Adequate water resources along the road provide a suitable environment and resources for seed germination and early seedling growth for invasive species. After the early establishment and the naturalized species overcoming different stresses to produce seeds, the rapid spread of the reproductive offspring makes the species invasive . Human-assisted dispersal potentially creates a longer-range spread than the dispersal mechanisms related to species’ reproductive traits. According to Mortensen et al. , human activities are the main facilitators of the weedy and invasive species spread, and their study indicated that paved roads could spread more weeds than forests and wetlands. Specifically, vehicles are the spreading vectors of long-distance dispersal for weedy and invasive species. The traditional species dispersal model described LDD as a rare event; most cases are seed dispersal by animals , where weed seeds are adhesive to animal fur and travel along with seasonal migration . However, Nathan proposed that human-mediated LDD has become the most important mechanism of LDD in plants and animals, which is a challenge for future LDD prediction. According to Baker , no specific weedy traits or natural dispersal mechanism to help invasive species overcome the large-scale geographical barrier. Nevertheless, human-assisted dispersal can potentially transfer seeds over 100 km away from the parent plants. The 100 km was an approximated cut-off to classify plants as alien species in the model proposed by Richardson et al. . A study in Germany collected seeds from roadside verges, cannabis dryer and their results indicated that nearly 30% of the species collected were by LDD and some species they identified are highly invasive in other countries .

Seeds dispersed by vehicles share common characteristics that might facilitate car-borne dispersal. Zwaenepoel et al. provided another perspective by collecting seed samples from mud attached to the car; the results suggested that carborne floras were pioneer species with small and light seeds. Other traits like large seed production and the ability to reproduce vegetatively are also reported in many studies . Also, a systematic review summarized that about 626 species in 75 families had been identified from cars, and Poaceae is the most frequent family , followed by Asteraceae and Fabaceae . The spread of invasive and weedy species along the road in the real world could be more significant than what has been reported in scientific studies. The large-scale spread of Microstegium vimineum was reported by observation; however, according to a model prediction, the species spread only by natural dispersal is limited . The contrasting results support that human-assisted dispersal leads to an increasing spread rate, and more resources and efforts should be put to roadside vegetation management. Roadside vegetation management is on a large scale, and the local government is the primary agent for management. For example, in California, the California Department of Transportation manages the vegetation along California state highways, and develops projects to protect motorists, cyclists, and potential wildfire spread along the roads . Compared to agricultural weed management, roadside vegetation management has limited tools. The most common practice is mowing, but it requires multiple applications in a short period; therefore, mowing is expensive and ineffective since only the foliar part of the plant is damaged . Herbicide application is used with mowing as the Integrated Vegetation Management . Chemical control could be effective under roadside conditions. For example, herbicide trials conducted in six different regions of Indiana demonstrated that herbicide application could effectively control broad leaf species for more than one year and grasses for months .

Herbicides can significantly lower the cost, but the increasing herbicide-resistant population is another potential concern for roadside weed management . IVM program is important to manage roadside invasive species, and similar to Integrated Weed Management, early detection and monitoring are also main components in IVM. The first step in studying and analyzing the ecological aspect of a specific invasive or weedy species is to conduct a species survey and map the population distribution.A species distribution map is a common approach for evaluating the extent of plant invasion and provides a baseline for the informed allocation of resources and efforts. Botanists usually conduct field surveys to collect plant species, including weedy species. The benefit of this detailed survey is the high accuracy of the species identification and location data, but a detailed survey requires enormous resources. For example, a county-level survey of 3000 km required 35 months, and the researcher had to travel by car, on foot, or even by boat . A typical 3000 km survey is considered small-scale but still time-consuming, labor-intensive, and requires equipment like a vehicle and an accurate GPS positioning system. A field survey is reasonable for species local population examination and species-environment interaction analysis. A car survey can be rapid by applying different sampling or examination methods. According to Shuster et al. , a car survey has a similar probability of finding Alliaria petiolata compared to a survey on foot but requiring four times fewer person-hours. The car survey can involve transects or random sampling sites along the roads base on land uses, soil types, rainfall, and vegetation types . The data collected from the car survey can be used to build a model to understand the relationship between species distribution and environmental factors. A car survey could yield consistent results when various factors are examined in the experimental design. For instance, the traveling speed can vary for different types of roads. For highways, the driver must drive above the minimum speed so that a higher speed can result in lower identification accuracy. Observation accuracy is another factor that affects data consistency. Catry et al. conducted accuracy tests to evaluate the potential human errors. However, it is challenging to include human error rates in the species distribution maps, and in most cases, the human errors in the car survey are unaccountable . A standard methodology for roadside species surveys should be established to yield consistent and comparable data. Some studies do not include all road types in the car survey to save time and reduce costs. For example, Catry et al. excluded the highway or freeway because they believed that the roadsides of the freeway are well-managed and there will be less possibility of having invasive species populations. A survey for all roads in a state will take an unrealistic time to complete, and the cost of traveling will be expensive. For example, California has about 622,000 km of roads, and it will take about 780 days if a driver drives 800 km per day . Thus, government agencies will hesitate to conduct surveys because of limited funding and resources. However, roadside vegetation assessment can help identify the level of invasion and the potential damage. A car survey is not cost-effective for accomplishing a quick assessment on a large scale. Furthermore, a species map can be used in large-scale species dispersal models in which the input data are usually from global or regional databases. Kadmon et al. argued that since randomized surveys on a large scale are rare, those models often rely on incomplete databases with biased data, such as herbaria, natural museums, and user-uploaded entries. The unified database includes data collected from different observers, and we cannot estimate the potential human error if we rely on these databases to run the ecological models. As a result, we need a more systematic approach for large-scale species surveys.Google Street View is a tool in Google Maps and Google Earth that allows users to interact with the panoramas along streets and roads in many countries. GSV and Google Earth are well-developed and well-maintained databases, and the imagery has been online for more than ten years.

Google sends numerous data-collection vehicles on the roads, and those vehicles take 360-degree photos, e.g., cannabis growing systems by installing a rosette camera on the top of the car . According to Anguelov et al. , this project aims to organize a large amount of information, and billions of users can have access to that information. GSV is well-known among ordinary users for educational and recreational activities, but now, these images can be used for ecological studies and vegetation management. For example, GSV was used to map the distribution of the Pine Processionary Moth , in an area of about 45,000 km2 . Their research suggested that this method can be effective if the target species are distinguishable in the GSV images. They also mentioned that the coverage area of GSV still needed to be completed back in 2013. In the past ten years, GSV has been used in several ecological studies. For example, according to Hardion et al. , the integration of ground and aerial images could create a better species distribution map of giant cane , a common grass species along the road, and the species distribution data produced better results in species distribution models compared to the traditional field survey. Additionally, two studies compared GSV and field surveys by car. Studies by Deus et al. and Kotowska et al. reported that the results produced by GSV resemble that produced by the field survey. The two studies surveyed different species of different sizes . Although GSV is more cost-effective than car surveys, studies discussed above have used human observers for plant detection, which is tedious, time-consuming, and not feasible for large-scale mapping. Furthermore, most previous studies reported some common limitations of this imagery database. Most studies suggested seasonality and time differences among the GSV images. The images from different areas were taken in different years or seasons and at different times during the day , which could impact the presence and absence of the survey species or detectability of species within the GSV images . Deus et al. also reported that contrast, ambient light, and sharpness would affect the identification accuracy in some images. Another issue with GSV is that most species were undetectable in their seedling stage when they were small and did not develop distinguishable features . GSV database has been successfully used as a cost-effective method in terms of time and resources, and this benefit can allow researchers to conduct a comparatively large-scale survey in a short period .Artificial Intelligence is a powerful tool to automate tasks, providing insightful solutions for scientific studies in different fields. For example, image detection built with deep learning algorithms can be used in plant species identification. Computer vision methods are successfully used in crop and weed classification to build robotic machines to conduct real-time weed detection in the field . Machine learning includes two main types: unsupervised and supervised learning. Unsupervised learning trains models with unlabeled data, while supervised learning requires labeled data, and most neural networks are examples of supervised learning algorithms . Artificial neural networks are models built based on the nervous system of the living vertebrate . In recent years, neural networks have evolved into the convolutional neural network , which consists of multiple convolutional layers. Many studies have proven that CNNs can reach high accuracy in object detection in images . Dyrmann et al. trained a CNN model to classify young seedlings of 22 species with the average accuracy of 86.2% under controlled indoor conditions. For example, Sugar beet , barley , and Thale Cress could achieve 97% to 98% accuracy . Dyrmann et al. tested another CNN model called DetectNet in overhead images from highly occluded cereal fields, and the model had a recall of 46.3% and a precision of 86.6% for detecting the non-crop plants. The high-occluded fields resemble roadside environments where plants overlap each other. Another well-known fast-detection CNN model called You Only Look Once can be used to detect weeds in outdoor and natural light conditions. Dang et al. tested different versions of YOLO detectors on 12 weed classes at different growth stages in cotton fields. The precisions of 12 weed classes ranged from 81.5% to 98.28%, and the recalls ranged from 78.62% to 97.9% on the YOLOv3 detector . The examples above are all based on overhead images in crop fields, but only a few similar studies have been done under roadside conditions. One example of the roadside condition is a study that integrated GSV Imagery and a CNN network to map the distribution of different crops along the roads and achieved accuracy levels of 92% in California and 98% in Illinois .

Additionally, an EV performing the same trip in August but charging under the Workplace Morning charging profile was found to emit nearly 14% more CO2 per kilometer when using hourly grid emissions profiles instead of annual averages and nearly 10% more instead of monthly averages. This variance is even more pronounced under the marginal scenarios, though not always with the same directionality. Assuming the Hourly Marginal Mix tends to reduce the per-kilometer CO2 emissions of an EV charged with the Workplace Morning profile in the summer months, making that charging profile the most attractive in terms of environmental benefit in some cases. Under Hourly Marginal, Resource X assumptions, the CO2 emitted per kilometer for an EV can vary as much as 58% depending on the time it is charged on a given day. Importantly, almost all simulated EV scenarios realized reduced CO2 emissions per kilometer compared to ICEVs. However, the magnitude of these reductions varies substantially under different emissions assumptions, charging profiles, and seasons. The extreme hourly and seasonal variations in effective emissions rates of EVs found in this study indicate that reliance upon annual or monthly average emissions rates for the modeling of EV environmental benefits is inadequate. Table 3-2 depicts the wide variation in emissions rates from simulation to simulation relative to the ICEV baseline.Average emissions rates at lower resolutions obscure vital information that could otherwise be used to optimize environmental benefits as well as inform policy. Effective communication of hourly or higher resolution of grid CO2 intensity would help the consumer make an informed choice on when to charge their EV to maximize environmental benefits. With the maturation of “smart-charging,” enabling communication between the grid or utility and smart charger units would allow the smart charger to control the rate of charge to minimize effective EV emissions, cannabis drying subject to user-configured constraints involving required time of use, desired battery capacity, and cost.

As expected, the HEV reduced CO2 emissions compared to an ICEV, but it also performed consistently on par or better than many EV scenarios. When annual or monthly average emissions rates are assumed, HEVs already perform better on a per-kilometer basis than EVs beyond a certain distance threshold. These de-facto superiorities of HEVs become less pronounced at certain times when hourly emissions rates are assumed. Failing to understand and incorporate higher-resolution evolutions in grid emissions intensities can lead decision makers to ill-informed conclusions that could be sub-optimal for reducing environmental externalities. It is worth noting that both EVs and grid generating resources are evolving dynamically, placing renewed emphasis on studies that consider environmental impacts during this transition period . There is likely some threshold of EV penetration that will trigger a realignment in marginal emissions trends. As electrical power demand increases at peak charging times when consumers are incentivized to charge their vehicles, marginal resources in addition to those observed in this study, will eventually be required to supply sufficient power. Often, due to the inherent need for dispatch ability, marginal resources are fossil-based or non-renewable in nature. Thus, if additional marginal resources need to be brought online, it could alter grid emissions profiles and lead to shifting environmentally optimal charging periods. Understanding the scaling behaviors of marginal power demand for growing rates of EV adoption will be critical for decision-makers to stay one step ahead of lagging realignments, anticipate them, and communicate optimal charging periods to consumers as well as intelligent infrastructure. An important benefit of the methodology employed in this study is that it can be easily adapted to model additional use cases, charging profiles, emissions profiles, and additional pollutants. To prove the feasibility of such adaptations, SO2 and NOx grid emissions were simulated for the same charging profiles as CO2 for the Suburban Errands trip in August and October.

