Weed management during spring crop production in eastern Washington presents many challenges. Many spring crops are weak competitors with weeds. In May of 2010 and 2011, two spring crop trials were initiated near Pullman, WA, to compare the relative competitiveness of barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), lentil (Lens culinaris Medik.), and pea (Pisum sativum L.) using cultivated oat (Avena sativa L.) as a surrogate for wild oat (Avena fatua L.) competition. The experiment was arranged as a split-block split-plot design with four replications. One set of main plots included three oat density treatments (0, 63, and 127 plants m−2), while a second set included each crop species. Crop species main plots were then split into subplots of two different seeding rates (recommended and doubled). Crop populations decreased as oat density increased and increased as crop seeding rate increased. As oat density increased, preharvest crop biomass decreased for all crops, while oat biomass and yield increased. Oat biomass and yield were greater in legume plots compared with cereal plots. Increasing oat density decreased yields for all crops, whereas doubling crop seeding rate increased yields for barley and wheat in 2010 and barley in 2011. Compared with legumes, cereals were taller, produced more biomass, and were more competitive with oat.

Kansas and North Dakota kochia populations identified as chlorsulfuron resistant (R) contained 20 and 30% susceptible (S) plants, respectively. Biotypes that were chlorsulfuron R or S were selected from each field R or S collection and selfed through three generations in the greenhouse. Chlorsulfuron at 7.6 and 17.8 g ai/ha suppressed shoot biomass of the Kansas and North Dakota R biotypes by 50%, respectively, which was a 30- and 105-fold greater dose than that required to reduce the respective S biotypes growth 50%. The R and S kochia biotypes are diploid with 2N = 18 chromosomes. Chlorsulfuron resistance is inherited in kochia as a dominant trait controlled by a single nuclear gene. Thus, the resistance trait can be spread by seed and pollen.

Addition series field experiments were conducted near Moscow, ID, in 1987 and 1988 to determine the relative aggressiveness of spring barley and wild oat and to determine the effect of barley and wild oat density and proportion on barley grain yield and wild oat seed rain. Regression analysis was used to describe the relationship of the aboveground biomass and grain yield to species density. Barley was more aggressive than wild oat. Barley biomass was affected most by intraspecific competition, while wild oat biomass was affected most by interspecific competition. Barley aggressiveness changed little throughout the growing season. Wild oat aggressiveness varied but was always less than barley aggressiveness. Increasing wild oat density had a negative, asymptotic-type effect on barley grain yield at all barley densities. However, the effect of wild oat was greatest at the lower density of barley. Increasing barley density decreased wild oat seed rain.

Seed germination, one aspect of fitness, of chlorsulfuron-resistant (R) and -susceptible (S) kochia biotypes collected in North Dakota and Kansas was compared at 8, 18, and 28 C. Cumulative germination, characterized for each biotype using a Weibull function, was different at 8 and 18 C but not at 28 C. The Kansas R biotype reached 50% and maximum germination 70 and 300 h before Kansas S biotype at 8 C and 12 and 100 h before the S biotype at 18 C, respectively. The North Dakota R biotype reached 50% and maximum germination 12 and 100 h before the North Dakota S biotype at 8 C, respectively, and they were not different at 18 C. The resistance trait affects the cumulative germination process of kochia and may affect resistant-weed management strategies implemented early in the growing season when temperatures are lowest.

Exotic annual weeds on western U.S. rangelands owe at least part of their invasion success to prolific seed production. Reproductive output is determined largely by timing of flowering in relation to soil moisture, light, and competing vegetation. This study investigated the influence of temperature (including vernalization), photoperiod, and intraspecific competition on reproductive phenology in three populations (two varieties, typica and bracbypappa) of common crupina. Monthly plantings at four densities were grown in field plots through two consecutive cycles, and the date each plant reached bud and flowering stage was recorded. Development of greenhouse-grown plants from the same populations was compared with those grown outside for 4, 6, 8, and 10 wk of cold induction. Reproductive development in common crupina was influenced by all factors investigated: temperature, photoperiod, density, and vernalization. Conditions fostering the shortest thermal time from emergence to floral induction were a period of cold temperatures/short photoperiod as seedlings followed by warming temperatures and lengthening photoperiod. Both varieties of common crupina responded quantitatively to vernalization, but lack of vernalization caused a greater delay of flowering in var. brachypappa than in var. typica. Vernalization contributed to convergence of spring flowering among the August to December plantings, but earlier emergence and lower plant density greatly increased final plant size and fecundity. Lack of vernalization, high temperatures, and shortening day length delayed flowering of spring/summer emergents, increasing the probability of succumbing to drought before producing seed.

