Due to small numbers in each category, organic, natural, NHTC and/or ASV status were combined to represent how management specific to a target consumer may influence AMR patterns overall. Pasture-based forage is common in California, with livestock grazing being California’s most extensive land use , but details on dryland versus irrigated pasture for beef cow-calf herds have not been reported. The types of diseases most treated with antimicrobials reported in our survey, namely pinkeye, respiratory disease, foot rot and scours, concur with prior data reported in a large survey on antimicrobial use on California cow-calf operations . Use of antimicrobials in feed is an uncommon practice in cow-calf herds and mastitis is not nearly as common in beef as in dairy production systems, so it is not surprising that these practices were not common amongst the farms surveyed. In addition, in California, veterinary oversight is required for the purchase and use of all medically important antimicrobials, which may explain the high percentage of farms that reported having a veterinarian-client-patient relationship . Of the E. coli isolates, approximately 36% were resistant or non-susceptible to at least one antimicrobial, excluding ampicillin, to which all isolates were resistant. AMR of E. coli in cattle or ruminants to various antimicrobials has been observed by other authors to varying degrees, but it is not always clear how resistant status is established. For example, vertical cannabis one study from Malaysia found 61.9% of E. coli isolated from diseased ruminants to be resistant to trimethoprim sulfamethoxazole compared to 4.9% in our study, 69% resistant totetracycline compared to 13.1% non-susceptible in our study, 54.1% resistant to amoxicillin, compared to 100% resistant to ampicillin in our study .

Discrepancies may be due to the choice of breakpoint to establish resistant status, meaning that a breakpoint can be chosen based on the species or it can be chosen based on the most similar bacteria for which there is an established breakpoint, both of which are routine practices and depend on the context of the study. Variations in results can also stem from the fact that diseased animals are more likely to have been treated with antimicrobials before isolation of the pathogen or because antimicrobial drug use patterns may vary between countries or regions. Ampicillin had the highest proportion of resistant isolates of E. coli , which was surprising, especially since none of the participating ranches reported any ampicillin use. In this study, a breakpoint of ≥0.25 μg/mL indicating resistance was chosen based on the veterinary literature for ampicillin resistance for treatment of metritis in cattle due to E. coli from VET CLSI. By contrast, the human breakpoint is ≥32 μg/mL indicating resistance. The most common MIC for ampicillin in this study was 4 μg/mL . The lowest prevalence of resistance or non-susceptibility for E. coli of all included antimicrobials was for ceftiofur , which was also only used by one of the enrolled farms. Restrictions were placed on extra-label cephalosporin use by the Food and Drug Administration in 2012 which aimed to decrease their use in livestock . The ampicillin breakpoint used in this study for Enterococcus was ≥16μg/mL indicating resistance. Although dramatically different from the breakpoint for E. coli, this human breakpoint was selected due to available data and differences between antibacterial spectrum and bacterium type. As no veterinary breakpoint is available for this bacterium/antimicrobial combination, the human breakpoint wasselected as outlined in the methods, resulting in only 1 resistant Enterococcus isolate to ampicillin. Second to ampicillin, the most common drugs for which E. coli was resistant or non-susceptible were sulfadimethoxine and trimethoprim-sulfamethoxazole.

A 2016 study of AMR in beef cattle found no associations between the prevalence of resistance of E. coli isolates to tetracycline, third generation cephalosporin, or trimethoprim-sulfamethoxazole and history of antimicrobial treatment with either ceftiofur or other antimicrobials . The authors conclude that mixing of treated and non-treated cattle may mask the effect of treatment or that animal-level effects due to treatment are short-lived. However, both ceftiofur and sulfa treatments were uncommon in our study population so that neither hypothesis would explain the prevalence of AMR to this class of antimicrobial observed. Florfenicol is a relatively new antimicrobial and limited published, peer-reviewed data exist on resistance profiles. It was first approved for use in cattle in 1998 . In this study, 2 animals had a history of being treated with florfenicol and 9 farms indicated that they use it on farm. For E. coli, there were 47 non-susceptible isolates to florfenicol, which was the drug with the third highest AMR prevalence, behind ampicillin and sulfadimethoxine. Reports of increasing AMR to florfenicol in Enterobacteriaceae exist in the literature. In addition to antibiotic use, mobile genetic elements and horizontal gene transfer are speculated to play a role in the replication of AMR genes resulting in the observed trend of AMR to florfenicol . Future research should also investigate genetic elements linked with phenotypic resistance to AMR to florfenicol in enteric bacteria from cow-calf operations to increase understanding of potential factors resulting in higher prevalence of AMR to this drug. Historically, bacterial resistance to tetracycline has had a high prevalence . In the present study, E. coli and Enterococcus isolates had a similar, relatively low proportion of isolates resistant to tetracycline, but Enterococcus isolates showed the highest proportion of non-susceptibility to this drug. No biologically relevant survey variables regarding farm description, animal management, or herd level antimicrobial use were significantly associated with AMR in our models while accounting for correlation between isolates from the same animal. Additionally, controlling for correlation between isolates from the same farm led to unstable models with non-positive G matrices indicating a lack of variation in the additional random effect. However, given the high prevalence of AMR at one of the farms, there may be exposures at farm or animal level associated with AMR that were not captured by this survey.

Calves have been shown to carry more AMR bacteria than cows in previous studies , however calves in two of those studies were less than 4weeks old. In contrast, calves in our study were up to one year old, and the bacterial AMR profile in neonates may differ from that of older calves. In dairy calves, antimicrobials may be used more often to treat and prevent disease, but in beef calves, the link is less clear. One hypothesis to explain AMR bacteria shed from calves is that AMR is acquired through other routes, such as genetic linkage or direct transfer from cows and may not be associated with antimicrobial use on farm. Another study found the frequency of water trough cleaning and size of operation were significantly associated with AMR prevalence . Although water trough cleaning was not significantly associated with AMR in our study, MFA analysis showed both water trough cleaning and whether or not farms used bleach to clean water troughs to be two of the variables contributing most to data variability. Other factors that have been found to be statistically significantly linked to AMR in other studies but were not explored in this study include spring versus fall born calves and proximity to dairy farms . None of the farms in the present study were within one mile of a dairy farm and spring versus fall calves was not examined. Antimicrobial use on farm has been suggested as a contributing factor for the development of AMR, but several studies have indicated that resistance is multifactorial and develops regardless of exposure or use of particular antimicrobials on farm , findings that may be substantiated by the results of this study. In addition, there is evidence that some AMR genes may be co-selected or have genetic linkages , in which resistance to one antimicrobial is genetically linked to resistance to a different antimicrobial and transferred either vertically or horizontally together . Alternatively, antimicrobial use in the cow-calf sector may not exert high enough selective pressures on bacterial populations to drive AMR. Multiple factor analysis showed that herd information and nutrition related factors accounted for approximately 52% of the total variance in the data. Several studies have shown herd health in farming systems, herd management,bio-security, population density, weed curing and external pressures to be linked to antimicrobial use . Previous studies reported an association between farm management factors and the prevalence of AMR in E. coli isolates . Markland et al. found that regular cleaning of water troughs and the addition of ionophores to feed were associated with a reduction in prevalence of cefotaxime resistant bacteria in fecal samples of beef cattle on grazing farms in Florida. Beef cattle require several minerals for optimal growth, health, and reproduction. Mineral deficiency may result in anemia, depressed immunity and increased opportunity for bacterial growth and dissemination of resistant bacteria . On the other hand, elevated heavy metal supplementation may co-select for antimicrobial resistance of fecal E. coli and Enterococcus spp. . A recent scientific report showed that synthetic smectite clay minerals and Fe-sulfide microspheres have antimicrobial properties and kill antibiotic resistant bacteria including E. coli and Enterococcus spp. but we did not inquire about the use of these products.