For these simulations, there were assumed to be no SO2 emissions for the ICEV and HEV baselines. NOx emissions for the ICEV and HEV baselines were calculated using a conversion factor of 0.000167 , as informed by the MoVES model. Figure 3-4 and Figure 3-5 depict pollutants that are greater per kilometer in EVs than ICEVs. SO2 and NOx are examples of pollutants emitted in the production of electrical energy at fossil power plants that are essentially absent from or significantly reduced in vehicular tailpipe emissions. While these additional pollutants should be acknowledged, it is critical to understand the spatial confines of their dispersion. While tailpipe, mobile-source emissions are present anywhere motor vehicles travel, emissions from electricity generation are localized in smaller areas immediately surrounding power plant facilities. Given that power plants are typically located in more rural areas, the per-unit damages from pollutants emitted by electricity generation can be much less. However, there are environmental justice issues inherent in these trade-offs that need to be addressed and explored further.Because of the potential opportunity of vehicle electrification to help decarbonize the transportation sector and improve air quality, the technical findings of this research could have some significant policy implications. To optimize the potential benefits, much greater attention will be required to the incremental difference in EV emissions relative to baseline ICEVs and HEVs. As some of the findings suggest, the individual vehicle and fleet wide improvements may be much lower than expected by some studies as scale-up occurs. However, the findings also provide some suggested means of ensuring that environmental and social improvements can be realized, and at the scales needed. Because this research begins to quantify technical parameters related to both the magnitude and the range of possible emissions impacts as compared to multiple baselines , the study’s findings can be useful for education and awareness by all EV users.

They also have clear implications on policy and public investment, including the urgent need for managed and coordinated charging, and greater attention to resource planning, in terms of generation resources, dispatch decision making, infrastructure funding, and the long-run environmental benefits and impacts for EVs across a range of use cases and time horizons.To investigate the true variability associated with CO2 and other transportation-related vehicle emissions, this study has developed a simulation framework that explores multiple parameters concurrently. The goal has not been to determine with high precision a given case as much as it is to develop a broad comparison among major inputs and factors. In this way, we explore electric vehicles as compared to a baseline case . We explore several driving cycles and charging profiles that represent typical approaches both for residential and workplace charging at various times of the day. And then, we develop various methods for estimating CO2 and other vehicle emissions. As noted, studies that have addressed this previously have often utilized annualized averages to simplify the analysis. In our research review of other tools and dashboards , we confirmed that a very basic algorithm is utilized . We acknowledge such traditional approaches provide a kind of first-order, initial estimation that can be useful to some audiences in some contexts. However, it is imperative to recognize and explain the limitations of accepted approaches, and the risk of relying too heavily on average emissions estimates, as they are highly subject to change in the future, and to variability during the present . In short, new tools and methodologies are needed that can estimate the impact of taking various assumptions for how the grid will meet marginal demands in the near, intermediate and long terms. This transition period from a few million EVs to 100 million EVs will take some time, and environmental impacts will need to be more fully understood. As EV adoption increases and the grid is expanded to meet new demands for electrification, such transition tools and methods can be increasingly valuable to researchers, planners, policymakers, drying cannabis and infrastructure decision-makers. As such, our present work provides much needed additional insight and may be useful to inform 2nd order factors and more complex and integrated guidance. Going a step further by exploring limitations and pursuing additional rough orders of magnitude could have tremendous value for the transportation research community. It would also facilitate a more direct and apples-apples comparison of EVs to other technologies there are substantial shortcomings as penetration rates grow. We conclude with a brief recap. It is clear that at certain very low very modest levels of EV deployment, something like an average assessment of the weighted mix of resources may not be illogical or even inaccurate. It is beyond the scope of this study to determine exactly at what penetration rates things change, but it can be stated that at significant increases in EV charging, in particular at certain hours of the day and months and seasons of the year, the assumption of weighted mixes breaks down. Some preliminary findings from the use cases investigated in the present study reveal that conditions most at risk of yielding higher than desired CO2 emissions rates include afternoon charging at the workplace and early evening charging at the residence. Conversely, it seems that residential overnight charging may, at present, be one of the lowest impact scenarios for EV charging.On the behavior side, it’s clear that managing charging events throughout the 24 hours of the day should merit greater attention. It appears that residential charging may be environmentally preferred compared to workplace charging under certain conditions. This may be an important near-term way to mitigate the unintended effects of higher marginal emissions impacts. This, however, is a simplified observation, since it assumes adequate all-electric range and adequate access to residential EV charging. Neither of these assumptions is necessarily sound at higher penetration rates or given certain economic barriers and social inequities. Furthermore, charging management and behavior alone will likely be inadequate as EV shares grow to levels that push up against current resource capacities and are not yet envisioned fully and accommodated for utility resource plans in the 3-to-10-year horizon. Future study is anticipated to further inform decision-making around such scenarios, including the ability to convert the predominantly historical approach dispatch to a predictive forecasting approach where a 2030 scenario is developed that can better simulate future resources, both fossil, and non-fossil, and how they will be deployed to meet a growing load to support electric transportation. While the use case results are of interest in their own right, it should be noted they are sensitive to the source data for the selected region and approaches taken to integrate electric charging behaviors. While the particular insights may not apply to other regions, it is important to note that the research term also intended to conduct a regional use case as a validation for the methodology. The methodology has been constructed and described in sufficient detail that it can be combined with other data sets and regional attributes for the purpose of adapting it as a decision support tools, beyond the particular region selected herein. Thus, the methodology is shown to be scalable and more broadly applied to other time horizons and regions, and leverage other data sets.This research study focuses on a few specific vehicle types around light-duty vehicle uses in order to develop a comparative framework with a manageable technical scope. While additional use cases and extensions are suggested as areas of future work, the frameworks and simulation-based comparisons are extremely generalizable and extendable because of the organizational approach. A lot of attention to detail has been paid to the development of physics-based vehicle models, including consideration of architectures, power train, overall accessory loads, and sensitivity to drive cycle and external ambient temperatures. Similar attention to detail has been paid to developing practical and representative EV charging profiles, reasonable mapping of standard drive cycles to real-world trips and travel behavior, and high-fidelity analyses of existing grid dispatch methods based on real-world data. A primary contribution of this effort is therefore the integration of each of the individual subsystems and independent data sources, including hourly grid characteristics, toward a novel understanding of the complex impacts of vehicle electrification. In short, the team has successfully achieved its chief aim of laying the groundwork for a more complete understanding of these results at scale. Regarding EV charging behavior, we have considered data from multiple concurrent sources which provides insight into when people are most likely to be charging their EVs today.

The diverse mix resulted in more consistent ground cover in this study, and ground cover led to greater weed suppression. However, cover crop incidence, not the specific cover crop treatment, was the primary driver for suppression and other effects on weeds in this study. These results are consistent with previous experimental results of cover crop and weed competition that highlight the importance of cover crop abundance, not diversity, in weed competition . It is important to note that these studies primarily measured cover crop and weed biomass, while the present study came to a similar conclusion by measuring incidence. Additionally, these studies are in annual cropping systems. Agricultural systems, whether annual or perennial, are designed to support ample plant growth, and this resource-rich environment favors the asymmetric competition that is associated with abundant, fast-growing, cultivated plants. Maintaining biodiversity is a major challenge for agroecosystems, but this study continues to challenge the importance of functional diversity for achieving agronomic management goals like weedy vegetation management. Agricultural plant communities are not diverse compared to plant communities in non-agricultural systems. The cover crop mixes in this study represented a significant increase in orchard plant diversity, essentially doubling species richness in the mature orchards . Among treatments, weed species richness was highest in the young orchard , where the orchard floor was relatively unshaded and still populated with many weed species carried over from the previous pasture system. Weed community assembly may be affected by cover crops during the early stages of orchard development, commercial hydroponic systems but more research is needed to understand the effects of cover crop competition on filtering weed communities over timescales relevant for orchard production.

Cover crop species in this study were primarily selected for their relevance to almond management goals other than weed suppression. When considering multifunctionality, there are significant tradeoffs between agroecosystem services associated with various cover crop mixes. Managing cover crops for maximum weed suppression, and therefore maximum abundance, may detract from other orchard or cover crop management goals. For example, rye was included in the multifunctional mix in this study and is known to be an important component species for weed suppression , but persistent residues from high-biomass species like rye could negatively affect on-ground almond harvest several months after cover crop termination. However, weed-suppressing cover crops are also likely to contribute to other ecosystem services. Large and abundant cover crops are more effective in exploitative competition due to asymmetric resource acquisition, such as root competition for soil nutrients . The same mechanism that facilitates competition in this example also facilitates improved soil structure and increased soil organic matter. In another example, cover crop functional diversity could enhance competition through niche differentiation, as well as enhance pollination services by increasing floral resource diversity. Abundant single-species cover crops may be the best for outcompeting weeds, but a multifunctional cover crop mix may be designed to enhance other orchard management goals and protect against environmental uncertainty. Weed suppression may be essentially aprerequisite towards achieving an abundant, competitive, and multifunctional cover crop, but cover crop species and management practices should be selected with consideration for other ecosystem services that may complement orchard production. Balancing multifunctionality against singular management goals like weed management presents opportunities for integration of cover crops into conventional cropping systems.

Conventional weed management is chiefly a tool for reducing biodiversity, but cover crops can reduce weed infestation while promoting functional biodiversity. Uncertainty of outcomes remains a challenge for the practical adoption of cover crops by orchard growers; specific cover crop management practices should be planned alongside specific management goals . Particularly important is uncertainty related to the timing of winter rainfall. In the almond study system, cover crop planting is timed to coincide with the beginning of winter rains, which would reduce demand for supplemental irrigation of the cover crop. Weedy plants also depend on this rainfall for germination, and timely planting of the cover crop can align cover crop emergence with weed emergence. Cover crop mix diversity could be one way to hedge against increasingly uncertain winter rains. In this study, the diverse mix had a level of diversity that led to more stability, even if that stability did not consistently lead to enhanced weed suppression. Adjustments in cover crop phenology could be an important line of future research. Perennial cropping systems have significant temporal flexibility compared to annual cropping systems, where relatively few options exist for growing a cover crop during the cash crop growing season. Optimization of when a cover crop is planted and terminated in the orchard could improve weed suppression or other ecosystem services. Furthermore, the timing of these management actions could differ across orchard cropping systems, depending on climate or various needs of the main crop. Examples that could facilitate different cover crop management timings compared to those used in the present study could include cropping systems such as citrus, which is harvested during winter months, pistachio, which utilizes off-ground harvest during the fall, or apples, which are frequently grown in climates with colder winters. While this study implemented cover crops on a time scale relevant for adoption in contemporary orchards, further understanding of the cumulative impacts of cover cropping on the decades-long scale of orchard lifespans could further improve temporal arrangements of cover crops.

Sustainable orchard cropping systems require vegetation management programs that produce accessible orchard floors while minimizing management intensity. Orchard systems in California require significant upfront investment that expose orchard growers to heightened risks related to climate change, water scarcity, and land use change compared to more flexible annual cropping systems. Sustainable management systems could reduce risk for orchard growers who manage over 1 million ha of almonds D.A. Webb, walnuts , stone fruit , and similar orchard crops . Weed management is an important area for orchard sustainability improvements, given that vegetation and vegetation management practices affect many environmental quality parameters across the orchard agroecosystem, including factors such as herbicide use intensity, soil health, water quality, and air contaminants . Rather than seeking vegetation-free orchard floors, growers could potentially cultivate orchard floor vegetation that contributes to ancillary management goals and provides additional ecosystem services . Cover crops offer flexible management options for creating a functional orchard floor . As one cultural management practice within a suite of integrated pest management practices, cover crops can provide a framework for understanding the seasonality and phenology of weed life cycles while also promoting grower acceptance for some level of orchard vegetation . Typically, commercial orchards in California will have a zone of high intensity weed management in a strip centered on the tree row, often 25-50% of the orchard floor, with less intensive weed management in the remainder of the alley between rows . The high intensity tree strip is maintained to keep weeds from interfering with irrigation infrastructure and minimize non-crop water use in the irrigated area. In crops that are harvested from the orchard floor, which includes many tree nut crops, the alley is generally managed to be weed free ahead of crop harvest in the late summer, where heavy plant residues could impede sweepers and other harvest equipment. Alley management in the winter can vary with grower preferences, but cover crops could easily be implemented in this zone so long as cover crop residues do not affect crop harvest operations. California has mild, rainy winters, which are conducive to cover crop growth. Furthermore, tree nut and stone fruit crops are deciduous, and dormant tree canopies allow ample light to reach the orchard floor throughout the winter, until trees leaf out in mid-February for almonds and later in the spring for other species. Therefore, cover crops in California orchards could have minimal negative impacts on the cash crop if they consist of winter annual plants, since these species have a predictable life cycle that could usually begin with winter rains without supplemental irrigation and ends during hot, dry summers common in the Mediterranean climate of central California. With this context, cannabis racking systems winter annual cover crop species could be used to displace winter weeds in orchard alleys. Literature focusing on cover crops and weed management often centers on annual cropping systems, with cover crops growing in the off season between annual cash crops resulting in temporal separation . Heavy cover crop residues drive weed control by limiting the emergence of weed seedlings before and during cash crop emergence . In contrast, cover crops in orchard systems have spatial separation between cover crops and cash crops, which increases the importance of interference with concurrently growing weeds .

