This article briefly reviews how long weed seeds can live in the soil and what happens to them during burial. Freshly matured seeds of many weeds are water-permeable, but those of others are water-impermeable. Water-permeable seeds may have morphological, physiological, or morphophysiological dormancy, with physiological dormancy (PD) being the one most commonly found in buried weed seeds. Further, nondeep PD is very common in buried weed seeds, and many of them exhibit annual dormancy cycles in response to seasonal temperature changes. The time of year when seeds are nondormant varies with the species, i.e., autumn, spring, or spring to summer. A light requirement for germination plays an important role in preventing nondormant seeds from germinating in the soil. To germinate, soil disturbance that exposes seeds to light must occur at a time of year when seeds are nondormant. Buried seeds of some species come out of dormancy and remain nondormant regardless of seasonal changes in environmental conditions; however, a light requirement for germination prevents them from germinating in the soil. Water-impermeable seeds have either physical dormancy (PY) or a combination of PY and PD, with PY being the most common, e.g., in members of the Fabaceae and Malvaceae. Seeds with PY have a water gap in the seed coat that opens in response to an environmental signal, thereby allowing water to enter. When disturbance brings seeds to the soil surface, temperatures that are higher than those in the soil can cause the water gap to open. Consequently, the water gap indirectly serves as a depth sensor. A challenge for the future is to use information about buried weed seeds to better manage weeds in crops, and modeling is an important step in that direction.

Two major properties that determine weed seed germination are soil temperature and moisture content. Incident radiation is the primary variable controlling energy input to the soil system and thereby influences both moisture and temperature profiles. However, many agricultural field sites lack proper instrumentation to measure solar radiation directly. To overcome this shortcoming, an empirical model was developed to estimate total incident solar radiation (beam and diffuse) with hourly time steps. Input parameters for the model are latitude, longitude, and elevation of the field site, along with daily precipitation with daily minimum and maximum air temperatures. Field validation of this model was conducted at a total of 18 sites, where sufficient meteorological data were available for validation, allowing a total of 42 individual yearly comparisons. The model performed well, with an average Pearson correlation of 0.92, modeling index of 0.95, modeling efficiency of 0.80, root mean square error of 111 W m−2, and a mean absolute error of 56 W m−2. These results compare favorably to other developed empirical solar radiation models but with the advantage of predicting hourly solar radiation for the entire year based on limited climatic data and no site-specific calibration requirement. This solar radiation prediction tool can be integrated into dormancy, germination, and growth models to improve microclimate-based simulation of development of weeds and other plants.

Because soil-residual PRE herbicides reduce and delay annual weed emergence and decrease later weed growth, susceptible weeds surviving or recovering from herbicide treatment reduce crop yields less than do untreated weeds. Recently, corn yields were shown to be reduced differently by untreated weeds emerging in and between crop rows. However, equations have not been reported before that relate corn yield to in-row and between-row weed cover of mixed weed populations recovering from PRE soil-residual herbicides. Published data from PRE herbicide screening research for 3 site-yr in Missouri were reanalyzed to characterize this relation. In-row and between-row weed cover of mixed weed populations, chiefly giant foxtail and common waterhemp, were measured from photographs at midsummer. In 2 of 3 site-yr and with the 3 site-yr average, corn yields were a nonlinear function of both in-row and between-row weed cover recovering from various PRE soil-residual herbicide treatments. In 1 of 3 site-yr, corn yields were a nonlinear function of only between-row total weed cover. Subdividing weed cover into in-row and between-row subpopulations in equations accounted for more data variability in yield estimates than including either subpopulation alone. For all 3 site-yr after PRE herbicide treatment, corn yields were a nonlinear function of only between-row visually rated total weed control. Visual evaluation was less sensitive than photographic weed cover for measuring the contribution of in-row weeds to corn yield loss and characterizing the functional form of the equations.