In addition, MFA in this study showed that farm level antimicrobial use, disease treatment, and antimicrobial dosing and record keeping practices accounted for 46% of the total variability in the study data. Similarly, a survey study of antimicrobial use in adult cows on California dairies found that antimicrobial stewardship practices, antimicrobial usage information, and producer perceptions of AMR on dairies accounted for 32.3% of the total variability in the survey data. On the other hand, the sampled animals’ life stage and antimicrobial treatment history and in particular the antimicrobial resistance data contributed to a lesser degree to data variability. Given that AMR seemed less variable than other factors describing the animals and farms in the data set, it is not surprising that statistical models were unable to find associations between AMR and animal or farm related factors. Overall, the MFA analysis identified important differences between herds that can be considered in studies that investigate the risk and the associations between farm practices and AMR of fecal bacteria. Cluster analysis identified some potential regional differences in management practices and antimicrobial use information among cow-calf operations in northern California since the Coastal Range was only represented by two clusters. The cause of the differences could be due to variable access to information or rancher education or due to the influence of veterinarians in the Coastal Range. One limitation for this study includes the use of a convenience sample of farms that could have introduced bias because the group of farms that are associated with the University of California teaching hospital or extension agents may have similar management tendencies. They could represent farms that have more progressive management, are more attentive to animal health and/or more willing to treat or may be more likely to adhere to legislation regarding antimicrobial use and antimicrobial stewardship. This is a significant factor to consider and, if true, could have biased the study either toward the null because of less antimicrobial use overall or away from the null because these producers may be more likely to watch carefully, identify, and treat any disease conditions that warrant antimicrobials. In addition to selection of farms, selection of animals for sampling was not random, as sampling is logistically challenging in a cow-calf setting. The animals sampled were either being put through the chute for another reason , were physically closest to the chute, or were the easiest animals to collect for sampling . Some other challenges associated with sampling in this system include limited animal identification, treatment records, and animal restraint. Many of the animal health records were based on the farmer’s recollection and therefore are subject to recall bias. In this case, those that were identified as treated were very likely actually treated; however, if a treatment was forgotten, that animal did not have any treatment to associate with AMR isolate status. In addition to logistical challenges, none of the farms put antibiotics in the feed which may have biased this study toward the null; however, it should be noted that this practice is not common in cow-calf operations in California. Finally, the use of human breakpoints for the determination of AMR status when no veterinary breakpoints were available is another limitation, underlining the need for further research into AMR in livestock species. A metagenomic analysis of isolates would have provided further information but was not possible at this time due to financial constraints.Food is essential; its infrastructure, complex.

A volunteer cares for the chicken coop, which houses four hens who provide eggs for the restaurant. A cat named Jolene resides at the farm and chases away pests .Through my field observations of 26 active sites, I found that community gardens, school gardens, urban farms had many unique and shared qualities. UA sites ranged in size from 0.06 to 8.5 acres, though exact measurements were not available for some sites . Sites that did not report an exact size were estimated to be less than one acre. Except for the two largest UA sites, LBCG and the Growing Experience most UA sites were smaller than two acres. Nearly all sites were secured by a chain-link fence or gate. In this study, the VA Hospital Patient Garden and the Michelle Obama Neighborhood Library Learning Garden were the only UA sites without a gated front entrance. However, the Patient Garden was protected by video surveillance, locked buildings, and fenced areas. Each site had decorations, reflecting the population using the garden . All UA sites offered communal areas for resting, in the form of logs, chairs, or picnic tables and benches. Trees, gazebos, and arbors covered in vine plants provided shade. UA sites typically implemented policies for membership, etiquette, and growing. LBO’s nine community gardens have a $55 minimum membership fee per six-month season, while LBCG’s membership fee is $160 per year. Though LBCG members pay more, they complete less service hours: LBCG requires four hours per year, grow rack compared to at least 20 hours per year for LBO members. Both organizations prevent gardeners from selling produce for profit. Even UA sites without membership fees enforced certain rules. Most UA sites prohibited the use of tobacco, cannabis, alcohol, or other illegal substances.

Ground Education’s gardens have signs with a list of rules for students. At the beginning of each class, Garden Educators ask students to respect others and “celebrate nature” by leaving insects alone and only picking plants with permission. Some UA sites enforced rules for the types of products and plants allowed. LBO and the Peace Garden only allow gardeners to use organic fertilizers and insecticides. To avoid plant diseases that occur in winter, LBCG only allows nightshade family plants from March 1st to November 15th. LBCG also has a common area for herbs, including rosemary and mint, which can quickly spread throughout plots and are difficult to remove. Several UA sites created food donation programs to distribute to community members, local pantries, and organizations. Every week, the LBO Director harvests from Zaferia Junction Community Garden, collects any produce donated by gardeners, washes the produce, then weighs and organizes donation bags. Connecting to my first research question, many UA sites were built by community members to revitalize vacant spaces and increase food access. For example, Santa Fe Community Garden and Farm Lot 59 were established by community members on littered, empty lots. In some cases, UA sites were intended for a specific population, such as the VA Hospital Patient Garden, which primarily serves veterans receiving long-term care at the hospital. Touching on my second research question, communities created UA by drawing on both agricultural knowledge and leadership skills. Typically, UA sites were built and maintained through community volunteers, who constructed raised beds, dug in-ground plots, weeded, and planted crops. UA sites were managed by an organization, city department, or at least one lead person. The partnership between UA leadership and landowners was critical for creating and maintaining sites. Over half of the active community gardens included in this study established a lease agreement with the City of Long Beach. School gardens were built with the permission of LBUSD.

Other sites were built on land owned by individuals or entities such as CVC, VA, and the LA County Housing Authority. The next section on former sites will discuss the significant influence that landowners hold over UA.The table is organized alphabetically, as there was limited information on when each former site was originally founded. Some websites provided outdated information, and many of the phone numbers listed were no longer in service. Gladys Avenue Urban Farm, originally owned by LBO founder Captain Charles Moore, was sold to another private landowner with the condition that the land must be used for UA. The site was rented to Heritage Farm in 2022, described previously in this chapter. Another urban farm, Long Beach Farms, is now a community garden managed by Puente Latino Association. Three Sisters community garden, owned by the City of Long Beach and located at Orizaba Park, was managed by a community group, and is now managed by LBO. In 2015, the landowner of former LBO community garden, Top of the Town, began renting the space to Organic Harvest Gardens. That same year, LBO opened Zaferia Junction Community Garden, which was built on the land of Wild Oats Community Garden. Wild Oats, which was constructed on a former Pacific Electric railroad, was closed due to construction of the Termino Avenue Storm Drain Project, a nearly two-mile long storm drain system designed for flood relief . These formerly closed sites demonstrate how UA can change over time due to changes in ownership and management, as well as public construction projects.As of 2023, most of former UA sites including Fifth Street Garden, Foodscape Garden, Hill and Atlantic Garden, New City Urban Farm, and Wrigley Village Community Garden, are empty lots. Former UA sites were forced to relocate or close due to the city or private owners choosing to not renew the lease. Figure 28 is a collage of Google Map images of the original Fifth St Garden , from 2008 to 2022. According to a blog written by Jon Rosene, the community garden was nearly 8,000 square feet. In 2009, the landowner offered a lease of up to three years for $1 a month . After the lease ended, gardeners built a school garden at Franklin Classical Middle School, which is now managed by Ground Education.Other former UA sites were repurposed for use by the city and other entities.

The Firehouse Community Farm was located at a former fire station, and featured beehives, community gardening classes, and monthly crop swaps. A neighborhood association managed the farm with a right-to-entry permit, but the permit expired in 2019 without the city’s renewal. The space is currently used by District 9 council office . Another city-owned property, the Civic Center Edible Garden, was removed when the previous civic center, city hall, and library were demolished. The buildings were “seismically deficient” according to a 2015 press release from the City of Long Beach. The Spring Street Farm Project, led by the Long Beach Community Action Partnership , planted an orchard, created an aquaponic system, and raised chickens, ducks, and a goose. The organic urban farm was part of the LBCAP Youth Opportunity Center’s Green Jobs program . According to an LBCAP employee, the space was leased from the Salvation Army. The Salvation Army asked LBCAP to relocate due to renovations, but LBCAP was unable to find a new location for its farm. Overall, it appeared that no matter how successful UA sites were, their longevity was determined by landowners, not the community members using the space. Regardless of the UA site’s scale or amenities, they could be demolished due to the construction of a new building or reverted into a vacant lot for sale. As of 2024, four of the nine nonoperational sites identified are still unused. The space that formerly hosted Wrigley Village Community Garden, which was closed in 2016 after a real estate investor sold the property, is covered in litter . Nonoperational sites highlight the precarious nature of UA. Without the support of landowners and policies to protect sites, UA benefits of food access, green space, drying cannabis and neighborhood beautification can be reversed. The next chapter will share insights from UA leaders and provide a deeper analysis of study findings in relation to CCW and SDOH.In the summer of 2023, I had the opportunity to visit Captain Charles Moore Urban Community Garden, which was constructed in April 2023 and officially named on February 18th, 2024. Before the garden received its name, gardeners would call LBO’s ninth garden, “the new garden,” or simply “3121,” from the address, 3121 Long Beach Boulevard. I interviewed a UA leader who rented a plot there, named Nana . Though Nana had just started renting her 10’ x 10’ in-ground plot at the new garden, she had decades of experience, as she had been growing plants since the age of six. With a smile, Nana reminisced how her grandmother “hauled [her family] into the garden.” As the descendant of slaves, her grandmother wanted to “pass along the skills of growing your own food.” Out of 11 grandchildren, Nana is the only one who continues to garden. She estimated that she grows 80% of the food she eats. Growing food was essential for Nana to take control of her own health after being diagnosed with cervical cancer. She used to take 27 different medications per day. At that time, Nana felt that she was “a zombie [who] woke up to sleep.” Growing her own food and medicinal plants empowered Nana to take control of her diet and improve her physical and mental health. She explained that if she has a bad day she goes into the garden. Nana said, “It just brings me so much happiness to grow.” With pride, she described her recent crops: watermelon, winter squash, onions, chives, fava beans, stringless string beans, snow peas, black-eyed peas, moringa, borage, chamomile, and mint. Watermelons were her biggest success.