Spatial separation also creates flexibility by reducing restrictions on the cover crop growing season imposed by annual cash crop planting and harvest, and information about the phenology of plant competition could help optimize the management of an abundant, competitive cover crop . Finally, California orchards undergo dormant-season management like pruning and orchard sanitation, which could create tradeoffs between these management practices and a winter cover crop. For these reasons, weed-suppressing cover crops require additional research that informs practical management guidelines relevant to orchard systems in this California. Specific cover crop management recommendations could help growers balance the many functions of cover crops and support various ecosystem services and management goals. Specific management recommendations also support adoption by reducing knowledge barriers of this complex cultural management practice. Would-be adopters of orchard cover crops need to develop a plan that addresses many aspects cover crop establishment and management and acknowledges potential tradeoffs. To address this need, we developed specific questions about cover crop planting date, the phenology of crop-weed competition, and intensified cover crop practices. Research on intensified cover crop management could help us understand how agronomic practices including planting rate, fertilizer or herbicide inputs, cover crop species mixtures, and cover crop termination practices interact with many aspects of agroecosystem function . Likewise, varied cover crop planting date information helps us understand how cover crop establishment affects cover crop development and when weed competition occur relative to cover crop establishment and the onset of winter rains. Our objectives were to assess how different aspects of orchard cover crop management affect winter weed management. We evaluated how cover crop management system and planting date impacted cover crop and weed biomass. We also evaluated how cover crop planting date affects cover crop and weed emergence rates. Finally, we evaluated how cover crop management systems differentially affect summer weed emergence through different levels of cover crop residue. Together, these research questions can provide information about to what extent covercrops contribute to overall orchard floor vegetation management and which cover crop management practices have the largest effect on weed suppression.We initiated two different experiments to separately examine the effects of intensified cover crop management systems and cover crop planting date in nut orchards. These were small plot experiments in research orchards with commercially relevant cultural practices, including tree spacing, tree strip management, and irrigation. The ‘intensification experiment’ involved a range of cereal rye cover crop management intensities, from minimal management to an intensively-managed forage intercrop, planted in a walnut orchard. The ‘planting date experiment’ involved two different multi-species cover crop mixes each planted at early and late planting dates in an almond orchard. These experiments focused on plant population and community characteristics of orchard floor vegetation in the orchard alleys only. We used the different orchards as a study system but did not intensively monitor orchard crop performance or yield. Namely, almonds maintain a leaf canopy for a greater portion of each year, but the almond orchard in this study was younger with a smaller tree canopy compared to our older walnut orchard. However, the orchard floor environment is generally similar in almond and walnut cropping systems, and each has similar cultural factors including irrigation, alley and strip management, and winter pruning and pest management operations. For cover crops to be a feasible management strategy, they should work in a variety of orchard systems, conditions, and life cycle stages. Therefore, understanding how cover crops influence vegetation management across different orchards is a key aspect of this study. The intensification and planting date experiments were managed independently of one another, but there is a shared treatment to facilitate comparisons between the experiments. Intensification experiment.

The cultivation will effectively hold soil moisture for 30 days or longer, allowing for successive plantings over time with minimal effort. To ensure harvest continuity for staggered plantings, plant the next round of beans when the prior planting is in the “crook” stage , approximately every 10 days.When produced on a commercial scale, beans should always be planted to moisture rather than irrigated up. If you plant beans into dry soils and then irrigate them to initiate germination, weed seeds will germinate at the same time as the newly planted beans. In most cases weeds will quickly outcompete the beans and compromise effective weed management. It is not possible to cover labor costs, through sale of the crop, for hand weeding when weed pressure is high. See the publication Tillage, Bed Formation, and Planting to Moisture in this Grower Guide series for additional details. When planting to moisture, use a wide “Alabama” shovel mounted on the planter to run ahead and push off the dry dirt on top of the bed. Set the shovel so that it goes deep enough to get into the sub-surface moisture. When set correctly, the shovel leaves a flat “V” pattern down the center of the bed. On most soil types, as long as you can see some slight darkening of the soil that is exposed when the bed top is knocked off compared to the drier surface soil, there should be enough residual pre-irrigation moisture in the soil at the bottom of the “V” to initiate germination of the newly planted bean seed. Plant beans at the low point in the middle of the bed to conserve moisture deeper in the soil . In most cases 1–1.5” is a good planting depth for strong germination, growth rack although beans can emerge when planted 2” deep as long as the soil is “loose” and not compacted above the seed. Loose soil above the seed line also limits evaporative loss.

When beans seeds all emerge at roughly the same time, you know you have done a good job of planting them. Note that most bean planters are designed to drop seed into a small trench that is then covered with soil and firmed up with the planter press wheel. Avoid planting when the soil is too wet as the press wheel can create a compacted layer over the seed that dries into a firm crust, which can significantly impede successful bean seed emergence.When choosing a tool-bar-mounted planter for larger-scale bean plantings , select a planter that singulates the seed, has double disc openers that cut deep into the soil , and has a press/tamp wheel. Options include the Clean Seeder TP , the John Deere 71 “flexi” planter , and the International 185 planter planter. Note that on smaller farms, the cost of this type of planter can be a significant capital expense. Although no longer available new, the John Deere 71 “flexi” planter is still one of the more common planters used on the Central Coast for planting beans . It is called a “flexi” planter because it is designed to “flex” or “float” over heavy residue. This design feature makes it an ideal planter for planting beans following cover crop incorporation in the spring.The Clean Seeder TP and John Deere 71 planters have double disc openers that create a very narrow opening in the soi lFigure 2. The seed falls into the opening while the sides of the opening are being held open by the discs. The small trench created by the openers easily collapses once the disc openers pass. The press wheel on the planter firms the soil over the seed and helps to reestablish capillarity, which improves soil moisture movement from lower in the soil horizon. If you question whether there is adequate soil moisture, assess moisture early the next day after planting. Soil moisture typically improves overnight as a result of the light compaction created by the press wheel. The advantage of double disc openers is that they can easily cut through or roll over residual cover crop or crop residue.

In comparison, Planet Jr. planters use a fixed opener shoe, which gathers field trash when used to plant at depths greater than 1 inch. When residual crop residue wraps on a fixed shoe, it pushes soil away from the seed line, causing skips in planting and an uneven surface. Plate planters such as the Clean Seeder TP-TB, John Deere 71, and International 185 do an excellent job of “singulation” of the bean seed. Driven by the press wheel, the seed plate rotates in the bottom of the seed hopper. The holes in the plate allow single seeds to drop into the hopper cells. The cells rotate over an opening in the bottom of the hopper, and with the help of a “knocker,” drop the seed at a selected spacing as the planter moves through the field. Planting depth can be adjusted with a rotating cam on the side of the planter, which changes the angle of the press wheel in relation to the disc openers. Seed spacing is set based on the number of holes in the seed plate, as well as gearing, which is easily changed. Select seed plates carefully to match varieties, since bean varieties vary significantly in size and shape.When beans germinate, they lift the two seed halves above the soil surface. This is referred to as “epigeal” germination. The emerging beans will first push through the soil with the stem in a “crook” position and then the cotyledons will emerge, followed by the first true leaves as the hypocotyl straightens out following emergence. The early stage of germination when the stem first appears above ground is referred to as “in the crook” . Emerging beans are very susceptible to heat damage at the soil surface as they push upward. When planting in late summer , farmers in warmer inland valleys of California commonly put a “soil cap” on the bean seed line with small disc hillers . The hillers are attached to, clone rack and run directly behind the planter to form a small mound of loose soil directly over the seed line. During times of high daytime temperatures, growers dig up the embibed seeds daily until they see uniform radical emergence. They then mechanically knock off the cap. If timing is good, the beans will emerge through the soil during the cool of the evening, thus avoiding the issue of stand loss due to high soil temperatures.

In cooler coastal production areas you do not need to cap the seed lines. However, a very light soil cap helps keep the soil loose and moist. This can improve ease of emergence and stand uniformity in both extremes—when the soil is either slightly too wet or too dry.When soil moisture is optimal, planting to moisture allows the beans to germinate but limits weed germination, as most weed seeds require more moisture to trigger germination compared to the large bean seed. The beans emerge in a small trench in the middle of the bed, where vigorously growing beans will easily outgrow most weeds . Let the beans grow as long as possible without irrigation to allow them to root deeply and to minimize weed competition. In most climate zones on soils with decent water holding capacity, the beans can grow to full bloom before you need to irrigate . Once beans are 5–6” tall, do a first cultivation. Use a standard 3-bar cultivator with a set of reverse disc hillers running along each side of the plant line, side knives along the sides of the beds, and sweeps in the furrows. Run small chisels behind the tractor tires to a depth of about 4” to break tractor tire compaction and facilitate subsequent cultivations. This first cultivation will effectively terminate most newly germinated weeds from seed line to seed line. Then lay drip tape along the seed line. As the beans continue to elongate, use a rolling cultivator for the second—and most effective—cultivation. Properly set, the cultivator will gently return the dirt that was pushed off the bed top at time of planting to the middle of the bed . The bed should end up looking just like it did prior to planting. If bean stems are long enough, this “dirting” cultivation will effectively cover both the drip line and smother any weeds that have emerged in the seed line while covering only the lower stem of the bean plant. This last cultivation, or “dirting,” leading up to harvest is commonly practiced on large acreages of many agronomic crops that are planted to moisture in situations where herbicides are not used. To perform this cultivation successfully requires specific and tightly adjusted implements, and a significant level of tractor skill. As small farms scale-up to mid-sized farms and larger acreages, planting to moisture and dirting can significantly reduce the labor required for weed control.On small plots , you can easily plant beans to moisture by hand. Pre-irrigate your beds, and use hand tools to take out the newly germinated weeds. Push the bean seed into the deeper moisture by hand. Any subsequent weed growth can be handled with a wheel hoe or hula hoe. On larger plots , plant beans to moisture with simple tools. Use a rototiller following preirrigation to terminate weeds and form a soil or “dust” mulch. Form a planting trench with a small furrowing shovel mounted on a wheel hoe to access deeper soil moisture. Plant with a Planet Junior push seeder using the general purpose “deep” shoe, or the Jang large seed push seeder . On this scale, weeds can be managed using hand tools or wheel hoes.Time the first post-emergence irrigation based on subtle signs of water stress in the bean plants during warmer days— especially later in the day. Pay attention to slight changes in the color of the bean plants: a plant with adequate soil moisture appears dark green; when stressed, the green color shows hints of gray. Following emergence of the first true leaves, water stress will be very evident as a stressed plant tends to push the first true leaves together and upright. These stress symptoms typically show up on field edges where pre-irrigation coverage may not have been adequate, or where soil is more compacted.Monitor stress daily and wait as long as possible before the first irrigation to allow for deep rooting, promote early and uniform flowering, and inhibit weed competition. Apply about an inch of water with the first drip irrigation. Subsequent irrigations should be scheduled using evapotranspiration data from your local CIMIS station or another sources , and based on the percent canopy of the bean plants at time of irrigation.Fresh market beans are at their best when the seeds inside the pod are still very small and the bean is still tender. Bean pods form quickly; the harvest must be timed well to avoid harvesting any beans that are “over-mature.” On many fresh market “round pod” bean varieties, you shouldn’t be able to see bumps in the pod indicating seed development. Open random beans to check for over-maturation. Another good field test to determine market quality is to break the beans in half—they should break easily and not bend. Harvest in the morning when the temperature is cooler. Harvest efficiency is related to the picker’s ability to grab as many beans as possible in a single handful and pull them off the plant with enough care not to break any beans at the stem end. Efficient bean harvest is a fine art that takes a strong back, practice, and fast hands. A good bean picker is able to pick 50 lbs., or roughly two 5-gallon buckets per hour. This rate is only possible when the beans are heavily laden with evenly mature green beans. Sorting beans when harvesting is simply not economically viable. Depending on variety and uniformity of maturation, a stand of beans can be harvested one, two, or three times. The over-mature pods from extended harvest need to be sorted out, and this task is simply not economical. When the next succession is ready to go it is time to walk away from the last planting.Field bindweed is a perennial weed that can persist in many cultivated and unmanaged landscapes .

