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The objective of this paper was to review the reproductive biology, herbicide-resistant (HR) biotypes, pollen-mediated gene flow (PMGF), and potential for transfer of alleles from HR to herbicide-susceptible grass weeds including barnyardgrass, creeping bentgrass, Italian ryegrass, johnsongrass, rigid (annual) ryegrass, and wild oats. The widespread occurrence of HR grass weeds is at least partly due to PMGF, particularly in obligate outcrossing species such as rigid ryegrass. Creeping bentgrass, a wind-pollinated turfgrass species, can efficiently disseminate herbicide resistance alleles via PMGF and movement of seeds and stolons. The genus Agrostis contains about 200 species, many of which are sexually compatible and produce naturally occurring hybrids and hybrids with species in the genus Polypogon. The self-incompatibility, extremely high outcrossing rate, and wind pollination in Italian ryegrass clearly point to PMGF as a major mechanism by which herbicide resistance alleles can spread across agricultural landscapes, resulting in abundant genetic variation within populations and low genetic differentiation among populations. Italian ryegrass can readily hybridize with perennial ryegrass and rigid ryegrass due to their similarity in chromosome numbers (2n = 14), resulting in interspecific gene exchange. Johnsongrass, barnyardgrass, and wild oats are self-pollinated species, so the potential for PMGF is relatively low and limited to short distances; however, seeds can easily shatter upon maturity before crop harvest, leading to wider dispersal. The occurrence of PMGF in reviewed grass weed species, even at a low rate, is greater than that of spontaneous mutations conferring herbicide resistance in weeds and thus can contribute to the spread of herbicide resistance alleles. This review indicates that the transfer of herbicide resistance alleles occurs under field conditions at varying levels depending on the grass weed species.
Multiple resistance to glyphosate, sethoxydim, and paraquat was previously confirmed in two Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] populations, MR1 and MR2, in northern California. Preliminary greenhouse studies revealed that both populations were also resistant to imazamox and mesosulfuron, both of which are acetolactate synthase (ALS)-inhibiting herbicides. In this study, three subpopulations, MR1-A (from seed of MR1 plants that survived a 16X rate of sethoxydim), MR1-P (from seed of MR1 plants that survived a 2X rate of paraquat), and MR2 (from seed of MR2 plants that survived a 16X rate of sethoxydim), were investigated to determine the resistance level to imazamox and mesosulfuron, evaluate other herbicide options for the control of these multiple resistant L. perenne ssp. multiflorum, and characterize the underlying ALS-inhibitor resistance mechanism(s). Based on LD50 values, the MR1-A, MR1-P, and MR2 subpopulations were 38-, 29-, 8-fold and 36-, 64-, and 3-fold less sensitive to imazamox and mesosulfuron, respectively, relative to the susceptible (Sus) population. Only MR1-P and MR2 plants were cross-resistant to rimsulfuron, whereas both MR1 subpopulations were cross-resistant to imazethapyr. Pinoxaden (ACCase inhibitor [phenylpyrazoline 'DEN']) only controlled MR2 and Sus plants at the labeled field rate. However, all plants were effectively controlled (>99%) with the labeled field rate of glufosinate. Based on I50 values, MR1-A, MR-P, and MR2 plants were 712-, 1,104-, and 3-fold and 10-, 18-, and 5-fold less responsive to mesosulfuron and imazamox, respectively, than the Sus plants. Sequence alignment of the ALS gene of resistant plants revealed a missense single-nucleotide polymorphism resulting in a Trp-574-Leu substitution in MR1-A and MR1-P plants, heterozygous in both, but not in the MR2 plants. An additional homozygous substitution, Asp-376-Glu, was identified in the MR1-A plants. Addition of malathion or piperonyl butoxide did not alter the efficacy of mesosulfuron on MR2 plants. In addition, the presence of 2,4-D had no effect on the response of mesosulfuron on the MR2 and Sus. These results suggest an altered target site is the mechanism of resistance to ALS inhibitors in MR1-A and MR1-P plants, whereas a non–target site based resistance apparatus is present in the MR2 plants.