Nana grew multiple watermelons per year in different varieties, like Klondike , moon and stars watermelon , and a sweet variety from Louisiana. She also loves mint tea because it soothes stomach aches and helps with her liver issues. As Nana showed me around her garden plot, she expressed her joy at seeing new life come from the seeds she planted, “like a mother birthing a child.” Following in her grandmother’s footsteps, Nana hopes to pass down her gardening skills and knowledge to her kids. She said that growing food was her grandmother’s “longevity”: a lasting contribution to her family. Nana’s story demonstrates how UA provides not only a space for growing food, but for community members to enhance their overall health and environment. Through interviews with UA leaders and field observations of gardeners, school garden educators, students, interns, and volunteers, I learned that UA allows people to connect with others, transform their neighborhoods, and share knowledge. Building on the previous chapter, which provided context for the UA sites, Chapter 4 will discuss recurring themes from interviews and field observations. While Chapter 3 provided a broad overview of how community members create, maintain, and engage in UA, this chapter will focus on the specific forms of skills and knowledge fostered by UA, and how UA addresses health. I analyzed transcripts and field notes by using ATLAS.ti to identify phrases and words that were emphasized by participants or related to CCW and SDOH. Following the primary-cycle and secondary-cycle coding procedure described by Tracy , I developed a codebook to organize qualitative findings.UA brought Long Beach community members together through the collective experience of being involved in a garden or farm, often by volunteering and sharing food. One UA leader explained that they were interested in creating “more venues for more classes [and] more activities.” They remarked, “It’s not just about people growing stuffany more. There’s more community involvement or community building.” Another described a “sense of social connectedness” by getting to meet community members at volunteer days. These are examples of social capital, described by Yosso as social networks and community resources. At LBO’s nine gardens and LBCG, gardeners socialized during Saturday “work parties.” Gardeners completed community service by weeding and cleaning common areas, but also mingled with one another, swapped crops, and enjoyed potlucks together. Though LBO only required a minimum of 10 community service hours per six-month season, one person had set a record of 102 hours. Others reached over 90 hours per six-month season. A volunteer had 70 hours completed at the time of writing. He volunteered every week “to beat that 102 record.” In this scenario, community members used social capital to maintain gardens, even if they were not growing food.

Tracy describes “the mind and body of a qualitative researcher” as a literal research instrument, “absorbing, sifting through, and interpreting the world through observation, participation, and interviewing” . I am a Social Ecology doctoral candidate and the Assistant Director of a Long Beach UA nonprofit, Adventures to Dreams Enrichment . AtDE empowers youth by providing the resources and education for youth to grow their own food. The organization’s mission is to engage youth in hands-on enrichment activities, create a safe environment to learn and play, and provide mentorship . While collecting and analyzing data, I will be mindful of how my subjective experiences may influence the research . I began volunteering at AtDE in 2017 while completing my Bachelor’s in Dietetics and Food Administration at California State University of Long Beach. Since then, I assisted AtDE in building and maintaining a youth garden, harvesting produce, coordinating volunteers and interns, and raising funding. These experiences allowed me to build rapport with not only AtDE, but with community members of Long Beach, which is essential for recruitment and data collection for this evaluation. For this study, I could be considered a “complete participant” as a researcher studying a context in which I already am a member . My role as the Assistant Director of a nonprofit engaged in youth gardening offered the advantage of insight into the world of UA. Subjects of a study may act more open and candid around a complete participant, as if a colleague or friend is visiting, rather than a researcher .This research investigated UA sites in Long Beach that fit the United States Department of Agriculture’s definition of cultivating, processing, industrial grow and distributing agricultural products. UA sites in Long Beach include community gardens, school gardens, and urban farms.

An important distinction between community gardens and farms is that community gardens are collectively maintained by a group of individuals to grow food, compared to farms which may be privately owned . Although rooftop farms, hydroponic, aeroponic, and aquaponic facilities, and vertical production qualify as UA, these UA types were not identified in Long Beach . Equipment facilities, distributors, and green spaces that do not grow food, such as botanical gardens, were excluded from this study. This study also collected information on UA sites that are no longer in operation, such as the community gardens deemed “no longer operational” by Ban et al. in 2013 . IRB approval was granted by the University of California, Irvine in May 2023. I used publicly available contact information to request a site visit and interview with the main person responsible for the site . Additional participants were recruited through snowball sampling, or recommendation by initial study participants . UA site leaders were contacted via email with a study information sheet. The interview was conducted with the interviewee’s verbal consent, and interviewees received a $25 gift card as compensation for their time.Data collection took place from June 2023 to December 2023. I interviewed 19 people in a leadership role at a Long Beach UA site . Interviewees were aged 22 to 69 years old, with the average age being 49. In addition to the broad range of ages, interviewees had varying levels of experience. The longest amount of time a UA leader held their position was 13 years, and the shortest amount was one month. About 58% of interviewees were female, and 42% of interviewees were male. I conducted field observations at 27 sites, about 39% of 66 sites that were actively operating in Long Beach at the time of writing, in 2024. I observed, interacted with, and volunteered with over 60 adults engaged in UA and over 200 LBUSD students.

Additionally, about 68% of interviewees identified as White, which is higher representation compared to the city’s population. Only less than a third of Long Beach residents are White . Therefore, the demographics of UA leaders who participated in this study may greatly differ from that of all gardeners, students, and farmers engaged in UA.During the site visits, I wrote field notes as a qualitative method for collecting descriptive information about the UA sites and people involved. Field notes allow researchers to understand others by immersing themselves in events, experiencing and interpreting those events as participants, and “transforming witnessed events, persons, and places into words” . This provides description that may otherwise be missed by a survey questionnaire with prefixed questions . Using a field observation protocol , I recorded the date, time, and duration of sites visit and notes of my initial impressions, including sights, tastes, smells, and sounds. Based on this protocol, I first created a “raw record,” my first, unprocessed writing of the site . Within 36 hours of the site visit, I typed the raw record and saved it as an electronic document . I recorded any site characteristics that corresponded with the SDOH domains of social and community context, economic stability, education access and quality, neighborhood and built environment, and health care access and quality . For example, while observing the Neighborhood and Built Environment, I noted the type of land that the site is located on and its size, any amenities , crops, plants, and vegetation, agricultural techniques, animals and/or insects kept at the site, nearby public transportation, and security features. I took notes on the UA site’s Social and Community Context by recording the number of people present, their visible characteristics , any ongoing activities, programs, or events, and any rules or policies followed at the site.