Model fitting is less sensitive to smaller n, allows for unbalanced designs , and is easier to calculate variances . Our experimental design for many performance measures requires subsampling multiple individuals within plots, and model fitting with random effects allowed for the incorporation of the variance among subsamples, which would be lost if we took the average to calculate an FEV. The performance measures of biomass, cover, and height were log transformed and fit with linear mixed effect models . We performed model selection using backwards stepwise Akaike Information Criterion and the ran ANOVAs followed by post-hoc multiple comparison tests. Percent cover was modeled at a) the community level to capture net community feedbacks that may be hidden when comparing smaller differences among species and b) the individual species level to see if a particular species was driving the feedback. Biomass was assessed only on the community level. Plant height was modelled individually for each species, as height inherently differs due to natural history, and we are primarily interested in how soil conditioning effects within-species height variation. Seed production measures were fitted with generalized linear mixed-effects model for the negative binomial family with the “glmmTMB” package . Likelihood ratio tests were used to determine significance of fixed effects. Native flowering individual was modeled on both the individual species level and community level, as done previously for percent cover. Kruskal-Wallis tests were used on A. triuncialis and S. pulchra seed production, vertical growing racks as the data violated model assumptions due to few surviving individuals. Germination of all seeded species was analyzed with a time-to-event model using the “drc” and “drmSeedGerm” packages .

This method models the cumulative germination curve with the interaction of soil conditioning and community treatment, assuming a log-logistic distribution of germination time and accounting for ungerminated seeds. The model parameters that correspond to time to reach 50% germination and maximum germination were compared via the compParm function to evaluate the drivers of differences in germination patterns between conditioning and community treatments.This long-term field study demonstrated that native and exotic communities both experienced negative feedbacks– performing better in the other community’s soil. The eleven year conditioning phase provided a unique opportunity to assess feedbacks in response to soil changes that may take years to develop, such as build-up of soil organic matter. Setting both experimental phases in the field was necessary to understand the overall strength and role of feedbacks in structuring plant communities in a more realistic setting, as both phases experienced high environmental variability. Any long-term soil changes due to vegetation composition were strong enough to be detected over the observed variability in soil texture, ground squirrel disturbance, and annual precipitation . The two-year feedback phase also experienced strong variation in annual precipitation, as it included an extremely wet year followed by an extremely dry year . The detection of feedbacks required measuring multiple plant responses, as the natives and the exotics did not exhibit feedbacks within the same trait, nor did either show a feedback in above ground biomass, the most commonly measured indicator of plant fitness. Overall, our results suggest the need to measure multiple traits and life stages to capture potential responses to soil conditioning . We detected negative feedbacks on both native and exotic grasses, suggesting California grasslands are structured by negative feedbacks, similar to many other systems , and that positive feedbacks are not a main factor in exotic grass dominance .

The feedbacks were stronger for the native community, which had improved performance in exotic soil, as measured by cover, height, and reproductive productivity. These results are similar to a number of other studies, indicating that negative plant-soil feedbacks are stronger for native than exotic species . Previous greenhouse studies of California grassland species showed that in the short term , native species experienced positive feedbacks and performed worse in exotic conditioned soil, the opposite of our results . This may be due to different feedback mechanisms at play in a shorter conditioning phase or the difference in life stages tested. The exotic grass community had greater below ground biomass in native-conditioned soils. Another feedback experiment with similar species linked greater deep-root exotic biomass to the increased soil organic matter and water holding capacity in deep soils cultured for 10 years by the native perennial Stipa pulchra . Our study did not detect these physical and chemical soil differences but that may be because our site was drier and had higher clay content. It is also possible that these soil changes did occur and were ecologically but not statistically significant in our study. It is also possible that other driving mechanisms increased exotic deep root-growth in native soils at our site, such as potentially enhanced soil aggregation from the deeper perennial roots with more fine root hairs which would increase plant suitability due to more pore space and water flow .The native vs. exotic communities did not differ in their effects on soil water holding capacity, percent carbon or nitrogen, nor soil organic matter. Differences did arise in their effects on net nitrogen mineralization and nitrification, and fungal and bacterial community composition. The exotic plant communities cultivated significantly different fungal and bacterial community compositions from those cultivated by natives, similar to many other studies .

The fungal communities were distinct across soil conditioning treatments at all soil depths, but the bacterial communities differed by conditioning treatment only in the shallowest and deepest soil zones, supporting our hypothesis that differences in rooting depths are a factor in soil conditioning. Changes in microbial composition may directly impact plant performance , or may indirectly alter plant performance by changing resource availability . The native vs exotic communities also differed in effects on the abundances of nitrifying bacteria, AMF, fungal pathogens and saprotrophs, and soil nitrogen cycling, and below we’ll discuss how similar changes have been linked to plant performance in other feedback studies. However, determining the causal mechanisms behind the observed feedbacks is beyond the scope of this experiment, as the observed net feedbacks might be due to these differences in soil properties, properties not measured in this study, or from their interactions.Fungi in the plant pathogen and plant pathogen-saprotrophs guilds were greater in abundance in native-conditioned soil compared to exotic soil. This difference may be due to the life histories of the two grass groups, as the perennial native roots provide a constant food source for pathogens whereas the annual exotic roots die off every spring. Alternatively, fungal pathogenic richness is positively correlated with specific root tip number, which is likely higher in native roots as they are deeper with more fine root hairs . Greater pathogen abundance in native-conditioned soil plots could also be attributed to being largely dominated by S. pulchra in the conditioning phase, and evidence suggests that greater soil pathogen accumulation occurs under monocultures . Negative plant-soil feedbacks are common and thought to maintain plant diversity, and are often attributed to the buildup of localized pathogens . Thus, the strong negative feedback observed in the native grass community may be influenced by lower exposure to pathogenic attack in exoticconditioned soils. In a study with similar species, native grasses also experienced a strong negative feedback, but doubled in growth when native soils were sterilized , supporting the suggestion that pathogens are driving the feedback. Further, pathogens accumulate over time, and the longer conditioning phase of our experiment may explain the difference in feedback direction compared to shorter-term studies . The lower fungal abundance in exotic-cultured soils did not benefit exotic grasses, however, as they performed worse in their own cultivated soils. They may culture their own specific pathogens and also be less susceptible to generalist pathogens than native grasses . Saprotrophs were also greater in native-conditioned soils and could potentially have become parasitic which can occur when soils are dominated by a single species, growing racks and the native soils were largely conditioned by S. pulchra . However, while these could potentially contribute to the natives’ negative PSF, these effects might be short-lived, as saprotroph composition can change quickly in response to the current plant community .We did not find any difference in total N between the two conditioned soils, but net mineralization and nitrification rates were lower in soils conditioned by exotic grasses compared to the native perennials. These results are similar to those found by Parker et al. 2012 and Carey et al. 2017. Lower net rates can occur because decomposition and N release are slower , and/or when there is higher microbial immobilization, resulting in high competition between plants and microbes for N .

If the difference in rates of N cycling influenced native performance, we would expect greater native above ground biomass on native-conditioned soil, which we did not see. Corbin and D’Antonio suggest that changes in mineralization and nitrification rates are easily reversed under a new plant community, and so would not lead to feedbacks. We also detected changes in the nitrifying bacteria; ammonia oxidizing and nitrite oxidizing bacteria were both greater in the deeper exotic-conditioned soils than the native-conditioned soils. As there are fewer deep roots in exotic plots, bacteria in those soils have greater access to ammonia and nitrite. Similarly, Hawkes et al. looked at soils under the native S. pulchra and exotics B. hordeaceus and A. barbata, species used in our study, and also found greater AOB abundance in exotic soils.The presence of a competitor can eclipse, neutralize, or change the strength of a feedback in a species . Assessing plants grown in a community with both intra and inter-specific competition can thus help us understand the proportional role of feedbacks in community structure, particularly if we are interested in communities comprised of species commonly found together in nature, such as our native mix and our exotic mix. Our community treatments do not allow us to tease apart individual species’ contributions to soil conditioning nor touch on whether the direction and magnitude of a feedback is dependent on the specific identity of the conditioning plant and the feedback plant , but did show feedbacks were still observed overall in our two communities. In California grasslands, certain groups can remain dominant over time, but the stability of the group is due to variations in which species dominate within the groups, as environmental conditions change . Our results thus are relevant to the diverse and shifting communities found in California grasslands, especially as feedbacks can be non-additive in a community compared to monoculture . Community type played a major role in native grass abundance, and only slightly affected the exotic grasses. Native establishment was so poor in the mixed native and exotic community that we were not able to analyze most performance measures. This is not surprising, as exotic annual grasses in this system both germinate and grow much faster than native perennials, which allows them to outcompete the native seedlings for light and soil moisture . The few native individuals growing in competition with the exotics, however, still experienced a negative feedback in percent cover. Thus, feedbacks influence natives more subtly in full competition with exotics but can be a stronger control in restoration settings where competition by exotics is actively minimized. As the exotic grasses are the better competitor at the seedling stage, competition with natives did not alter exotic feedback overall. Our results show that competition among native and exotic grasses clearly outweighs the role of plant-soil feedbacks in community structure, with exotic dominance resulting regardless of soil provenance.Our results do not support our hypothesis that exotic annual grass invasion negatively impacts native restoration through the soil, suggesting that soil amelioration may not be necessary to improve restoration success. Studies comparing remnant, restored, and invaded grasslands found that soil biotic communities take years to recover , although another found mycorrhizal communities specific to S. pulchra returned quickly after restoration . Fortunately, it appears that exotic soil conditioning at our site does not majorly hinder native establishment and restoration success but rather benefits natives, even though exotic soils still have been found to decrease native performance when compared to sterilized soil , highlighting native grass susceptibility to pathogens. When establishing native cover is the main goal of a restoration project, reaching 30% native cover is considered a success. Higher cover is very important for the long-term success of a project, as once established, native perennial grasses become more competitive against future exotic annual seed pressure . Thus, the 15% difference in percent cover observed in our study is substantial.

Valuable crop resources require maintenance and protection. In ant fungus gardens, Escovopsis fungi are well known as specialized parasites, especially in the tropics . Infection of the fungus garden by Escovopsis decreases colony fitness and can lead to colony collapse . However, Escovopsis does not regularly parasitize fungus gardens cultivated by Trachymyrmex septentrionalis, the northernmost fungus-growing ant, a finding based on a single culture-based study that detected Trichoderma and several other microfungi but not Escovopsis in T. septentrionalis fungus gardens and that did not test its infectiveness . Many other fungi have also been isolated from ant fungus gardens, although the culture-based methods used and the often nonsystematic sampling obscures their ecological distribution and symbiotic role . Beyond Escovopsis, only Trichoderma and Syncephalastrum have been shown to exhibit some degree of pathogenesis toward Atta ant fungus gardens [but not toward T. septentrionalis. More work is needed to fully understand the diversity and ecology of these and other potential fungus garden pathogens and the mechanisms by which ants respond to protect their fungus gardens. Ants have developed numerous chemical and behavioral mechanisms to avoid infection of their fungus gardens and prevent colony collapse . Chemical defenses include the application of antimicrobials from ant metapleural gland and fecal secretions , and from antibiotic-producing Pseudonocardia bacteria that the ants host on their cuticles . Ant behavioral defenses include grooming their own bodies and those of their nestmates , task partitioning between different members of the colony , grow racks and preprocessing of foraged material before its incorporation into the fungus garden . Fungus garden grooming and especially weeding represent important ant behavioral responses to fungal pathogens that have invaded the fungus garden .

