Decreased yields or prices for transgenic rice, ceteris paribus, would reduce the gross rents from the technology. Furthermore, the seller of the transgenic seed is likely to charge a premium of up to 60 percent of total per-acre seed costs, depending on the pricing structure of the technology. Roundup Ready® and Bt seed for commercially produced transgenic crops has historically been priced from 30 to 60 percent higher than non-transgenic varieties, and price premia for LibertyLink® corn seed range from 0 to 30 percent, although average chemical costs per acre are typically greater . Furthermore, growers will likely pay at least part of the burden of the fees assessed by the CRCA. Assuming that these effects are constant per cwt of output, they can all be represented as a unit increase in costs in terms of net returns. Increased unit costs of this form, ceteris paribus, would alter the distribution of the rents between stakeholders but not dissipate gross rents. As points of reference, base assumptions on price and yields are $6.50 per cwt and 80 cwt per acre, so gross revenues from sales of rice output are assumed to be $520. A price premium of $0.25 per cwt for conventional rice as compared to transgenic rice with no associated change in yields would thus have the equivalent effect on net returns to the grower of a fee of about $20 per acre. Note that changing output prices does not affect the cost structure of the average farm operation and, thus, there is a direct, linear relationship between net returns and price. To calculate the impact of these effects, weed curing simple subtraction of the product of the price change and yield from the baseline scenario is appropriate. On the other hand, both a technology fee and the CRCA assessments directly enter the cost structure and, as such, affect interest costs as well.

Tables 4 and 5 lay out these effects. A 30 to 60 percent technology fee, assuming a seeding rate of 1.5 cwt per acre and price of conventional seed of $14 per cwt, is equivalent to $6.30 to $12.60 per acre. Total fees assessed as a result of the CRCA would currently be $8.50 per acre at identical seeding rates and yields of 80 cwt per acre, although it is unlikely that 100 percent of these assessments would be passed to the grower. Table 4 assumes no pass-through to growers of the legislated fees while Table 5 assumes the maximum pass-through, thus bounding the estimates. Both conservatively assume two applications of glufosinate per growing season. Without the CRCA legislation, adoption of LibertyLink® rice is profitable for a technology fee of $6.30 regardless of any realistic yield assumptions and profitable at a technology fee of $12.60 per acre so long as yield drag is no greater than 8.9 percent . With zero yield gains, net returns per acre in this range of seed price premium increase by between 21 and 25 percent over conventional rice returns with even greater benefits for those experiencing positive yield gains. If we assume a small price premium of, say, $0.25 per cwt, the technology is profitable for either yield losses of 7 percent with no technology fee or no yield change with an unrealistic $25.89 technology fee. This highlights the importance of yield and price assumptions on the calculation of net benefits. However, it is clear that, even with a small output price premium and a seed price premium at the upper end of the observed range, the most likely adopters will benefit from increased returns over costs. Allocation of maximum CRCA assessments to the grower slightly changes the per-acre benefits but does not affect the qualitative conclusions . Net returns over the baseline scenario with a $6.30 technology fee are no longer positive with an 8.6 percent yield drag nor for a $12.60 technology fee and a 6.7 percent yield drag. However, identical yields still result in net benefits of between $24.50 and $30.80 per acre, more than enough to cover a $0.25 price premium for conventional rice.

To bound the per-acre benefits, we assume a lower bound of $0.25 per cwt price premium and an upper bound of no price premium with no CRCA pass-through. Under these assumptions, we conclude that the per-acre benefits of the transgenic HT technology are between –$7.22 and $58.10 for any given California rice grower with a midpoint estimate of $21.90. However, if we restrict attention to those producers most likely to adopt, as defined by at least zero difference in net returns, yield drag at the lower end of the range can be as high as 1.2 percent and they will still adopt.The preceding deterministic sensitivity analysis accounts for heterogeneity in land, weed infestation, and management ability as well as for the distribution of the rents generated by the technology. However, the magnitude of these rents is determined primarily through assumptions regarding yield and the price of rice as well as base assumptions on the price of alternative herbicide systems. While these point estimates are based on the best information available, another approach is to parameterize the distributions of those variables, which can be perceived as stochastic, and use Monte Carlo simulations to estimate the distribution of the surplus benefits of the transgenic rice technology. We take the specification in the equation and estimate distributions for a transgenic yield premium, the transgenic-rice price, and a conventional-rice price premium. Yields for the HT cultivar are assumed to vary according to a symmetric triangular distribution centered around 80 cwt per acre with a minimum value of 72 cwt and a maximum value of 88 cwt . This distribution allows for the possibility of yield gains and losses and, with symmetry, tends to be very conservative given the state of weed infestation and resistance across the state. Prices for California rice are essentially determined on the world market and thus are not influenced by the individual producer.

Using historical data from USDA for 1986 through 2002, we assume a log normal distribution for output price with a mean of $6.50 per cwt and a standard deviation of 1.67. Finally, the price premium for conventional rice is assumed to be distributed as a skewed triangular with a most-likely value of $0.25 , a minimum value of zero, and a maximum value of $0.52 or about 8 percent. These values are consistent with experience with corn, soybeans, and canola cited previously . To run the simulations, the technology fee and all CRCA assessments are set equal to zero and 10,000 draws from the distributions are made for each of four scenarios, depending on which parameters are assumed random. This gives an estimate of the gross surplus generated by the technology before pricing and assessment policies determine the distribution of those benefits. The first and second simulations assume no price premium with yields only and with both yields and price random; the third assumes that yields and the price premium are stochastic with the output price fixed at $6.50 per cwt, and the fourth assumes that all three parameters are random. As peracre benefits do not vary with output price alone, this scenario is excluded. In addition, each simulation is run for two groups—one that exhibits yields across the entire range of the distribution, labeled “all producers,” and one in which attention is restricted to those growers who are expected to increase their yields with adoption of the transgenic crop. This group is labeled “yield gainers” and yields are distributed as a non-symmetric triangular distribution with a most-likely and minimum value of 80 cwt per acre and a maximum value of 88 cwt . The yield gainers are most likely to adopt the new technology, and results from these simulations may more accurately represent the distribution of benefits among those who actually grow transgenic rice. Results from the Monte Carlo analyses are reported in Table 6. Under these assumptions, gross benefits from the technology are generally positive except on the lower end of the distributions. Yield gainers, on average, see a return of between $9.84 and $11.60 per acre more than the overall average producer with a slightly smaller variance due to the smaller yield variance assumed for this group. For both groups, indoor cannabis grow system introduction of the price premium increases the variability of the benefits by more than the introduction of output price variability. The price premium also reduces the magnitude of the surplus gains by approximately $20 at the median. Table 6 does not account for CRCA assessments or technology fees, generally bounded between $6.30 per acre and $21.10 per acre . Although not exact, a “back of the envelope” calculation suggests that median farm-level benefits, after accounting for these fees, are expected to be positive; however, not all farmers will see increased returns. The same is true for yield gainers in that median benefits are greater than $21.10 for each scenario but the lower end of the distribution may experience negative returns from adoption. The majority in each group, however, will benefit. More specifically, the exact probabilities of net returns greater than zero can be calculated. Assuming all three parameters are stochastic and bounding the fees according to the preceding assumptions, the probability that net returns are greater than zero for all producers is between 60.14 and 85.8 percent. For yield gainers, this range increases to between 89.4 and 100 percent, once again highlighting the importance of yield assumptions on net returns and hence on adoption.To further test the potential adoption impacts of the LibertyLink® transgenic rice variety, we apply the preceding methodology to the results of a three-year field study conducted by Fischer . The study covered growing seasons between 1999 and 2001 and was funded by DPR. The exercise uses the weed-management regimes and corresponding yield measures of the Fischer study, together with the pricing assumptions previously maintained, to estimate net returns for a hypothetical farm using identical herbicide rotations. To elaborate, Table 7 describes the rice-variety and herbicide-treatment regime used in each year of the Fischer study. The project was implemented on a rice field in Glenn County, California, on which watergrass was found to be resistant to molinate, thiobencarb, and fenoxaprop—three of the four chemicals registered in the state to control grass weeds at the time of the study . Four treatment regimes were analyzed: continuous molinate each year, an intensive combination of several chemicals each year, a rotate-mode-of-action regime in which chemicals with differing properties were rotated from year to year, and a continuous transgenic regime resistant to glufosinate. Each regime was applied to four plots of 0.57 acres each, and indicator measures such as yields were averaged for each treatment group . It is important to note that the choice of treatment regime was not related to economic considerations but, rather, to evaluation of the effi- cacy of differing treatment regimes under resistance conditions .To estimate potential returns over operating costs, the yield and herbicide regime data are used in conjunction with the structure presented in Table 2 to estimate per-acre costs and revenues on a hypothetical farm unit. Herbicides, custom operations, contract operations, interest on operating capital, assessments, and yields vary according to the experimental data while the remainder of the cost components are held constant at the levels presented in the first table. Again, to provide a basis for comparison, we set output prices for the transgenic variety equal to the conventional product and the CRCA assessments and technology fee equal to zero. Table 8 reports the results of the exercise. The first year of the trial included eight plots planted with LibertyLink® M-202 seed treated once with varying levels of glufosinate mixed with ammonium sulfate and eight plots planted with conventional M-202 seed, four of which were treated once with molinate and the remainder of which were treated once with propanil. The continuous-molinate treatment served as a baseline for the entire experiment as the field had demonstrated watergrass resistance to this particular chemical . From an economic standpoint, the intensive-combination regime was slightly superior to the two transgenic regimes with net returns per acre approximately 4 to 10 percent greater but less than the yield advantages of 8 to 13 percent. As operating costs for this treatment were higher than those for the transgenic rice, the difference in returns is explained primarily through yield advantages.

Beyond portfolio support, VC ecosystems also vary in scale from local to international. When VCs evaluate which startups to fund, the criteria depend on the stage of the startup. During the seed stage, VCs judge startups based on their technology, team, and the extent to which the startup has a believable market opportunity. Moving towards the Series A funding round, VCs begin to care about unit economics, proof of traction through contracts and letters of intent, and revenue. At the Series B stage, VCs continue to value revenue metrics and begin to look for established customer pipelines, go-to-market strategies, and proof of high growth companies. All three stakeholder groups had varying opinions of the role of government in the precision weeding ecosystem. Under existing conditions, growers viewed the government as offering little support and being out-of-touch with grower needs. Because specialty crops are a small percentage of America’s total agricultural production due to large commodity crops like rice, soy, and corn, government intervention for specialty crops would not provide as positive of a return on investment. While the government is slow, some of the growers did commend effective government funding for irrigation. However, in the future, because hand labor for weeding is arduous, some growers have hope for increased government support because of precision weeding’s positive social implications. Startups viewed government involvement as limited to grants and the USDA’s agronomy advice. Though pushed by local politicians, drying cannabis particularly in Salinas Valley, R&D tax credits remain trivial. In addition, startups and VCs noted the role of regulatory agencies such as CalOSHA and the Department of Pesticide Regulation.

In connection to the government, all three stakeholder groups mentioned government funding for land grant university research and the UC Extension system in a positive light. Some startups mentioned that they want to become more involved with universities to influence the curriculum and develop two-year technical degrees to combat workforce constraints in agtech implementation. However, some interviewees, such as V2, voiced that the Extension has lost grower influence and that now, Extension advisors may not be the farmer’s first call or key advisor anymore. Similarly, growers felt that though Advisors are helpful in educating and advising, a lack of funding and relatively low salaries have prevented the UCCE from gaining more influence over grower behavior and precision weeding adoption. In total, the thirteen concepts mentioned most in the interviews were identified to measure the overlap of themes between the stakeholder groups, . Five described current limitations preventing precision weeding from proliferating, four involved the role of government in promoting precision weeding, three concerned the interactions between startups and VCs, and one was about the role of large corporate farms. Some concepts were more polarizing than others, as demonstrated by the color imbalances between the bars for each concept. Concepts about the limited involvement of government and the role of the government in funding land-grant university research and the UCCE were agreed upon by all three stakeholder groups. However, only VC interviewees addressed the concept of ‘Big Ag is looking for strategic returns/outsourcing innovation’ to explain why large corporate farms engage with precision weeding startups. Additionally, the complexity of the machines to operate was brought up as a blocker by the startups and the growers, but not VCs.To visualize the results about the third objective, interviewee responses were mapped onto a user experience template, colloquially known as ‘swim lanes.’ After overlaying the results for growers, the most common touch points identified in the growers’ awareness phase were social media, in-person networking through conferences and conventions, and collaborations with universities.