Reduced control of Italian ryegrass in California with herbicides has raised concerns about the evolution of populations with resistance to multiple herbicides. The goal of this study was to investigate variation among populations in plant response and resistance to glyphosate and glufosinate in Italian ryegrass from vineyards and orchards in northwest California. Population resistance screening using field-collected seed revealed up to 56.9% of individuals surviving glyphosate treatment at 1,678 g ae ha−1, and 53.5% of individuals surviving glufosinate treatment at 2,242 g ai ha−1 in the same population. Frequencies of surviving plants within populations varied among screening times, particularly for glufosinate. Treating vegetatively propagated, genetically identical tillers with each herbicide pointed to separate mechanisms of resistance rather than cross-resistance to glyphosate and glufosinate. Dose–response experiments were conducted for each herbicide at two different screening times using a subset of populations, field-collected seed, and 10 herbicide rates. Plant survival and biomass were evaluated for each population at 3 wk after treatment and for plant regrowth 1 wk thereafter. Log-logistic regression models fit to the data were used to estimate LD50, GR50, and RD50 values and calculate resistance indices (R/S ratios). Based on LD50 values, the most highly resistant population was 14.4- to 19.2-fold more resistant to glyphosate than the most susceptible population tested but only 1.6- to 2.0-fold more resistant to glufosinate than the most susceptible population tested. Levels of resistance to both herbicides varied with screening time period and variable measured. Results indicate high frequencies of glyphosate-resistant plants but an early stage in the evolution of glufosinate resistance in some Italian ryegrass populations of northwest California.
The importance of various factors influencing the evolution of herbicide resistance in weeds is critically examined using population genetic models. The factors include gene mutation, initial frequency of resistance alleles, inheritance, weed fitness in the presence and absence of herbicide, mating system, and gene flow. Where weed infestations are heavy, the probability of selecting for resistance can be high even when the rate of mutation is low. Subsequent to the occurrence of a resistant mutant, repeated treatments with herbicides having the same mode of action can lead to the rapid evolution of a predominantly resistant population. At a given herbicide selection intensity, the initial frequency of resistance alleles determines the number of generations required to reach a specific frequency of resistant plants. The initial frequency of resistance alleles has a greater influence on the evolutionary process when herbicides impose weak selection, as opposed to very strong selection. Under selection, dominant resistance alleles increase in frequency more rapidly than recessive alleles in random mating or highly outcrossing weed populations. In highly self-fertilizing species, dominant and recessive resistance alleles increase in frequency at approximately the same rate. Gene flow through pollen or seed movement from resistant weed populations can provide a source of resistance alleles in previously susceptible populations. Because rates of gene flow are generally higher than rates of mutation, the time required to reach a high level of resistance in such situations is greatly reduced. Contrary to common misconception, gene flow from a susceptible population to a population undergoing resistance evolution is unlikely to slow the evolutionary process significantly. Accurate measurements of many factors that influence resistance evolution are difficult, if not impossible, to obtain experimentally. Thus, the use of models to predict times to resistance in specific situations is markedly limited. However, with appropriate assumptions, they can be invaluable in assessing the relative effectiveness of various management practices to avoid, or delay, the occurrence of herbicide resistance in weed populations.
In F2 progeny, derived from F1 hybrids, shoot growth of seedlings, measured 4 d after germination, distinguished susceptible (S) and resistant (R) phenotypes. Chisquare values indicated that the F2 data fit a 3:1 (S:R) ratio for both populations and all trifluralin concentrations in which S and R phenotypes could be differentiated. Results indicate that trifluralin resistance in these green foxtail populations is controlled by a single, nuclear recessive gene. This study is the first to demonstrate recessive gene control of herbicide resistance in a weed species. The highly selfed nature and prolific seed production of green foxtail may have facilitated evolution of the recessive trait.