Although these defensive responses have been described in detail, how fungus-growing ants detect threats to their fungus gardens remains poorly understood . Insects are well-known to communicate using chemical cues. For example, Mastotermes darwiniensis termite soldiers respond to the cuticular hydrocarbon p-benzoquinone with increased mandible openings, indicating excitement . In another example, diverse ant species destroy diseased pupae in response to cuticular hydrocarbons emitted during fungal infection . Although the mechanism by which fungus-growing ants detect pathogen infections remains unknown, they do detect and respond to chemical cues that promote other aspects of fungus-garden health. For example, Acromyrmex lundii ants use carbon dioxide as a spatial cue to position their fungus gardens at optimum soil depth . Based on unfavorable CO2 levels, ants will relocate their gardens, a remarkable demonstration of their sensitivity to small molecule cues. Pathogenic fungi also produce metabolites that can affect fungus-growing ant health and behavior such as shearanine D produced by Escovopsis fungus garden pathogens, which reduces ant movement, inhibits Pseudonocardia growth, and directly causes ant death . Thus, chemical communication mechanistically underpins diverse symbiotic interactions in ant fungus gardens. In this study, we sought to identify the chemical cues that induce hygienic weeding behavior during infections of ant fungus gardens. We established that Trichoderma fungi are common in T. septentrionalis ant fungus gardens and that T. septentrionalis ants weed their fungus gardens in response to treatments with live Trichoderma spores, Trichoderma chemical extracts and fractions, and Trichoderma-derived pure compounds. Our results suggest that peptaibol metabolites are produced by Trichoderma fungi during fungus garden infection and cue ant weeding behaviors that promote fungus garden hygiene.

This study fills the gap between the well-studied hygienic behavioral responses of fungus-growing ants and the hitherto unknown chemical cues that induce them. Such chemical cues are likely widespread in other agricultural systems where they are used by hosts to detect and prevent pathogen infections.We used internal transcribed spacer region 2 community amplicon sequencing to investigate microfungal communities in field-sampled and apparently healthy T. septentrionalis fungus gardens from across the Eastern USA . Reads classified as Trichoderma, a common genus of mycoparasites that also includes some saprophytes and plant mutualists , were both the most abundant and prevalent noncultivar reads in field-sampled T. septentrionalis fungus gardens, with a median relative abundance of 1.2% and a maximum of 68.6% in the most extreme case . Other noncultivar fungi in these fungus garden samples were only rarely abundant , and no reads in this dataset matched the common tropical fungus garden pathogen Escovopsis. Only four samples out of 83 were dominated by a noncultivar fungus; two of these were dominated by Meyerozyma, one by Trichoderma, and one by an unclassified member of the family Stephanosporaceae . Although the sampled fungus gardens did not visually appear to be diseased at the time of their collection, our ITS sequencing results suggest that Trichoderma spp. may be a low level but constant threat to T. septentrionalis fungus gardens in situ. In a parallel analysis, we also generated environmental metabolomes from 53 field-sampled T. septentrionalis fungus gardens, 18 of which were the same as those sampled for our ITS dataset. Using untargeted liquid chromatography-tandem mass spectrometry and Global Natural Products Social molecular networking , we identified chemical evidence for the presence of Trichoderma spp. in T. septentrionalis fungus gardens.

After searching our network of specialized metabolites from these fireshly collected fungus gardens for metabolites produced by potential pathogens, we identified one cluster that contained a feature whose molecular weight and fragmentation pattern were consistent with the peptaibol trichodermide D along with a suite of related peptaibols, most of which were originally isolated from Trichoderma virens CMB-TN16 . A related series of peptaibol features were detected in three fungus gardens collected from North Carolina, as shown by the nodes in the network that were closely related to known peptaibol features . Given that peptaibols are characteristic of mycoparasitic members of the Hypocreales and especially prevalent in Trichoderma , our detection of peptaibols from these samples further supports that Trichoderma is present and metabolically active in field-sampled T. septentrionalis fungus gardens.To identify the underlying mechanisms by which Trichoderma inoculation induced waste production by the ants, we exposed T. septentrionalis fungus gardens to extracts of Trichoderma sp. JKS001884. Colonies were tested multiple times, including both intracolony and intercolony replicates . In all tests, ant waste production was greater in extract-treated fungus gardens compared to the negative controls treated only with DMSO or left untreated . These results suggest that ant waste production was induced by metabolites from the Trichoderma extracts and that ant responses were not solely due to the physical presence of Trichoderma cells. To identify the metabolites responsible for this bioactivity, we evaluated semi-purified fractions of our Trichoderma extract for their ability to induce ant behavioral responses. Fractions B, D, and E induced the greatest amount of ant waste production , although further analyses determined that fraction B was chemically dissimilar to fractions D and E and was instead highly similar to fraction A , one of the least bio-active fractions . Given that such early fractions often contain pan-assay interference compounds , we prioritized fractions D and E for further analysis. Comparative metabolomics was used to prioritize and identify metabolites that were highly abundant in fractions D and E. These fractions grouped together along non-metric multidimensional scaling axis 1, distinct from all other fractions , demonstrating their high chemical similarity, as also determined using Spearman’s correlation . Comparisons of total ion chromatograms indicated considerable overlap of peaks in fractions D and E especially between 7 and 8 min, planting racks retention times at which numerous peptaibols elute. In addition, a large number of features that cooccurred in fractions D and E had molecular weights above 1,000 Da, consistent with peptaibol metabolites . This motivated further chemical analysis to identify features that may underpin the ant behaviors induced by fractions D and E.Based on our prioritization of fractions D and E , we generated a heat map to identify features shared between fractions D and E and dereplicated these features using NP Atlas . Fractions D and E exclusively shared 118 features , although an additional suite of features was highly enriched in fractions D and E but present in lower abundances in other fractions. Based on their molecular weights, retention times, and fragmentation patterns, many of these shared features were consistent with the structure of peptaibols. Three peptaibol-like features were exceptionally abundant in fractions D and E : [M + Na]+ peaks m/z 1197.7557 and 1183.7406, and [M + H]+ peak m/z 1452.8756. Together, the ion abundances of these three features represented a combined 35.5% and 75.5% of total metabolite abundance in fractions D and E, respectively. Further exploration of the accurate masses and fragmentation patterns of these features confirmed that all three likely represent peptaibols, two of which have masses consistent with the peptaibols trichodermides B/C and D/E, although several other peptaibols have similar masses. These results prompted further ant weeding assays using a small library of purified peptaibols to determine if specific, individual peptaibols induce ant behavior and if this behavior is a result of collective and/or nonspecific peptaibol metabolites. We tested six peptaibols isolated from Trichoderma arundinaceum and one purchased peptaibol to evaluate their ability to induce ant waste production. Although these purified peptaibols varied in their bioactivity, all induced ant waste production, withsome replicates having higher levels of bioactivity than the extract . Two of these peptaibol metabolites, 1 and 2 , are previously undescribed compounds given the trivial names trichokindins VIII and IX, respectively. Mass spectrometric analysis confirmed that both metabolites were present in our Trichoderma extract and in the bioactive fractions D and E .

Full characterization of 1 and 2 indicated that these previously undescribed compounds have a classical peptaibol structure, being composed entirely of amino acids, including characteristic α-aminoisobutyric acid moieties. Because each isolated peptaibol induced ant weeding, this behavior is likely characteristic of the peptaibol class, in general, and may not be specific to individual peptaibols. Our results strongly suggest that ant waste production is induced by Trichoderma-derived peptaibol metabolites; however, we cannot discount that other fungal secondary metabolites were present in our Trichoderma extracts that may also induce waste production. Using comparative metabolomics, we identified a feature suggestive of the fungal metabolite roselipin 1A , although this feature had similar abundances across fractions D, E, and F. Because fraction F did not induce substantial ant waste production, this feature did not likely cause the observed ant weeding behavior. Features with masses matching two other common fungal metabolites, gliovirin and heptelidic acid , exhibited similar patterns of abundance in both inactive and bioactive fractions, and thus were also unlikely to induce the observed ant weeding behavior. Thus, the unique correlation between peptaibol-enriched fractions and increased ant waste production underscores the relationship between Trichodermaderived peptaibols and ant waste production.Our data show that Trichoderma spp. are common in wild T. septentrionalis fungus gardens sampled from across a broad geographic range , which suggests that at least some Trichoderma spp. may naturally cause fungus garden disease. Supporting this hypothesis, our isolation of Trichoderma spp. from diseased gardens, experimental infection of healthy gardens, and detection of Trichoderma during experimental infections using ITS2 amplicon sequencing all provide experimental evidence that Trichoderma spp. can be opportunistic pathogens of T. septentrionalis fungus gardens and fully satisfy the experimental aspects of Koch’s postulates for disease causality, which include the isolation of a pathogen from a diseased host, experimental infection of a naive host using that isolate, and reisolation of that disease-causing isolate . The ecological aspects of Koch’s postulates are partially fulfilled in this study by our detection of Trichoderma in environmental fungus gardens, even though these were not visually diseased at the time of collection, a difficult to detect event due to acute disease leading to rapid colony collapse and our detecting colonies to collect based on the presence of active ants, likely indicative of colony health. We also note that fungus garden diseases can be present but not visually apparent , making it challenging to definitively link Trichoderma presence to disease in the field, and that a focus on pathogen presence/absence without consideration of pathogen load, microbiome composition, or environmental conditions is a noted weakness of Koch’s postulates . Although the species identity, ecological source, and relationship to disease of the low levels of Trichoderma present in T. septentrionalis fungus gardens remains unclear, our results indicate the consistent presence of these potential disease-causing agents that could at least in some cases necessitate defensive responses by the ants. Together, our ecological and experimental data support our conclusion that, at least under some conditions, Trichoderma spp. can infect T. septentrionalis fungus gardens. Metabolomics analyses of lab-reared fungus gardens inoculated with T. septentrionalis-isolated Trichoderma spp. revealed the presence of peptaibols in infected gardens .

The bracts are green and extend beyond the tepals. Notably, pistillate flowers possess bracts that are comparatively longer than those of staminate flowers . Pistillate flowers have five tepals, which are rounded or blunt with an apical notch . Each pistillate flower has one superior gynoecium. Fruit are single seeded utricles and become wrinkled when dry . Seeds are dark reddish-brown to black, lens-shaped, and 1.0 to 1.3 mm long. Staminate flowers have five stamens and five acute tepals with a dark green midrib . Based on these observations, the floral diagrams and formulae for Amaranthus palmeri pistillate and staminate flowers are shown in Fig. 4. In summary, a staminate flower has one to three bracts, five tepals in a quincuncial sequence, and five stamens. A pistillate flower has one to three bracts, five tepals in a quincuncial sequence and one superior gynoecium made of a single ovary containing one ovule.In the axils of the young leaves, inflorescence primordia appear soon after the reproductive transition. The initiation of tepal primordia is the first indication of floral organogenesis . The diameter of the central meristem above the tepal primordia is about 30 µm. The meristem broadens, and five stamen primordia are initiated as hemispherical mounds in a spiral pattern along the outer rim of the floral meristem . A protuberance forms at the center of the meristem shortly thereafter . This protuberance has similarmorphology and position to the early stages of carpel initiation in pistillate flowers. Stamen primordia soon become elliptical, and anthers have elongated sufficiently to arch inward and cover the floral apex . Differentiation into anther and filament is obvious when the stamen primordia broaden, commercial grow racks which is accompanied by a change of shape . The lobes will later develop into the pollen sacs. The filament remains short and starts to elongate just prior to anthesis. The diameter of A. palmeri pollen is about 31 µm and the number of apertures per grain is about 25.

The centrally-located putative carpel primordium shows little change in size, with the approximate diameter ranging between 45 µm and 70 µm, and the approximate height between 30 µm and 50 µm . This structure remains undeveloped and surrounded by the bases of the filaments rather than progressing to form a fertile mature gynoecium .With the transition to flowering, five tepal primordia are initiated first, in a weakly spiral pattern on the flower apical meristem . At the center of the flower meristem, the gynoecium arises, consisting of one carpel primordium. The primary carpel primordium is differentiated into an annular ovary wall primordium around a central single ovule primordium . The ovary wall grows up from the ring primordium, forming two style primordia . Each style primordium elongates and forms one long style. The gynoecium elongates by intercalary growth and forms the ovary that later closes post-genitally at the top . Styles elongate and a stigmatic region differentiates along the adaxial surface. The stigmatic branches are unifacial and papillate. After fertilization and seed maturation, stigmas and styles desiccate . The single ovule of A. palmeri is anatropous or campylotropous . We also found somemature pistillate flowers with three styles . We speculate that the protuberance located near the inwardly elongating two styles may develop and become the third style. Further research is needed to confirm this.This is the first study of floral development in Palmer amaranth and documents the developmental differences between staminate and pistillate flowers. Flower and plant sex in A. palmeri can be distinguished morphologically by sharpness of bracts and shape of tepals prior to anthesis. Bracts are sharper in female plants than those in male plants. Tepals are of obtuse shape in pistillate plants while tepals are acutely pointed in staminate plants. Based on the progression of organogenesis in flower development, we also classified floral development of A. palmeri into ten stages. The distinction between the two flower types only became apparent at stage 4 with the formation of stamen primordia .