Growers perceived startups to be concerned about their lack of connection to the agricultural community, the risk of wasting time with unideal pilots, and ensuring the grower has the right field conditions for what the startup needs feedback for . On the other hand, startups perceived their concerns to be the dual marketing of value propositions towards growers as well as their investors, supply chain issues that may limit their technical execution of commercializing manufacturing, and large growers having bureaucratic issues that prevent demonstrations and pilot projects from becoming recurring customer relationships . During the pilot phase, growers perceived themselves to be concerned about the risk of crop damage, support staff, startup longevity, and startup quality and capabilities . During the piloting and purchasing phases, startups perceived growers’ concerns to be the price model, logistics, weeding quality, and the startup quality and capabilities . While many startups were concerned about matching customer expectations because imitating human dexterity and vision is technically challenging, one grower explicitly did not have concerns in the piloting phase because they have realistic expectations: “I don’t expect it to be like a John Deere tractor that’s just going to come out and be perfect and do everything that’s expected. I get it with technology companies that when it’s going to come out, it may suck.” Most of the areas of improvement brought up were in the consideration/piloting phase. Growers felt that points of improvement in their user journey included the prioritization of larger growers over smaller growers: smaller growers should have the same access as larger growers have to new technologies . In addition, smaller growers may value other pain points, such as food safety, over precision weeding . Startups felt that improvements could be made by educating growers about misperceptions about a lack of equipment availability within weeding-as-a-service business models. Some startups were also concerned about the ability of dealers to devalue the primary piece of farmers’ equipment, such as a tractor; the additional implements, such as precision weeding add-ons, could devalue the equipment .

The most common motivations for precision weeding technology adoption were labor concerns, environmental sustainability, costs, and return on investments. Growers were the most vocal and detailed about the shortage of labor motivating their interest in precision weeders. Because of the increase in minimum wage and AB 1066 qualifying farmworkers for overtime pay, growers and producers are growingly concerned about labor regulations . These increased labor expenses push producers to increase on-farm efficiency and mechanization, particularly on vegetable and organic farms. California growers’ issues with labor scarcity and thus increased labor costs has been a long-standing trend that also contributed to early mechanization during the 20th century. Because of California’s niche growing conditions, there was the advent of new gasoline tractors and mechanical pickers and harvesters . Now, labor scarcities are especially pressing because of California’s large production of specialty crops. Labor expenses are also especially pertinent because of the state’s strong organic sector and its associated costs. In 2019, data from the California Department of Food and Agriculture’s State Organic Program found that California’s organic sector is growing: organic acreage has increased from 1.8 million acres in 2014 to 2.6 million acres in 2019, and in 2019, organic products in the state sold for more than $10.4 billion . Additionally, California’s organic production made up 40 % of all organics in the U.S., indicating the state’s importance as the trailblazer of organic agriculture . This increase in organic production has arguably been fueled by support from the State Organic Program, a regulatory and educational department within CDFA which has, for example, implemented cost share programs for USDA certification . In addition, the consumer preference for organics has driven this trend: multiple studies have demonstrated consumers’ willingness to pay premiums for organics, with the market demand influencing grower decision making . However, organic farms face logistical and operational challenges because they employ more workers per acre. A survey of organic farms revealed that farms that have less than half of their land in organic production have fewer direct-hire workers per acre, 0.58, in comparison to farms with more than half, 0.84 . Similarly, another study found that compared to conventional farms, organic farms have both more workers per acre and a higher proportion of full-time employees to seasonal contractors . Interestingly, despite copious literature on the positive correlation between increased costs—particularly from labor—and organic farming, pipp racking the results of this study align more closely with literature suggesting that digital technologies are often closely adapted to conventional/industrial farming practices. All the growers we interviewed produce both organic and conventional crops and most startups we interviewed still included herbicides in their weed management regimes. The trend of agricultural technologies being more suitable for conventional agriculture has been shown in the use of big data, an aspect of digital agriculture defined as large sets of heterogeneous data. While harnessing big data has proven environmental and economic benefits, access may not be realistic for small-scale farmers, further widening the accessibility gap between industrial players and more vulnerable ones .

Elaborating on this accessibility gap, a review of digital agriculture revealed that top-down technological development, as opposed to farmer-driven initiatives, often are designed for very specific production systems . In addition, agricultural machinery exhibits economies of scale at the farm level, favoring larger-scale farms . Beyond the larger farm size associated with conventional growers, technological solutions may not target the needs of organic growers. A study found that digital technology use for production was underrepresented on organic farms because of a mismatch in the technology solution and the grower needs . For example, GPS deployment may help a conventional grower save on diesel, fertilizer, and weed killer, but it will only help an organic grower save on diesel. As a result, literature suggests that digital agriculture, including precision weeding technologies, may be adapted more towards conventional agriculture despite the labor stresses felt by smaller-scale, organic growers. All venture capitalists interviewed were motivated by environmental sustainability while only one grower mentioned it. This venture capital emphasis on environmental concerns such as soil quality, water quality and quantity, and unsustainable practices spur agtech investments. Investors not only valued financial returns but were also motivated by social impact and environmental returns . Because of the venture capital emphasis on environmental concerns, startups may align themselves similarly to raise funding. In a study examining how agrifood tech startups pitch themselves to venture capital firms, researchers found that VC firms make investment decisions not only on the substance and hard facts, but also based on the performance and cultural signaling of the pitch . Therefore, precision weeding startups may drive narratives of social entrepreneurship and sustainability to develop ‘visions of desirable futures’ and add moral justifications to their technologies . Paralleling such startup pitches are the mission statements of agri-food tech investors, which often combine profit and purpose . Despite both stakeholder groups emphasizing sustainable stances, these aspirations may fall short: ‘techno-fixes’ are overly simplistic and cannot realistically correct global food system challenges and the investors’ ROI requirements may curb ambitions .Considering the varying views of government conveyed by the interviewees, the political identities of the interviewees may influence their views on the effectiveness and ideal roles of government. Growers also expressed an increased distrust of government, a trend consistent with the general population . A study using ANES survey data found a shift from democratic identification to independent and conservative ideologies . In addition, in Imperial County, the most impactful work-related stressor for farmers and ranchers were unpredictable factors like government regulations . Though growers felt that the government did not understand the realities of agriculture, many actively advocated and were involved in agricultural leadership efforts . These generally negative sentiments from growers towards the government are juxtaposed by the involvement of the public sector in the digitization of agriculture. A case study examining precision dairy farming in Australia found that public R&E played the largest roles, relative to private R&E, in market formation and the creation of legitimacy . In particular, the public sector galvanized a community of interest around precision dairy farming and developed the National Livestock Identification Program to establish industry standards . In addition, an example of public action promoting digital agriculture is the regulatory pressure against glyphosate use incentivizing industry players to decrease chemical inputs . Considering the parallels for all on-farm technology adoption, existing literature about digital agriculture and the public sector can be contrasted by our case study of precision weeding in which the startup-VC-grower matrix does not consider government interactions as a factor for technology adoption.

The onus is on those producing the evidence to actively engage governments, stakeholders and policymakers, and outline the human and economic advantages of preventive strategies like behavioral interventions over a treatment-focused model of healthcare provision. Related to this, behavioral scientists need to better demonstrate how theory-based behavioral interventions that work in lab and field experiments, and have been shown to be effective in larger randomized controlled trials and in real world contexts, can be implemented in practice. Such evidence should be the focus of evidence presentations to government and policymakers advocating investment in, and implementation of, behavioral interventions. The expanding discipline of implementation science focuses on translation of research findings into evidence-based practice, and is receiving increased attention in the fields of behavioral science, public health, health promotion, and health policy . In the context of behavioral interventions, implementation science examines the pathways and strategies necessary for the uptake and implementation of interventions by policymakers and providers. Evidence on how behavioral interventions can be developed by key workers within existing networks, who will ultimately be responsible for implementing the intervention , and how users of the intervention can be involved in the implementation, is important to ensure that interventions are practically relevant and sensitive to the contextual and cultural characteristics of target populations. In addition, equipment for weed growing research on how theory-based behavioral interventions can be upscaled so their reach within target populations is maximized and the changes in health behavior and health outcomes promised by formative research realized.

Research is needed to identify the conditions necessary to up-scale behavioral interventions in real world contexts, including identifying the partnerships needed to fund, implement, monitor, and maintain interventions; engaging stakeholders to assess the feasibility and acceptability of implementing the intervention in the target community or setting; assisting governmental agencies in developing multi-level and multi-sectorial plans to implement interventions; and developing ways to embed interventions in existing networks throughout development from inception to implementation.In conclusion, interventions based on behavioral theory have been shown to be effective in changing health behavior. However, there is still need for more research on interventions that systematically and precisely map intervention content with theoretical determinants, and the need for greater transparency in the reporting of intervention content and protocols. Arguments that such behavioral interventions do not work in the real world based on observations that pandemics of non-communicable disease continue to rise, and large scale interventions have not shifted population-level participation in health behavior, as my colleague contends, are specious and miss the point. The issue is not that interventions based on behavior theory do not work in changing behavior in ‘real world’ contexts, they do, rather, it is a lack of investment in, and inadequate upscaling and implementation of, these interventions that has failed to translate their efficacy into sustained, long-term change at the population level.Over 50 years positive population behaviors or health outcomes for nutrition and physical activity have fallen or flatlined globally, and in individual countries. Data shows: rising global obesity since 1975 , and inindividual countries including England, Chile, and Australia; falling or flatlining fruit and vegetable consumption in USA since 1994, and in Japan and Brazil since 1965; and rising physical inactivity globally since 2001, in Spain since 1995, in USA since 1997, and in China since 1989.

For health outcomes, European Environment Agency data show loss of healthy life years attributable to non-communicable diseases has grown by more than 20% since 1990. These data illustrate global trends, and their replication in individual countries. Something isn’t working! Noting disjoint between a body of behavioral theory literature that appears to show promise at the individual level, and global and national data that shows no change in population behaviors and health outcomes for half a century, Hallal et al. argue “after more than 60 years of scientific research… more of the same will not be enough” . It appears behavioral theory has a case to answer, and some fundamental questions to face. But is the problem scale-up of behavioral theory in population level interventions and policies, is it intervention designs that act as the vehicle for behavioral theory, or is it simply that behavioral theory itself does not work in the real world?For decades fields such as exercise physiology, public health, epidemiology and the behavioral sciences have undertaken research showing that if behavioral theory is deployed “under scientifically controlled circumstances, behavior change is achievable for increasing physical activity” . However, many “so-called effective physical activity interventions” are small-scale, controlled efficacy trials that do not demonstrate effectiveness or ecological validity, and leave gaps in the chain of evidence between participants, theory, behavior and health outcomes . An intervention is efficacious if it works in cohorts who receive it, whereas it is effective if it works in cohorts who have been offered it. This is confused in the literature, and interventions based on behavioral theory claim effectiveness when available evidence demonstrates only their efficacy. Many trials of interventions based on behavioral theory do not venture beyond controlled environments of phase I-III trials, which seek to establish, respectively, concept, efficacy and comparative efficacy. Thus, at best, evidence demonstrates that impact on those who receive the intervention exceeds impact on those who receive alternative interventions. But still, this shows only that an intervention is comparatively efficacious for those who receive it, not that it is effective, or comparatively effective, in cohorts that are offered it.

The problem is this: the features of design and implementation associated with good phase I-III trials to establish concept, efficacy, and comparative efficacy, have important limitations for informing practice and policy decisions, which require more generalizable information relating to outcomes of societal consequence, such as a sustained impact on health outcomes at population level. Such impact, or the potential for it, must relate to real world effectiveness “as evaluated in an observational, non-interventional trial in a naturalistic setting” . To establish effectiveness, phase IV trials require a more diverse set of methods than those required to establish concept, efficacy and comparative efficacy in phase I-III trials, and must involve a diversity of settings, participants and deliverers . However, in reviewing studies purporting to examine effectiveness of physical activity interventions in the real world , Beedie, Mann and Jimenez found that many still tried to adopt laboratory style methods and controls that would be impractical or uneconomic in real-world settings. Some authors have advocated the RE-AIM framework as a Phase IV tool to develop the effectiveness of interventions shown to be efficacious at phases I-III. But, with its focus on ensuring reach, adoption, implementation integrity, and maintenance of the features of the intervention over time, RE-AIM merely attempts to deliver effectiveness by maintaining the controlled environment of phase I-III trials in the real world, which as well as being impractical or uneconomic, is also likely to be futile. Establishing effectiveness in phase IV trials is difficult, and requires longer timescales, and greater scale and resources than establishing concept, efficacy and comparative efficacy in phase I-III trials. As such, it is not surprising that, in an area where research funding is relatively sparse, pipp horticulture and doctoral studies are often the bricks contributing to edifices of knowledge, genuine phase IV effectiveness trials are rare. Nevertheless, there is a moral obligation to conduct them, otherwise advocacy for behavioral theory interventions based only on efficacy evidence risks wasting participants time and taxpayers money on unproven interventions in unproven populations.Analyses of national participation data suggest interventions based on behavioral theory may be recipients of individual behavior change, rather than the stimulus for it. This is because populations’ behaviors are qualitatively different to individual behaviors, and incorporate individual behavioral volatility within their steady state. Forexample, in England two national surveys, Active People and Taking Part, show population participation in sport and related physical activity has flatlined for 10 years, with no sustained change beyond +/− 2%. Furthermore, data synthesis across six surveys shows falling or flatlining participation for 25 years. However, both cross-sectional retrospective report data and panel time-series data from the surveys also shows considerable individual behavioral volatility, with circa 20% of the population dropping out or doing less sport, 20% taking up or doing more sport, 20% maintaining participation, and 40% consistently doing no sport.