In my reflections, I documented key events or incidents that are perceived as “significant” or “unexpected” by myself and/or those at the site . I also noted any aspects of the UA site that demonstrate CCW, which will be further explored in interviews with UA leaders .The interview guide included 31 questions organized into 7 sections: 1) Description of Urban Agriculture Site, 2) Management, 3) Transportation, 4) Description of the Community, 5) Community Engagement, 6) Relationships and Partnerships, and 7) Successes and Challenges. Interviewees were asked to describe their role, their UA site or organization, participants at the UA site , the surrounding community and environment, types of community outreach and programs, collaborators, obstacles related to maintaining the site, and any notable accomplishments. Interviews lasted about 45-60 minutes and were audio recorded. During the interview, I wrote short notes to record my observations . Interviews were transcribed with the assistance of Otter.ai, a speech-to-text transcription tool. The interview guide was designed to address the five SDOH domains and CCW forms of capital . SDOH interview questions served to collect detailed information about the community from the perspective of the UA leader, that may not be available from field notes and external sources. For example, Question 15 asked interviewees to describe the UA site’s social and community context: “In your own words, how would you describe the community where your site is located?” Question 17, “How would you describe your community’s environment?” specifically asked for information on the neighborhood and built environment domain of SDOH. CCW questions focused more on abilities, resources, skills, or knowledge actively contributed or gained by the community through participation in UA. For example, Questions 21 “How do community members contribute to the site?” and 22 “How do community members benefit from your space?” were created with social capital in mind. Questions 26, “What are some of the biggest challenges in sustaining a space for urban agriculture?” and 27, “How have you overcome these challenges in the past?” touched on aspirational capital , navigational capital , and resistant capital .Rigorous qualitative research requires care and effort to ensure that there is enough data to support claims, the context or sample is appropriate, and methods are valid and reliable . Tracy outlines eight criteria for producing qualitative work with rigor: 1) worthy topic, 2) rich rigor, 3) sincerity, 4) credibility, 5), resonance, 6) significant contribution, 7) ethical, and 8) meaningful coherence. As mentioned in the previous chapters, this study’s topic is relevant, timely, significant, and interesting due to emerging UA literature, and limited research on UA in the City of Long Beach. The study design addresses rich rigor by carefully explaining how survey and interview questions were developed, based on the SDOH and Yosso’s CCW model. I aim to be sincere and transparent in this dissertation, by reflecting on my own involvement with UA in Long Beach and providing clear details on methodology. Regarding credibility, open-ended interview questions invited participants to describe their narrative on their own terms. This research incorporated thick description, an in-depth illustration that will allow readers to understand context and come to their own conclusions about the data. The study’s major contribution is that it will offer a new lens on the topic of UA in the context of communities addressing health inequities, by exploring the perspectives of UA leaders in Long Beach. Findings may resonate with others involved with UA and community health. The results of this study will be informative for community groups or organizations who are operating, developing, or interested in creating similar UA sites. Additionally, equipment for weed growing readers may be able to replicate methods to transfer findings to another context, such as another city or region . The following chapters will provide meaningful coherence by explaining how the study achieved its goals and connecting findings to previous literature.In this chapter, which explains the dissertation’s theoretical significance, I will describe the social determinants of health and how they apply to the City of Long Beach. Then, I will explain how Yosso’s community cultural wealth model is applicable to addressing health inequities through community-led urban agriculture . From a social ecology perspective, UA can influence multiple, interrelated factors, such as individual attributes and behaviors, interpersonal relationships, the surrounding environment, organizations, corporations, government, and culture .

Although the research questions of this study focus on the community’s role in UA, this dissertation will later explore UA impacts on interconnected, social-ecological systems. The SDOH framework offers specific dimensions to further study health factors health within systems, such as access to education and health care . SDOH provides context to study health inequities, which are systematic differences in the health of different population groups . Health inequities result from socioeconomic inequality, not natural causes or harmful behaviors . This dissertation will build on existing UA research by connecting SDOH to the CCW model, which highlights communities’ cultural knowledge, skills, and abilities . CCW is necessary for developing and maintaining UA spaces, often converted from lots that were abandoned or not designated for growing food . UA is the cultivation, processing and distribution of agricultural products in urban and suburban areas, including tribal communities and small towns . Examples include community gardens, rooftop farms, hydroponic, aeroponic, and aquaponic facilities, and vertical production. UA can improve health by increasing access to fruits and vegetables, which prevent disease and supply nutrients . However, UA provides more than just dietary benefits. I developed Figure 7 to illustrate the conceptual framework for this study, which analyzed how CCW is used to develop UA, which in turn bolsters CCW. Both CCW and UA can address inequities in different facets of SDOH .Rather than focusing on disadvantages faced by lower SES populations, the CCW model highlights their cultural knowledge, skills, and abilities . Yosso’s CCW model describes six forms of capital: 1) aspirational, 2) linguistic, 3) familial, 4) social, 5) navigational, and 6) resistant. Aspirational capital is the resilient ability to maintain hopes and dreams for the future, despite barriers. Linguistic capital includes communication skills in more than one language or style. Familial capital refers to cultural knowledge nurtured among kin, which fosters commitment to community well being. Social capital includes networks of people and community resources. Navigational capital is the ability to maneuver through social institutions not created with communities of color in mind, and resistant capital is built from oppositional behavior that challenges inequality . Social capital, resistant capital, and other aspects of CCW can be seen in community led initiatives to create UA . Urban areas are complex systems and networks , which the United States classifies as “densely developed territory” that has “residential, commercial, and other non-residential urban land uses.” Any areas not included within this definition of urban are classified as rural.1 Because access to agricultural land is less common in urban areas, urban dwellers typically purchase their food from stores .

The results of this proposed work would help us to determine if 1) there is variability in vertically transmitted seed microbiomes across location and host genotype and 2) what these differences arise from. By fully describing the bacterial community of the leaves and fruits as well, we could determine seed colonists’ origin and address if transmission of leaf epiphytes is possible via the seeds. A similar culture-based approached could be used to determine the protective ability of vertically transmitted microbes, as it is possible that taxonomic identity may differ- but function may be the same. In conclusion, the work described in Chapter 2 makes an important step in filling in the gap in the literature as to the existence and importance of vertically transmitted symbionts in this system. Future work will help us understand the origin of these symbionts and if genotype specific microbes are physically heritable through seed transmission.Breeding for agriculturally beneficial traits, such as disease resistance, is an area of ongoing research in the tomato industry, and agriculture in general. Many resistance genes in modern tomatoes originate from their wild Peruvian relative, S. pimpinellifolium, which has a much larger genetic diversity than modern cultivars. Whether or not there are differences in tomato microbiota due to domestication and the presence/absence of resistance genes is a relatively unexplored topic. My work on adult phyllosphere microbiomes originally began as a way to test the hypothesis that breeding for disease resistance genes in tomatoes would ultimately impact the microbiome of those plants. I was, indeed, able to show that host genotype shaped the phyllosphere community for the first two passages of the experiment. When genotypes are classified “resistant” or “susceptible” , there is no overall effect of resistance in microbiomes that had been fully selected on various tomato varieties.

This lack of an overall effect of resistance leads me to conclude that it may not be the resistance genes themselves, drying and curing bud but rather other genetic differences that existed between the genotypes that drove genotype specificity of the bacterial communities. Although I chose two pairs of near-isogenic lines and one out-group, it is likely that other genetic differences existed between near isogenic lines due to the introgression breeding technique that was used to generate the lines. Furthermore, the pairs of near isogenic lines are different tomato cultivars, further contributing to genetic differences amongst hosts. Future work by others will further test the degree to which differences in host genetics impacts the phyllosphere community, and indeed, some evidence for heritable taxa already has been produced using genome wide association studies in corn and Arabidopsis. Moving forward, if there are taxonomic differences between microbiomes, whole genome metagenomics sequencing will help us determine if the functional capability of the microbiomes differed as well. One of the puzzling results from the microbiome passaging work that we were not able to fully explain is that host genotype had a significant impact on bacterial community at the beginning of the experiment, but this declined over time. Through identifying the specific taxa that were significantly associated with the five genotypes in P1 and P2 it’s clear that it is not only the rare taxa associated with particular genotypes that drove such a genotype effect on the microbiomes, and thus the decline in genotype effect cannot be fully explained simply by an overall decrease in diversity. It seems likely that the microbiome underwent environmental selection driven by three factors: 1) the greenhouse, 2) the tomato phyllosphere, and 3) specific tomato genotypes. It seems reasonable that the relative strength of each selection pressure would change over time, whereby host genotype is important early on, but the community experiences progressively more time in the tomato phyllosphere in the greenhouse, the pressure of those environments overshadows a genotype effect.

