Nitrogen-fixing cyanobacteria are vital photosynthetic microorganisms that contribute to soil fertility by fixing atmospheric nitrogen and are also important for maintaining ecosystem stability. These microorganisms can be very sensitive to herbicides because they possess many characteristics of higher plants. Six days after the application of monosulfuron at 0.03 to 0.3 nmol L⁻¹ under laboratory conditions, growth of the nitrogen-fixing cyanobacteria Anabaena flos-aquae, Anabaena azollae, and Anabaena azotica was stimulated, but at higher concentrations (30 to 300 nmol L⁻¹) protein synthesis was inhibited. The production of 16 amino acids in A. flos-aquae was reduced from 7 to 69% with increasing monosulfuron concentration. Application of monosulfuron at 3 to 300 nmol L⁻¹ substantially inhibited in vitro acetolactate synthase (ALS) activity as indicated by 50% inhibition index values of 3.3, 65.2, and 101.3 nmol L⁻¹ for A. flos-aquae, A. azollae, and A. azotica, respectively. In contrast, extractable ALS activity was not affected in these algal species with monosulfuron treatments ranging from 0.03 to 300 nmol L¹ except in A. flos-aquae at higher concentrations (30 to 300 nmol L⁻¹). The most sensitive species to monosulfuron was A. flos-aquae, followed by A. azollae and A. azotica. Molecular analyses showed that the genomic DNA of A. azollae and A. azotica differed in only one amino acid. Results from photogenetic analyses revealed a high degree of homology between these algae. In contrast, the genomic DNA of A. flos-aquae differed from that of A. azollae and A. azotica in 44 and 45 amino acids, respectively. Our findings support the view that monosulfuron toxicity in these three nitrogen-fixing cyanobacteria is due to interference with protein metabolism via inhibition of branch-chain amino acid biosynthesis, and particularly ALS activity.

Nomenclature: Monosulfuron; Anabaena flos-aquae (Lyngb) Breb; Anabaena azollae Strasb; Anabaena azotica Ley

The transgenic corn line 98140 has a high level of resistance to glyphosate and all five chemical classes of herbicides that inhibit acetolactate synthase (ALS). The dual herbicide resistance is due to a molecular stack of two constitutively expressed genes: gat4621, which produces a glyphosate acetyltransferase that rapidly inactivates glyphosate, and hra, which produces a highly resistant ALS. On a rate basis, the positive 98140 isoline with a single copy of the gat4621 gene is over 1,000-fold more resistant to glyphosate than a negative isoline without the transgene. Similarly, the positive 98140 isoline with the hra gene is over 1,000-fold more resistant to ALS-inhibiting herbicides such as chlorimuron and sulfometuron at the whole-plant and enzyme level. The gat4621 and hra genes do not change the natural tolerance of corn to selective herbicides, so new corn hybrids based on 98140 will give growers more options to manage weeds and delay the evolution of herbicide-resistant weeds.

Nomenclature: Chlorimuron, glyphosate, sulfometuron, corn, Zea mays L

Goatsrue is an introduced perennial plant which has proven to have great invasive potential, leading to its classification as a noxious weed in many states and at the federal level. Very little research has been done on its basic biology. Physical dormancy of mature goatsrue seed was tested through scarification with sulfuric acid for up to 60 min resulting in 100% germination. Comparison of dormancy for 26-yr-old and 6-mo-old goatsrue seed indicated that aged seeds had reduced dormancy levels compared to newly harvested seeds. Maximum germination was similar among the 6-mo old and 26-yr-old seed lots, suggesting no loss of viability had occurred in seed stored dry for 26 yr. Goatsrue seedling emergence was inversely related to burial depth, and decreased as burial depth increased. Emergence of seed buried at 0.5 to 3.0 cm soil depth was 93 to 87%, respectively, and no emergence occurred from 12 and 14 cm. When the soil seed bank of five goatsrue-infested areas was sampled, the largest density of seeds found was 74,609 seeds m⁻² while the lowest was 14,832 seeds m⁻². Viability and dormancy of seeds recovered from the soil seed bank survey ranged from 91 to 100% and 80 to 93%, respectively. Management, which reduces the soil seed bank and controls emerging seedlings, is as essential as control of mature goatsrue plants in order to avoid seedling establishment and reinvasion of a location.