Exotic annual weeds on western U.S. rangelands, including yellow starthistle, owe at least part of their invasion success to prolific seed production. Occurrence of flowering in relation to soil moisture and development of competing vegetation heavily influences reproductive output. Yellow starthistle flowers much later than associated Mediterranean invaders, which avoid summer drought by early flowering and senescence. This study used successive planting dates and four densities to investigate the influence of temperature, photoperiod, and intraspecific competition on reproductive phenology in a population of yellow starthistle from Lewiston, ID. A base temperature for seed germination of 2 C was determined by experiments at constant temperatures. Under the conditions of this study, density, photoperiod, and vernalization did not regulate reproductive development, as measured by onset of bud, flowering, and achene dispersal stages. A thermal time model adequately predicted phenology in this population of yellow starthistle. Plants emerging between October and July required about 1,240 degree days for 50% of the plants to reach bud stage, and an additional 500 and 900 degree days to flowering and achene dispersal, respectively. The relatively long time from emergence to mature achenes in this species influences management options such as prescribed fire, livestock grazing, and management of competing vegetation. Insensitiviry to photoperiod and lack of a vernalization requirement allow late germinating plants to reproduce if moisture is adequate.

The effect of barley seeding rate and row spacing, and triallate, diclofop, and difenzoquat herbicide rate on barley grain yield and quality, and wild oat control were evaluated in field experiments near Bonners Ferry, Idaho, in 1989 and 1990. The purpose of the study was to develop integrated control strategies for wild oat in spring barley. Barley row spacing (9 and 18 cm) did not affect barley grain yield. Barley grain yield was greatest when barley was seeded at 134 or 201 kg ha–1 compared to 67 kg ha–1. Wild oat control increased as wild oat herbicide rate increased and barley grain yield was greatest when wild oat herbicides were applied. However, barley grain yield was similar when wild oat biomass was reduced by either 65 or 85% by applications of half and full herbicide rates, respectively. Net return was greatest when the half rate of herbicide was applied to 100 wild oat plants per m2 and was greatest when half or full herbicide rates were applied to 290 wild oat plants per m2. Net return increased when the seeding rate was increased to 134 or 201 kg ha–1 when no herbicide was applied and when 290 wild oat plants per m2 were present.

Repeated use of sulfonylurea herbicides in continuous, no-till winter wheat selected for a herbicide resistant biotype of prickly lettuce in Idaho. Greenhouse experiments were conducted to compare the relative competitiveness and growth rate of sulfonylurea herbicide resistant (R) and susceptible (S) prickly lettuce. The S biotype of prickly lettuce produced 31% more aboveground biomass than the R biotype averaged over all densities. Both biotypes were equally competitive when analyzed for both inter- and intrabiotype competition. In relative growth rate studies, regression analysis showed that the S biotype accumulated biomass 52% faster than the R biotype. The results of this study showed that the S biotype was superior to the R biotype in biomass production and growth rate, but competitiveness appeared to be equal for both biotypes. Other fitness parameters must be measured before fitness differences between biotypes can be determined.

The persistence of herbicide-resistant biotypes within a given weed population can be highly correlated with the longevity of its seed in the soil and its reproductive ability. This study compared seed longevity of sulfonylurea-susceptible (S) and -resistant (R) biotypes of prickly lettuce in soil at three depths and two locations. Seed longevity in soil was not different between R and S biotypes. Seed longevity was longer when seed were buried compared to seed placed on the soil surface. A field study on seed production showed that prickly lettuce plants produced an average of 14 flower heads and 181 seed per day. Average seed weight was 0.6 mg. No differences were observed in the fecundity or seed viability between the R and S biotypes. However, seed from R biotype plants germinated as fast or faster than seed from S biotype plants.