Even with well-designed and well-controlled experiments, it is difficult to disentangle the selection pressures at play.Through our microbiome transplant and passaging technique that is biologically relevant to how the phyllosphere is naturally colonized, we were not only able to select upon entire host-associated microbial communities, but we could also experimentally test hypotheses regarding microbiome adaption in subsequent experiments. Again, this is due to the physical accessibility of the phyllosphere community and the ease at which it can be inoculated onto hosts. These findings also shed light on a notable challenge in microbiome research. Our data suggest that when describing the microbiome of an open environment, such as plant surfaces, many of the taxa found there may be transient visitors. In the case of the phyllosphere, there are microbes on leaf surfaces that may have emigrated from air, soil, surrounding plants, or other non-plant habitats and do not necessarily represent an adapted community that is capable of growth and persistence. Passaging of microbiomes on a particular host seems to be a powerful way of differentiating those taxa that are, or can become, well adapted to a plant host environment and those that were present upon sampling, but are not well adapted to the environment. Across all systems, much of the work in microbial ecology is highly descriptive: the community associated with a particular host or ecosystem at a given time is described to be its microbiome, implying strong selection for a particular interactive community- rather than a context-dependent assemblage with many recent immigrants, for example. Our findings raise the question as to if a microbiome should be defined as the community that is merely found there upon sampling, or alternatively, if a true microbiome is only one that is adapted to its host or environment. The latter definition might prove hard to establish in many habitats, but fortunately can be readily addressed in the phyllosphere. Thus we expect that our phyllosphere studies will provide important conceptual contributions to the field as a whole.The final chapters of my dissertation explore the importance of bacteriophages in the phyllosphere community.

There are many challenges facing phage research, and studying environmental phages is an especially difficult field due to lack of a universal marker gene for sequencing, a lack of cultivability, and our nascent understanding of phage genetic diversity. Thus, we are unable to describe the abundance and diversity of phages within our samples without shotgun metagenome sequencing. Some of these challenges I was able to overcome, and others I was not. My work primarily depended on the assumption that there were phages on the leaves used to generate the initial inoculum. I took a “black box approach” in which I isolated the size fraction of the microbiome that should contain most lytic phage particles. I treated this as the “phage fraction”. I then looked for an effect of this fraction on bacterial abundance, composition, and diversity. This approach allowed me to overcome the difficulty of identifying and quantifying phages. My findings show that there is, indeed, an important effect of the phage fraction on the microbiome as a whole. This work also provides empirical support for the theory that phages mediate prokaryotic diversity and contribute to temporal population size dynamics. In order to measure phage abundance in starting samples, I attempted to use both fluorescence microscopy and transmission electron microscopy. Although both approaches yielded images of “phage-like particles”, it was impossible to quantify these particles, primarily due to the amount of background fluorescence that interfered with microscopy and the sheer difficulty of identifying low-abundance phages using electron microscopy. Another alternative for quantifying phage particles is flow cytometry, but this method suffers from the samelimitations due to the presence of intrinsically fluorescent contaminating particles. In Appendix 1, I describe a method that I was able to develop for quantification of known phages. If I were to continue the work described in Chapter 4, I would do so with a defined synthetic community of bacteria and phages, from which I could sensitively measure both bacterial and phage abundance throughout the course of the experiment. There remains much to learn about lytic and temperate phages. My findings in Chapter 5 attempt to disentangle the effect of lytic versus temperate phages on the bacterial community on leaves. This work is an important extension from Chapter 4 in a number of ways. First, I wanted to test if the patterns that I observed of the effect of lytic phages on the bacterial community after only a short time together on leaves were persistent over time. I found that patterns of the effect of phages on bacterial communities differed when examined after 3 weeks compared to 1 week. This has important implications in how we think about the issue of timescale in microbial community interactions. It also begs the question: how many lytic phages were present at the start of the experiments, cannabis drying and how long did they persist on the surface of the plants? If lytic phages do not persist, can selection for lysogenic phages produce some of the same patterns in the bacterial community as well? Interestingly, I did observe that treatment consisting only of bacteria that were passaged on leaves for several weeks, i.e. the treatment in which lysogenic phages would have been selected, had a qualitatively higher alpha bacterial diversity than the other treatments. This may suggest that lysogenic phages are capable of promoting bacterial diversity over longer time scales We were not, however, able to find conclusive evidence for an increased presence of lysogenic phage in the communities of bacteria passaged on plants in the absence of lytic phage.

The questions that I attempted to address in Chapters 4 and 5 are difficult to answer with current, common bacteriophage techniques. Moving forward, the best way to uncover both lytic and temperate phage abundance and diversity in the phyllosphere is likely through shotgun metagenomic sequencing. Sequencing the phage fraction would better describe the lytic phages in the system. Sequencing the bacterial fraction should reveal the prevalence of temperate phages integrated into the bacterial genomes. This approach is not devoid of challenges, however, as it can be difficult to sequence microbiomes associated with plants because of the presence of abundant contaminating plant genetic material. Improvements in high throughput sequencing are allowing us to overcome this limitation, if only by the sheer amount of sequences that can be obtained in environmental samples. I see this approach as the most promising way to comprehensively understand the abundance, diversity, and importance of bacteriophages in the phyllosphere.That the microbiome is an entity that fundamentally influences host health and function has caught the attention of researchers, medical doctors, nutritionists, and every other person interested in the microbial world that exists around and within them. Next generation sequencing and other “omics” approaches have enabled us to address the diversity and complexity of various microbial communities, but there are limitations to these approaches. For example, many labs frequently use 16S rRNA amplicon sequencing to describe bacterial communities. This is the most accessible approach due to reasonable cost, accessibility to protocols, and ease of use of sequence analysis pipelines. However, 16S amplicon sequencing only gives us coarse taxonomic resolution of the community, and it does not give any idea of function . The movement of the field away from the division of bacterial diversity within Operational Taxon Units to Exact Sequence Variants should provide more resolution of bacterial diversity, but still does not provide much insight into the functions of these taxa. It seems likely that as the cost of sequencing continues to fall and more labs have access to both the sequencing and analysis technology required, shotgun metagenomics will surpass 16S amplicon sequencing in popularity. Even so, these advanced sequencing approaches must be coupled with hypothesis-driven experiments and highly controlled experimental design. This, in addition to culture-based approaches and the use of synthetic communities when possible, will enable us to move the field beyond observational and correlational findings.Reconstructing the timing and magnitude of changes in human population size is important for understanding the impact of climatic fluctuation, technological innovation, natural selection, and random processes in the evolution of our species. With census population sizes estimated to be only in the millions during most of the Pleistocene, it is obvious that human population size has increased dramatically towards the present.

At that point, the start inoculum was divided into 6 aliquots and stored in glycerol freezing buffer. For each inoculation in the first passage, an aliquot was thawed and cellspelleted for 10 mins at 4000 X G. Cells were re-suspended in 200mL 10mM MgCl2 buffer. Of this, 40mL were and heat killed in an autoclave for a 30 minutes at 121°C. Inoculum was plated, and an absence of growth confirmed that the heat-kill was effective. To get initial concentration of inoculum, dilution plating was performed on Kings Broth agar plates . Soil from each site, which had been stored at -20°C, was combined in a sterile Nalgene bucket and thoroughly mixed before inoculation.Soil inoculation: The top layer of every pot was supplemented with 40 grams of UC Davis Farm Soil. Soil inoculation was only performed once and only for the first passage of plants. Spray inoculation: Each plant was sprayed, using misting spray tops placed in 15mL conicals, with approximately 4.5mL of inocula. Control plants from passage 1 were inoculated with the heat-killed inocula. Control plants from subsequent experiments were inoculated with sterile 10mM MgCl2. Immediately after inoculation, plants were placed in a random order in a high humidity misting chamber for 24 hours. After 24 hours, the plants were moved to a greenhouse bench. Plants were inoculated once per week in the same manner and were placed in the misting chamber for 24 hours after every inoculation. Passage one plants received 5 weeks of inoculation, P2-P4: four weeks, and the fifth cohort: five weeks.Ten days after the final spray inoculation, plants were sampled.

With the exception for plant cohort 5, all plants were cut off at the base and immediately placed into sterile 1L bottles individually. By the end of cohort 5, dry marijuana the plants had grown too large to sample the entire plant, and instead, roughly 2/3 of the plant material was sampled from each plant, with care taken to sample the same age of branches from every plant. After collection, plant material was weighed, and 200mL of sterile 10mM MgCl2 were added to each bottle containing the plant material. The bottles were submerged in a sonicating water bath, sonicated for 5 minutes, vortexed, and sonicated for another 5 minutes. Half of the volume from each plant was pelleted for 10 mins at 4200 X G, re-suspended in ~1mL of 1:1 KB Broth Glycerol, divided into aliquots, and stored at -80°C for inoculation of the subsequent passage. The other half of the volume was pelleted in the same manner and then stored as a pellet at -20°C for DNA extractions. To prepare inoculation of the next passage, microbiome glycerol stocks were thawed, briefly pelleted to remove glycerol, and re-suspended in sterile 10mM MgCl2. Volume of re-suspension depended slightly on the size of the plants, but in general ranged from 5-10mL. Microbiomes were never pooled.Genotypes 2706, 3472, and 2934 were used for this experiment, and four plants of each genotype received each treatment . One control plant of each genotype wasspray inoculated with MgCl2 as a control. To prepare the inoculum, microbiomes from the end of passage one and the end of passage four were used. All aliquots were thawed and combined. The same was done for all of the individual microbiomes that came off of passage 4 plants.