Pistillate flowers only develop female reproductive structures whereas staminate flowers develop both female and male reproductive organs initially. This finding places A. palmeri in the type I group of unisexual species.Unisexual species are believed to have evolved from hermaphroditic ancestors through a variety of evolutionary processes . Both androecial and gynoecial primordia are often initiated in the unisexual flower of dioecious plants. The developmental halt of the organs of the opposing sex, which occurs at different phases of development in different species, gives rise to unisexual flowers . In Silene latifolia , the development of male and female organs is identical until stage 5 when stamen development is terminated after anther differentiation in pistillate flowers, but in staminate flowers rudimentary gynoecia continue to grow throughout flower development . In Celtis iguanaea, termination of gynoecium development in staminate flowers happens earlier than the arrest of androecium development in pistillate flowers . Results of A. palmeri flower development show staminate flowers initially develop both androecium and gynoecium, but eventually become functionally male with a central bulge instead of a fertile gynoecium whereas pistillate flowers do not go through a hermaphroditic stage. This implies that the sex of pistillate flowers is determined earlier than staminate flowers. Sex determination of pistillate flowers may occur before flower initiation or even before floral evocation because pistillate flowers only develop a fertile gynoecium with no anther primordia at any stage. Differences in the timing of residual organ termination suggests that the developmental program that suppresses gynoecium development in staminate flowers is probably independent from the program that stops stamen growth in pistillate flowers . This observation implies the existence of different mechanisms involving different genes, which does not corroborate the hypothesis that stage of organ abortion in male and female flowers is temporally correlated within species .

Similarly, Grant et al. found that genetic lesions in the Y-linked genes which prevent gynoecium growth have no effect on stamen development in S. latifolia.It is interesting that S. latifolia with heteromorphic sex chromosomes exhibits a similar pattern of late floral sex differentiation as A. palmeri which lacks visually distinct sex chromosomes. Sex in A. palmeri is controlled by a male specific genome region perhaps with an XY system without dimorphism between X and Y . However, sex-determination loci have not been identified in these taxa. Early cytogenetic studies in S. latifolia show that there are three regions identified on the Y chromosome related to sex expression: a gynoecium suppression region and two promotion regions of stamen development . The speculation was made that the male Y chromosome linked genes with gynoecium-suppressing functions are expressed in staminate flowers before the first sex-specific difference appears . Miller and Kesseli suggests the Y chromosome in S. latifolia remains quite similar to the X chromosome, probably with the main differences in the primary sex determination regions. The slow differentiation of staminate flowers in A. palmeri may relate to the allocation of resources to male compared with female reproductive functions . According to Bateman’s Principle , female fitness tends to be limited by resources needed to fill seeds and fruits, dry racks for weed whereas male fitness is more likely to be limited by mating opportunities. Reproduction is more costly to females than males; sex allocation theory therefore predicts that the environmental conditions favorable for plant growth should induce femaleness whereas resource-poor environments induce maleness . This strategy is very important for A. palmeri to establish a population after colonizing a new habitat. In expressing an initial stage of hermaphroditism, the A. palmeri pattern seems to differ from a few other species studied in this family. For example, in dioecious Spinacia oleracea L. flowers appear to be unisexual from inception and only initiate development of either stamens or pistils . In Amaranthus hybridus, a monoecious species, flowers bear only either a primary gynoecium primordium or stamen primordia at early stages. Our result suggests the evolution of A. palmeri from a cosexual ancestral state to dioecy is at an early or intermediate stage, which is in line with the findings from the whole-genome sequencing analysis . By identifying a potential Y chromosome in the A. palmeri draft genome sequence, Neves et al. suggested that dioecy in A. palmeri is at an intermediate evolutionary state with a young Y chromosome. Our study is the only detailed floral developmental study of a dioecious member of the Amaranth genus and may offer unique insights into the evolution of sex determination in plants and into the development of novel control strategies to control dioecious weeds such as changing the sex through manipulation of the environment . Amaranthus palmeri is of major interest because it represents one of the most important agronomic weeds in North America. The species can evolve resistance rapidly and repeatedly to herbicides . Understanding the reproductive biology of weeds can aid in the development of agronomic strategies and to reduce herbicide resistance and weed populations. Mesgaran et al. found water stress induced a female sex expression of Palmer amaranth resulting in female to male ratio of 1.78:1, which was significantly different from 1:1 sex ratio.

This finding is consistent with our observation that males produce rudimentary gynoecia and can be potentially bipotent . If there are more females than expected due to water stress, they could have been produced from males since males initially produce female organs. Further, water stress reduced the synchrony in anthesis between the two sexes of A. palmeri mainly through a delay in male anthesis whilst females were almost unaffected . To better decipher the above observations, future research should investigate the floral development in male and female plants under water stress conditions.Comparing floral organogenesis of both sexual types, we found that Amaranthus palmeri staminate flowers initially develop both androecium and gynoecium, but eventually become functionally male with a central bulge instead of a fertile gynoecium, whereas pistillate flowers only develop a fertile gynoecium with no anther primordia at any stage. Timing of residual organ termination varies across the two sexes in A. palmeri. Sex determination in pistillate flowers probably occurs before flower initiation or even before floral evocation, which is much earlier than staminate flowers. The results of our floral development study suggests that the evolution of A. palmeri from a cosexual ancestral to complete dioecy is still in progress since males exhibited transient hermaphroditism whilst females produced strictly pistillate flowers. It is very important to understand the reproductive biology of this species as it can help develop weed control methods and reduce herbicide resistance. Techniques such as skewing the sex ratio and reducing the flowering overlap between the two sexes have been offered to reduce seed output in A. palmeri and perhaps other dioecious weeds for which a better understanding of weed reproductive biology is required.Current agriculture systems rely heavily on the use of herbicides and tillage for weed management but both have negative impacts on the environment and farm productivity in longterm use while herbicide-resistance is increasing . An integrated approach to weed management which incorporates ecological principles and involves using multiple tactics that vary in timing and type of control is needed to reduce the probability of rapid weed adaptation to management practices . Moreover, weed management decisions should aim to prevent soil seedbank inputs rather than just minimize current yield loss for agricultural profitability . While there have been many studies focused on weed seed biology and seedbank management , research focused on reducing weed seed production by manipulating flowering and seed set is lacking. At anthesis, pollen grains landing on a compatible stigma may germinate and produce pollen tubes which grow through the style to fertilize the ovules. Later pollen tubes are unable to enter fertilized ovules as the first pollen tube’s sperm cell delivery causes an immediate block to further fertilizations . During its journey inside the pollen tube, the generative cell of a pollen grain divides into two male gametes. One gamete fuses with the egg cell nucleus and the other fuses with the pair of central cell nuclei. Together, these two fertilization processes are referred to as double fertilization , which is unique to angiosperms . The fertilized egg cell will give rise to an embryo while the fertilized central cell will give rise to the endosperm .

A seed transfer certificate is required anytime untagged seed moves, no matter where it is going outside of the county in which the seed is residing, such as from the field to conditioner, from conditioner to conditioner, from California to Minnesota, or from California to Chile. The three types of seed transfer certificates are inter-county, intra-county, and inter-agency . The primary market for sunflower seed is Eastern Europe , where more than 50 million acres of sunflowers are grown for cooking oil. Seed is also marketed and sent to the U.S. Midwest, where about 1.7 million acres of sunflowers are grown primarily for cooking oil, but also for confectionary seed, with the Dakotas being the top sunflower producer in the United States. Other hybrid sunflower seed producers include Turkey, Chile, and Argentina.Broad leaf Weeds A wide range of broad leaf weeds infest small grains . The more common weeds are mustards , wild radish , London rocket , shepherd’s purse , coast fiddleneck , annual sowthistle , prickly lettuce , burning nettle , pineapple weed , miner’s lettuce , common chickweed , field bindweed , swamp smart weed , common lambs quarters , and yellow starthistle . Broad leaf weeds vary in their ability to compete with small grains. For example, an average of 1 wild radish plant per square foot , when established at the same time a wheat crop emerges, can reduce yield by as much as 66 percent by completely over topping the wheat canopy and competing for light. Low-growing weeds such as common chickweed, henbit , growing racks and miner’s lettuce are generally less competitive, but even high populations of common chickweed can smother small plants, reduce yield, and remove soil nutrients and moisture. Poor weed management also causes weed problems in succeeding crops.

Grasses Grass weeds are difficult to control in small grains because they mimic the growing cycle and growth habit of the crop. Many grass weeds germinate at the same time as small grains and mature slightly before or at the same time as the crop, assuring an ample supply of seed for next year’s weed crop. These weeds compete for light and space and also remove soil moisture and nutrients needed for crop growth. Winter annual grassy weeds in California’s small grains include wild oat , Italian, or annual, ryegrass , ripgut brome and downy brome , hare barley , rabbits foot grass , and hood canary grass and little seed canary grass . Wild oat emerges throughout the cool season from autumn through spring. In small grains it causes lodging, slows harvest, clogs harvester screens, and lowers yields. An average of 7 wild oat plants per square foot can reduce wheat yields by 3,000 pounds per acre in a crop with a yield potential of 6,000 pounds per acre . Barley, because of its more competitive early growth, is less affected by wild oat than is wheat. In one study a wild oat density averaging 14 plants per square foot reduced barley yield by 27 percent and wheat yield by 39 percent . Ripgut brome is a particular problem in rainfed production areas. The weed reduces yield by competing with the crop, and its seed can contaminate the grain and reduce its marketability. Italian ryegrass is a major weed in the central and northern valleys of California. Infestations of hood and little seed canary grass can reduce yields by more than 50 percent. Hood canary grass occurs in the central region and coast rainfed production areas, while little seed canary grass is most prevalent in the Imperial Valley and Southern California. Canary grass is a prolific seed producer, and populations of canary grass in fields continuously cropped to small grains often exceed 100 plants per square foot . Hare barley and rabbits foot grass are common in the southern part of the state, although hare barley is sporadically found elsewhere in California.An integrated weed management system combines crop rotation, fertilization, irrigation, tillage, herbicide applications, and high plant populations to help control weeds.

Field sanitation is a prerequisite for weed control. Planting and tillage implements should be free of weed seeds and other plant propagules to avoid spreading weeds from field to field. Field perimeters should be kept free of weeds because they serve as a reservoir for seed to infest the field. A properly prepared seedbed can increase yield and reduce weed pressure . Plant high-quality, vigorous, weed-free certified seed. Using non-certified seed risks the introduction of new weed infestations. The sowing date can influence weed competition. Late sowing produces shorter small grain plants that have fewer tillers and are less competitive with weeds. Lower seeding rates also can intensify weed pressure. Studies in the Sacramento–San Joaquin Delta have shown that higher seeding rates are very effective at reducing competition by swamp smart weed, johnson grass, mustard, wild oat, canary grass, and common chickweed. Row spacing should be as narrow as feasible to promote early development of a solid, competitive crop canopy. Mulch planting can give a small grain crop a head start over weeds. In mulch planting, a shallow cultivation is done following rainfall or irrigation, when weed seeds germinate before planting. The crop seed is then sown into moist soil below the mulch layer of dry soil that resulted from the cultivation. Because the crop seed is placed into moist soil, it germinates quickly, ahead of weeds. Fertilization is essential to maximize small grain vigor and health and is an excellent weed suppression practice . Starter fertilizer may be required in some areas. Place starter fertilizer near the seed to provide early availability to the crop, not to weeds. Broadcast-applied starter fertilizer enhances weed growth, especially for wild oat and canary grass; broadcast applications are less efficient and should be avoided. Irrigation and proper drainage keep small grains in a vigorous growing condition for maximum competition with weeds .

