, respectively. Seed production plant −1 was lowest in corn and barley at 5,227 and 9,392 seeds plant −1 , respectively, followed in ascending order by B. scoparia in soybean and sugar beet at 38,029 and 45,904 seeds plant −1 , respectively, and was greatest in fallow at 231,979 seeds plant −1 . B. scoparia seed production plant −1 in corn, barley, soybean, and sugar beet was 98, 96, 84 and 80% less, respectively, compared to the seeds plant −1 in fallow (Table 2). Seed production m −2 were lowest for B. scoparia in corn and barley at 158,498 and 284,788 seeds m −2 , respectively, followed in ascending order by B. scoparia in soybean and sugar beet at 1,153,256 and 1,391,927 seeds m −2 , respectively, and was highest in fallow at 7,034,239 seeds m −2 ( Table 2). B. scoparia seeds m −2 was reduced by 98, 96, 84, and 80% in corn, barley, soybean, and sugar beet, respectively, compared to B. scoparia in fallow. Among the different crops, there were additional differential effects. Crop treatment affected the number of days for B. scoparia to reach 50% owering (p<0.001, Figure 2B) with barley having the greatest effect. Time to 50% owering was shortest in sugar beet and soybean at 66.  Figure 2A, Figure 2C) but no interaction was observed between the two factors (p=0.261).  However, B. scoparia biomass m −2 increased 14-fold when B. scoparia density increased from 3 to 188 plants m −2 . The increase in B. scoparia density from 3 to 188 plants per m 2 reduced seeds plant −1 by 85% but increased overall seed production m −2 9-fold.  Figure 4]. However, most signi cant differences were only observed between fallow and crop treatments rather than among crops except for the seeds plant −1 and seeds m −2 response variables. In both instances, density effects were limited for barley and corn crops ( Figure 4A and 4B). In terms of seed production plant −1 in each crop treatment, the increased B. scoparia density showed a decreasing trend ( Figure 4A). In fallow, there were 609,138 seeds plant −1 at the lowest density of 3 plants m − In corn, seeds per plant was 20,729 at lowest density but started to be reduced at density of 13 plants m −2 density with 14,056 seeds plant −1 ( Figure 4A). In terms of B. scoparia seed production per area, the increased B. scoparia density showed an increasing trend in seeds m −2 from each crop treatment ( Figure   4B). In all crop treatments, seed production per area started to be increased starting at 13 plants per m 2 .
At the lowest density, seed production was 1,827,391 seeds m −2 in fallow, 431,663 seeds m −2 in sugar beet, 254,308 seeds m −2 in soybean, 45 As a general rule, B. scoparia grew taller and produced less seeds plant −1 as densities increased (Table 3, Figure 2, and Figure 4). This observation was similar to previous work 40 . In our study, seed production plant −1 started to be affected at a density of 13 and 24 plants m −2 (Table 3 and Figure 4). This occurred regardless of crop treatment indicating that weed to weed competition became signi cant at this point in these crop canopies. With that said, it is important to emphasize that even though B. scoparia seeds plant −1 were decreased as the result of increased B. scoparia densities, the total biomass, and total seeds produced per unit area (m 2 ) were greatly increased by the higher B. scoparia densities (Table 3, Figure 3, and Figure 4). This indicates that high densities allowed B. scoparia plants to better capture and exploit available resources. Interestingly, the patterns of B. scoparia seed production observed in fallow, soybean, and sugar beet were less pronounced in corn and barley plots, which may be an indication that crop on weed competition in these crops was a greater factor on B. scoparia performance than weed to weed competition regardless of B. scoparia densities.