Nomenclature: Goatsrue, Galega officinalis L

Seeds from natural populations of fierce thornapple and velvetleaf collected in a corn-growing area in central Spain were incubated at a range of constant temperatures and water potentials to model the progress of germination on the basis of the accumulation of hydrothermal time. Previous to the germination tests, the seeds were treated in two different ways: (1) dark storage under dry conditions (nonchilled seeds), and (2) burying in the original soil at 10-cm depth during 2 mo in winter (naturally chilled seeds). The results indicated different mechanisms inhibiting germination in both weed species. Whereas fierce thornapple displayed some type of embryo dormancy, the lack of germination in velvetleaf appeared to be entirely due to the seed coat. On the other hand, significant differences between nonchilled and naturally chilled seeds in fierce thornapple were observed, mainly due to the decrease in the mean base water potential of the 50th percentile in the latter, which indicated a loss of dormancy by exposure of the seeds to natural conditions. Hydrothermal time appears to be a good description of the germination patterns in both weed species, but in the case of fierce thornapple, only for naturally chilled seeds. Thus, the development of the hydrothermal model in fierce thornapple raises some questions for consideration concerning the influence of the type of seeds (conditions of storage, pretreatments of the seeds before germination tests) on its germination capacity.

Nomenclature: Fierce thornapple, Datura ferox auct. non L. DATFE; velvetleaf, Abutilon theophrasti Medik. ABUTH; corn, Zea mays L

Synthetic seed banks are a useful tool for tracking how weed populations change over time. By sowing a known number of seeds of a given species within a quadrat with defined boundaries, an investigator can measure the number remaining and thereby calculate demographic rates (e.g., mortality). The alternative is to use in situ seeds and estimate their initial population density via sampling. To make a synthetic seed bank approach useful within an agricultural system subjected to soil disturbances such as tillage, one would need a way to account for seeds leaving the initial quadrat (i.e., a way to follow how the area encompassing the sown seeds changes over time). Without accounting for the change in location/extent of the synthetic seed bank, any field operation moving soil will create additional uncertainty in population size. Depending on the “aggressiveness” of specific field operations and the initial size of the quadrat, this effect might be negligible or so large as to be intractable. Here, we describe a method for following a synthetic seed bank over time using a “living boundary” of nondormant seeds, which effectively play the role of tracers used in the study of dynamics in other scientific disciplines. Study quadrats in East Lansing, MI, and Arlington, WI, were sown with giant foxtail and velvetleaf at a rate of 2,000 seeds m⁻². The study quadrats were marked on the perimeter and diagonals using nondormant seeds of three marker species: kale, radish, and rye. The areas were then subjected to tillage and planting operations. Spatial coordinates of seedling locations for the marker and weed species were obtained through digital image processing. A nonparametric comparison of the spatial displacement of marker and weed species indicated that their empirical spatial distributions did not differ. The marker species quadrats described by the 50th, 90th, and 99th quantiles of movement contained all velvetleaf seedlings in Wisconsin, all velvetleaf seedlings in Michigan, and all giant foxtail seedlings in Michigan, respectively. The results suggest a simple rule for applying the method to field demography studies: after the original quadrat is deformed and seedlings have emerged, flag the polygon containing all marker seedlings to obtain the expanded quadrat containing the study weed population.

Nomenclature: Giant foxtail, Setaria faberi Herrm.; velvetleaf, Abutilon theophrasti Medik.; kale, Brassica oleracea L.; radish, Raphanus sativus L.; rye, Secale cereale L

Research was conducted to determine the competitiveness and fitness of a protoporphyrinogen oxidase (protox)-resistant common waterhemp biotype. Protox-resistant and protox-susceptible biotypes were grown under noncompetitive and competitive arrangements in the greenhouse. In the noncompetitive study, a single plant of each biotype was planted separately in 15-cm-diam pots. Photosynthesis, leaf area, and plant biomass were measured 10, 20, 30, and 40 d after transplanting (DATP). In general, photosynthesis rate and plant biomass were similar between biotypes. However, the protox-resistant biotype had higher leaf area than the susceptible biotype at 20, 30, and 40 DATP. A replacement series study was conducted in the greenhouse to evaluate the relative competitiveness of protox-resistant and protox-susceptible common waterhemp. Photosynthesis, leaf area, plant height, and plant biomass were measured 7, 14, 21, and 28 DATP. Protox-resistant and -susceptible common waterhemp were equally competitive 28 DATP. Relative crowding coefficient values 28 DATP were 0.86, 0.89, 1.09, and 1.13 for photosynthesis, leaf area, plant height, and plant biomass, respectively. This suggests protox-resistant and -susceptible common waterhemp were equally competitive and the frequency of protox-resistant biotype is unlikely to decrease in the absence of protox–herbicide selection pressure.