To remove the glycerol, the samples were spun down and re-resuspended in 10mM MgCl2. In order to generate the 50/50 mix of P1 and P4 microbiomes, live/dead PCR with PMA treatment was used, adapted from the following method. Briefly, serial dilutions of P1 and P4 were performed in MgCl2. Each sample then received PMA at a final concentration of 100uM and vortexed. Samples were incubated in the dark at room temp for 5 minutes. Then they were placed in ice on a tray exactly 10cm away from a 700 watt halogen lamp. The light was turned on for 30 seconds, and turned off for 30 seconds. During the 30 seconds without light, the samples were all vortexed. This was repeated three more times. Samples were then pelleted for 10 minutes at 5000 X G. The supernatant including the excess PMA was removed, and cells were re-suspended in sterile 10mM MgCl2. Droplet Digital PCR was then utilized to quantify bacteria from each sample, and concentration was matched to 7.7 x 106 cells/mL. P1 and P4 were aliquotted separately and then recombined for the mixed inoculum so that each plant received ~9 x 104 bacteria each week that they were inoculated. Plants were inoculated for three weeks and harvested 10 days after the final inoculation as described previously.The neutral model was proposed by Sloan et al. to describe both microbial diversity and taxaabundance distribution of a community. Burns et al. have developed a R package based on Sloan’s neutral model to determine the potential importance of neutral process to a community assembly. In brief, the neutral model creates a potential neutral community by a single free parameter describing the migration rate, m, based on two sets of abundance profiles – a local community and meta communities. The local community describes the observed relative abundance of OTUs, while the meta community is estimated by the mean relative abundance across all local communities. The estimated migration rate is the probability of OTU dispersal from the meta community to replace a randomly lost individual in the local community.

The migration rate can be interpreted as dispersal limitation. In each microbiome passage, half of the samples were randomly selected and the relative abundance profile at the OTU level was used. The neutral model fit and migration rate were estimated in the resolution results of 200 iterations for P1, P2, P3, P4, and P4 Combined.We applied a null model approach on the serial passaging data P1-P4 to characterize the changes of stochastic process driving the assembly of plant microbiome over time. Lines that had high quality sequencing data at every time point , were used for this analysis. The null scenario for each line at each passage was generated using the data for that same line at the previous passage. The null scenario of P1 was generated using the original field inoculum sample. The null model approach was based on community pairwise dissimilarity proposed by Chase and Myers and extended by Stegen et al. to incorporate species abundance . Chase and Myers proposed a degree of species turnover by a randomization procedure where species probabilistically occur at each local community until observed local richness is reached. However, the estimated degree of turnover does not include species abundance. To take full advantage of our dataset, we also incorporated species relative abundance into the procedure proposed by Stegen et al. Zinger et al. has developed R code for the null model and applied the null model approach on the soil microbiome. This approach does not require a priori knowledge of the local community condition and determines if each plant microbiome at the current passage deviates from a null scenario generated by that same microbiome at the previous passage. In brief, the null scenario of each was generated by random resampling of OTUs and remained the same richness and number of reads with the original sample. Total OTUs observed in the sample and the corresponding relative abundance were used as probabilities of selecting an OTU and its associated number of reads, respectively. The BrayCurtis distance is used to calculate dissimilarities across null communities with 1,000 permutations. The null deviation shows the differences between average null expectation and the observed microbiome of the same line.Bacteriophage viruses that infect bacteria are both ubiquitous and abundant, so much so that they are estimated to largely outnumber bacterial cells in the environment. Their role in controlling bacterial populations has been studied since their discovery as “bacteria-killers” in the early 1900s, and there are countless studies investigating bacteria–phage pairwise dynamics. Even the fundamental Luria–Delbruck fluctuation experiment that demonstrated mutations arise in the absence of selection was conducted using phage as the selective pressure. In addition to fundamental research, marijuana grow system lytic phages have been widely studied for their use as biological control and therapeutic agents, and have been successfully used in control of plant pathogens, including in tobacco, tomato, detached flowers of Rosaceae trees, and even some ready-to-eat foods such as hot dogs and lettuce leaves. Beyond just controlling bacterial abundance, phage predation in the ocean is thought to impact bio-geochemical cycling and food web processes through bacterial lysis, converting biomass into dis- solved organic matter and contributing to the dissolved organic carbon pool. Recently, increased interest in the human microbiome is also beginning to acknowledge a key role of lytic phages in these communities, but in contrast to free-living microbiota, little empirical work has been done to uncover the role of phages in these systems. Specifically lacking is an understanding of when and how phages shape the abundance and composition of host-associated bacteria. Phages can have important impacts on the competitive dynamics and structure of bacterial communities, and they are predicted to maintain bacterial diversity through a variety of mechanisms. As bacteria evolve to escape phage predation and phages counter-adapt to these resistances, evolutionary and co-evolutionary dynamics can drive important phenotypic and genotypic variation within the bacterial community . One idea that is frequently put forth in marine systems, known as “kill-the- winner” dynamics, suggests the most abundant bacteria should also be the most susceptible to phage predation. In this model, an increase in bacterial abundance is followed by an increase in the associated phage population and a subsequent decrease in bacterial abundance, effectively preventing one type of bacteria from ever dominating the community. Antagonistic co-evolution between bacteria and phage has recently been put forth as a driver of bacterial diversification and variation within the human gut microbiome, with potential impacts on microbiome function and human health through phage-mediated homeostasis or dysbiosis.

The impact of lytic phages on bacterial cell density and community diversity may in part be the result of cell lysis, which not only has a direct effect on the population of cells, but also has an indirect effect on competition among bacterial strains and species within a community. Phages may also increase bacterial density and diversity by releasing nutrients into the environment via lysis byconferring metabolic or morphological traits to bacteria upon integration into the genome . Furthermore, culturing phages can be difficult, as it is reliant on having an isolate of a suitable bacterial host. Despite these difficulties, studying phages in host-associated microbiomes may reveal interactions between bacteria and phages that are different from those occurring in free-living microbial populations. For example, recent work has suggested that microbiomes may be dominated by temperate phages that integrate into the host genome as opposed to lytic phages that lyse their host cells . In this case, changes in bacterial density or composition due to lysis would likely represent only one small way in which phages impact their microbiome. Furthermore, host factors such as age, immunity and health are likely to change the dynamics between bacteria and phages within the host environment . Another key difference in host-associated microbiomes compared to free- living bacterial communities is the process of colonization of a new host. Phages may play a key role in early microbiome establishment, the importance of which will be specific to the mode of microbiome transmission and the diversity and composition of colonizing bacteria. In this work, we sought to investigate the role of lytic phages in shaping bacterial abundance and community composition during colonization of the phyllosphere . We used a filtration method to deplete phages from the microbial community associated with tomato leaves, modified from an approach that has previously proven effective for separation of phage and bacteria in seawater. Through inoculation of a size fractionated field-grown tomato microbiome onto juvenile, growth chamber-grown plants, we are able to test whether the lytic phage fraction of the phyllosphere has an impact on bacterial abundance, composition and diversity during microbiome establishment. We find an impact of phages on overall bacterial abundance and relative abundance of specific taxa that is measurable after 24 hr, but not at 7 days post-inoculation. We also find evidence for slightly higher alpha diversity after 7 days in those communities in which phages were initially present in the inoculum relative to those in which they were depleted.

We found one particularly protective seed-associated microbial community that was able to significantly decrease the density of P. syringae pv tomato DC3000 growth on seedlings and reduce disease symptoms across multiple tomato types. Community profiling uncovered that Pantoea spp. dominated this seed microbiome, regardless of which seedling type it was applied to, and we were able to culture specific Pantoea strains directly from the surface of these seeds. When we applied these culturable isolates to seeds, we found that individual strains were as protective when applied in isolation as when combined. In order to understand how application density impacts protection, we varied the dose of isolates ZM1, ZM2, and ZM3, and we found a non-linear pattern of inoculation density correlation with pathogen density. The seed surface is the primary site of contact between seed and fruits, and it is known to harbor a diversity of microbes across plant species. Despite this, few studies have included seed epiphytes when investigating seed-associated microbes, focusing primarily on seed endophytes , endogenous seed-microbiota were found to suppress disease symptoms in juvenile seedlings of their natural hosts when challenged with a common tomato pathogen, Pst . When TT4 microbiota was inoculated onto two other field tomato types, it was able to significantly reduce disease symptoms and decrease the density of Pst by 10 to 100-fold . Although the tomato types themselves differed in their overall susceptibility to disease, we did not observe that any single tomato type was more protected by the TT4 microbiome than another. This may suggest that the pathogen- suppressive effects of TT4, pipp mobile storage whether attributable to microbiome members with antagonistic activities against Pst or immune system priming, are capable of acting independently of their host genotypic context.