In areas where flooding and high water tables occur, small grains should be sown on 30- to 60-inch raised beds. For rainfed production systems, growing weed vertically fields can be fallowed every other year to prevent weed seed buildup and to conserve moisture for maximum small grain growth. Weeds should not be permitted to produce seed during the fallow period. Tillage operations before planting should be delayed until the first fall rains germinate the weed seeds so that tillage can kill the first flush of weeds before sowing. Weeds may also be treated with an herbicide during the fallow period . Rotating small grain crops with other crops reduces infestations of johnsongrass, wild oat, Italian ryegrass, and other weeds that are important in small grains . Crop rotation allows weed populations to be reduced chemically, mechanically, and physically in the alternate crop. Growing different crops at different times of the year helps break the reproduction cycle of some problem weeds. Small grains are often grown so that weeds important in higher-value crops can be controlled. For example, small grains grown in rotation with vegetable crops allow post emergent broad leaf herbicides to be used to control nightshades and sowthistle, major problems in vegetable crops.Good cultural practices help reduce weed competition, but an integrated approach involving these measures as well as herbicide applications is often needed for complete weed control. An integrated approach reduces weed seed production and aids weed control in succeeding crops. The effectiveness of a chemical weed control program depends on the weed species present, application timing, thoroughness of spray application, environmental conditions at the time of application, herbicide use rate and spray volume, and crop management after the application is made. For example,weeds may again cause problems if late-winter rains stimulate additional weed seed germination after a herbicide application is made. Also, drought-stressed weeds are very difficult to control with post emergent herbicides, especially if they are beyond the seedling stage. Susceptibility of problem weeds to available herbicides is given in the susceptibility table in UC IPM Pest Management Guidelines, Small Grains . This table is kept up to date with the latest available herbicides.Only post emergent herbicides, which are applied after the crop has emerged, are used for weed control in small grains. Fall-sown small grains are usually treated between December and mid-March, depending on the sowing date and growing conditions. Spring-sown small grains in the inter mountain area of northern California are treated between April and June. Several post emergent herbicides are registered for use in small grains. Phenoxy herbicides, including 2,4-D and MCPA, are commonly used in small grains alone or in combinations. Dicamba, another hormonal-type herbicide, is often included in the phenoxy herbicide group because of its similar mode of action.

These herbicides are most effective when applied to small, succulent weeds. Small grains vary in their sensitivity to these herbicides; for example, oat is more tolerant to MCPA than to 2,4-D. Ester and amine formulations of 2,4-D and MCPA amine formulations control most broad leaf weed species encountered in small grains. The ester form is usually more effective than the amine form. However, ester use is not permitted in most counties, or applications are limited to certain times of the year. Figure 1 illustrates the proper application timing of these herbicides. Phenoxy herbicides should be applied after the small grains are well tillered but before they reach the boot stage in order to avoid yield reductions caused by phytotoxicity . Late applications are sometimes ineffective because the crop canopy shields the weeds, preventing herbicide contact. Dense weed populations require a more thorough application with a greater spray volume to ensure contact between the herbicide and weeds. The use of aircraft often facilitates timely herbicide application, but care must be taken to make applications at the appropriate time to avoid injury to adjacent crops from drift or volatilization. MCPA does not control large weeds as well as 2,4-D amine and 2,4-D ester herbicides, but it has greater crop safety, especially when applied to small grains in early growth stages. Dicamba is effective for broad leaf weed control; however, small grains are generally more sensitive to it than they are to 2,4-D. Dicamba is safter when applied at early growth stages . It cannot be used on fall-sown barley. Dicamba controls small plants of common chickweed and coast fiddleneck, which are not controlled by 2,4-D or MCPA. It usually is combined with bromoxynil and MCPA. When applied early, this combination is very effective and increases the weed spectrum controlled compared with either of the herbicides used alone. Bromoxynil , a contact herbicide, is effective on young seedling weeds with no more than 2 to 4 leaves. It is less effective on older weeds and must be tankmixed with other herbicides, for example, when larger mustards are present. Bromoxynil is not translocated from the site of absorption like the phenoxy herbicides. Therefore, higher-volume application and thorough coverage is more important with bromoxynil than with phenoxy herbicides. An advantage of bromoxynil is that it controls the toxic weed coast fiddleneck when applied at early growth stages of the weed; phenoxy herbicides often fail to control coast fiddleneck. Bromoxynil is also recommended in areas with phenoxy-sensitive crops such as grapes, cotton, and tree crops. Chlorsulfuron is registered for use on wheat in a wheat-fallow rotation. It is a sulfonyl urea herbicide with a very low application rate. It is not widely used in California because it has a long soil life , which prevents its use in areas where many different crops are grown. This herbicide controls most broad leaf weeds, including coast fiddleneck and common chickweed. It should be applied to small weeds when the small grain crop is in the 2 to 3 leaf stage to boot stage and should not be used on soils with pH above 7.5. Clopyralid , a picolinic acid, is registered for use on wheat, barley, and oats. It translocates systemically through weeds, similar to phenoxy herbicides. It has a longer soil persistence than phenoxy herbicides, which limits planting of some broad leaf crops before 12 to 18 months after application. It is effective on a different spectrum of weeds than 2,4-D, MCPA, or dicamba.

All suspected disease samples are sent to the CDFA Plant Diagnostic Lab in Sacramento for disease identification by plant pathologists to ensure accurate and complete identification. After harvest, the county agricultural commissioner office issues a certificate that is attached to the batch of seed produced in their county that is used for tracking across county or state lines. This certificate is used as proof that the seed meets foreign phytosanitary requirements for diseases that can be visually observed in the field. If additional lab tests are required for an export phytosanitary certificate, the exporting county will run the tests required according to either USDA Standards or an import permit provided by the exporter. The exporting county is not always the same as the county of origin because seed lots are moved to different counties for export. For example, seed produced in Sutter County may be moved to Yolo County for export, but all seed is tracked as to origin, to ensure regulations are met.Sunflowers have relatively large seeds and are less sensitive to seeding depth than smaller-seeded crops. However, at planting, they still need a well-worked seedbed that is smooth, fine , firm , and preferably with good soil moisture at planting, to ensure simultaneous emergence of male and female lines. It is well worth the extra effort to prepare good seedbeds. Poor and uneven seedbeds can affect the rate of seed germination, resulting in a poor “nick” and subsequent yield losses due to poor pollination. For land preparation for planting, primary tillage operations depend on field conditions and irrigation practice . On sandier soils with minimal soil compaction, beds can be reshaped after disking in the previous crop residue. However, growing racks soils with more clay, as tend to occur in the Sacramento Valley, have more problems with soil compaction and often require more extensive field preparation.

Furrow-irrigated fields are ripped to a depth of 18 inches, whereas fields with subsurface drip systems are chiseled in the furrows, to a depth of 12 inches, taking care not to destroy the drip system. Afterwards, fields are disked and ring-rolled in one operation in the fall twice to incorporate the previous crop residue and break dirt clods, taking care not to go too deep and disrupt any subsurface drip systems. A finishing disk further breaks clods and makes a fine seed bed, followed by a GPS drag scraper to smooth the ground and level fields. Afterward, beds are formed using bed-making equipment, with the bed size depending on the sunflower variety and production capability and also on the growers’ equipment preference. Subsurface drip fields are mapped with GPS technology so that the beds are always formed over the buried drip tape. Bed size will vary from single-seed rows on 30-inch beds to double seed rows on 60-inch beds, and sometimes three seed rows on 80-inch beds. The minimum soil temperature at planting is 50°F. Weeds that have germinated during the wintertime must be controlled prior to planting, either by cultivation or by an herbicide application, such as glyphosate . Fields are cultivated for weed control and to incorporate herbicides prior to planting .Overlap in flowering between male and female lines is needed in hybrid sunflower seed production to ensure good pollination by pollinators and seed set. Honey bees are used for moving pollen between the male and female parent lines at a stocking rate of 1.5–2 hives per acre. Growers commonly contract with beekeepers for hives at a current cost of $40 to $50 per hive. Hives should be set around the fields when the male plants begin to flower to ensure that the bees stay in the field. Insecticide applications for pest control should be made before the delivery of bees to the field or early in the morning before most bees are actively foraging. Male lines are usually highly branched and have more flowers to maximize pollen production and pollination, compared to the single female flower.

Poor seed set can occur when simultaneous bloom doesn’t occur, if the female parent is unattractive to bees , if the male parent line is a poor pollen producer, or if weather conditions are unfavorable for pollen production and honey bee activity. High temperatures can reduce the number of pollen grains per flower in sunflower; however, no differences in pollen germination rates at an upper limit of 88°F have been observed, indicating pollen viability is resilient. Honey bee activity and subsequent seed set can be reduced by wind or if it is too hot or too cold. Honey bee activity ceases below 55°F and above 95°F. Seed set can also be less in the center rows when wide passes of 12 or more female rows are planted due to a lack of honey bee foraging activity. Symptoms of poor pollination include empty or underdeveloped hulls. Native bees, including a digger bee and long horned digger bees , sometimes referred to as ‘sunflower’ bees, primarily collect pollen. Honey bees either forage for nectar or pollen, but not both. Native bees often jostle honey bees around in sunflower fields, causing honey bees to disperse more, making them better pollinators. Some species of native bees are solitary and nest in the ground and can be encouraged through on-farm insectary plantings . Chop and destroy the male plants once the female line is finished flowering and has set seed to prevent seed contamination of the female line at harvest. In addition, destroying the male rows before they set seed also helps reduce volunteer sunflowers that can be difficult to control in subsequent crops, especially for herbicide tolerant sunflowers, like Clearfield or ExpressSun.Prior to planting, sample the soil from 0 to 6 inches deep to determine the likelihood of crop response to phosphorus , potassium and zinc fertilizer. If soils are deficient in these nutrients, sunflowers are likely to be responsive to them. If yield differences existed within a field for the previous crop, sample and analyze these areas separately by taking 12 to 15 cores in each problem area from 0 to 6 inches deep and mixing them together to make up a composite sample. Separate samples should also be taken from areas of the field with different soil types that could affect nutrient availability. The soil pH should be from 6.0 to 8.0 for good sunflower production. Although sunflowers appear to tolerate soils with pH as low as 5.5, growing weed vertically consider liming if the pH is below 6.0 to improve nutrient availability in the soil.