Nomenclature: Common waterhemp, Amaranthus rudis Sauer

Theory and models of crop yield loss from weed competition have led to decision models to help growers choose cost-effective weed management. These models are available for multiple-species weed communities in a single season of several crops. Growers also rely on crop rotation for weed control, yet theory and models of weed population dynamics have not led to similar tools for planning of crop rotations for cost-effective weed management. Obstacles have been the complexity of modeling the dynamics of multiple populations of weed species compared to a single species and lack of data. We developed a method to use limited, readily observed data to simulate population dynamics and crop yield loss of multiple-species weed communities in response to crop rotation, tillage system, and specific weed management tactics. Our method is based on the general theory of density dependence of plant productivity and extensive use of rectangular hyperbolic equations for describing crop yield loss as a function of weed density. Only two density-independent parameters are required for each species to represent differences in seed bank mortality, emergence, and maximum seed production. One equation is used to model crop yield loss and density-dependent weed seed production as a function of crop and weed density, relative time of weed and crop emergence, and differences among species in competitive ability. The model has been parameterized for six crops and 15 weeds, and limited evaluation indicates predictions are accurate enough to highlight potential weed problems and solutions when comparing alternative crop rotations for a field. The model has been incorporated into a decision support tool for whole-farm management so growers in the Central Great Plains of the United States can compare alternative crop rotations and how their choice influences farm income, herbicide use, and control of weeds in their fields.

Weed management decisions based on weed threshold models offer the opportunity to reduce herbicide use by allowing the possibility of forgoing treatment or lowering rates. Weed thresholds based on a relative leaf-cover model were tested during a 4-yr period at two locations. Two 1.62-ha fields, planted to conventional and glyphosate-resistant corn (2004, 2005, 2007) or soybean (2006), were divided in 900 m² sections. Herbicides were applied postemergence to each of these sections with either variable rates based on weed thresholds, or constant full rates. Variable herbicide rates included: no application, half rate, or full rate. Relative weed cover values of 0.2 and 0.4 (corn) or 0.1 and 0.3 (soybean) served as thresholds for incremental rates. Digital images were used to evaluate the relative weed cover. Weed density was assessed before and after herbicide application. Weed seed production was estimated for two species in 2004 and 2005. No difference in crop yield, relative weed cover, weed density, or weed seed production was observed between conventional and glyphosate-resistant cropping systems. During the first year, herbicide use reduction was obtained (−85.4%) with marginal crop yield loss (5 to 15%). In the subsequent 3 yr, preherbicide weed densities increased and concomitant increases in relative weed cover values did not allow more than a 10% overall reduction in herbicide use. This threshold model designed to maintain crop yields within a given year did not allow significant reduction in herbicide use during the following 3 yr. Residual weed populations most likely replenished the seed bank to levels that allowed weed densities to increase afterward. Increased weed density over time in plots treated with full rates of herbicide every year also indicated that a single postemergence herbicide treatment was not sufficient to contain weed populations at low levels every year in this corn–soybean rotation.

Nomenclature: Glyphosate; corn, Zea mays L.; soybean, Glycine max (L.) Merr

In recent years, interest has increased in late-winter sowing of corn in northern Italy because of many agronomic advantages. However, cold and rainy weather slows initial crop growth, which can favor weed infestation. There is, therefore, a need for appropriate timing of weed control tactics based on an understanding of the competitive relationship and dynamics between crop and weeds. Five experiments were conducted over 4 yr, with a series of treatments increasing either duration of interference or length of weed-free period. Yield data were fitted with sigmoidal equations to find the critical point (CP) and critical period of weed control (CPWC). Although the CP is determined only by the competition between weed and crop, the CPWC is also market dependent. To quantify the effect of weed flora on the CP, a multiple regression model was tested, taking into account weed density, inflection point, and slope parameter of the Gompertz model of the cumulated infestation. The results confirmed that the late-winter sowing date increases the importance of late winter– and early spring–emerging weeds. In general, the precompetitive period was longer in the late winter–sown corn than in traditional midspring-sown corn. The delayed start of the CPWC makes control more difficult with a preemergence herbicide, which raises questions on the utility of this agronomic technique. Multiple regression analysis showed that the position of CP can be estimated with the density, earliness, and competitiveness of the infestation. Furthermore, the slope/inflection point ratio of the Gompertz model appears to be independent of sowing date. Results suggest that the weed–crop competition mechanism can be represented with simply the weed flora dynamic parameters and that a combination of crop–weed competition studies and emergence prediction models can predict the position of CP and give useful information about the CPWC and weed management.