Discussion
Corn had the greatest negative effect on B. scoparia biomass and B. scoparia seed production. Even though B. scoparia plants were tallest in corn compared to other crops, they were thinner stemmed, and had fewer secondary branches, and leaves, resulting in lower biomass and seed production (Table 2, Figure 3, and Figure 4). This dramatic change in B. scoparia's architecture is likely due to its struggle for light interception within the corn canopy. Under irrigated and high fertilizer production system, corn rapidly accumulates biomass and height, thus, light becomes the primary source of competition for weeds 57 . Increases in total canopy leaf area index, height, rate of canopy closure and height at which the leaf area occurs have all been associated with improved tolerance and suppressive ability of corn relative to weeds 58-60 . In particular, corn's relative growth rate and speci c leaf area strongly correlated with relative competitiveness among corn cultivars 61 . This was demonstrated in sweet corn, where the dense canopy and rapid growth of the hybrid variety Rocker was found to contribute to season long performance of sub-rates of the herbicide sethoxydim against Panicum miliaceum (L.) fecundity 62 .
Barley suppression of B. scoparia growth and fecundity was second only to corn. Barley had the greatest effect in reducing B. scoparia height, width, number of primary branches, and in increasing the number of days for B. scoparia to reach owering ( Figure 1, Figure  Unlike corn and barley, B. scoparia would outgrow soybean and sugar beet. B. scoparia in soybean produced less biomass and seeds (both per plant and per unit area) than in sugar beet suggesting that soybean is more competitive than sugar beet. Many different studies have shown that soybean is not very competitive against weeds. One study has shown that soybean is not very competitive at the early growth stages and soybean cultivars vary in their competitive abilities against different weeds with as much as 45% difference in weed biomass observed among soybean cultivar treatments 52,79,80 . Another study showed that variation in soybean canopy width, height, area, and volume have no consistent relationship with soybean competitiveness against weeds 81,82 . Instead, competitiveness was found to be associated with the increased vegetative growth of late-maturing soybean cultivars 82 . To improve weed suppression by soybeans, recommendations that increase the rate of row closure have been suggested including decreasing soybean row width, and increasing planting density 83,84 . Lastly, sugar beet had the least effect on B. scoparia as compared to all other crops in this study. B. scoparia biomass and seed production were greatest in sugar beet, which was second only to fallow (Figure 3 and Figure 4). Like soybean, many studies have shown that sugar beet is poor competitor against weeds. Due to its lowstature and rosette growth habit, sugar beet has been shown susceptible to competition from B. scoparia with signi cant reductions in yield reported even at low B. scoparia densities 85-91 . In the past, sugar beet's sensitivity to weed competition and the many different herbicides available for weed control have led to a complex weed management program that involved mechanical weeding and several herbicide modes of action 92 . Despite the complexity, these herbicide regimens were only 32% effective against B. scoparia, which is lower than those used in corn (99%), soybean (96%), winter wheat (93%) or fallow This study eliminated herbicide effects from those associated with cropping choice. This was particularly important as herbicide options are an especially powerful contributor to B. scoparia control, particularly in corn and barley 44,86 . Our study demonstrated the heightened competitiveness of corn and barley relative to other cropping systems that is independent of herbicide treatment. In addition, nitrogen rates were limited to high (corn and soybeans) and low rates (barley and sugar beets). As quickly becomes apparent while observing the response data, B. scoparia responses were independent of nitrogen rate. The other common cultural practices associated with each crop species were accommodated by the trial design.
Cultural practices (i. e., cultivar choice, irrigation, planting date, seeding rate, row spacing, fertilizer rate) were admittedly confounded with the crop's competitive effects on the weed's overall performance and they may have had a signi cantly affected outcomes for B. scoparia growth and fecundity.
For our trials, B. scoparia was harvested on a single day independent of crop harvest. This disjunction may misrepresent the differences in control different cropping systems offer, particularly barley where crop harvest occurred prior to weed owering. This may be relevant not only for a particular crop but for crop usage as well i.e., hay barley and silage corn. Recently, pulses (i.e., pea, lentil, and chickpea) and oil crops (i.e., camelina, canola) have gained popularity within Montana due to increased demand for plantbased protein for food and feed, and for biofuels. How these crops relate to each other and to the crops used in this study would be of considerable interest especially given their relative sensitivity to herbicides.