Areas of known or suspected high salinity or boron should be sampled at depths of 0 to 6, 6 to 12, and 12 to 24 inches if there is reason to suspect toxicity problems.Knowledge of field history and past nutrient deficiencies or toxicities should be taken into consideration before planting sunflowers.Sunflowers have a deep taproot and are good scavengers of nitrogen . Some N will be available from the previous crop, long-term fertilization practices, and N release from soil organic matter. For example, more N will be available in the soil after a tomato crop, than after corn or wheat. If N is deficient, the older sunflower leaves will turn uniformly pale green to yellow, plant growth will be reduced, flowers may not develop, and heads will fill poorly. As a starting point for determining N needs in sunflowers, the seed has an average N content of 3.7 percent. For a yield of 1,400 pounds per acre, the seed will need at least 52 pounds of N per planted acre to account for crop removal. An additional 25 pounds of N per acre will be needed for the plant . Adding 25 percent more N for male acreage , the total N needed by a sunflower crop producing 1,400 pounds per acre yield is approximately 100 pounds of N per acre, with yield calculated on a whole-acre basis. Fertilizer trials in sunflowers have generally not shown yield benefits at N application rates exceeding 100 to 150 pounds N/acre. To ensure good hybrid sunflower seed production, fertilization begins with a starter fertilizer of 8-24-6 with 1-2% Zn band-applied during planting, 2 inches below and 2 inches to the side of the seed row. Apply about 100 pounds of dry fertilizer or 10 gallons of liquid fertilizer of similar analysis per acre. The starter fertilizer is particularly important for spring plantings with cooler soil temperatures, when phosphorus and zinc are less available. Exercise particular care with starter fertilizer placement in order to avoid salt damage or ammonia toxicity to the germinating seed. Do not use urea or diammonium phosphate, either 18-46-0 or 16-48-0. Do not place any fertilizer in direct contact with the seed. As a general rule, a monoammonium phosphate is the preferred base fertilizer and should be placed no closer than about 2 inches to the side and about 2 inches below the sunflower seed. At lay by, when the plants are about 12 inches tall, fertilize the fields with N so that it is readily available for rapid plant growth and development. Prior to the N application, residual N levels in the soil should be determined about 10 to 15 days prior to the planned side-dressing. This allows for the rate of applied N to be based on the available nitrate-N in the top 24 inches of the soil . Take soil samples from 0 to 6 inches, 6 to 12 inches, and 12 to 24 inches deep at 2 to 3 locations in each field, as described in Geisseler and Horwath , and request analysis for nitrate-N. For furrow-irrigated systems, N should be side-dressed during a cultivation for weed control, with aqua ammonia or a similar N fertilizer. If using subsurface drip, start injecting N in the drip line when the plants are about 12 inches tall and continue until the sunflowers begin to head out . Nitrogen rates can also be reduced somewhat if the irrigation water contains high nitrate levels. Calculate the number of pounds of N per acre-foot of irrigation water by multiplying the parts per million nitrate-N in the irrigation water by the factor 2.72. Have your water tested, because irrigation water sources vary considerably in nitrate-N concentration. Excess N applications may delay flowering, leading to yield and quality reductions.Phosphorus can be especially important for sunflower production in California due to the relatively early planting dates and cooler soil temperatures that reduce P solubility and uptake. Phosphorus is particularly important in the early stages of plant growth because it promotes the development of extensive root systems and vigorous seedlings, which also helps the plants out compete weeds. A phosphorus deficiency is characterized by slow plant growth, poor tap root development, thin stems, and older leaves that turn yellow and drop prematurely, while the new leaves are small and dark green. If a representative soil test prior to planting indicates a P deficiency, apply a starter fertilizer at the rate indicated in table 4 as pounds of P2 O5 per acre. The soil test using the Olsen bicarbonate extract should be used on soils with a pH of 6.5 or greater, while the Bray #1-P extract should be used for soils with a pH less than 6.5. Soil tests showing very low and low extractable P levels would be expected to show a yield response to P fertilization. Crops grown in soils that have test levels in the moderate range are less likely to respond to P fertilizer applications.Potassium is essential for translocation of sugars, starch formation, and for regulating the opening and closing of stomata, which helps water use efficiency. Potassium additionally promotes root growth, produces larger, more uniformly distributed xylem vessels throughout the root system, and increases plant resistance to diseases. Sunflowers also need relatively large amounts of K for stalk and tissue strength, since it is a tall plant. When K is limiting in sunflowers, deficiencies include smaller leaves, yellowing and necrosis of the lower leaves, stunting, and thinner stems that make the plant more susceptible to lodging. If a representative soil test indicates a K deficiency, correct it using a starter fertilizer containing K at the rate indicated in table 5 as pounds of K2 O per acre. Soil test results that fall in the low range indicate that plants should respond to K fertilization; test levels in the medium range indicate that the plants are less likely to respond to K fertilization.

Occasionally, may weed , Wright’s ground cherry and volunteer tomato survived the 1.5 lb. a.i./acre rate of ethalfluralin. Weed species composition after the 0.75 lb. a.i./acre treatment of ethalfluralin was similar, but also included a few surviving seedlings of lambsquarters. Weed composition on plots that received no herbicide resembled the 1999 weed survey and included barnyard grass, black nightshade, hairy nightshade, redroot pigweed, annual sowthistle, Wright’s ground cherry, cheese weed , purslane and lambs quarters. Generally, higher weed-seedling survival after reduced herbicideapplication rates is typical. Griffin et al. reported lower weed control with reduced rates of soil herbicides in soybean fields. Preplant incorporated application of imazaquin at the full rate gave 95% control, whereas the half rate gave 88% control. Greater seedling survival after reduced herbicide rates may be due to the density thresholds used in this study. For example, Williams et al. used a reduced rate at or below one seedling per square yard of Polygonum aviculare in corn. A relatively high weed-density threshold used for the no-herbicide plots was probably responsible for the low success of the no-herbicide approach in this experiment. The threshold for the zero rate was defined as a seedling density below 10 plants per square yard and for mature plants, as less than one weed plant per square yard. Since treatment maps were based on counts of emerged plants, the threshold for the no-herbicide rate should be set to zero weed plants per square yard. In this experiment, areas treated with the medium rate had about 5% weed cover at 2 and 4 weeks after application and about 12% at 6 weeks; whereas, the high-rate plots had about 2% weed cover at 2 weeks, 5% at 4 weeks and 8% at 6 weeks. Increases in weed cover over time are due to herbicide decomposition in the soil, indoor grow table although ethalfluralin persists for a long time, with an average field half-life of 60 days . High or full herbicide rates should only be applied to high-density weed patches. However, even the full herbicide rate was not able to control weeds in highly infested areas.

Other researchers have also observed that weed clumps persist despite uniform full-rate treatment . High weed-density areas may require a slightly higher rate than what is currently considered full rate, assuming crop tolerance is sufficient. Variablerate herbicide applications could allow higher rates to be applied in high weed density areas, while still applying less herbicide to the field as a whole.When the herbicide application was based on the seedling map, 15% of the experimental area did not receive any herbicide and 63% received a medium rate. The treatment map indicated that 2.18 acres of the site were treated with 0.75 lb. a.i./acre, 0.75 acre with 1.5 lb. a.i./acre, and 0.52 acre with no herbicide. A 47% reduction in herbicide use was achieved with the seedling-map approach when compared with a uniform full-rate application. Reduced rates were applied to 78% of the experimental area. The treatment map that we developed based on mature plants recommended that 1.02 acres of the site be treated with 0.75 lb. a.i./acre, 1.77 acres with 1.5 lb. a.i./acre, and 0.66 acre with no herbicide. Nineteen percent of the experimental area did not receive any herbicide and 30% received the 0.75 lb. a.i./acre rate. A 34% reduction in herbicide use was achieved with the variable-rate application based on a mature-plant weed map when compared with a uniform full-rate application, and 49% of the experimental site received a reduced herbicide treatment. Since using no herbicide may present too much risk for many growers — particularly in the early stages of adoption for precision weed management — rates may be limited to medium and high applications, in which case the herbicide reduction would have been 39% for the seedling-map and 24% for the mature map approach.It took approximately 20 seconds to count mature weeds in each 32-squareyard measurement area. Depending on the level of experience, it would take 2.2 to 6.6 hours to count the weeds in 100 acres . In the variable-rate experiment, a 34% herbicide reduction was achieved with the mature-weed map approach. At a commercial price of $50 per gallon for the herbicide Sonalan, savings were $17. It would take $22 to produce a detailed weed map . In this scenario — based on a mature-weed map — no financial benefits would be achieved.

In the case of the weed-seedling map approach, where a 49% herbicide reduction and $24 herbicide cost savings was achieved, plus the approximate $22 cost of a weed map, variable-rate application brings some modest financial benefits of about $2 per acre. However, we did not account for the conversion of a weed map into an herbicide treatment map in this estimation of economic returns. Our economic analysis should be verified in another study before a firm decision is formed about the economic value of variablerate technology. The economic efficiency of site-specific herbicide application depends on the cost of herbicide, cost of producing the weed map and treatment map, and the spatial characteristics of the weed population. Since weed distribution within a field is slow to change, maps created in one year may be useful for several years. Additionally, there are research efforts currently examining the use of camera systems to mechanically map weeds, which will likely decrease the cost of weed mapping and improve its accuracy, since a greater portion of the field will be sampled.The results from this experiment show that when information about the spatial distribution of the previous year’s mature weeds is used, weed control in terms of subsequent weed cover is comparable to uniform one-rate herbicide application, while simultaneously the total amount of herbicide applied decreases. We conclude that variable-rate spraying based on maps created from estimating weed population density and levels of infestation just before harvest gave the best weed control. However, further improvement is likely when the prediction and modeling of weed-seed redistribution from harvest to application time is incorporated into treatment maps. The simulation of seed movement from the measurement event to herbicide application should be incorporated in any preemergent treatment map.In the modern era of global trade, species are being inadvertently and deliberately introduced widely beyond their historic ranges . A crucial focus of evolution‐ ary ecology of introduced species is to understand their pattern of spread and to identify their native origins and pathways of intro‐ duction to better prevent and manage biological invasions . Inferring the origins and spread of these exotic species is challenging and rarely are the true pathways or origins known. Thus, a fruitful approach may be to use documented intro‐ ductions, such as those performed in classical biological control, as model systems to provide greater insights into population genetic analyses, as well as insight into the consequences of population movement and ecological processes for the genetic structure and variation of a species .

Classical biological control uses natural enemies to control invasive populations of weeds, and arthropod pests and disease vectors in the introduced range . These natural enemies, as biological control agents, are often imported across disjunct geographic ranges for the long‐term control of the target invasive species. In the modern era, these importations are well‐regulated and well documented . Thus, they provide model systems to study the repercussions of invasion pathways and multiple intro‐ ductions—including their effects on inter‐ and intraspecific hybrid‐ ization, bottlenecks, inbreeding, genetic variation, and correlations of genetic diversity with population performance of the biological control agents . To enhance the establishment and success of biological control agents, often multiple separate introductions are made, and large numbers of individuals are released . Multiple introductions here refer to introducing individuals from more than one population, or of more than one species, or both into the same geographic areas. Multiple introductions can increase the genetic diversity in an introduced population due to genetic admix‐ ture of different source populations . Alternatively, multiple introductions of more than one population could interfere with local adaptation, particularly in the native range . Additionally, hybridization can occur when more than one closely related species or strain is introduced, which can poten‐ tially lead to hybrid breakdown or hybrid vigor . Hybrid vigor can result from positive epistatic interac‐ tions among loci, drying rack cannabis heterosis due to masking of deleterious alleles, or heterozygote advantage, whereas hybrid breakdown can occur from negative epistatic effects among loci and/or the under dominance of loci . Thus, the presence of multiple introductions and hybrids can greatly impact the growth and spread of introduced populations, and the efficacy of biological control programs. The introduction of large numbers of individuals is critical to im‐ prove establishment success, as it buffers against demographic sto‐ chasticity and helps minimize loss of genetic variation . Nonetheless, introduced populations often endure demographic bottlenecks , which can decrease allelic richness and heterozygosity, with the latter depending on the rate of population growth following the initial bottleneck . Certain alleles might increase or decrease in frequency by chance during bottlenecks, leading intro‐ duced populations to diverge from native populations . Genetic drift and inbreeding can also lead to increased homozygosity , which can be associated with reduced fitness . However, population bottlenecks do not always reduce genetic variation or lead to genetic differentiation from the native population , particularly if populations grow rapidly following introduction . Evaluating the effects of bottlenecks in population size on genetic diversity can enhance our understanding of the consequences of introductions and spread of species. Although great efforts are taken to introduce many individuals from the native range to enhance establishment success, regulatory processes can make this difficult. Thus, the number of individuals imported to a region ranges widely from 10 to more than 1,000.

While regulations vary by country , each collection from the native range for release typically passes through quarantine to prevent unintentional introductions of other species . In many countries, such as the United States, fur‐ ther screening to characterize host range is often required for each new collection from the native range, which can mean many additional generations in quarantine even for agents that have already been approved. During this time, inbreeding and adaptation to the quarantine and mass‐rearing environment can also occur . Following quarantine screening, population size is typically increased as much as possible in order to release hundreds to thousands of individuals . However, the proportion of individuals that survive in the field and contribute to the next generation may be low, resulting in another demographic bottleneck . Regulatory and logistical obstacles limit sampling from the native range; thus, biological control agents for release in new regionsare often collected from a population already in use for biological control rather than revisiting the native range. This introduction process is analogous to the movement of invasive species, whereby an introduced population becomes the source of several secondary introductions, and is therefore acknowledged as a “bridgehead population” . Similarly, biological control agents frequently undergo serial importation steps, and thus serial bottlenecks in population size. By using the known introduction pathways from biological control programs, we can evaluate our ability to reproduce the introduction pathways by analyzing data from molecular markers. Here, we examine the importation history, genetic diversity, and population structure of two closely related species introduced for biological control to gain insight into the consequences of population movement and ecological processes for the genetic structure and variation of these two species. Here, we ask: Is there evidence of hybridization between these species, and how do introduction processes affect the genetic variation and structure of these species? More specifically, are there indications of decreased heterozygosity and allelic diversity in the introduced populations relative to the native range, do increases in the number of in‐ dividuals initially released or genetic admixture from multiple introductions result in increased genetic diversity, do populations with more introduction steps between them and the source population in the native range exhibit greater loss in genetic variation com‐ pared to populations with fewer introduction steps, and despite originating from the same initial populations, have introduced populations differentiated from the native range and from each other? To address these questions, we use the documented importation history and polymorphic microsatellite loci of two weevils, Neochetina bruchi and N. eichhorniae Hustache from their native and introduced ranges.