Crop yield loss–weed density relationships critically influence calculation of economic thresholds and the resulting management recommendations made by a bioeconomic model. To examine site-to-site and year-to-year variation in winter Triticum aestivum L. (winter wheat)–Aegilops cylindrica Host. (jointed goatgrass) interference relationships, the rectangular hyperbolic yield loss function was fit to data sets from multiyear field experiments conducted at Colorado, Idaho, Kansas, Montana, Nebraska, Utah, Washington, and Wyoming. The model was fit to three measures of A. cylindrica density: fall seedling, spring seedling, and reproductive tiller densities. Two parameters: i, the slope of the yield loss curve as A. cylindrica density approaches zero, and a, the maximum percentage yield loss as A. cylindrica density becomes very large, were estimated for each data set using nonlinear regression. Fit of the model to the data was better using spring seedling densities than fall seedling densities, but it was similar for spring seedling and reproductive tiller densities based on the residual mean square (RMS) values. Yield loss functions were less variable among years within a site than among sites for all measures of weed density. For the one site where year-to-year variation was observed (Archer, WY), parameter a varied significantly among years, but parameter i did not. Yield loss functions differed significantly among sites for 7 of 10 comparisons. Site-to-site statistical differences were generally due to variation in estimates of parameter i. Site-to-site and year-to-year variation in winter T. aestivum–A. cylindrica yield loss parameter estimates indicated that management recommendations made by a bioeconomic model cannot be based on a single yield loss function with the same parameter values for the winter T. aestivum-producing region. The predictive ability of a bioeconomic model is likely to be improved when yield loss functions incorporating time of emergence and crop density are built into the model's structure.
The inheritance of resistance to dicamba in wild mustard was determined by making reciprocal crosses between a resistant (R) population derived from a field treated repeatedly with auxin-type herbicides, and a known susceptible (S) population. The resulting F1 hybrids were selfed to produce F2 populations and backcrossed to the S parent. At the three- to four-leaf stage, parental, F1, F2, and backcross populations were screened for resistance to dicamba at three dosages (50, 200, and 400 g ai ha−1). F1 progeny survived all dosages and exhibited levels of injury similar to the R parental population. F2 populations segregated in a 3:1 ratio of R to S phenotypes. Progeny of backcrosses segregated in a 1:1 (R:S) ratio. Responses of the F1, F2, and backcross populations to treatment with dicamba indicate that resistance is determined by a single, completely dominant nuclear allele.
Basic factors contributing to the rapid evolution and broad distribution of acetolactate synthase (ALS)-inhibiting herbicide resistance in smallflower umbrella sedge L. have not yet been investigated. The objectives of this study were to examine patterns of cross-resistance to ALS herbicides and genetic diversity within and among smallflower umbrella sedge populations in California rice fields to provide insight into the processes contributing to resistance spread. Twelve different patterns of herbicide cross-resistance were found across the 56 populations sampled. The frequency of populations with at least one resistant individual in the North, Central and South Sacramento Valley, and the San Joaquin Valley were 76, 86, 67, and 50%, respectively. Analysis of the genetic diversity of 29 populations using 73 sequence-related amplified polymorphism molecular markers revealed little genetic diversity within populations, with estimates of Nei's gene diversity index, h, ranging from 0 to 0.049, and Shannon's information index (I) ranging from 0 to 0.079. Hierarchical analyses of molecular variance indicated that the majority of genetic variation was partitioned among populations, rather than within populations or among regional groups. No isolation by distance was evident. Unweighted pair group method with arithmetic averages analysis indicated that population clustering was not region specific. The results suggest that resistance to ALS-inhibiting herbicides in smallflower umbrella sedge populations from California rice fields appears to have evolved independently multiple times rather than spread from a single population where resistance originated. Consequently, prevention and management of smallflower umbrella sedge in California rice fields should emphasize in-field strategies that focus on decreasing the selection pressure caused by ALS-inhibiting herbicides.
Recent advances in molecular methods and statistical analyses provide weed scientists with powerful tools for examining the genetic structure of weedy plant populations. The value of these studies depends on effective sampling protocols; however, there is little consensus on how to sample plant populations for genetic diversity analyses. In this review, we draw on published literature that incorporates sampling theory and spatial statistics in population genetic analyses to identify key factors to consider when designing a sampling strategy. We discuss how sampling design is affected by research objectives, biology of the study species, population structure, marker choice, and the genetic parameters to be investigated, and we offer suggestions on defining sampling units and developing sampling protocols.