Growth, competitiveness, and fecundity differences between resistant (R) and susceptible (S) biotypes affect management strategies. This greenhouse research examines growth, competitiveness, and fecundity of chlorsulfuron-resistant (R) and -susceptible (S) kochia collected from North Dakota and Kansas. In noncompetitive studies, sulfonylurea R and S kochia biotypes from Kansas and North Dakota had similar growth rates and seed production. All biotypes produced about 12000 seeds per plant. Competitiveness of R and S biotypes from Kansas was similar. Interbiotype competition reduced R and S plant biomass more than intrabiotype competition. The relative competitiveness of the R and S biotypes was 0.75 and 0.85, respectively. The resistance trait did not reduce growth, seed production, and competitiveness of R compared to S kochia in greenhouse studies.

The movement of sulfonylurea herbicide-resistant (R) kochia pollen was investigated in a spring barley field near Moscow, ID, using a Nelder plot design in 1991 and 1992. Each 61 m diameter plot had 16 rays spaced 22.5° apart and contained 211 kochia plants. There were 12 susceptible (S) plants and one R plant along each ray. The R and S plants were 1.5 m and 3.0 to 30.5 m from the center of the plot, respectively. Wind direction and speed in the 16 vectors, air and soil temperature, and rainfall were monitored continuously. Mature kochia seed was collected from individual plants, planted in the greenhouse, and sprayed with chlorsulfuron to test for resistant F1 progeny. Results from the 2-yr study showed outcrossing of R pollen onto S plants at rates up to 13.1% per plant 1.5 m from the R plants and declining to 1.4% per plant or less 29 m from the R plants. At least 35% of the total R x S crosses occurred in the direction of prevailing southeastward winds. Predicted percentages of R x S crosses per plant ranged from 0.16 to 1.29 at 1.5 m, and 0.00 to 0.06% at 29 m. Thus, resistant kochia pollen can spread the sulfonylurea-resistant trait at least 30 m during each growing season.

Thermal time models for predicting phenological development require an estimate of base temperature, an attribute not previously defined for common crupina, a Mediterranean winter annual introduced in western North America. The stage of seed germination was selected for estimating base temperature, because facilities were available for experiments over a range of constant temperatures and base temperature is relatively constant throughout the life cycle in other species. Achenes from three populations of common crupina, including two varieties, typica and brachypappa, were produced under uniform conditions. Cumulative germination was recorded at 12 h intervals for achenes in darkness and optimum moisture at 23 constant temperatures from 4 to 17 C. The time course of germination was best described by a logistic growth curve from which time to 50% germination was estimated. A parabolic model provided the best fit in a regression of germination rate (reciprocal of time to 50%) against the temperature gradient, yielding base and optimum temperatures of 1 and 10.5 C, respectively. Bootstrap confidence intervals indicated no significant difference in base and optimum temperatures in germination between the two varieties nor between two populations of var. typica of common crupina introduced in the northwestern United States.

Dose–response analysis is widely used in biological sciences and has application to a variety of risk assessment, bioassay, and calibration problems. In weed science, dose–response methodologies have typically relied on least squares estimation under the assumptions of normal, homoscedastic, and independent errors. Advances in computational abilities and available software, however, have given researchers more flexibility and choices for data analysis when these assumptions are not appropriate. This article will explore these techniques and demonstrate their use to provide researchers with an up-to-date set of tools necessary for analysis of dose–response problems. Demonstrations of the techniques are provided using a variety of data examples from weed science.

Wild oat, a troublesome weed in small grain cereals, infests about 11 million ha of cropland in the United States. Diversifying cereal production with alternative crops, such as yellow mustard and canola, provides flexible cropping systems, decreases production risks, and may allow more effective weed suppression. A greenhouse study was conducted to assess the competitive ability of yellow mustard and canola with wild oat in 1999 and 2000, using replacement series interference experiments to relate the results to plant development stages. Yellow mustard, regardless of its proportion in mixture, reduced aboveground biomass of wild oat 33 to 66%, leaf and tiller number 34 to 36%, and panicle production 58% compared with wild oat in monoculture. Canola did not affect wild oat biomass in mixtures. Yellow mustard per plant biomass in 2000 and inflorescence production in 1999 decreased 30 and 20% with increased density of yellow mustard in mixtures. Yellow mustard biomass was not affected by the addition of wild oat to the mixture, indicating the greater importance of intraspecific competition between yellow mustard relative to interspecific competition with wild oat. Canola per plant biomass was affected more by interspecific competition with wild oat than by intraspecific competition. A second greenhouse experiment was conducted to compare plant height and biomass accumulation by the three species over 7 wk. Yellow mustard had the greatest biomass accumulation and plant elongation rate, followed by canola and wild oat. The greater competitive ability of yellow mustard with wild oat, compared with canola, is likely associated with the rapid growth and canopy elevation of yellow mustard.