Consequently, within any 1 year circa 40% of the population change their sport participation behavior, but aggregate population level participation is unchanged. Thus, steady state population behaviors incorporate considerable individual behavioral change. This suggests behavioral theory interventions are reflecting and facilitating individual behavior changes that take place as part of the steady state behaviors of populations, with participants often presenting as already motivated to change [88, 93]. Sport England’s Get Active: Get Healthy first-year pilots, for example, claimed to be the stimulus for more than 30,000 people becoming active, but the evaluation showed the majority of participants were “ready to change” when they joined. This suggests the interventions were the recipients rather than the stimulus for individual behavioral changes, which are to be expected as a normal part of steady state population behaviors. It is known that poor health outcomes, particularly non-communicable diseases, correlate with social deprivation, low employment, poverty, poor housing, and other indices of multiple deprivation. Behavioral theory provides neither the explanation nor, through interventions targeting individuals, the solution to such problems, which must focus on wider causal systems that underpin the social practice and economy of behaviors such as low physical activity and poor diet. Undoubtedly, it is the focus on the individual rather than the population that undermines the real-world effectiveness of behavioral theory. The etiological model on which it is based – that poor health outcomes are caused by exposure to a substance, for example, sugar, and that health outcomes can be improved by modifying or moderating individual behaviors to remove or reduce exposure – is fundamentally flawed. This is because solutions – interventions based on behavioral theory – have no relationship to causes – the factors that lead to behaviors in the first place. Furthermore, behavioral theory is assumed to be universal: that is, it is assumed the same behavioral theory can address any behavior, be that smoking, alcohol consumption, poor diet, or low physical activity – the transtheoretical model, which was developed for smoking cessation, is a case in point. Cleary these behaviors are underpinned by different antecedents, so why would we assume they can all be addressed by the same theory? Furthermore, categories of behavior are not homogenous – the existence of health inequalities is, in itself, evidence that the factors that lead to behaviors in relation to, for example, diet, differ across the population, and so poor diet is an agglomeration of behaviors rather than a single behavior. Why would we expect that these multiple complex behaviors could all be addressed by the same theory?I have argued that while interventions based on behavioral theory have been shown to be efficacious in the controlled environments of phase I-III trials, there is no evidence from genuine phase IV effectiveness trials to demonstrate they work in the real world. However, crucially, I argue that evidence from controlled trials of behavior change interventions simply capture individual behavioral volatility that is a normal part of steady state population behaviors. Furthermore, such interventions fail in shifting population behaviors because they focus on individuals rather than on the multiple complex factors that drive the distribution of behaviors in the population. As such, behavioral theory within such interventions is not an active ingredient, rather it is a dormant recipient of behavior change. Put simply, behavioral theory has no active influence on changing behaviors in the real world.I am grateful to my colleague for raising important points on the implementation of theory-based behavioral interventions and the need for more evidence for the effectiveness of behavioral interventions in ‘phase IV’ trials. These are good points that have been made many times elsewhere, including my opening statement. However, as an argument against the proposal, his statement is not fit-for-purpose. As I predicted, my colleague claims that interventions based on behavioral theory do not work in changing behavior in ‘real world’ contexts because there has been no year-on-year change in rates of non-communicable diseases and health-related behavior participation at the population level. He also suggests that behavior theory focuses solely on individual behavior, targets only the motivated, and fails to incorporate structural determinants of behavior. Here I illustrate how his arguments reflect a poor understanding of behavioral theory, and are not based on appropriate evidence, or, in some instances, any evidence at all.

The study has characterized the magnitude and the range of possible emissions impacts as compared to multiple baselines . A clear message that emerges is that decision-makers must avail themselves of better foresight and informed decision-making on near-term and longer-term timescales. More comprehensive awareness of vehicle use cases, and energy needs in time and space will help small businesses and utilities predict and plan for EV charging events. This research suggests that when marginal emissions can be at or below the weighted average values, environmental benefits stand to be greater. A unique attribute of this study compared to prior efforts is that its scope speaks more directly to small business owners and vehicle fleet operators. These stakeholder groups and their associated applications are known to realize a few advantages in comparison with individual vehicle owners driving LDVs. The reason is that the selected categories of service vehicles largely return to a central base and navigate similar, standardized routes on a recurring basis. They also travel sufficient but not overly excessive distances: a factor that may help approach the Goldilocks state. Finally, and perhaps not coincidentally, this audience seems to be targeted by automakers of late, given a limited growing number of new EV models entering the market. Though both LDV and MD use cases have societal implications involving decisions around the generation mix and utility infrastructure, it is the potential to leverage an EV to save money that could pull the technology quickly ahead and spur scale up in other vehicle sectors. The study has implications for policy and public investment, cannabis drying including an even more urgent need for managed and coordinated charging, and greater attention to resource planning.

This is especially relevant for infrastructure funding, for which the Federal Government has deployed upwards of $7.5B to states and set a goal to realize 500,000 chargers by the year 2030. The report concludes with a few suggestions for future work, including the need to leverage this methodology to quantify the monetized value of CO2 emissions in conjunction with other investment costs for capital and operations. Finally, the research team believes the model has relevance and can be scaled and adapted for conducting similar analyses in other regions.In short, it is imperative to not only manage EV charging events in time and space, but also consider our latitude to control or influence other large loads on the grid in conjunction with EV deployment growth. This study reveals that several Medium and Heavy-Duty EV use cases can offer significant benefits, but also makes it clear that decisions around charging operations, infrastructure and grid support must be conducted at a system level that considers vehicles, their use cases, as well as the temporal nature of grid generation. In this way, the electrification of transportation is more likely to result in measurable decarbonization gains, substantive environmental and health benefits, and reasonable returns on investment.Vehicle electrification not only continues to garner momentum, but also public and private funding, and is considered a viable means of growing the national economy and decarbonizing major segments of the transportation sector. A growing body of evidence demonstrates that substitution of gasoline-consuming vehicles with electrified alternatives eliminates tailpipe emissions contributing to reductions in CO2 emissions as well as in criteria pollutants. Whereas CO2 reductions can favorably affect global climate change trends, pollutant emissions reductions can improve urban air quality on a more local scale, and by extension improve public health.

A key advantage of Electric Vehicles compared to internal combustion engine vehicles is that their carbon and emissions footprint is not fixed based on the vehicle technology from a given past model year, but instead can progressively improve in lock step with a grid that is evolving toward a cleaner and lower carbon generating mix. Driven in part by policy, declining prices, and product availability, EV deployments are accelerating, having surpassed 2,000,000 vehicles sold in the U.S. fleet by Dec 2022. Though EVs still account for less than 1% of the domestic vehicle fleet, the growth is definitely accelerating. Projections for continued EV growth through the present “second decade” of mass deployment are varied, and uncertainty is a factor for both capital costs and energy costs. Still, many sources suggest sustained growth approaching double digit shares of the fleet by 2030. EVs are increasingly seen as a win-win solution by many policymakers, in that they can provide benefits to consumers, automakers, and utilities, while also reducing environmental impacts. In spite of substantial progress and aggressive policy support, non-trivial barriers remain. These barriers may simultaneously threaten both broader adoption and certain beneficial outcomes of EV growth. Among one the most critical and poorly understood, is the need to ensure environmental benefits live up to their promise as deployments exceed 10% of the future fleet. This seems to be a kind of threshold of market penetration beyond which grid capacity, resource adequacy, broader electrification, levelized energy costs, and decarbonization may be challenged. While much public attention is focused on light duty vehicle markets , significant opportunities are believed to exist in Medium Duty and certain Heavy Duty applications. For this reason, the EVALUATE research team has conducted a twoyear, two-phase research investigation focused on methodologies and applications across major Light Duty and Medium Duty vehicle classifications. Key contributions of our Phase I included the development of a rigorous methodology involving a high-fidelity system of systems model.

This included a sub-system model for vehicle power trains which provide accurate estimates of energy consumption for representative driving cycles. Additionally, it included a literature review, survey data, observed experimental data, and a protocol to inform EV charging profiles. And finally, it included a series of datasets and procedures developed to understand how electric power is dispatched and delivered at the bulk grid level. More specifically, it generated a high-resolution characterization of the emission rates associated with electric power generation on an hourly, daily, seasonal, and annual basis. While studies have explored each of these sub-systems independently, the research team has been among the first to develop them in an integrated manner to forecast the emissions outputs of a class of vehicles and a range of use cases. The phase I findings were significant and explored light-duty vehicles through typical urban commuters and households that operate LDVs for daily personal use. [See Phase I final report for more on the initial study and its key findings, 1].The over-arching goal of the EVALUATE project has been to ensure that reductions in CO2 and pollutant emissions are more fully understood, and that decision-makers have guidance and tools to help realize them. The research team believes this will be imperative as EV market penetration scales up . To achieve this goal, Phase I of this project developed a system of integrated vehicle, transportation, and electric power system models designed to evaluate hourly marginal CO2 emissions rates for a regional study under various demand scenarios between now and 2030. As noted, the focus was on personal vehicles in the light-duty category. Phase II of this project, presented here, demonstrates the usefulness of these tools in providing policy-relevant information to practitioners and decision-makers. As such, we focus on a series of targeted case studies that extend prior work from LDVs operated by individuals to service oriented vehicles operated by small and medium businesses.To augment the analysis and build upon prior work, additional inquiries were made into the type and capacity of EV charging devices that would be required for these larger vehicles and different use cases. For instance, Phase II has focused more extensively on medium rate and fast charging methods1 . In conjunction, the research team assessed likely charging behavior that would be typical of small businesses in the subject categories. Again, the goal has been to better understand how vehicle use case, charging behavior, and assumptions around the grid, with a particular focus on marginal emissions, may affect the environmental impacts and other relative pros and cons of EVs as a substitute for the incumbent vehicle technology . The selected scenarios and simulated outputs are based upon a series of case studies in the Atlanta, Georgia metropolitan area using local assumptions along with historical and projected grid data for Georgia Power and the Southern Company balancing authority. These case studies evaluate the influence of vehicle classification, usage, best way to dry bud and charging strategies for EVs in both light-duty vehicles and medium-duty trucks .