Resistance to the thiocarbamates has been selected in early watergrass populations within the rice-growing region of California. To elucidate the processes contributing to the spread of resistance among rice fields, we characterized the genetic diversity and differentiation of thiobencarb-resistant (R) and thiobencarb-susceptible (S) populations across the Central Valley using microsatellite markers. A total of 406 individuals from 22 populations were genotyped using seven nuclear microsatellite primer pairs. Three analytical approaches (unshared allele, Shannon–Weaver, and allelic-phenotype statistics) were used to assess genetic diversity and differentiation in the allohexaploid species. Low levels of genetic variation were detected within populations, consistent with other highly selfing species, with S populations tending to be more diverse than R populations. FST values indicated that populations were genetically differentiated and that genetic differentiation was greater among S populations than R populations. Principal coordinate analysis generated two orthogonal axes that explained 88% of the genetic variance among early watergrass populations and differentiated populations by geographical region, which was associated with resistance phenotype. A Mantel test revealed that genetic distances between R populations were positively correlated with the geographical distances separating populations. Taken together, our results suggest that both short- and long-distance seed dispersal, and multiple local and independent evolutionary events, are involved in the spread of thiobencarb-resistant early watergrass across rice fields in the Sacramento Valley. In contrast, resistance was not detected in early watergrass populations in the San Joaquin Valley.
Weed science has contributed much to agriculture, forestry and natural resource management during its history. However, if it is to remain relevant as a scientific discipline, it is long past time for weed scientists to move beyond a dominating focus on herbicide efficacy testing and address the basic science underlying complex issues in vegetation management at many levels of biological organization currently being solved by others, such as invasion ecologists and molecular biologists. Weed science must not be circumscribed by a narrowly-defined set of tools but rather be seen as an integrating discipline. As a means of assessing current and future research interests and funding trends among weed scientists, the Weed Science Society of America conducted an online survey of its members in summer of 2007. There were 304 respondents out of a membership of 1330 at the time of the survey, a response rate of 23%. The largest group of respondents (41%) reported working on research problems primarily focused on herbicide efficacy and maintenance, funded mainly by private industry sources. Another smaller group of respondents (22%) reported focusing on research topics with a complex systems focus (such as invasion biology, ecosystem restoration, ecological weed management, and the genetics, molecular biology, and physiology of weedy traits), funded primarily by public sources. Increased cooperation between these complementary groups of scientists will be an essential step in making weed science increasingly relevant to the complex vegetation management issues of the 21st century.
Selection by herbicides has resulted in widespread evolution of herbicide resistance in agricultural weeds. In California, resistance to glyphosate was first confirmed in rigid ryegrass in 1998. Objectives of this study were to determine the current distribution and level of glyphosate resistance in Italian ryegrass, and to assess whether resistance could be due to an altered target site. Seeds were sampled from 118 populations and seedlings were treated with glyphosate at 866 g ae ha−1. Percentage of survivors ranged from 5 to 95% in 54 populations. All plants from 64 populations died. One susceptible (S) population, four putatively resistant (R) populations, and one S accession from Oregon were used for pot dose–response experiments, shikimic acid analyses, and DNA sequencing. Seedlings were treated with glyphosate at eight rates, ranging from 108 to 13,856 g ae ha−1. Shoot biomass was evaluated 3 wk after treatment and fit to a log-logistic regression equation. On the basis of GR50 (herbicide rate required to reduce growth by 50%) values, seedlings from putatively R populations were roughly two to 15 times more resistant to glyphosate than S plants. Shikimic acid accumulation was similar in all plants before glyphosate treatment, but at 4 and 7 DAT, S plants from California and Oregon accumulated approximately two and three times more shikimic acid, respectively, than R plants. Sequencing of a cDNA fragment of the EPSPS coding region revealed two different codons, both of which encode proline at amino acid position 106 in S individuals. In contrast, all R plants sequenced exhibited missense mutations at site 106. Plants from one population revealed a mutation resulting in a proline to serine substitution. Plants from three R populations exhibited a mutation corresponding to replacement of proline with alanine. Our results indicate that glyphosate resistance is widespread in Italian ryegrass populations of California, and that resistance is likely due to an altered target enzyme.