Weeds generally occur in patches in production fields. Are these patches spatially and temporally stable? Do management recommendations change on the basis of these data? The population density and location of annual grass weeds and common ragweed were examined in a 65-ha corn/soybean production field from 1995 to 2004. Yearly treatment recommendations were developed from field means, medians, and kriging grid cell densities, using the hyperbolic yield loss (YL) equation and published incremental YL values (I), maximum YL values (A), and YL limits of 5, 10, or 15%. Mean plant densities ranged from 12 to 131 annual grasses m−2 and < 1 to 37 common ragweed m−2. Median weed densities ranged from 0 to 40 annual grasses m−2 and were 0 for common ragweed. The grass I values used to estimate corn YL were 0.1 and 2% and treatment was recommended in only 1 yr when the high I value and either the mean or median density was used. The grass I values used for soybean were 0.7 and 10% and estimated YL was over 10% all years, regardless of I value. The common ragweed I values were 4.5 and 6% for corn and 5.1 and 15.6% for soybean. On the basis of mean densities, fieldwide treatment would have been recommended in 6 of 9 yr but in no years when the median density was used. Recommendations on the basis of grid cell weed density and kriging ranged from > 80% of the field treated for grass weeds in 3 of 4 yr in soybean to < 20% of the field treated for common ragweed in 2002 and 2004 (corn). Grass patches were more stable in time, space, and density than common ragweed patches. Population densities and spatial distribution generally were variable enough so that site-specific information within this field would improve weed management decisions.

Greenhouse and field studies were conducted with a population of common waterhemp resistant to POST protoporphyrinogen oxidase (protox)-inhibiting herbicides to compare its response to PRE and POST applications of selected herbicides. In the greenhouse, a dose–response study of PRE applications of acifluorfen, fomesafen, or lactofen was conducted on protox-susceptible and -resistant common waterhemp. The protox-resistant biotype was approximately 6.3, 2.5, and 2.6 times more resistant than the susceptible biotype to acifluorfen, fomesafen, and lactofen, respectively. In a separate study under field conditions, protox-resistant common waterhemp were treated with PRE and POST applications of acifluorfen, azafenidin, flumioxazin, fomesafen, lactofen, oxyfluorfen, or sulfentrazone. At 14 and 28 d after POST treatment (DAPT) in 2002 and 2004, all PRE applications of herbicides gave greater control than did POST applications. At 14 DAPT, oxyfluorfen had the greatest difference in PRE and POST control, with 85 and 10% control in 2002, respectively. An additional field study was conducted to determine the stage of growth at which resistance to protox-inhibiting herbicides becomes most prevalent. Protox-resistant common waterhemp were treated with herbicides at the 2-leaf, 4- to 6-leaf, and 8- to 10-leaf growth stage. Acifluorfen and fomesafen at 420 g ha−1 gave greater than 90% control at the 2-leaf stage and 4- to 6-leaf stage, except in 2003 when control was 85% with acifluorfen. In 2003 and 2004, common waterhemp control at the 8- to 10-leaf stage ranged between 54 and 75% with acifluorfen or fomesafen. Results indicate that common waterhemp resistance to customary rates of POST protox-inhibiting herbicides becomes prevalent after the 4- to 6-leaf growth stage.

The release of Bt cotton varieties genetically modified for increased tolerance to major cotton insect pests provided impetus for the reestablishment of a cotton industry in northern Australia. However, this stimulated concern that the addition of the gene might facilitate an increase in the potential for weediness of genetically modified cultivars in noncropping habitats. Bt and conventional cottonseeds were planted in 12 sites in northern Australia to test the hypothesis that there would be no increase in the ability of Bt cotton vs. conventional cotton to establish weedy, or invasive populations, defined as population growth over time greater than one, irrespective of location, habitat, seed type, or population density. Invasiveness was a factor of germination, survival, and recruitment. We examined whether the addition of the Bt gene would increase fitness of these parameters, and associated invasiveness. An irrigation drain was considered a high-risk habitat for cotton establishment, so an additional site was sown at that habitat to provide supplementary data to the original 12 sites. Location and habitat were the dominant factors influencing germination, survival, fecundity, and invasiveness. Bt and non-Bt cottonseeds did not differ in their ability to germinate, establish, and survive. After 2 yr, cotton plant survival was very low, and only 3 of 13 sites established fecund cotton populations. Measurements continued for an additional 2 yr at these sites. There was no increase in values for invasiveness for the Bt genotype treatments at any location or habitat after 2 yr or at two selected habitats after > 4 yr, demonstrating that the addition of the Bt gene will not confer increased fitness for weediness. Mean invasiveness values for each habitat, irrespective of genotype, were less than one, indicating that neither conventional nor Bt cotton would establish invasive cotton populations in northern Australian habitats.

Weed seeds initiate most weed invasions of arable fields, yet there is relatively little information on the value of managing weed seed banks. Matrix population models were used to examine the relative importance of managing weed seed banks, in relation to other life stages, for four model weed species with varying life histories. Simulations for giant foxtail and common lambsquarters, summer annual weeds of arable fields; garlic mustard, an obligate biennial invasive weed of temperate forests; and Canada thistle, a perennial weed of pastures and arable fields, were run under conditions of varying population density and efficacy of seedling control. The models were subjected to elasticity analysis to determine what happened to weed populations when different life stages were targeted. Losses from the dormant seed bank were most important for summer annual weeds, of intermediate importance for biennial weeds, and of low importance for perennial weeds. More effort is needed to develop weed seed-bank management techniques for summer annual weed species as part of integrated weed management systems.