All case studies explore the relationship between the selected scenarios and the resulting carbon intensity of marginal electrical power generation. This investigation provides an important theoretical contribution to our overall understanding of vehicle electrification for intermediate market penetration rates. Equally important, the study demonstrates the ability of the EVALUATE modeling system to produce practical policy-relevant findings that are valuable to stakeholders that relate to our selected scenarios, the Southeast region, and more broadly. This research is uniquely positioned to address critical gaps and inform strategic decisions that will be economically viable and favorably advance EVs, sustainable transportation solutions, and their concomitant policies. This research identified representative use cases that included Light and Medium Duty return-to-base fleets. Prior to the present study, the research team oversaw a Georgia Tech student-led effort that conducted a preliminary techno-economic investigation into residential service vehicles such as those used by HVAC, exterminator, plumbing, and landscaping personnel, with some high-level economic indicators depicted in Fig 1-1. To this, the current research team added new business-related scenarios including ecommerce, package delivery vehicles, moving trucks, and refuse trucks. In the present study, the team applies the marginal emissions methodology to these expanded use cases, to further demonstrate how the methodology can be applied, and yield some illustrative insights for several discrete vehicle categories and use case scenarios. Finally, the study provides guidance that can inform how decision-makers can optimize effectiveness and cost based on the team’s approach .This research requires the synthesis of three independent sub-system models and data developed or identified by the research team in the areas of vehicle propulsion and auxiliary power and energy need to satisfy prescribed trip/travel demands for a range of vehicle technologies and applications, EV charging profiles that would be considered typical for the service, fleet and medium duty vehicle use cases, and grid generation dispatch with commensurate consideration of emissions intensities for CO2 and major criteria pollutants. The team has extensive experience developing high-fidelity sub-system models and applying them to both generalizable and regional scenarios. As an input to the two phases of the EVALUATE project, the team drew upon more than three years of prior efforts acquiring and conditioning open-source data, alternative vehicle architectures, customized datasets for regional electric power dispatch , and numerous travel route pathways. Under the EVALUATE project, the team deepened its experience by integrating several of these subsystem resources into a holistic picture of emissions by vehicle type and use case. The scope of the second phase of this project has been to update and develop new, more accurate subsystem models and datasets that are granular and of specific relevance to service fleets and medium-duty vehicle operators. The end result of the two phases, therefore, is a set of integrated models built upon high-fidelity data from real-world use cases that generate a range of simulations. Throughout the EVALUATE project, the simulations are generated primarily to draw comparisons, understand the impact of fundamental assumptions around charging behavior and grid emissions, and develop initial guidance around the relative merits of EVs under representative use cases. The use of these tools to guide private sector fleets and medium-duty vehicle operators can be timely since few high-fidelity emissions calculators are available to accompany proprietary economic assessment tools.The team’s methodology was developed in Phase I and expanded in Phase II for the purpose of investigating a broader set of vehicles and charging profiles that typify urban service fleet and medium-duty delivery applications. A brief recap of the major steps in the analysis is presented here. First, physics-based vehicle energy consumption models are developed which facilitate comparisons among vehicle architectures that utilize energy from disparate primary sources . As noted, the Phase II effort extended the modeling from light-duty cars used for personal use, to light-duty pickup trucks and vans used for serviceoriented businesses. Additional models were derived and corroborated against background data to characterize medium-duty delivery trucks and a heavy-duty urban application . A related task involved the identification of driving cycles that approximate typical routes traveled by the associated vehicles.

This publication summarizes the steps involved in establishing hedgerows on farms in California and concludes with a discussion of potential food safety issues associated with hedgerows and attracting wildlife to farms. Farm Plan When considering habitat restoration work on farms it is important for landowners to develop a whole farm plan to integrate their conservation goals and methods with current farming operations. Examples of habitat restoration goals include the use of hedgerows for soil erosion reduction, wildlife enhancement, increasing biodiversity, water and air quality protection, windbreaks, attracting beneficial insects for pest control and bees for pollination in adjacent crops, and weed control. The goals of the restoration work will affect the types of plants selected and where the project should be established on the farm. Consult an aerial map of the farmland to assess the topography, hydrology and drainage, crop production areas, non-crop areas, and buildings before defining the appropriate use of the land for different types of restoration purposes. Also consider potential funding sources, since restoration projects can be expensive. A good source of information for cost-share programs and additional farm plans is your local Natural Resources Conservation Service as well as the Yolo Resource Conservation District , Robins et al. 2001, and CAFF 2004. Site Selection Once a farm plan has been developed, select sites for the proposed work. The most suitable areas for restoration projects include non-cropped areas along roadsides, agricultural drains, fences, canals, marijuana grow system field borders with different elevations, and gullies. Sites should be easily accessible by equipment for project construction and maintenance. Access to water during the growing season is essential for establishment of shrubs and trees for at least the first 3 years or until the plants are well rooted to survive California’s long, dry summers.

Site Analysis After selecting a site for a hedgerow, analyze the area to determine which design and plants would perform best. Some hedgerows fail because the plants used are not well adapted to the local field site conditions. Determine the soil type, assess the area for potential flooding, and identify obstructions such as overhead wires that would limit tree planting. High and low spots that have standing water should also be noted, as well as potential for plant injury from nearby livestock, or competition from established vegetation such as shading from trees, equipment traffic, and herbicide drift. Planning and Design Once the site has been analyzed, make a drawing of the area that shows the size of the restoration project, types of plants to be incorporated in the design, and the planting layout. In general, linear plantings are the easiest to maintain with the large-scale equipment such as mowers, disks, or sprayers commonly used on farms. A single strip of shrubs and/or trees bordered by strips of native perennial grasses, and/or sedges and rushes if riparian, and a forb strip works well as a hedgerow design on field crop farms . Access roads separating the hedgerow from the crop help prevent birds from feeding on newly emerged crop seedlings, which may occur when native grasses and shrubs are planted adjacent to the crop.Figure 1 shows a typical plant spacing for trees, shrubs, and forbs. In mixed perennial plantings one grass type may initially dominate the stand, but over time other species will begin to emerge. In addition to the forbs listed above, the forb strip seed mix can include lupines , clovers , tarweeds , vinegar weed , and California poppy . Additional trees include oaks , California sycamore , and California buckeye . A more complete list of plants and perennial grasses adapted to various regions in California and information on where to purchase them can be obtained from the Resource Guide for Hedgerows in California and the Pictorial Guide to California Native Grasses . For large-scale plantings of shrubs and trees, place orders at least 6 months in advance to ensure plant availability.

Site Preparation and Planting Hedgerow sites should be disked and shaped to prepare the area for planting, providing a good seedbed for the native perennial grasses and forb seed mix. Although the grass seed can be planted into ground that has not been recently worked using a no-till drill, weed control will become more difficult and costly later on. Some hedgerows are planted flat, others on raised 60-inch beds. If the site is flood-irrigated and soils are heavy with a high water-holding capacity, use only plants that tolerate flooding. Space the larger shrubs at a 15-foot spacing and the smaller ones in between the large ones at 7.5 feet . Trees need a 20- to 30-foot spacing, depending on the variety. Fertilize the shrubs and trees with compost or a slow-release fertilizer at recommended rates at time of planting. Plant the native perennial grasses at 12 to 14 pounds per acre and the forb strip at 15 to 20 pounds per acre. Use a no-till drill for the native grasses because the long awns on some varieties tend to get stuck in the drills. Sometimes a carrier such as bran may need to be added to the seed mix to achieve this low planting rate. Perennial grass seed can also be broadcast at 20 to 25 pounds per acre, and forbs at 20 to 30 pounds per acre, then lightly harrowed by dragging a chain across the site to cover the seed. The best time to plant perennials in California is in the fall when cooler and wetter conditions help plants establish before the summer heat sets in. Irrigate every 1 or 2 weeks during the growing season for the first 3 years, or until the plants are well rooted. The duration and frequency of the irrigations will depend on plant evapotranspiration rates and soil type. So, for example, plants in sandier soils on hot days will need more frequent watering than those in heavier clay soils with a high moisture-holding capacity. After 3 years, the hedgerow plants will still benefit from an occasional summer watering. In areas lacking access to water, water tanks can be used with pumps to pressurize and deliver the water through drip lines. Native perennial grasses and many direct-seeded forbs go dormant in the summer and do not need to be irrigated.

Bird herbivory on new forb seedlings can be prevented by the use of bird scare tape on poles and netting. Weed Management Weed control is the most difficult and challenging part of establishing hedgerows of native grasses, trees, and shrubs on farms. For hedgerows of shrubs and trees , the most cost effective and long-term solution for weed control is to use mulches, such as walnut shells or compost, or weed mats. Preemergence herbicides such as Ronstar can be used, but they may not provide enough broad-spectrum weed control. That is, several weeds may be controlled, but others often take their place. Roundup provides effective weed control, but drift to nearby hedgerow plants must be prevented when spraying,especially when the plants are small. Once the hedgerow plants establish, they will help shade out competing weeds. For establishing native perennial grasses and forb strips, let the winter rains bring up the first flush of winter weeds prior to planting; control these by harrowing or spraying with Roundup. A second application of Roundup can be made about a week after planting to help control the faster growing annual weeds before the perennial grasses emerge . Walk the area to make sure the native grasses have not emerged prior to spraying with Roundup or you will lose the stand. These may be difficult to identify so if you are not sure, either skip the Roundup spray or call someone with experience in native grass plantings for help in identifying the seedlings. If drill-seeded, look for rows of seedlings. For broadleaf weed control in native grasses a number of herbicides can be used, including the phenoxys MCPA and 2,4-D, curing and drying weed as well as Buctril , Garlon , Milestone , and Vista . Be sure to check with your local agricultural commissioner for restrictions on the use of these materials, especially with the phenoxys that cannot be used after March 1 in many counties. These herbicides may also injure newly emerging native grass seedlings, so wait until the grasses are at least several inches tall before applying them. Grass weeds in native perennial grass stands are difficult to control. Preemergence herbicides do not give a broad enough spectrum of annual grass weed control, and there are no registered postemergence herbicides that can be used in mixed native grass stands without injuring them. To help the perennial grasses compete, mow annual grasses in the spring before the weeds set seed during the first 2 years of stand establishment. Weed whacking, weed wicking, and spot spraying with herbicides will also help maintain a healthy stand. Burning the native grasses in the fall helps control weeds, but do not burn on a hot day or the native grasses will be injured. Be careful as well not to burn the native shrubs, which can be injured or killed by fire. More information on weed control can be obtained through the University of California Gophers and voles will feed on the roots and crowns of establishing shrubs and trees, sometimes causing extensive plant losses. To prevent vole damage, place plastic tree tubes around plants at the time of planting to keep the rodents from girdling them. In severe vole outbreak years, apply zinc phosphide, diphacinone, or treated grain to control these pests. These rodenticides are available through some county agricultural commissioner offices. Follow the label carefully to avoid poisoning non-target species such as birds. Monitor and trap for gophers when activity is observed. Poison baits are also available for gopher control. Barn owl boxes can also be placed in the hedgerows to attract owls that prey on these rodents.Once established, hedgerows of shrubs, trees, sedges, and native perennial grasses compete fairly well with weeds, but they still require yearly maintenance to keep weeds under control. Grasses should be mowed, grazed, or burned every couple of years to maintain the health of the stand, with the timing and frequency dependent on the weed complex and severity in the stand. In general a good time to mow established grasses is after July, when the bird-nesting season is over. Monitor shrubs and tree plantings yearly for rodents and weeds, as weedy hedgerows tend to attract insect and rodent pests that may cause problems for adjacent crops. Established hedgerows of shrubs and trees may also benefit from an occasional summer watering, especially during drought years.The cost of establishing a hedgerow for the first 3 years is estimated to be $3,847 for a 1,000-foot-long hedgerow with a single row of shrubs and trees bordered by native perennial grasses . This cost includes labor for site analysis and design and field preparation, including disking and shaping the site and preparing a seedbed. The cost also includes plants, seed mixes, fertilizers, and labor for planting. Weed control costs include mulches, herbicides, and hand-hoeing; although high initially, these costs will decline as the native perennial grasses and shrubs mature and outcompete weeds. Irrigation costs include drip tube and emitters as well as labor for installing the system and irrigating the plants for at least 3 years. Vertebrate pest control costs include tree tubes to protect young plants from voles and squirrels, rodenticides, and trapping. Additional costs to manage the hedgerow will be incurred beyond 3 years, but these costs should be minimal, consisting of mowing or spot treatments with herbicides and the occasional watering during the summer or drought years. NRCS cost-share programs are available to help plant hedgerows on farms, covering from 50 to 75 percent of the costs, depending on the program and hedgerow type.Outbreaks of the food pathogens Escherichia coli O157:H7 in leafy green vegetables, as well as outbreaks of serovars of Salmonella enterica in nut crops, have prompted a variety of preharvest food safety concerns about management practices including establishing wildlife habitat and related potential vector attractants to farms. These concerns are largely focused on raw horticultural foods. Although various types of E. coli naturally occur in many animals , research indicates that domestic cattle are the primary reservoir of toxin-forming pathogens such as E. coli O157:H7 associated with foodborne illnesses.