Two broad aims drive weed science research: improved management and improved
understanding of weed biology and ecology. In recent years, agricultural
weed research addressing these two aims has effectively split into separate
subdisciplines despite repeated calls for greater integration. Although some
excellent work is being done, agricultural weed research has developed a
very high level of repetitiveness, a preponderance of purely descriptive
studies, and has failed to clearly articulate novel hypotheses linked to
established bodies of ecological and evolutionary theory. In contrast,
invasive plant research attracts a diverse cadre of nonweed scientists using
invasions to explore broader and more integrated biological questions
grounded in theory. We propose that although studies focused on weed
management remain vitally important, agricultural weed research would
benefit from deeper theoretical justification, a broader vision, and
increased collaboration across diverse disciplines. To initiate change in
this direction, we call for more emphasis on interdisciplinary training for
weed scientists, and for focused workshops and working groups to develop
specific areas of research and promote interactions among weed scientists
and with the wider scientific community.
Three models that empirically predict crop yield from crop and weed density were evaluated for their fit to 30 data sets from multistate, multiyear winter wheat–jointed goatgrass interference experiments. The purpose of the evaluation was to identify which model would generally perform best for the prediction of yield (damage function) in a bioeconomic model and which model would best fulfill criteria for hypothesis testing with limited amounts of data. Seven criteria were used to assess the fit of the models to the data. Overall, Model 2 provided the best statistical description of the data. Model 2 regressions were most often statistically significant, as indicated by approximate F tests, explained the largest proportion of total variation about the mean, gave the smallest residual sum of squares, and returned residuals with random distribution more often than Models 1 and 3. Model 2 performed less well based on the remaining criteria. Model 3 outperformed Models 1 and 2 in the number of parameters estimated that were statistically significant. Model 1 outperformed Models 2 and 3 in the proportion of regressions that converged on a solution and more readily exhibited an asymptotic relationship between winter wheat yield and both winter wheat and jointed goatgrass density under the constraint of limited data. In contrast, Model 2 exhibited a relatively linear relationship between yield and crop density and little effect of increasing jointed goatgrass density on yield, thus overpredicting yield at high weed densities when data were scarce. Model 2 had statistical properties that made it superior for hypothesis testing; however, Model 1's properties were determined superior for the damage function in the winter wheat–jointed goatgrass bioeconomic model because it was less likely to cause bias in yield predictions based on data sets of minimum size.
Technological advances in molecular biology have contributed substantially to our understanding of plant genetic diversity. Early studies of allozyme variation employing protein electrophoresis revealed that plant populations have high levels of genetic diversity, most of the variation at polymorphic loci is found within populations, and geographic range and breeding system explain the largest proportion of variation in genetic diversity. With the discovery of restriction endonucleases, the first DNA-based markers allowed the detection of variation in DNA sequences in plant population studies. More recently, techniques that utilize the polymerase chain reaction have allowed a more representative assessment of genetic variation in plants by screening multiple loci distributed throughout the genome. The analyses reveal sufficient polymorphism for the examination of fine-scale genetic differences among individuals. Information on plant genetic diversity is also emerging from studies of plant genome structure. Comparative genetic mapping studies of members of the Brassicaceae, Poaceae, and Solanaceae show that gene content is highly conserved between closely related species, although gene order on a chromosomal segment may differ between species. Comparative sequencing studies reveal higher degrees of diversity at the microstructural (less than 1 million base pairs) level than predicted at the genetic map level and suggest that genes are densely packed in gene-rich regions, rather than randomly distributed along chromosomes in species with large genomes. Sequencing of the entire genomes of rice and Arabidopsis thaliana will help identify genes controlling agronomically important traits, improve our understanding of genetic variation for fitness-related traits in wild plant populations including weed species, resolve evolutionary relationships among plant taxa, and potentially revolutionize current ideas on plant diversity and evolution.