Clopyralid, picloram, triclopyr, metsulfuron, and tebuthiuron were applied to control kudzu on four loblolly pine forest regeneration sites during July 1997. Spot treatments were applied to recovering kudzu in June 1998 and June 1999. Soil leachate was monitored for these five herbicides from July 1997 to December 2000. All herbicides were detected in shallow (51–58 cm deep) and deep lysimeters (84–109 cm deep). Clopyralid was not persistent and limited leaching occurred, with residue levels of 0.4 to 2.8 μg L−1 in 12 of 102 deep lysimeter samples. Picloram was mobile and persisted at 0.6 to 2.5 μg L−1 in shallow and deep lysimeters for at least 10 mo after the initial application. Triclopyr residues were not persistent in shallow lysimeters and remained < 6 μg L−1 during the study. Metsulfuron persisted at < 0.1 μg L−1 for 182 to 353 d in shallow lysimeters and at < 0.07 μg L−1 for 182 to 300 d in the deep lysimeters in various plots. Tebuthiuron peaks in the deep lysimeters ranged from 69 to 734 μg L−1 34 to 77 d after the first spot treatment. In the soil that was essentially a fill area, tebuthiuron residues remained > 400 μg L−1 (402–1,660 μg L−1) in the shallow lysimeter samples and > 180 μg L−1 (181–734 μg L−1) in the deep lysimeters throughout a 354-d period that followed the first spot application. When used as part of a forest regeneration program, the relative potentials of the herbicides to move into shallow groundwater were: tebuthiuron > picloram > metsulfuron > clopyralid > triclopyr.

To better understand seed predation and enhance weed seed losses in arable fields, we developed a conceptual model that integrates seed dispersal, seed burial, and seed demand, the three processes that determine the dynamics of summer annual weed seeds on the soil surface in late summer and autumn. Published and unpublished experimental data were used to parameterize a simulation model for a number of crop–weed combinations. Sensitivity analyses of models for giant foxtail in corn and soybean indicated that factors related to seed availability were more important in determining overall seed losses due to predation than those related to seed demand. Delaying harvest date and destroying unshed weed seeds collected at harvest emerged as promising strategies to reduce seed input into the seed bank. The role of plant debris in hiding weed seeds from predators was ambiguous and requires further investigation. Estimates of overall seed losses due to predation based on model simulations in various crops and cropping systems indicated that weed seed predation could serve as an important tool in ecological weed management.

The effects of time of precipitation and soil type on runoff losses of cyanazine and metolachlor were studied using a tilted-bed, microplot system. Two silt loam soils, Bosket and Dubbs, and a Sharkey silty clay were evaluated. Rainfall (22 mm h−1) was simulated at 0, 2, and 14 days after treatment (DAT). Time of precipitation did not impact herbicide losses or any of the runoff parameters evaluated in this study. Water runoff occurred sooner and in greater quantities from the surfaces of Bosket and Dubbs silt loam soils than from the surface of Sharkey silty clay. Runoff losses of cyanazine did not vary by soil type. Soil drying produced large cracks in Sharkey silty clay, which greatly reduced runoff in this soil. Combined runoff and leachate losses were highest from Dubbs silt loam. Runoff losses of metolachlor were not affected by soil type. However, regression analyses indicated that time of precipitation and soil type interacted to affect initial metolachlor concentration. At 14 DAT, initial metolachlor concentration was highest in runoff from Sharkey soil. Time of precipitation ranked with respect to initial metolachlor concentration in runoff from Bosket and Dubbs silt loam soils were 0 > 2 > 14 DAT and 0 = 2 > 14 DAT, respectively.

A two-year surface water reconnaissance of the Bogue Phalia and its tributaries was conducted in 1997 and 1998. Cyanazine and metolachlor in surface water samples were quantified using enzyme-linked immunosorbent assays (ELISA). Cyanazine and metolachlor were detected in 101 and 132 of 160 samples, respectively. Cyanazine concentrations ranged from 0.1 to 2.2 g L−1 and exceeded the U.S. Environmental Protection Agency (EPA) lifetime health advisory level (HAL) of 1 g L−1 in eight samples. However, concentrations never exceeded the HAL for shorter exposure times. Metolachlor concentrations never reached the lifetime HAL of 100 g L−1. Metolachlor concentrations ranged from 0.1 to 20.6 g L−1. Metolachlor was detected more frequently and found to be more persistent throughout the growing season than was cyanazine. Higher cyanazine and metolachlor concentrations were detected at sampling dates that coincided with herbicide applications. One of the Bogue Phalia's tributaries, Clear Creek, was found to be a point-source of cyanazine for the watershed.