The delay in the appearance of resistant weeds is generally attributed to the slower generation time of plants, incomplete selection pressure from most herbicides, soil seed reserves, and the plasticity of weedy plants, all of which keep susceptible individuals in a population and thus delay the evolution of resistance. The appearance of herbicide resistance in plants today is increasing at an exponential rate , mirroring the trends previously seen with insecticide and fungicide resistance. Besides triazine resistance, there are biotypes of 172 weed species expressing resistance to 16 other herbicide classes.The most common mechanism of action or target site of herbicides, the chemical class, and the number of species with biotypes resistant to each herbicide class are summarized in Table 1. In California, herbicide resistance today is most widespread among aquatic weeds in rice production . Many of these weed species have been selected for resistance to the sulfonylurea herbicide bensulfuron. There has also been one report of triazine resistance as well as one report of sulfonylurea resistance in a noncrop area. A roadside survey conducted in 1995 and 1996 found that resistance to sulfonylurea herbicides was common in Russian thistle . Most recently, a rigid ryegrass biotype exhibited resistance to glyphosate in a northern California orchard. Despite these examples, there are few reports to date of herbicide resistance in California, but the problem is significant in the United States and worldwide . Many current and pending registrations in California, however, curing bud involve herbicides that act on branched-chain amino acid synthesis . The use of herbicides in this group has selected many weed species for resistance in the United States and several in California .

In addition, a number of genetically engineered crops that are resistant to specific herbicides—such as Roundup Ready cotton and corn—will soon be available in California. Sole reliance on the herbicide to which these crop varieties are resistant will increase the selection pressure on weeds for resistance to the herbicide used. Herbicide-resistant crops will not be an end-all solution to weed problems, and they will not be a useful tool for weed management if used exclusively. Nationally, an average of six to seven herbicides were registered every year from 1955 to 1975. Since the mid 1970s that number has declined, reaching lows of one to two herbicides per year in the 1980s. Even fewer herbicides are registered for use in California. Re-registration requirements for pesticides have also resulted in the loss of herbicide registrations in many crops. With few new herbicide registrations and a loss of existing compounds, the potential for repeated use of the limited number of herbicides available is increasing, and that increases the potential for selecting resistance in weeds. Weed control programs should include strategies that reduce the likelihood of selection for herbicide-resistant weeds and conserve existing chemical tools.Evolution and natural selection are the processes that have led to the plant species found around the world today. Many plants, particularly weeds, contain a tremendous amount of genetic variation that allows them to survive under a variety of environmental conditions. Most herbicides affect a single specific site of action, and that site is usually under the control of a single gene, or at most a few genes. With a single gene mutation, even minor changes in gene expression can confer resistance by modifying the site where a herbicide has its toxic effect: the site of action. The evolution of a resistant population in a species comes about in response to selection pressure imposed by that herbicide or by another herbicide that shares the same site of action. When a herbicide exerts selection pressure on a population, plants possessing the resistance trait have a distinct advantage. Unlike susceptible plants, resistant plants will survive and reproduce.

Continuous herbicide exposure maintains the selection pressure and thereby rapidly increases the number of resistant plants. Weeds possess traits that promote the evolution of resistance. A high rate of seed production with most seed germinating within a year can accelerate the evolution of resistance. When susceptible plants are removed from the population by the herbicide, prolific seed production by resistant plants rapidly shifts the population toward resistance. High seed production coupled with genetic variation increases the probability that resistance will evolve. Perennial weeds, particularly those with vegetative reproductive tissues, are less likely to evolve resistance than are weeds with an annual life cycle that produce abundant seeds, since generally there is less genetic diversity in perennial weeds that reproduce vegetatively and fewer opportunities for new mutations to be transferred to offspring via seeds. The most common weed genera that contain herbicide-resistant populations are listed in Table 3. All of these genera are dominated by annual species.In the absence of herbicide treatment, weeds resistant to the triazine herbicides are not as fit as are susceptible plants of the same species. This is because the efficiency of photosynthesis is reduced in resistant plants by the alteration of a specific photosynthetic protein that is also the herbicide binding site, so conferring resistance. Since resistant plants are less fit, they reproduce at lower rates and consequently represent a smaller fraction of the number of individuals within a population. In contrast, some resistance traits do not have the same fitness cost. In those cases, resistant individuals often represent a larger fraction of a population . The frequency of the resistance trait within the population is an important factor in determining the rate of selection for resistance among weed species. For example, resistance to triazines evolved after 10 years of continual use of the herbicides. Unlike the triazines, the sulfonylurea herbicides have not been shown to have a significant fitness cost associated with the resistance trait. Resistance to these herbicides took only 4 years to evolve. For weed species with resistance to sulfonylurea herbicides, the initial proportion of resistant plants in a population has been estimated at approximately 1 in 1 million individuals. Thus, if a weed population has a density of 10 plants per m2, one would expect to find one resistant individual in every 10 hectares of infestation. Without multiple control strategies, these resistant individuals are likely to survive long enough to produce resistant seed. Several factors, such as herbicide characteristics, plant characteristics, weed control practices, and production practices, can increase the probability of selection for herbicide resistance. Herbicide factors that contribute to the potential for resistance include a long soil residual activity, a single target site and specific mode of action, and a high effective kill rate for a wide range of weed species. Herbicides with prolonged soil residual activity exert selection pressure for a longer time period since they will kill most of the susceptible plants that germinate over a growing season. A herbicide with a single target site controlled by few genes is more likely to encounter plants with mutations for resistance than is a herbicide with several modes of action. A high effective kill rate rapidly depletes susceptible genes from the population, and the result is a rapid increase in resistance among the progeny of a few initial resistant plants. Although the most common mechanism of herbicide resistance in weeds is an alteration at the site of action, resistance can also result from an enhancement of the plant’s ability to metabolize and detoxify the herbicide. This mechanism is not yet widespread in the United States.

Like target site changes, selection for enhanced metabolism can also occur in response to repeated applications of the same herbicide or of a group of herbicides that are vulnerable to the same detoxification enzymes. For example, enhanced metabolism is thought to confer resistance to picolinic acid herbicides in yellow starthistle in eastern Washington. Weed biotypes with enhanced metabolism have a much lower level of resistance than weeds expressing resistance through site of action changes. Selection for weeds with enhanced metabolism is more rapid when a herbicide is used continuously at or below the low recommended rate. This allows a gradual increase of the weed biotypes that are more able to metabolize the compound. The most likely way to cause evolution of resistant weed populations is to exert selection pressure on weeds with the same herbicides over several generations. By using long–soil-residual herbicides, cannabis drying rack the same herbicide continuously, or a rotation of herbicides that target the same site, you apply selection pressure for resistance over several generations. The continuous planting of the same crop within and between growing seasons reduces your options for rotating to herbicides with different target sites. For example, crop rotation with California rice is difficult, so fields are planted continuously to the same crop. The herbicide bensulfuron was registered for rice in California in 1989. It was highly effective on most rice weeds. Few alternative control techniques were used in rice, so Londax was used extensively for several years. Resistance evolved quickly, and now at least four weed species are resistant to Londax . The limited number of herbicides registered for many minor crops restricts the grower’s ability to rotate among compounds with different sites of action. This often leads to continuous use of one or a few herbicides and increases the probability that herbicide resistance will evolve among weed populations in those fields. Resistance has not yet become a problem in California’s minor crop production areas, however. This is probably because of the extensive use of hand labor, cultivation, and frequent rotation among a number of crops for which herbicides with different target sites are registered. While hand labor and cultivation continue as effective methods for preventing resistance, the herbicide rotation that has accompanied crop rotation may become ineffective as herbicides that target branched-chain amino acid synthesis are being registered for several of the nationally minor crops grown in California, including tomatoes and sugar beet. In addition, ALS inhibiting herbicides have been registered for cotton, corn, and alfalfa. The risk that weeds will evolve resistance to these herbicides will increase if ALS inhibiting herbicides are used continuously in several crops within a rotation. The exclusive use of herbicides for weed control can rapidly select for resistance when other control practices such as tillage or hand hoeing are not also used to control herbicide-resistant weeds. In general, non-chemical methods will not select between susceptible and resistant plants, so they should be used whenever possible. Resistance also evolves more quickly in lower-value solid-seeded crops grown on large acreages, since cultivation and hand-weeding of these crops may not be feasible. Farmers who grow crops over large areas tend to rely heavily on herbicides for weed control. Any management action that reduces the selection pressure for resistance will reduce the rate of resistance evolution. Crop rotation is one of the best tools for preventing resistance. Rotation to another crop allows the grower to use both chemical and non-chemical control methods. Manipulation of planting time, the competitiveness of the crop, cultivation techniques, hand weeding, and applications of herbicides with different target sites all are possible in a crop rotation system. Farmers and Pest Control Advisors in California use many of these methods to control weeds. Probably because of these characteristics of California agriculture, few weed species have evolved herbicide resistance in this state. As highly effective herbicides with the same target site become registered in California in multiple crops of a rotation, however, the risk increases that resistance will evolve.Herbicides with different chemistries and trade names but with a target site in common can reduce the effectiveness of herbicide rotation. Some common crop rotations include cotton, corn, tomato, sugarbeet, and alfalfa. All of these crops now have registered herbicides that target the same site . As noted earlier, biotypes resistant to these herbicides may have no fitness cost associated with resistance and there may be high numbers of resistant individuals in a population. Weed species will evolve resistance rapidly unless farmers rotate to herbicides with different target sites. Herbicide-resistant crops represent a new technology whose use is increasingly widespread. In many cases, farmers who grow these crops will rely more heavily on a single herbicide. Such a strategy will likely select for weed biotypes that are resistant to that herbicide or mode of action. Tank mixing, rotating herbicides, rotating to varieties without the resistance trait, and integrating non-chemical control options within the weed management program will reduce the potential that weed biotypes will evolve resistance.

The challenge now is to develop crops and agricultural systems that will continue to provide good yields in the face of continuous evolution and global dissemination of pests, pathogens, and weeds as well as changing and more stressful growing environments. Sustaining the world food supply requires excellence in both foundational and translational research in parallel with agriculture becoming more data-driven. The necessary technologies and expertise are available such that, with sufficient investment, the future is bright for improving plant health as part of integrated and sustainable agricultural systems. Online feedback provided by the international community at large within the first four weeks of the paper’s online publication will be collated and included as an addendum.Cytological, morphological , and molecular data suggest that tetraploid Sorghum halepense arose as a naturally occurring hybrid between S. bicolor , an annual, polytypic African species which includes cultivated sorghum; and S. propinquum , a perennial southeast Asian native of moist habitats. While a firm estimate of its antiquity is lacking, S. propinquum is thought to have shared ancestry with S. bicolor ∼1–2 million years ago , roughly circumscribing the maximum age of S. halepense. Occasionally used as forage and even food , S. halepense has spread in postColumbian times from its hypothesized west Asian center of origin across much of Asia, Africa, Europe, North and South America, and Australia. Its establishment in the U.S. is probably typical of its spread to other continents, hydroponpic rack system being introduced intentionally as a prospective forage and unintentionally as a contaminant of seedlots .

However, while sorghum largely remained confined to cultivation, S. halepense readily naturalized and has spread across much of North America, both to agricultural and non-agricultural habitats – suggesting capabilities for adaptation well beyond those of sorghum. Its common name thought to be a misnomer [the eponymous Col. Johnson may have obtained propagules from his wife’s family, who accidentally introduced it to South Carolina shortly after the Revolutionary War ], ‘Johnsongrass’ has the rare distinction of being both a noxious weed in 20 U.S. states and an invasive species in 16 . With at least 24 herbicide-resistant biotypes now known , Johnsongrass appears likely to become even more problematic in the future. For example, a glyphosate resistant biotype discovered in Argentina in 2002 covered 10,000 ha by 2009 . Its ability to cross with sorghum despite a ploidy barrier makes Johnsongrass a paradigm for the dangers of crop ‘gene escape,’ and restricts deployment of many transgenes that could reduce the cost and increase the stability of sorghum production. Here, we integrate several diverse data types to elucidate the evolution of S. halepense, its invasiveness as exemplified by rapid spread across the United States in post-Columbian times, and the roles of polyploidy and interspecific hybridity in distinctive features of its growth and development. As the first surviving polyploid in its lineage in ∼96 million years , S. halepense may also open new doors to sorghum improvement, with synergy between gene duplication and interspecific hybridity nurturing the evolution of genes with new or modified functions .Sorghum halepense, S. propinquum, S. timorense and representatives of each of the wild S. bicolor races were sequenced using standard methods implemented at the US Department of Energy Joint Genome Institute, as part of a larger project including 27 genomes and 39 transcriptomes in total.