Inheritance of glyphosate resistance was investigated in hairy fleabane
populations from California as part of providing the information needed to
predict and manage resistance and to gain insight into resistance mechanism
(or mechanisms) present in the populations. Three glyphosate-resistant
individuals grown from seed collected from distinct sites near Fresno, CA,
were crossed to individuals from the same susceptible population to create
reciprocal F1 populations. A single individual from each of the
F1 populations was used to create a backcross population with
a susceptible maternal parent, and an F2 population. Based on
dose response analyses, reciprocal F1 populations were not
statistically different from each other, more similar to the resistant
parent, and statistically different from the susceptible parent, consistent
with nuclear control of the trait and dominance to incomplete dominance of
resistance over susceptibility in all three crosses. Glyphosate resistance
in two of the three crosses segregated in the backcross and the
F2 populations as a single-locus trait. In the remaining
cross, the resistant parent had approximately half the resistance level as
the other two resistant parents, and the segregation of glyphosate
resistance in backcross and F2 populations conformed to a
two-locus model with resistance alleles acting additively and at least two
copies of the allele required for expression of resistance. This two-locus
model of the segregation of glyphosate resistance has not been reported
previously. Variation in the pattern of inheritance and the level of
resistance indicate that multiple resistance mechanisms may be present in
hairy fleabane populations in California.
Empirical models of crop–weed competition are integral components of bioeconomic models, which depend on predictions of the impact of weeds on crop yields to make cost-effective weed management recommendations. Selection of the best empirical model for a specific crop–weed system is not straightforward, however. We used information–theoretic criteria to identify the model that best describes barley yield based on data from barley–wild oat competition experiments conducted at three locations in Montana over 2 yr. Each experiment consisted of a complete addition series arranged as a randomized complete block design with three replications. Barley was planted at 0, 0.5, 1, and 2 times the locally recommended seeding rate. Wild oat was planted at target infestation densities of 0, 10, 40, 160, and 400 plants m−2. Twenty-five candidate yield models were used to describe the data from each location and year using maximum likelihood estimation. Based on Akaike's Information Criterion (AIC), a second-order small-sample version of AIC (AICc), and the Bayesian Information Criterion (BIC), most data sets supported yield models with crop density (Dc), weed density (Dw), and the relative time of emergence of the two species (T) as variables, indicating that all variables affected barley yield in most locations. AIC, AICc, and BIC selected identical best models for all but one data set. In contrast, the Information Complexity criterion, ICOMP, generally selected simpler best models with fewer parameters. For data pooled over years and locations, AIC, AICc, and BIC strongly supported a single best model with variables Dc, Dw, T, and a functional form specifying both intraspecific and interspecific competition. ICOMP selected a simpler model with Dc and Dw only, and a functional form specifying interspecific, but no intraspecific, competition. The information–theoretic approach offers a rigorous, objective method for choosing crop yield and yield loss equations for bioeconomic models.
Resistance to glyphosate in hairy fleabane and horseweed is a problem in
orchards and vineyards in California. Population genetic analyses suggest
that glyphosate resistance evolved multiple times in both species, but it is
unknown if resistance to other herbicides is also present. Two approaches of
research were undertaken to further evaluate herbicide resistance in
Conyza sp. in the perennial crop systems of California.
In the initial study, the distribution of Conyza sp. in the
Central Valley, using a semistructured field survey, was coupled with
evaluation of the presence and level of glyphosate resistance in plants
grown from field-collected seed. In a subsequent study, single-seed
descendants representing distinct genetic groups were self-pollinated in the
greenhouse and these accessions were evaluated for response to glyphosate
and paraquat. Conyza sp. were commonly found throughout the
Central Valley and glyphosate-resistant individuals were confirmed in all
field collections of both species. The level of glyphosate resistance among
field collections varied from 5- to 21-fold compared with 50% glyphosate
resistance (GR50) of the susceptible, with exception of one
region with a GR50 similar to the susceptible. When
self-pollinated accessions from different genetic groups were screened, the
level of glyphosate resistance, on the basis of GR50 values,
ranged from 1.7- to 42.5-fold in hairy fleabane, and 5.9- to 40.3-fold in
horseweed. Three accessions of hairy fleabane from different genetic groups
were also resistant to paraquat (40.1- to 352.5-fold). One
glyphosate-resistant horseweed accession was resistant to paraquat
(322.8-fold), which is the first confirmed case in California. All
paraquat-resistant accessions of Conyza sp. identified so
far have also been resistant to glyphosate, probably because glyphosate
resistance is already widespread in the state. Because glyphosate and
paraquat resistances are found across a wide geographical range and in
accessions from distinct genetic groups, multiple resistant
Conyza sp. likely developed independently several times
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