Reduction of seed-bank persistence is an important goal for weed management systems. Recent interest in more biological-based weed management strategies has led to closer examination of the role of soil microorganisms. Incidences of seed decay with certain weed species occur in the laboratory; however, their persistence in soil indicates the presence of yet-unknown factors in natural systems that regulate biological mechanisms of seed antagonism by soil microorganisms. A fundamental understanding of interactions between seeds and microorganisms will have important implications for future weed management systems targeting seed banks. Laboratory studies demonstrate susceptibility to seed decay among weed species, ranging from high (velvetleaf) to very low (giant ragweed). Microscopic examinations revealed dense microbial assemblages formed whenever seeds were exposed to soil microorganisms, regardless of whether the outcome was decay. Microbial communities associated with seeds of four weed species (woolly cupgrass, jimsonweed, Pennsylvania smartweed, and velvetleaf) were distinct from one another. The influence of seeds on microbial growth is hypothesized to be due to nutritional and surface-attachment opportunities. Data from velvetleaf seeds suggests that diverse assemblages of bacteria can mediate decay, whereas fungal associations may be more limited and specific to weed species. Though microbial decay of seeds presents clear opportunities for weed biocontrol, limited success is met when introducing exogenous microorganisms to natural systems. Alternatively, a conservation approach that promotes the function of indigenous natural enemies through habitat or cultural management may be more promising. A comprehensive ecological understanding of the system is needed to identify methods that enhance the activities of microorganisms. Herein, we provide a synthesis of the relevant literature available on seed microbiology; we describe some of the major challenges and opportunities encountered when studying the in situ relationships between seeds and microorganisms, and present examples from studies by the ARS Invasive Weed Management Unit.

Because herbicide and cultivation efficacy is generally density independent, seedling density following these weed control practices will be proportional to the density of germinable seeds in the seedbank. Most farmers would therefore benefit from management practices that reduce seed inputs, increase seed losses, and reduce the probability that remaining seeds establish. Germination, predation, and decay are the primary sources of loss to the seedbank that may respond to management. Farmers have long prepared stale seedbeds in which shallow soil disturbance encourages germination losses. Postdispersal seed predation by vertebrate and invertebrate granivores may cause high rates of seed mortality in a wide range of cropping systems, but seed dispersal asynchronous with predator activity, and seed burial, may limit the overall effect on the seedbank. Although seeds would seem to be an ideal carbon source for soil microorganisms, limited evidence from a study of wild oat suggests that decay may be less responsive to management than germination, and likely predation. A final management objective, supporting a program that aims to reduce seedbank inputs and increase losses, is to reduce the size of the effective seedbank through manipulation of residues and disturbance to reduce the probability of establishment. Incorporation of green manures generally reduces weed establishment, whereas larger-seeded or transplanted crops may better tolerate the residue-mediated changes in the chemical, biological, and physical properties of the soil surface environment. Evidence from no-till systems further support the hypothesis that changes in soil surface conditions may regulate the abundance of “safe sites” for weed establishment, thereby modulating the size of the effective seedbank.

Land managers typically use herbicides, biological controls, fire, grazing, and revegetation to manage and restore rangeland dominated by invasive plants. Without careful planning and implementation, these tools may temporarily control the weeds but may ultimately have minimal influence on ecological processes, fail over the long term, and lead to weed reinvasion. This can result from the lack of a broad ecological perspective. Successional management provides a process-based framework for weed ecologists to develop and test integrated weed management strategies and for land managers to organize implementation of these strategies in a way that adequately addresses ecological processes. This framework offers land managers practical methods for modifying ecological processes to direct plant community composition away from invasive species and toward desired plant assemblages. To date, successional management has not gained widespread application because, in part, it has not been conceptually linked to other successional models. Therefore, we illustrate how other successional models can be incorporated within the framework. Incorporating other prevailing successional models will further elucidate ecological processes, offer additional management strategies, and widen the possibilities for ecologically based management of rangeland weeds. Approaching management of weed-infested rangeland through this process-based framework will enable managers to implement strategies that maximize the likelihood of success because these methods will be integrated based on ecological principles. Successional management should be adjusted as we gain a better understanding of the factors that drive succession.