From each accession, 76-bp paired-end reads were aligned to the Sorghum bicolor reference genome using BWA version 0.5.9 . Multiple-sample SNP calling was performed using the mpileup program in the samtools package and bcftools . Reads with mapping quality score > = 25 and base quality > = 20 are used for SNP calling. Raw SNPs are further filtered according to read depth distribution to avoid paralog contamination and low coverage regions. Each accession’s genotype is calculated using maximum likelihood estimation using reads with coverage between 4 and 30X. The genotype with the largest likelihood is assigned to each individual. SNPs with allele frequency > = 0.01 are used for downstream analysis. As tandem genes are often recently derived and share high sequence similarity, they can complicate short read alignment and introduce ‘false SNPs’ from paralogs. To address this, the coverage of genomic reads was examined for every tandem gene in the sorghum genome. The average coverage of the whole genome across the 27 genomes studied is about 553X. There were 31 tandem genes with more than twice the genome coverage , of which 7 have coverage more than 2500X . A total of 14 of the 31 high coverage tandem genes have SNPs called, and were removed from further analysis.To identify S. halepense SNPs, reads from S. halepense were aligned to the reference S. bicolor genome by BWA and SNPs determined with nucleotide groups for each reference S. bicolor genomic position by an in-house script. False positive S. halepense SNPs for each position of the reference S. bicolor genome were inferred and removed, based on three criteria: if the top two nucleotide groups are the same as reference S. bicolor and S. propinquum, respectively, there are no false positive SNPs; if read depth of an SNP is 1 , a false positive was inferred; if p-value calculated by the Fisher exact test for the actual and theoretical read depths , is less than 0.1, a false positive was inferred. The full SNP table with the reference S. bicolor, S. propinquum, and S. halepense SNPs as well as wild S. bicolor and S. timorense SNPs determined with total RNA and genomic DNA, respectively, against the reference S. bicolor genome, is provided .

Classifications of duplicated genes into paralogs versus homologs followed the S. bicolor reference genome .Arabidopsis GO-slim gene annotation was used for function enrichment analysis. GO-slim terms are assigned to sorghum genes based on sequence similarity inferred from best blastp hit. Binomial distribution based on the proportion of a GO-slim term among all annotated genes in the sorghum genome is used asthe null distribution. Test significance threshold is defined as p < 0.05, unless specified otherwise.Despite a presumed genetic bottleneck during polyploid formation, S. halepense is richly polymorphic. A survey of 182 genetically-mapped restriction fragment length polymorphism loci found 18 S. halepense or ‘Sorghum x almum’ genotypes to average 6.13 alleles per locus, versus 3.39 for a worldwide sample of 55 landrace and wild sorghum accessions and 1.9 for 16 F1 hybrid sorghums from eight commercial breeding programs . While some apparently novel alleles in the draft genome may reflect intraspecific polymorphism, a remarkable 67.1% of CDS polymorphisms differentiate S. halepense from representatives of both putative progenitor species and the outgroup S. timorense . The functional impact of these non-synonymous single-nucleotide polymorphisms was assessed by comparison to an evolutionary conservation profile of amino acids from orthologous genes in a panel of diverse plant species, calculating a ‘functional impact score’ using a modified entropy function – 8738 SNPs with high inferred functional impact score’ suggest important consequences for protein function in 5957 S. halepense genes . SNPs causing premature protein translation termination are most abundant, followed by loss of stop codons and loss of translation initiation site . These functionally important mutations are significantly enriched in plasma membrane genes with kinase activity, suggesting changes in environmental sensing and associated intracellular processes such as cell differentiation and metabolism .Rhizomes, subterranean stems that can comprise 70% of its dry weight , are a key link between morphology and ecology of S. halepense. Rhizome growth of polyploid S. halepense transgresses that of its rhizomatous diploid progenitor, S. propinquum. We conducted a field trial in Bogart, GA during 2012-3 of widely spaced tetraploid F2 progeny from a cross between S. bicolor BTx623 and S. halepense Gypsum 9E ; side by side with plots of 161 diploid recombinant inbred lines from a cross between BTx623 and S. propinquum . SbxSh progeny had a higher frequency of rhizome-derived shoots emerging from the soil , larger average number of rhizomes producing above-ground shoots , and greater distance of rhizome-derived shoots from the crown than SbxSp . Rhizome number showed heritabilities of 0.077 and 0.34 in SbxSh and 0.44 in SbxSp . Rhizomatousness is closely related to the ability of S. halepense to overwinter in the temperate United States. In the Bogart,GA field trial, 139 SbxSh progeny showed regrowth after overwintering, air racking while there was no survival of SbxSp in 2012-3 or in two additional years. Moreover, in SbxSh BC1F1- derived BC1F2 families grown in 3 m plots with two replications following conventional sorghum recommendations, those with rhizomes had significantly higher frequencies of survival than those lacking rhizomes . Survival in Salina, KS among replica plots of the same BC1F2 families was too low to evaluate statistically. More extensive rhizome growth than its rhizomatous diploid progenitor is also related to the ability of S. halepense to survive tropical dry seasons. From a total of 96 BC1F2 families selected for rhizome growth in Bogart GA, single 3 m rows were tested for 15 months at the ICRISAT research station in Samanko, Mali . A total of 45 families contained one or more plants that survived the dry season of 8 month duration with zero rainfall. A logistic regression model showed that for each 1 cm increase in rhizome spread from the crown based on Bogart GA trials, the probability of surviving the Malian dry season increased ∼3%. Factors other than rhizomes are also important to perenniality – lines surviving the tropical dry season were only randomly associated with those surviving the mild 2014-15 temperate winter in Bogart, GA , survivors of the harsh 2013-14 winter being more closely associated with dry season survival but too few in overall number to be conclusive .Curiously, rhizome growth is correlated negatively with that of other vegetative organs but positively with reproductive growth. Across four environments , early flowering is correlated with reduced above ground vegetative biomass , but increased rhizome growth in tetraploid SbxSh progeny. Because rhizomes are a vegetative organ, our a priori expectation was that increased vegetative biomass above ground would be correlated with increased rhizome growth. However, we measured rhizome growth primarily based on counting above ground shoots derived from rhizomes. In another rhizomatous grass , rhizome axillary buds experience apical dominance until anthesis, being suppressed by auxins . By excising S. halepense rhizomes from the plant, we found that axillary buds consistently develop as vertical shoots and not as rhizomes . So, once flowering of the primary stalk is initiated, a rhizomatous plant permits the development of additional ramets – which in principle should be able to exert apical dominance themselves. Moreover, our observation that these new buds invariably become ramets and not rhizomes raises questions about their additional dependence on a mobile ‘florigen’ such as that translocated to the plant apex . There may be much to be learned about nature of signaling among ramets at different developmental stages that are interconnected by rhizomes.While ∼80% of annotated sorghum genes are expressed in S. halepense rhizomes, many alleles with striking enrichment of expression more closely resemble the sequences of the non-rhizomatous S. bicolor progenitor than rhizomatous Sp. By laser capture microdissection, we collected meristems and compared transcripts from buds induced to develop as rhizomes or leafy shoots , respectively obtaining 163,264,254 and 152,162,240 Illumina Hiseq reads, of which 67.7% and 67.2% could be anchored to 27,566 and 27,183 sorghum gene models. About 1% of genes showed differential expression between rhizome buds and shoot buds . Appreciable recruitment of alleles from non-rhizomatous S. bicolor to rhizome-enriched expression is indicated by 44 S. bicolor versus only 23 S. propinquum derived transcripts with at least two SNPs supporting these origins and no contradictory SNPs . Consistent with rhizomes being ∼70% of the mass of a Johnsongrass plant , genes highly expressed in rhizome buds were enriched for diverse functions associated with rapid cell division and maturation. Cellulose synthase, Sb06g016760, was the most rhizome enriched gene, also implicated in rapid cell growth. Shoot-bud enriched genes were over-represented in three gene ontology categories associated with cell recognition , perhaps in preparation for new biotic interactions after emergence from the soil. The most shoot-enriched genes were glutathione S-transferase , catalyzing conjugation of the reduced form of glutathione to xenobiotic substrates for detoxification; a glycoside hydrolase , suggesting cell wall loosening during the rhizome-to-shoot transition; and a member of the major facilitator superfamily of transmembrane single-polypeptide secondary carriers implicated in control of sorghum seed size , a trait that shows strong negative correlation with both rhizome development and winter survival .

It is often presumed that activation is associated with a change in oligomerization state that imposes or induces proximity or conformational changes on the N-terminal signaling domain . However, knowledge of whether this occurs, and of ensuing steps in the process, is inadequate. There is a need for research on NLR mechanisms in multiple pathosystems. Although we cannot yet design new disease resistance genes, foundational knowledge has enabled some new recognition capacities to be created. For example, changing a protease recognition sequence in the PBS1 “guardee” protein enabled its guard, the RPS5 NLR protein, to recognize different protease effectors . Knowledge of which pathogen proteases are important players in plant-pathogen interactions will facilitate the development of multiple novel R genes. A major constraint on obtaining novel recognition abilities is the capacity to screen for R proteins that provide a useful phenotype without constitutive activation. If clones could be transiently delivered and tested for capacity to recognize specific effectors, for example with a defense promoter:luciferase reporter fusion, thousands of clones could be evaluated in a high-throughput manner. Synthetic biology and genome editing tools can also be used to develop rules for assembly and engineering of novel NLRs. Signaling from cell surface PRRs is slightly better understood than signaling from NLRs . We are, however, again not yet at the stage where PRRs can be designed with novel recognition capacities. As with NLRs, more detailed structural information is required before this will be possible. In the interim, pipp vertical racks identification of additional natural diversity in PRR recognition capacity would impact crop improvement. A promising approach is to screen diverse plants for novel PRR recognition capacities and to transfer useful corresponding receptors between taxa.

For example, species in the Brassicaceae can detect the apoplastic bacterial translation factor EF-Tu via the RLK EFR, but Solanaceous species cannot; transfer of EFR to species in the Solanaceae elevates resistance to several bacterial diseases . There is an urgent need to discover novel PRR ligands from a broad spectrum of pathogens/pests, including nematodes and aphids . PRR ligands will be useful for direct identification of new PRRs, screening for natural variation in strongly responding PRRs, and engineering new PRRs. Prospecting for novel recognition capabilities should involve biochemical exploration of pathogen components that trigger defense responses, searching for natural or induced genetic variation in such recognition capacity, cloning the corresponding receptor, and inter-generic transfer. Sequence capture targeted to RLKs and RLPs could enhance the efficiency of identification of novel PRR genes. Development of methods to engineer effector-insensitivity into PRR response pathways that are disrupted by pathogen effectors is an additional opportunity.In addition to canonical plant immune receptors such as NLRs and PRRs, genes encoding other types of resistance are important for adding diversity and potential durability to resistance. One source of useful genes will be quantitative disease resistance loci. QDR determine host resistance that results in a reduction, but not complete absence of disease. QDR can be controlled by quantitative variation in NLR or PRR activation or by completely different mechanisms . QDR is frequently controlled by multiple quantitative trait loci that interact with each other and are influenced by the environment . Some QTL may encode modifiers that enhance immunity; others may encode genes that are not components of the immune system. Emerging opportunities for engineering enhanced resistance includes a better understanding of the mechanisms underlying QDR, including the role of chloroplasts and other organelles in plant defense. Genes have been identified that confer partial resistance to multiple diseases, including several rust species, and even to broad ranges of pathogens .

Pyramiding multiple QDR loci, either through marker-assisted breeding or the 8 / Molecular Plant-Microbe Interactions application of genomic selection, can provide broad spectrum resistance; for example, four QDR loci, each controlling a different aspect of resistance to the blast fungus, have been pyramided in rice . Natural variability at QDR loci can be identified using classical genetic approaches, pathogen phenotyping, and analyzing molecular markers of defense. Characterization of QDR loci can determine at which step during infection resistance is acting and if weak activation of classical defense signaling is induced. Transfer of existing, evolutionarily unique resistance mechanisms to other plant species is likely to be feasible in many instances. Pyramiding multiple sources of QDR with canonical immune receptor loci is a desirable strategy to achieve durable resistance. There is great interest in the identification of plant susceptibility genes that facilitate pathogen development and their manipulation for durable disease control . S genes that act during different stages of infection and against different pathogens and insects have been identified . Recent advances in genome editing technologies greatly enhance our capacity to manipulate multiple S genes in crops. This approach is exemplified by S genes that control viral replication and translation in their hosts. Potyviruses require the host translation initiation complex including the cap-binding protein eIF4E . Natural variants in eIF4E and eIF4E have been identified in multiple plant species that abolish susceptibility to potyviruses . Importantly, plants possess more than one initiation factor complex isoform; isoforms seem to function redundantly and mutation of one isoform does not affect plant vigor . A natural knockout of eIF4E in Brassica resulted in broad-spectrum potyvirus resistance . CRISPR/Cas9-mediated mutations of eIF4E have been shown to be a viable strategy for engineering resistance to multiple potyviruses in cucumber . Similarly, knockout of eIF4E in tomato provided resistance to two potyviruses; however, plants remained susceptible to other potyvirus strains , indicating further research is needed to understand potyvirus-eIF4E/eIF4E interactions to inform exploitation and development of durable resistance.