Due to the way in which tomatoes were collected , we were not able to point to the specific differences amongst host genotypes, but this would be useful in future studies. Furthermore, as we did not sequence the microbiome of adult plants from which seeds were collected, future work should explore if differences amongst seed microbiomes are driven by differences in the microbiome composition of the adult plants themselves. These microbiome differences may be a result of field location, host genotype, or other unknown factors. Our data suggest that it may be possible to breed plants to specifically recruit or harbor beneficial seed microbiomes that may ensure a more disease resistant crop in subsequent generations. To better understand the protective effects observed, we sequenced the bacterial communities associated with seedlings inoculated with the TT4 microbiome and found the communities to be dominated by Pantoea spp . This is in line with community profiling results from the seed surface of Triticum and Brassica. We then isolated culturable bacteria from seeds, and again found primarily Pantoea spp. Inoculation of seeds with our Pantoea isolates showed that they are highly protective against Pst, both in terms of colonization and disease . Pantoea spp. is a known antagonist of many bacterial as well as fungal pathogens, and they are common biocontrol strains. Pantoea dispersa strain ZM1 appears to be novel and not previously described as a biocontrol species, but provides protection that is on par with, if not better than, currently commercially available strains. Genome sequencing will reveal if P. agglomerans strains ZM2 and ZM3 are novel bio-control strains. Our work also helps to disentangle the link between diversity and disease protection. Although there exists a speculative relationship between taxonomic diversity and the strength of a microbiome’s disease-resistance effect, little empirical evidence exists to support or disprovethis.

A recent study on the protective effect of a constructed community against Pst shows that variation in inoculum diversity affects disease-resistant effects in a significantly non-linear manner, demonstrating that increasing taxonomic diversity can have no impact, or even decrease, the protective effect of the community. In this study, seedling bacterial communities are low in richness and diversity, dominated primarily by one genus: Pantoea, although there are multiple species and strains of Pantoea. It is possible that a greater diversity of bacteria existed on the seeds, but we still find that inoculation of individual strains of Pantoea is sufficient in seedlings for protection against the pathogen used in this study. We are also aware that the fermentation step used to collect seeds might have enriched certain members of the seed microbiome that are able to survive acidic conditions. However, this may be a biologically relevant filtering step for epiphytic seed microbes, as seeds are likely to experience acidic conditions both during fermentation of fruit in the field or through the digestive track of animals. Although we only test the protective ability of isolates against a bacterial pathogen, the Pantoea isolates and the Bacillus isolate may have other growth promoting capabilities as well, as a recent paper describes various growth promotion traits of tomato seed endophytes. They may also have protective effects against fungal pathogens, as has been previously demonstrated in Pantoea species. Practically, seed associated bacteria are an excellent target for probiotic/biocontrol application, and it may even be possible to apply the protective strain to the flowers of the previous generous, as was demonstrated with a plant growth promoting endophyte. Taken together, these studies and our results suggest that the common agricultural practice of seed sterilization may be disrupting persistent mutualisms between plants and microbes across generations.

While seed sterilization is an agriculturally important procedure to purge seed-transmitted pathogens, we and other groups have shown that it may also be removing beneficial symbionts. How the simultaneous disruption of pathogenic and mutualistic symbioses would impact host health over ecological time scales, and how agricultural practices should preserve the beneficial traits conferred by the vertically transmitted microbiome while still preventing the spread of pathogens, are outstanding questions in need of future research. The focus of this work was to examine the potential protective effects of seed epiphytic communities rather than describe the mechanisms underlying protection. Previous work has demonstrated that some Pantoea spp. are protective through antibiosis activity, or it may also be mediated through competition for resources. In addition to direct interactions between microbes, application of Pantoea spp. to seeds ensures that germinating seedlings are in immediate contact with microbes, and this may prime the plant’s immune system so that it is better able to mount a response against Pst, thus indirectly protecting against disease. In our experiments, the data suggest that both direct and indirect mechanisms are mediating protection. We find that all strains of live bacteria, including a non-plant associated strain of E. coli, are capable of decreasing disease severity symptoms when compared to non-treated controls. When seeds are treated with UV-killed bacteria, we find that none of the strains are capable of decreasing disease severity. Our results suggest that all bacteria included in our experiment can protect seedlings against Pst through direct interactions, as UV-killed bacteria were unable to decrease disease severity. Additionally, we found that all live isolates except for E.coli lowered Pst densities in seedlings, suggesting that this characteristic may be unique to our Pantoea isolates. When seedlings were treated with UV-killed bacteria, we again found that ZM1, ZM2, and ZM3 were capable of lowering Pst densities, but E.coli was not. This suggests that some of the protective capability we are observing is conferred through indirect mechanisms, grow rooms perhapsthrough immune activation by UV-resistant membrane-bound antigens. The inability of UVkilled E. coli to decrease Pst density suggests that these Pantoea strains may have plant host or pathogen specific protective traits. Future work will explore the protective ability of these isolates in adult plants and will further dissect direct versus indirect mechanisms of protection.

By varying the concentration of Pst inoculated onto seedlings, we observed that increasing Pst increases AUDPC, as expected . Interestingly, we also observed a decoupling of plant disease symptoms and pathogen density. This was similarly observed when we tested for protective effects of each isolate . Here, we saw a linear increase of disease severity as Pst inoculation was increased in inoculation density, but saw a much weaker linear correlation between dose and Pst densities. We posit that this non-linear increase of Pst density might either be due to 1) a carrying capacity of Pst density that is reached on the seedling leaves, or 2) the possibility that the detection of dead or inactive Pst cells disguises a linear pattern. Furthermore, disease severity was calculated based on foliar symptoms, but it is very likely that Pst also asymptomatically colonizes the seedling root tissue. The entire seedlings, including roots, were homogenized prior to Pst quantification; this may have obscured differences in foliar Pst densities. By varying the dose of the protective strain , we were able to find that an increased dose does not necessarily correlate with decreased pathogen density, as was recently uncovered in a study investigating the protective effects of the phyllosphere community in adult tomato plants. We vary the dosage of protective Pantoea strains from less than one CFU/seed to 108 CFU/seed, the highest of which is five orders of magnitude higher than the concentration at which we originally recovered bacteria on the seeds . When analyzing Pst density seven days after inoculation, all culturable isolates’ ability to Pst suppress growth resulted in a non-linear pattern of pathogen density, whereby increasing Pantoea does did not linearly correlate with decreasing Pst density. The same is true for the two commercially available bio-control strains. Most notably, all three TT4 isolates exhibit optimal suppression of Pst at densities close to that found in naturally occurring seeds . At isolate densities above 104 CFU/seed, Pst density as detected by ddPCR, reached a similarly high level for all strains, suggesting a maximum density beyond which additional cells of the protective strains do not result in further protection. In light of our results that UV-killed Pantoea are capable of decreasing Pst density through presumed plant-immune activation, we posit that this activation, or priming, may be dependent on bacterial density on the seeds. In such a model, induction of resistance responses in the plant would be fully activated when such a threshold of signal is achieved. This is further supported by the result that UV-killed isolate C9-1 was the only Pantoea isolate unable to decrease Pst density , and its dose response curve was also the only one that did not follow the cubic pattern observed in the other Pantoea isolates. To rule out the possibility that higher densities of Pantoea resulted in the killing of Pst, a scenario that would be undistinguishable because of the use of ddPCR to quantify the pahtogen, we treated samples with a PMAxx TM and repeated the ddPCR. The data are quantitatively similar , indicating that even when only live cells are quantified, Pst densities reach an asymptote. Our results are suggestive of the possibility that plants may not only preferentially passage beneficial symbionts, . Tomato Type 1-3 were collected from non-neighboring lanes from one field, and the heirloom variety program; USDA-NIFA award # 2015-51300-24157 was collected from a neighboring field. Fruits were transported to UC Berkeley on ice and immediately stored in 4°C until processing. Intact tomato fruits from the same type were pooled in a sterile 1L beaker until they reached roughly the 500 mL line . To ensure that no additional microbes other than those found naturally were introduced to the seed surface, we surface sterilized the tomato fruits themselves before processing of seeds. Tomatoes were submerged in 75% ethanol for 20 minutes. They were then washed with sterile double-distilled H2O three times. The last wash was plated onto Kings Broth agar, and no colony forming units were detected. Sterilized tomatoes were then pooled into another sterile one-liter bottle, crushed with sterile forceps and spatula until becoming a thick fruit mixture, and allowed to ferment at room temperature for seven days. We employed this as a common seed collection method for removal of seeds from the fruit endocarp. After fermentation, seeds were then strained out from the fermented liquid with a sterilized metal strainer, minimally washed with sterile ddH2O to remove any excess fruit, and dried on filter paper within sterile petri dishes. All procedures were carried out sterilely in a Biological Safety Cabinet. Harvested seeds were stored in sterile petri dishes in darkness at 21°C, and these same seed stocks were used for all experiments.