Farmers grow crops in the dryland region of the Pacific Northwest (PNW) using tillage practices ranging from moldboard plowing to no-tillage. The objective of this study was to determine the effect of tillage on persistence of imazamox herbicide in intermediate and high precipitation zones of the inland PNW. Along with a nontreated control, imazamox was applied to imidazolinone-tolerant winter wheat in the fall and spring at one, two, and three times the maximum labeled rate at locations near Genesee, ID, Davenport, WA, and Pendleton, OR. Moldboard plow, chisel plow, and no-till tillage treatments were implemented soon after wheat harvest and yellow mustard was planted the following season to determine crop response. Experiments were conducted at each location in 2005 to 2007 and 2006 to 2008. There were significant location by year and year and location interactions. There was no significant tillage by imazamox rate interaction, except at Pendleton in year 2, for all measured yellow mustard responses (crop injury, biomass, and yield). Genesee was colder than Pendleton and had more precipitation than Davenport, resulting in more injury to yellow mustard at Genesee than at Pendleton but less than at Davenport. Davenport had greater injury than the other two locations, likely due to lower soil pH, higher organic matter (OM), and cooler, drier climate, which allowed imazamox to persist longer in the soil. Overall, Pendleton had the least yellow mustard injury, which likely was related to its warmer, wetter climate and the concomitant rapid soil dissipation of imazamox. Tillage did not reduce the persistence of imazamox. Yellow mustard had the lowest injury and had greater mature biomass and seed yield in no-till seeded plots when averaged across imazamox rates compared to moldboard and chisel-plowed plots.

Failure to detect noxious weeds with current survey methods prevents their control and has contributed to their ability to establish and spread in remote range and forest sites. Techniques used in remote sensing can classify plant occurrence on maps, offering a method for surveying invasive species in remote locations and across extensive areas. An imaging hyperspectral spectrometer recorded images on July 19, 1998 in Farragut State Park near Bayview, ID, in the reflected solar region of the electromagnetic spectrum ranging from 440 to 2,543 nm to detect spotted knapweed. The sensor records 128 spectral bands in 12- to 16-nm intervals at a spatial resolution of 5 m. A spectral angle mapper (SAM) algorithm was used to classify the data. Infestations in Idaho with 70 to 100% spotted knapweed cover that were 0.1 ha were detected regardless of the classification angle. However, narrow angles (2 to 8°) did not completely define the extent of the infestation, and the widest angle tested (20°) falsely classified some areas as infested. The overall image error for all classes was lowest (3%) when SAM angles ranged from 10 to 11°. Specific errors for the spotted knapweed class for the 10 to 11° angles showed that omissional and commissional errors were less than 3%. Areas with as little as 1 to 40% spotted knapweed cover were detected with an omissional error of 1% and a commissional error of 6%. Further verification sites were established on August 11, 1998 near Bozeman, MT, using the algorithms developed for Idaho. The omissional error for the Montana sites was 0%, and the commissional error was 10%. The hyperspectral sensor, Probe 1, proved an effective detection tool with the ability to detect spotted knapweed infestations.

Digital imagery from satellites and airborne remote sensing offer an opportunity to accurately detect weed infestations. Image resolution and plant growth stage are critical factors for maximum weed detection with low errors. Data analysis in traditional image assessment has relied on agreement measures, such as Cohen's kappa and asymptotic procedures, that compare what is on the image but not on the ground and what is on the ground but not on the image. Statistical comparisons of multispectral images, however, require some knowledge of the variability of the image classification results to determine significant differences among agreement measures. Bayesian methods were used to develop probability distributions for an agreement measure, conditional kappa, and were then subsequently applied to assess and compare image resolutions and plant growth stages. Results showed that images of a study site known to have yellow starthistle populations could identify the noninfested areas with greater accuracy than infested areas at spatial resolutions of 0.5, 1.0, 2.0, and 4.0 m. The detection accuracy of yellow starthistle in the images taken either prebloom or at flowering with 4.0-m spatial resolution usually was equal to or better than spatial resolutions of 0.5, 1.0, and 2.0 m for the cover classes that were not, moderately (31 to 70%), and highly (71 to 100%) infested. The 0.5-m resolution was better than 4.0-m spatial resolution when detecting the moderate cover class, but both resolutions had high omissional and commissional errors. Contrasting the best detection resolution for finding yellow starthistle colonies across flight times indicated that flying at flowering stage with the 4.0-m spatial resolution provided the best detection of the yellow starthistle cover classes considered. In the cases where different spatial resolutions resulted in equal detection accuracy, the larger spatial resolution was selected because of lower costs of acquiring and processing the data.