However, these pathosystems illustrate the potential of S loci as sources of resistance. The identification of effector targets also provides opportunities for detection and targeting of new plant S genes. Multiple Xanthomonas transcription activator-like effectors enhance the expression of genes encoding SWEET sugar transporters, which are attractive targets for genome editing . The wild type MLO gene in barley suppresses defenses against powdery mildew disease and is conserved across the plant kingdom. Natural and induced loss-of-function mlo alleles have been generated in multiple species using a variety of approaches including radiation and genome editing . However, mutation of MLO can have deleterious physiological consequences requiring analysis over multiple environments and possibly introgression into an appropriate genetic background . Pathogen lifestyle should also be taken into account when targeting S genes and stacking different resistance genes. An R gene against a biotrophic pathogen can function as an S gene during infection by necrotrophic pathogen . Enhancing the foundational understanding of QDR and S genes provides an opportunity to expand our understanding of the mechanisms controlling both resistance and susceptibility. This information can then be translated into effective disease control strategies, especially with the advent of genome editing.Small RNAs are central players of RNA silencing, which is a universal and fundamental mechanism of gene regulation in eukaryotes. Extensive studies have established small RNAs as essential regulators of growth and development; moreover, accumulating evidence implicates small RNAs as having an integral role during plant-pathogen interactions that influences the outcome of pathogen challenge . Specific plant and pathogen small RNAs are activated during infection and there is bi-directional trafficking of silencing RNAs between multiple filamentous pathogens and their hosts . The importance of host small RNA pathways in plant defenses is evidenced by the multiplicity of effectors produced by viral, bacterial and oomycete pathogens that target host RNA silencing pathways . Our understanding of the involvement of small RNAs in pathogen/pest interactions is far from complete; for example, additional foundational studies are needed to address the regulation of immune-related host genes via endogenous microRNAs and small interfering RNAs or other silencing pathways, with potential implications in epigenetics . There is also an urgent need to understand the mechanisms by which small RNAs are transferred from pathogens/pests to host cells and vice versa. As our understanding of small RNA function and evolution advances, the number of novel opportunities to deploy this knowledge to safeguard plant health will increase. Pathogen suppression of host silencing pathways may be mitigated to maintain or enhance endogenous resistance. Host-induced gene silencing and RNA interference are being demonstrated in an increasing number of biotrophic, hemibiotrophic, and necrotrophic interactions . The efficacy of these approaches should be tested in numerous pathosystems, pipp drying racks particularly against insects, pests, and parasitic weeds for which there are currently few alternative control measures. Constitutive ectopic expression of small RNAs can profoundly affect endogenous small RNA profiles with potentially deleterious consequences; research is needed to fine tune approaches such as HIGS. Research is also needed to determine if exogenous application of small RNAs is an efficacious approach to pathogen control and if so, what is the most effective way to deliver small RNAs exogenously. Because HIGS and RNAi can be targeted against vital pathogen/pest processes, they are anticipated to be durable; however, research is necessary to investigate the potential of pathogens and pests to counteract control strategies based on small RNA-centric approaches and to identify optimal targets to reduce the chances of evolution of resistance.

Multiple technological advances can facilitate a greater foundational understanding of small RNAs as well as aid in the deployment of translational approaches to utilize small RNAs for crop improvement. High-resolution imaging will enable investigations of transfer and localization of RNAs, both in vitro and in vivo, at tissue and subcellular levels, throughout the dynamic process of infection. Similarly, sequencing and quantification of small RNA, mRNAs, and small RNA targets in single cells will allow informative dissection of small RNA biology in plant-pathogen/pest interactions. Continued increases in genome sequences of both crops, models, and their pathogens, coupled with detailed molecular and biochemical experiments, will enable studies of the diversity of mechanisms by which plants and pathogens deploy and manipulate small RNA pathways to enhance resistance or avoid disease.These compounds can collectively be considered metabolite immuno modulators. Their characterization could lead to breeding or engineering efforts to enhance plant health; also, some modulators may be useful for direct application to plants either as sprays or soil additives. Both beneficial and pathogenic microbes and pests also produce chemical-based effectors/toxins that might be exploited. Examples of activities of potentially useful metabolites include direct antimicrobials/antipests , signaling intermediates and pathway modulators , secreted compounds that can impact the phyllosphere or rhizosphere microbiomes , and pest/microbe chemical effectors that modulate plant behavior and resistance . To successfully exploit chemical immunomodulators, we need to define the chemical repertoires of plants and interacting organisms under diverse conditions, infer processes impacted by diverse sets of metabolic outputs, identify biosynthetic and regulatory mechanisms, and identify targets and modes of action. Furthermore, plants have diverse chemistries, some of which are family- or species-specific. Therefore, screening broad taxonomic groups is warranted. This will require collaborations with analytical chemists for natural products analysis and synthesis for proof of concept and/or deployment. A finer understanding of the roles of these metabolites will be gained when single cell metabolic analyses are feasible in order to dissect their roles in space and time during the infection process. An important goal will be to identify pathways for synthesis and action using biochemical genetic screens, metabolite-based genetic mapping, and expression based analyses; however, to fully realize the opportunities for identifying metabolites with potential value as control agents, additional assays may need to be developed. Opportunities also exist to generate novel compounds through using combinations of biosynthetic enzymes that may not occur naturally together . 10 / Molecular Plant-Microbe InteractionsAt present, comprehensive metabolite analysis is not routine, especially when mixtures are complex, chemical libraries are limited, and there are many unknown compounds. Investments in national/international repositories for plant/microbe/pest metabolite identification and analysis are needed. Several approaches can be used and combined to identify immunomodulating chemicals. These include exploiting differing chemistries among diverse genetic backgrounds and mutant collections, informaticsled searches for novel predicted enzymes and activities, and bio-assay-based approaches for discovery of new activities . As the sensitivity of instruments for chemical analysis improves and chemical libraries expand, it will become increasingly feasible to survey root exudates, vascular exudates, apoplastic extracts, plant-pathogen interface sampling, secreted molecules from microbes and pests to identify high value metabolites. As new activities and compounds are inferred, partitioning can be used to reduce the complexity of metabolite extracts. For this, it will be important to utilize multiple and complementary methods of extraction, derivatization, separations, and analysis.

Grower interviews. In 2006, late rains prevented many growers from normal spring tillage operations and a few growers were faced with the option of no spring tillage, and planting late or not planting at all. In winter 2007, we did phone interviews with three growers who did not use spring tillage in 2006 — as many as we could find. The purpose was to compare results from our relatively small experimental plots with what growers found at the field scale. Growers were asked to compare their minimum-till field with an adjacent conventional field, and to answer questions about productivity, tillage practices, and weed and fertilizer management. Growers were also asked how they would improve the minimum-till system and if they thought it was economical.Similar rice yields. The highest yield was more than 9,300 pounds per acre in 2004, and the lowest was about 7,300 pounds per acre in 2005 . These annual yield fluctuations are in line with countywide fluctuations in California and reflect climate variation. Better weed control. The minimumtill treatment was extremely effective in depleting weed populations from the upper soil layer and markedly diminishing weed emergence with the crop . When this practice was used, little weed control was needed after the glyphosate application. In fact, no additional herbicides were needed in 2004. The most important rice weed in these systems during the study period was small flower umbrella sedge . On average for the 3 years, rolling grow table the minimum-till treatment suppressed small flower umbrella sedge populations by 94%. Infestations by the aquatic rice field bulrush also became relevant in 2006, and were 91% suppressed under the minimum-till treatment . Water-seeding rice strongly suppressed both barnyardgrass , the main Echinochloa species in this field , and sprangletop .

However, Echinochloa spp. populations became somewhat higher in the last year of the experiment, and the minimum-till treatment also exhibited potential for suppressing this weed. Success with the stale seedbed technique depends on keeping the seedbed moist or highly saturated, depending on if aquatic weeds are present, and allowing sufficient time for weeds to emerge prior to the glyphosate application. In 2006, there was neither sufficient seedbed moisture nor sufficient time for substantial weed emergence. Consequently, few weeds were present when the glyphosate was applied. Even so, the minimum-till treatment was successful in controlling weeds, suggesting that leaving the soil undis-turbed in the spring helped discourage weed emergence. While the stale seedbed technique worked well when enough weeds had emerged prior to the glyphosate application, the late-emerging aquatic weeds ducksalad and redstem/redberry were not well suppressed ; in fact, ducksalad became an increasing problem over time in the minimum-till treatment.There were no differences in rice water weevil levels between the conventional- and the minimum-till treatments in a given year, although there was a trend toward more weevils with minimum tillage. The weevils were present at low levels in all plots in 2005 and 2006. The incidence of adult feeding scars was higher in 2005 than 2006, with 15% and 7% of plants scarred, respectively. Likewise, larval densities, which peaked at 0.2 per sample in 2006, did not differ between the two treatments in any given year.When no nitrogen fertilizer was applied, the minimum-till treatment had smaller yields than conventional tillage . This is probably because minimum tillage had two flooding events while conventional tillage had only one. When soil is flooded and then drained, nitrate accumulates during the aerobic period but may be subsequently lost through denitrification during the following anaerobic period . In response to added fertilizer, the results varied between years but suggested that minimum tillage requires more nitrogen than conventional tillage to reach similar yields.

In 2004, the minimum-till treatment required three times as much nitrogen as the conventional-till treatment to achieve optimal yields . In contrast, in 2006 similar nitrogen rates in the two till systems resulted in similar yields. Splitting the nitrogen fertilizer dose has previously been shown to increase its use efficiency . However, that was not the case in the nitrogen fertility trial portion of this study. Splitting the 150 pounds of nitrogen per acre in 2004 did not affect yields. This may be because this nitrogen rate exceeded that required for optimal yields, masking any increases in use efficiency. Splitting the 100 pounds of nitrogen per acre equally in 2006 actually resulted in lower yields than a single application of this rate at planting. However, it is possible that higher yields would have resulted from an unequal split, such as 75 pounds of nitrogen per acre at planting and 25 pounds per acre 40 to 50 days after planting. The nitrogen fertility experiments were not conclusive, and further research is warranted. However, some general conclusions can be drawn based on our results. First, the additional flush of water in the minimum-till system will likely result in the loss of native soil nitrogen. Second, nitrogen fertilizer in the minimum-till system is applied to the soil surface, where it is used less efficiently . Both of these factors suggest that the minimum-till system will require a higher nitrogen rate to maintain yield levels. While we can not determine a precise rate from our data, it appears that minimum tillage requires approximately 50 pounds of nitrogen per acre more than conventional tillage. This is based on the 2004 response and the fact that in both years the zero nitrogen yields were lower in the minimum-till treatment, which suggests a loss of native soil nitrogen.Three growers were interviewed who established rice using water seeded practices in 2006 onto fields where there had been no spring tillage . In all cases, the growers incorporated rice straw or stubble in fall 2005 either by disking or wet rolling. Winter flooding varied between the fields but due to a wet winter, all were flooded for at least a portion of the winter. Growers 1 and 2 used a modified stale seedbed in which late spring rains germinated weed seeds and glyphosate was used to kill the weeds before flooding the field to plant.