Nomenclature: Corn, Zea mays L. cv. ‘PR33 J24’

Rigid brome is a problematic weed of southern Australian cropping systems. Increased knowledge about the ecology of rigid brome and the influence of management strategies on its seedbank dynamics could facilitate development of more effective weed control programs. A field study was undertaken to investigate seedbank persistence and the influence of different management strategies on rigid brome control at Lock in South Australia during 2003 to 2005. Seeds of rigid brome were found to persist in the soil for up to 3 yr, with > 20% of the seedbank persisting from one season to the next. Therefore, a single year management program against this weed species is likely to be ineffective and could result in rapid buildup in weed infestations. However, management strategies that combined effective herbicides (Clearfield^TM technology) and crop competition over consecutive years provided effective control of this troublesome weed. Such cropping systems reduced rigid brome density (1 to 10 plants m⁻²) and seed production (8 to 160 seeds m⁻²) in the final crop of the 3-yr cropping sequence as compared to common grower practice of trifluralin and triasulfuron mixtures (138 plants m⁻²; 1,866 seeds m⁻²). These treatment combinations were able to deplete the initial seedbank (1,748 seeds m⁻²) to manageable levels (< 5 seeds m⁻²) within 3 yr. The results of this study should provide growers with confidence that severe rigid brome infestations can be managed effectively without compromising crop productivity.

Nomenclature: Triasulfuron; trifluralin; rigid brome, Bromus rigidus Roth BRORI

Increased reflection of far-red light among plants can lower the red:far-red ratio (R:FR) of horizontally-propagated light before substantial shading among plants occurs. Although previous research suggests that altered R:FR can affect corn growth, it is not understood how early-season low R:FR (associated with higher plant densities in corn–weed communities than in weed-free corn) affects corn productivity in the field. We conducted field experiments from 2005 to 2007 to determine the effects of reduced R:FR on corn growth and yield. Corn was established at 53,800 plants ha⁻¹ for a control R:FR treatment (weed-free corn) and at 107,600 plants ha⁻¹ for a low R:FR treatment (simulated corn–weed community). The low R:FR treatment was thinned to the control plant density at V7 corn (seven fully-expanded leaf collars), which simulated total weed removal. Before thinning, R:FR (645:735 nm) at V7 corn in the low R:FR treatment (0.23) was less than 50% of that in the control R:FR treatment (0.49) across years. In 2005, stalk diameter, stem length, stem mass, leaf mass, specific leaf area, and total plant mass were less for V5 corn in the low R:FR treatment than in the control R:FR treatment. In 2006, V5 corn was taller in the low R:FR treatment than in the control R:FR treatment, but other morphological characteristics were similar between treatments. The shoot:root ratio of V5 (five fully-expanded leaf collars) (2005) and V7 corn (2006) was not affected by R:FR treatment, nor was shoot mass and grain yield of R6 corn (physiological maturity). Measurements in 2006 indicated that soil moisture and nutrient availability were not limiting and did not differ between treatments. Early-season R:FR in simulated corn–weed communities was similar to that in in situ corn–weed communities. These results suggest that low R:FR typical of early-season corn–weed communities was not associated with corn grain yield loss under field conditions in which water and nutrients were not limiting resources.

Nomenclature: Corn, Zea mays L

The next generation of weed seed germination models will need to account for variable soil microclimate conditions. To predict this microclimate environment we have developed a suite of individual tools (models) that can be used in conjunction with the next generation of weed seed germination models. The three tools that will be outlined here are GlobalTempSIM, GlobalRainSIM, and the soil temperature and moisture model (STM²). Each model was compared with several sets of observed data from worldwide locations. Overall, the climate predictors compared favorably. GlobalTempSIM had a bias between −2.7 and 0.9 C, mean absolute errors between 1.9 and 5.0 C, and an overall Willmott d-index of 0.79 to 0.95 (where d  =  1 represents total agreement between observed and modeled data) for 12 global validation sites in 2007. GlobalRainSIM had a bias for cumulative precipitation ranging from −210 to 305 mm, a mean absolute error between 29 and 311 mm, and a corresponding d-index of 0.78 to 0.99 for the sites and years compared. The high d-indices indicate that the models adequately captured the annual patterns for the validation sites. STM² also performed well in comparisons with actual soil temperatures with a range of −2 to 4.6 C biases and mean absolute errors between 0.7 and 6.8 C, with the d-index ranging from 0.83 to 0.99 for the soil temperature comparisons. The soil moisture prediction annual bias was between −0.09 and 0.12 cm³ cm⁻³, mean absolute errors ranging from 0.02 to 0.16 cm³ cm⁻³, and possessed a d-index between 0.32 and 0.91 for the validation sites. These models were developed in JAVA, are simple to use, operate on multiple platforms (e.g., Mac, personal computer, Sun), and are freely available for download from the U.S. Department of Agriculture Agricultural Research Service website ( http://www.ars.usda.gov/Services/docs.htm?docid=11787).