Yellow starthistle is an invasive plant species common in the semiarid climate of central Idaho and other western states. Early detection of yellow starthistle and estimation of its infestation potential in semiarid grasslands have important scientific and managerial implications. Weed detection and delineation of infestations are often carried out by using ground survey techniques. However, such methods can be inefficient and expensive in detecting sparse infestations. The distribution of yellow starthistle over a large region may be affected by various landscape variables such as elevation, slope, and aspect. These exogenous variables may be used to develop prediction models to estimate the potential for yellow starthistle invasion into new areas. A nonlinear prediction model has been developed using a polar coordinate transformation of landscape characteristics to predict the likelihood of yellow starthistle occurrence in north-central Idaho. The study region included the lower Snake River and parts of the Salmon and Clearwater basins encompassing various land-use (range, pasture, and forest) categories. The model provided accurate estimates of yellow starthistle incidence within each specified land-use category and performed well in subsequent statistical validations. This prediction model can assist land managers in focusing their efforts by identifying specific areas for survey.

The transfer of herbicide resistance genes from crops to related species is one of the greatest risks of growing herbicide-resistant crops. The recent introductions of imidazolinone-resistant wheat in the Great Plains and Pacific Northwest regions of the United States and research on transgenic glyphosate-resistant wheat have raised concerns about the transfer of herbicide resistance from wheat to jointed goatgrass via introgressive hybridization. Field experiments were conducted from 2000 to 2003 at three locations in Washington and Idaho to determine the frequency and distance that imidazolinone-resistant wheat can pollinate jointed goatgrass and produce resistant F1 hybrids. Each experiment was designed as a Nelder wheel with 16 equally spaced rays extending away from a central pollen source of ‘Fidel-FS4’ imidazolinone-resistant wheat. Each ray was 46 m long and contained three rows of jointed goatgrass. Spikelets were collected at maturity at 1.8-m intervals along each ray and subjected to an imazamox screening test. The majority of all jointed goatgrass seeds tested were not resistant to imazamox; however, 5 and 15 resistant hybrids were found at the Pullman, WA, and Lewiston, ID, locations, respectively. The resistant plants were identified at a maximum distance of 40.2 m from the pollen source. The overall frequency of imazamox-resistant hybrids was similar to the predicted frequency of naturally occurring acetolactate synthase resistance in weeds; however, traits with a lower frequency of spontaneous mutations may have a relatively greater risk for gene escape via introgressive hybridization.

Yellow starthistle is an invasive plant of canyon grasslands in north-central Idaho. The distribution of yellow starthistle is associated with general landscape characteristics that include land use and specific terrain-related features such as elevation, slope, and aspect. Slope and aspect can be considered as indicators of plant community composition and distribution. Hence, these variables may be incorporated into prediction models to estimate the likelihood of yellow starthistle occurrence because plant communities differ in susceptibility to invasion. An empirically derived nonlinear model based on landscape characteristics has previously been developed to predict the likelihood of yellow starthistle occurrence in north-central Idaho. Although the model was used to predict the invasion potential of yellow starthistle into new areas, it could also be used as auxiliary data for classifying this weed species in remotely sensed imagery. To accomplish this, the predicted values from the model are regarded as prior information on the presence of yellow starthistle. A Bayesian image classification algorithm using this prior information is then applied to a corresponding set of remotely sensed data. This results in a map indicating the posterior probabilities of yellow starthistle occurrence given the landscape characteristics. This technique is demonstrated and is shown to reduce omissional error rates by 50% when the landscape characteristics are incorporated into the classification process.