In conclusion, corn and barley were the most B. scoparia suppressive crops. Corn's effects on B. scoparia were primarily on biomass, height, and seed production. These effects were likely due to corn's dense, tall canopy that effectively shaded the B. scoparia stand. The most dramatic effect barley had on B. scoparia was in delaying owering until after barley senescence. This may present an opportunity to virtually eliminate B. scoparia seed production if post-senescence weed control practices are applied in a timely manner. If not properly handled however, enough time and resources are available post barley senescence for B. scoparia to recover and produce a signi cant amount of weed seeds in the remainder of the cropping season. Regardless of post-harvest treatment, B. scoparia seed production under barley was still signi cantly reduced relatively with soybean and sugar beet. Barley's effects on B. scoparia likely relate to its ability to rapidly grow and achieve row closure under cool conditions. Soybean and sugar beet were not particularly competitive with B. scoparia. Between them, soybean was the better. Techniques to enhance crop competition include choosing competitive cultivars, narrowing rows, increasing plant population, and orienting rows from east to west 96 . Given the advent of glyphosate-resistant B. scoparia in sugar beet cropping systems and the particular sensitivity of sugar beets to weedy competition, B. scoparia control in sugar beet is a particularly a troublesome issue. With no alternative herbicide option that is effective for its control, B. scoparia will greatly in uence key weed management decisions in sugar beet farms especially when conservation tillage systems (i.e., strip tillage, no-till) are adopted. Additionally, B. scoparia possess biological traits (i.e., high genetic diversity, highly outcrossing, short life cycle, e cient seed dispersal mechanism) that will likely enable it to persist and evolve resistance to a new herbicide site of action (SOA) if introduced as added trait in sugar beet (i.e., stacking dicamba resistance to glyphosate-resistant sugar beet to control glyphosate-resistant B. scoparia eld populations). There is no guarantee that a new SOA will be used/misused with limited intensity and coverage to control resistant weed populations, thus selection pressure towards resistance to multiple SOAs is expected to be high and the utility of the added herbicide trait will be at risk of being lost to resistance. Gaines et al. argued that if the manner of herbicide use remains unchanged, the rate of evolution for multiple herbicide resistance will eventually exceed the rate of new herbicide discovery, and herbicide options available for weed control in certain crops will be much limited in the future even as new SOAs are discovered 97 . An example is the water hemp [Amaranthus tuberculatus (Moq.) J. D. Sauer] population collected from a continuous soybean eld reported resistant to six SOAs 98 which extremely limited herbicide options available for its control. Thus, the importance of integrated weed management approaches in conjunction with other methods (i.e., depleting soil seedbank, maximizing cropping systems diversity, effective monitoring and rapid diagnosis for emerging resistance) to combat herbicide resistance have been greatly emphasized since a new SOA will not solve the issue 97 . In the future, long rotations away from sugar beet and towards crops (and herbicides) that are more suppressive will likely play an important role in B. scoparia management for sugar beet production.
In a time when the advance of herbicide-resistant B. scoparia populations is rapid and widespread 99 , and as herbicide options will increasingly be limited with time 97 , taking advantage of the competitive abilities of crops is not only a robust and effective strategy for short-term weed control but also holds great value in the long-term reduction of B. scoparia soil seedbank through reduced weed seed rain 96 . Additionally, this strategy is simple, inexpensive, and compatible with the mechanized crop production systems in the US Great Plains. Its integration with other weed management strategies such as use of suppressive cultivars, use of cover crops, modifying row width spacing, increasing planting density, and use of harvest replications. Whole plots were the cropping treatments, while sub-plots were the six B. scoparia density treatments randomly placed within each whole plot.
Treatments. The whole-plot crop treatments were sugar beet, soybean, barley, corn, and fallow (bare ground). The crop treatments were randomly assigned within each block. Corn was seeded at a rate of 101, 800 seeds ha − 1 with rows spaced at 76 cm. Soybean was seeded at a rate of 432,400 seeds ha − 1 with rows spaced at 15 cm. Sugar beet was seeded at 123,500 seeds ha − 1 with rows spaced at 61 cm.