Grower 3 aerially broadcast rice seed into water from the winter flood period and drained the field shortly after planting. In all cases, nitrogen was applied aerially in three to four applications. Total nitrogen was comparable to what each grower normally applied and ranged from 140 to 210 pounds per acre. One issue raised by the growers was fertilizer management, specifically how and when to apply nitrogen and phosphorus. Results from the on-station study suggest that only one or two nitrogen fertilizer applications are necessary. Also, phosphorus should be applied in the fall and incorporated because surface phosphorus applications may result in an algae problem, which grower 2 experienced. Despite the late spring rains, all three growers were able to plant early, before May 3 . These were the first planted fields in their respective areas, and as a result, growers reported some rice seed predation by ducks. While two of the three growers used slightly higher seeding rates than the recommended 150 pounds per acre, data from the on-station experiment suggests that this may not be necessary. Two of the three growers reported that yields from their minimum-till fields were comparable to or better than their other fields. However, vertical grow system grower 3 reported that yields were about 600 pounds less per acre. These lower yields may have been due to phosphorus deficiency since none had been applied, although this grower typically did apply phosphorus fertilizer. A second possibility for this lower yield is that rather than draining the field following the winter flood, grower 3 retained winter flood water until after planting, which may have lowered soil oxygen levels and resulted in poor crop establishment. The predominant weed species found in the minimum-till fields were similar to those typically found by these growers , and the severity of the weed problem was similar to or less than normal. The two growers using a stale seedbed reported that the rains germinated weeds, which they were able to kill with glyphosate. All growers reported that either lower rates of herbicides, fewer applications or a different program was used on their minimumtill fields. On-station research showed that the stale seedbed system was able to control much of the weed problem . However, research is needed to better understand how long soils should remain moist or flooded and what temperatures are required to germinate specific weed seeds.All three growers interviewed reported that the economic benefits of minimum tillage were similar to or better than their conventional-tillage practice, and some said they might try it again. The main reason was that minimum tillage resulted in six to eight fewer tractor passes, which amounts to a fuel and labor savings of $120 per acre . However, some of these savings were offset by the additional air passes required to apply glyphosate and fertilizer. Based on research from the on-station experiment, growers could apply fertilizer once or twice instead of the three to four times that they reported. Growers also indicated that if they were planning on no spring tillage, they would do more tillage in the fall, which would further offset the economic benefits. In addition to possible economic benefits, one major benefit was that growers were able to plant early despite late rains. One drawback of the minimum-till system is the increased amount of nitrogen required to maintain yields. Since nitrogen must be applied on the surface, it is more susceptible to denitrification losses. This can have the effect of reducing the economy of these systems and increasing emissions of nitrous oxide, a greenhouse gas.In both on-station research and grower fields, the minimum-tillage system maintained rice yields in the absence of spring tillage. Where does minimum tillage fit in to a grower’s overall farm-management strategy? First, minimum tillage can be useful when late spring rains prevent early planting under conventional tillage practices, as in 2006. Second, growers could employ minimum tillage to plant fields early. In such cases, additional tillage and phosphorus and potassium applications would be recommended in the fall. Finally, minimum tillage can be used to control herbicide-resistant weeds by germinating weeds and subsequently killing them with glyphosate, an herbicide to which California’s rice weeds are not yet resistant. Soil moisture must be carefully monitored and controlled because weed species require varying wet periods and temperatures for germination; this is an area of ongoing research. While glyphosate can currently control all types of California rice weeds that are resistant to other herbicides, glyphosateresistant weed biotypes have evolved in areas of California where this herbicide has been used for many years . Therefore, glyphosate should be alternated with other herbicides, such as paraquat and glufosinate-ammonium, that are also lethal to herbicide-resistant rice weeds .

Within each quadrat, we determined the identity and percent cover of all species present. We also recorded the percent cover of bare ground, water, and thatch . In addition, we estimated the number and percent cover of germinating seedlings for native species. Because lowgrowing graminoids and forbs were often overlaid by taller species, the total percent cover could exceed 100% in each quadrat. To measure the pool area, we used a Trimble GPS to map out the perimeters of each pool. We used a laser level to measure the depth of each pool. We obtained climate data from the National Oceanic and Atmospheric Administration Daily Summaries dataset for the Santa Barbara Municipal Airport weather station to calculate the average annual rainfall each pool experienced after it was restored .The 69 pools surveyed in this study were restored between 1986 and 2017. The pools all shared similar attributes in terms of past and restored abiotic and biotic conditions, so we constructed a chronosequence that used a space-for-time substitution to examine the effect of time since restoration on native and exotic cover and richness. Past restoration actions included grading and berm enhancement to attain basin topography with an area ranging from 66 to 1,367 m2 and a maximum depth ranging from 53.5 to 80 cm, planting of locally-sourced native plant species via seeding and transplanting, and hand-weeding and herbicide treatments of exotic species during a 2- to 5-year implementation phase . In the spring of 2019, we conducted vegetation surveys in each pool when the majority of the native species were at peak biomass. For each pool, we laid out 2 transects bisecting the pool along its elliptical major and minor axes . Every other meter along each transect, grow room we laid down a 1 m2 quadrat with 1% subdivisions. We identified every plant species present and estimated its percent cover in each quadrat. We also estimated the percent cover of bare ground and thatch. Because low growing graminoids and forbs were overlaid with taller species, the total percent cover could exceed 100% in each quadrat.

We also categorized each quadrat as being in the central, transition, or upland zone of the pool. To measure relative elevation, we used a laser level to calculate the elevation of each quadrat above the deepest point of the pool. To determine pool hydroperiod, we installed 0.8 m rulers in the deepest part of each pool in January 2019 and recorded the depth of the water in each pool every week beginning 11 January until all the pools dried up by 5 July. To measure the site and pool area, we used a Trimble GPS to map out the perimeters of the sites and the pools. We also used these data to calculate each pool’s perimeter-to-area ratio and the distance of each pool from the edge of the restoration site. We obtained climate data from the National Oceanic and Atmospheric Administration Daily Summaries dataset for the Santa Barbara Municipal Airport weather station to calculate the precipitation each pool experienced the year before restoration began, the precipitation each pool experienced the year that restoration began, the precipitation each pool experienced the year after restoration began, and the average annual precipitation each pool experienced after restoration began .For each quadrat in each sampling year, we calculated the maximum monthly exotic plant species percent cover, total exotic plant species richness, maximum monthly native plant species percent cover, and total native plant species richness. The exotic species cover distribution was skewed right as determined by histogram and Q–Q plot analyses, so we used raw data to construct a generalized linear mixed effects model with a gamma distribution, using a logarithmic link function. The exotic species richness and native species richness distributions were not normally distributed as determined by histogram and Q–Q plot analyses, so we used raw data to construct a generalized linear mixed effects model with a Poisson distribution. The native species cover distribution was normally distributed according to histogram and Q–Q plot analyses, so we used raw data to construct a linear mixed effects model.

All four models were predicted by the age of the pool during each sampling year and the zone , and the interaction thereof, as fixed effects, with sampling year, quadrat name , pool depth , pool area , and average annual precipitation included as random effects.The increase in exotic cover and richness in our multiyear monitoring study suggests that short-term restoration efforts do not guarantee long-term success in the transition and upland zones of restored pools. The pools in this study were created and planted with native species within a grassland landscape. Intensive exotic species weeding continued for about 2–5 years after each pool was created, but then the pools entered the maintenance phase and were only periodically hand-weeded or cleared with a weed-whacker. Although the initial intensive weeding kept exotic cover low, exotic cover increased in the transition and upland zones over time. This suggests that the initial weeding successfully reduced exotic species, which is why exoticcover remained low for several years after the implementation phase. However, without continual removal, recruitment from exotic populations adjacent to the restored pools allowed for eventual recolonization of the site. Previous studies have shown that restored native populations can subsequently decline and even go extinct due to low growth rates that are negatively affected by interannual environmental variability and competition by invasive species . Indeed, other long-term monitoring studies in other ecosystems, such as grasslands and forests, have also shown that restored plant communities never reach the species diversity of natural reference ecosystems . Our study adds to a growing body of evidence that short-term restoration projects do not guarantee the long-term persistence of diverse native assemblages. Our results indicated that exotic plants invaded pool transition and upland zones, but not central zones, suggesting that invasion into the pool edges comes from the surrounding invaded grassland matrix. Invasive exotic species are often unsuccessful in the central zones because of their inability to tolerate prolonged inundation . However, increased drought due to climate change may result in drier conditions even in the deepest parts of pools, perhaps making the zone less hospitable for vernal pool specialists and more susceptible to natural recruitment by invasive species .

Although restoration efforts may plant and establish native populations within a vernal pool, the surrounding landscape often consists of unrestored grassland invaded by exotic grasses, which may contribute many propagules to pool edges. In addition, once propagules establish in the pool, positive feedbacks such as litter build-up can cause exotic populations to invade and persist . These edge effects are common throughout restored ecosystems . Small-scale restoration projects, which typically occur amidst fragmented habitat in the form of patches, can be susceptible to edge effects due to stressful environmental conditions and disturbances originating outside of the habitat patch . For example reinvasion of Phragmites australis from the surrounding landscape into wetlands is common, as is the encroachment of trees from forests into adjacent meadows . Several studies have shown that exotic species abundance increases closer to forest edges, where disturbance and exotic propagule supply is high . It is, therefore, critical to evaluate and manage edges of restoration projects as they face unique pressures that can jeopardize native assemblages.Our results highlight the importance of both sustained inundation of central zones and active management of transition and upland zones of vernal pools to reduce invasion. Collinge et al. have similarly emphasized the role of both abiotic and biotic filters in creating and sustaining restored native communities that are resistant to exotic invasion . Biotic filters that can decrease susceptibility to reinvasion include adaptive management strategies, such as planting with competitive native species and active control of exotic competitors through an array of long-term weed management techniques . In vernal pools, drying cannabis strategically planting suites of species at different elevation zones within pools can also increase native establishment and persistence. For example, in our studies, E. macrostachya, J. mexicanus, and J. phaeocephalus were able to dominate the central zone, while Carex praegracilis, E. macrostachya, Distichlis spicata, J. mexicanus, and E. triticoides performed well in the transition zone, and Stipa pulchra, Cyperus eragrostis, and Hordeum brachyantherum were able to establish and persist in the upland zone despite exotic invasion, so these species can be the foci of zonal planting palettes for future local restoration projects. Although intensive hand-weeding did not create resistance in the edges of the pools and may not be sustainable in the long run due to time and resource constraints, feasible long-term weeding strategies may focus more on large-scale contexts. For example, the upland and surrounding unrestored grassland matrix probably accounted for the exotic invasion of the transition and upland zones of the pools, so large-scale grassland management techniques such as grazing and prescribed fire disturbance may reduce exotic species dominance in both the grassland and the edges of the vernal pools . Even periodic reductions of exotic species could help to sustain greater native abundance in the edge zones. Overall, our studies evaluating the trajectories of plant assemblages post-implementation suggest that active management of restored habitats should persist beyond the implementation phase, which means projects need to be budgeted with long-term monitoring and adaptive management plans. Although 5 years of intensive restoration efforts can successfully reestablish native assemblages, our studies showed that native cover and richness decreased significantly in older pools. Other studies of restored wetlands similarly showed that restored wetlands initially achieving high native plant diversity can subsequently experience a decline in native diversity and an increase in exotic diversity 5–11 years post-implementation . Our long-term monitoring dataset provides unique insight into plant community trajectories over time by showing that, even when central zones of restored vernal pools can remain native-dominated, the drier pool edges exposed to the surrounding exotic grassland matrix can experience reinvasion over time, much like how forest edges and other edge habitats can experience reinvasion when not actively managed . Short-term success can be misleading, and long-term monitoring is important to evaluate the success of restoration and guide adaptive management over time. Identifying drivers of reinvasion can be particularly useful for guiding adaptive management. In our study, the main abiotic variables that correlated with increased exotic diversity and/or decreased native diversity were the amount of edge area, relative elevation, and precipitation. For example, less precipitation during restoration implementation can correlate with higher exotic richness, although a wet year before restoration may promote higher exotic cover and lower native cover in the upland zone, perhaps due to competition from exotics taking advantage of higher winter water resources . Although the precipitation that a restoration site experiences cannot be manipulated, knowing whether it is a particularly wet or dry year at a restoration site can inform management decisions, e.g., resources should be allocated to weeding exotic species out of pool edges during wet years. In addition, the invasion front of vernal pools may be reduced by creating circular pools with less edge area exposed to the surrounding exotic grassland matrix and associated edge effects. Because surrounding invasive grassland populations contribute propagules that invade pool edges, restoration efforts can also prioritize creating or restoring vernal pools in smaller grassland sites with fewer invasive species. For example, vernal pools may be constructed in smaller green spaces within urban areas that are traditionally deemed too small for other habitat restoration projects. However, manipulation of these abiotic environmental variables alone cannot be relied upon to maintain high native cover and low exotic cover, especially in the higher-elevation transition and upland zones that are more hospitable to generalist species. These edge zones experienced an increase in exotic diversity and/or a decrease in native diversity over time, possibly due to the overwhelming propagule pressure from the surrounding unrestored grassland. These propagules likely take advantage of the higher-elevation edge zones of the vernal pools that, when not seeded with native species, provide hospitable open niche space for generalist grasses and forbs to inhabit . Other studies have shown that abiotic manipulation can lead to incomplete restoration, especially in hospitable environments that are easily colonized by exotic species . Sengl et al. showed that retired farmland passively restored to grassland did not achieve the same native species richness as reference sites and were instead colonized by invasive grasses.