Barley was seeded at 2,100,300 seeds ha − 1 with rows spaced at 19 cm. The whole-plot were 6 m by 4.5 m and spaced 4.5 m from neighboring whole-plots. The sub-plot treatments were the increasing B. Crop seeds were planted and mature B. scoparia seeds from the herbicide-susceptible B. scoparia accession were sown within 3 days after crop seeding.
B. scoparia growth and fecundity. B. scoparia plant height, canopy, and number of branches were measured for three representative B. scoparia plants from each experimental plot at the maximum vegetative stage to determine B. scoparia growth. Dates of when the B. scoparia plants from each treatment were rst observed to undergo ower initiation, owering, and seed set were recorded. B. scoparia reproduction data on B. scoparia days-to-ower initiation, days-to-owering, and days-to-seed set were determined by the number of days (starting from B. scoparia emergence) it took for 50% of the B. scoparia plants in each experimental plot to rst form reproductive structures, protruded in orescence and shed pollens, and produced mature dark brown seeds, respectively. B. scoparia seed production was determined by harvesting three representative mature B. scoparia plants from each experimental plot. Seeds from the mature B. scoparia plants were separated and cleaned. All the seeds from the three harvested B. scoparia plants were mixed thoroughly, pooled and total weight of seeds were recorded. From the seed pool, 1000 seeds were counted, and the weight was recorded. The process was repeated three times. The total weight of the pooled seeds was divided by its average 1000-seed weight multiplied by a thousand to determine the total number of seeds from the three B. scoparia plants. The total number of seeds was divided by three to determine B. scoparia seeds plant −1 .
B. scoparia seed viability and seedling vigor. Seed viability test was done at the MSU-SARC physiology laboratory in 2015 and 2016. A total of 125 seeds from each treatment were tested for viability and seedling vigor. Twenty-ve seeds were placed in between two layers of lter papers (Whatman®, Grade 2, Sigma-Aldrich Inc., St. Louis, MO 63178, USA) inside 10-cm diameter petri dishes (Sigma-Aldrich, Sigma-Aldrich Inc., St. Louis, MO 63178, USA) The seeds were soaked with 10ml of double distilled water. B. scoparia seed germination does not require light thus, petri dishes were wrapped in aluminum foil to maintain moisture within each plate and then the plates were placed in an incubator (VMR International, Sheldon Manufacturing Inc., Cornelius, OR 97113, USA) at 25°C for optimum B. scoparia seed germination 54,55 . Radicle length of three randomly selected seedlings from each petri dish was measured 24 h after incubation. Germinated seedlings were counted daily for 15 days and then terminated.
Ungerminated seeds were tested for viability using a 1% w/v tetrazolium chloride solution 33 . Seeds were considered germinated when the radicles emerged, and the tip of the radicle uncoiled 56 . Seed viability was calculated as the percentage of germinated seeds and seeds that were positive in the tetrazolium chloride test. The petri dish experiment was conducted in a randomized complete block with ve replications using the shelves inside the incubator as blocks.
Data analyses. Data were subjected to type 3 split plot analysis of variance test (α = 0.05) combined over trial years following the procmixed procedure in SAS (Statistical Analysis Systems®, version 9.2, SAS Institute Inc., SAS Campus Drive, Cary, NC 27513-2414) to test the signi cance of trial year, treatment, replication, and interaction. The trial year, treatment, and interaction were considered xed effects.
Replication, trial year*replication, and treatment*replication were considered random effects. All observations were transformed to their natural logarithm (log e) values before being subjected to analysis of variance test except for observations taken for days to owering, height, and number of primary branches. Data assumptions for normality of residuals and homogeneity of variance were met when tested with shapiro-wilk and levene's test, respectively, following the procunivariate procedure in SAS. Means were separated using Tukey-Kramer's HSD (α = 0.05) test. Results from the two trial years were not signi cantly different across the response variables. Given the trends within the data being consistent across trial years, the results from two trials were combined for simplicity of presentation.

Declarations Data availability
Data for the current study will be made available by the corresponding author upon request.