These results confirm that, even without the celestial instruments used by Europeans at the time of their arrival , the people in the Basin of Mexico could maintain an extremely precise calendar that would have allowed for leap-year adjustments simply by using systematic observations of sunrise against the eastern mountains of the Basin of Mexico. A recent report indicates than an average American consumes about 17 teaspoons of added sugar daily, which is nearly twice the amounts of the 6 and 9 teaspoons, recommended for women and men, respectively. This dietary behavior is linked to various adverse health effects such as increased risk of diabetes, obesity, high blood pressure and cardiovascular diseases. Hence, there are worldwide efforts to reduce sugar consumption. For instance, the World Health Organization made a conditional recommendation to reduce sugar consumption to less than 5% of the total caloric intake, along with a strong recommendation to keep sugar consumption to less than 10% of the total caloric intake for both adults and children. Currently, added sugar consumption accounts for approximately 11–13% of the total energy intake of Canadian adults, is greater than 13% in the US population, and is as high as 17% in US children and adolescents, the latter principally from sugar-sweetened beverages . Consequently, taxes on SSB have been proposed as an incentive to change individuals’ behavior to reduce obesity and improve health. Notably, dry racks for weed the city of Berkeley, CA, USA successfully accomplished a 21% decrease in SSBs consumption within a year of implementation. Therefore, it is expected that more states and cities will adopt this policy.

On the regulatory level, the U.S. Food and Drug Administration updated the Nutrition Facts label requirement on packaged foods and beverages, starting 1 January 2020, to declare the amount of added sugars in grams and show a percent daily value for added sugar per serving. The expansion of these efforts to spread the awareness on sugar consumption habits and the resulting health issues has generated demand for safe, nonnutritive sugar substitutes. There are many sweeteners on the market to help consumers satisfy their desire for sweetness; however, each of the sweeteners available to consumers has specific applications and certain limitations. Artificial sweeteners have been used as sugar substitutes in numerous applications; however, their long-term effects on human health and safety aspects remain controversial. For example, ATS appear to change the host microbiome, lead to decreased satiety, alter glucose homeostasis, and are associated with increased caloric consumption and weight gain. Moreover, some health effects such as dizziness, headaches, gastrointestinal issues, and mood changes are associated with the consumption of a commonly used ATS, aspartame. Additionally, Kokotou et al. have demonstrated the impact of ATS as environmental pollutants, concluding that when artificial sweeteners are applied in food products or eventually enter the environment, their transformation and/or degradation may lead to the formation of toxic substances. Consequently, there is currently an increase in the production of natural sugar alternatives based on the shift in consumer preferences toward more natural products to meet their dietary need and restrictions. Stevia, the common name for glycoside extracts from the leaves of Stevia rebaudiana, is a natural, sweet-tasting calorie-free botanical that is currently gaining popularity as a sugar substitute or as an alternative to artificial sweeteners. Recent reports project the annual growth rate of stevia compounds to be 6.1% and 8.2%, during 2015–2024 and 2017–2024, respectively.

Stevia has gained industry acceptance in recent years due to its ease of cultivation in several countries across the globe and its high sweetness index . This shows that the growth of stevia’s use as a sugar substitute, despite taste limitations of the marketed glycosides, was contingent on the feasibility of its large-scale manufacturing. Thaumatin, monellin, manbinlin, pentadin, brazzein, curculin, and miraculin are sweet tasting proteins that are naturally expressed in tropical plants. Studies have found that human T1R2-T1R3 receptors expressed in taste buds in the mouth and recognize natural and synthetic sweetness while T1R1-T1R3 recognize the umami taste. These receptors, which have several binding sites, are activated when the compounds that elicit sweet taste bind to them. However, these proteins have unique binding properties and do not all bind at the same sites, which leads to varying perception of sweetness. This work focuses on thaumatins, a class of intensely sweet proteins isolated from the arils of the fruits of the West-African plant Thaumatococcus daniellii. The distinctiveness of thaumatin lies in its sweetness index being up to 3500 times sweeter than sugar. According to the 2008 Guinness World Records, it is the sweetest natural substance known to mankind. Thaumatin I and II, the two main variants of the protein, are comparable in their biological properties, structure, and amino acid composition. The structure consists of a single polypeptide chain of 207 amino acids that are linked together by 8 disulfide bonds. The two variants differ by only five amino acid residues. Through chemical modifications and site-directed mutagenesis, it has been determined that the residues on the cleft-containing side of the protein have the strongest effect in eliciting sweetness to taste receptors on the tongue. The specificity of these residues demonstrates the importance of the protein structure in inducing thaumatin’s sweetness.

In the USA, extracted thaumatin and thaumatin B-recombinant were initially affirmed Generally Recognized as Safe flavor enhancers/modifiers, but not as sweeteners. In the USA, plant-made thaumatin I and/or thaumatin II were granted GRAS status by the FDA in 2018 for use as a sweetener . In 2020, the FDA granted GRAS status to recombinant thaumatin II produced in Nicotiana plants for use as a sweetener and as a flavor enhancer/modifier . In the EU, thaumatins are allowed as both sweeteners and flavor enhancers. Thaumatin’s safety has been extensively documented. The Joint FAO/WHO Expert Committee on Food Additives report claims that the protein is free from any toxic, genotoxic, or teratogenic effects. Thaumatin is currently used as a flavor modifier in food applications such as ice creams, chewing gum, dairy, pet foods, soft drinks, and to mask undesirable flavor notes in food and pharmaceuticals. The current top global thaumatin manufacturers are Naturex , France; Beneo Palatinit, Germany; Natex, UK and KF Specialty Ingredients, Australia. The global production of thaumatin increased to 169.07 metric tons in 2016 from 138.47 MT in 2012. However, the current production method through aqueous extraction from the fruits of the tropical plant T. daniellii limits its availability while the demand is increasing. T. daniellii is not cultivated and harvesting of the arils takes place in plants growing wild in rainforests of West Africa ranging from Sierra Leone to the Democratic Republic of Congo. The current production process is substantially dependent on the availability and quality of the native plant from year to year, which limits thaumatin’s use as a commodity product. The emergence of recombinant DNA technology and the use of cultured cells have allowed the production of proteins in large quantities. Enzymes and structural proteins are used in many industrial applications including the production of food and beverages, biodiesel, cosmetics, biopolymers, cleaning materials, and waste management. Most importantly, recombinant production allows for the expression of a protein outside its native source. Therefore, there exists a viable alternative to secure the desired quantities of thaumatin reliably and sustainably, without impacting rainforest ecosystems. Notably, there have been many attempts to produce thaumatin by means of genetically engineered microorganisms and plants. Despite successfully expressing thaumatin in yeast, bacteria, fungi, and transgenic and transfected plants, biotechnological large-scale production facilities have yet to be established. Molecular farming, the production of recombinant proteins in plants, offers several advantages over bioreactor-based systems. In this application, plants are thought of as nature’s single use bioreactors, offering many benefits such as reduced upstream production complexity and costs , linear scalability, and their inability to replicate human viruses. Specifically, open-field growth of plants has the potential to meet the market’s need for a large-scale, continuous demand of a commodity product at a competitive upstream cost. It has been marked suitable for this operation as plants can be easily adapted on an agricultural scale to yield several metric tons of the purified protein per year. Here, we present a feasibility study for a protein production level of tens of metric tons per year. The success of a new product in the biotechnology process industry depends on well-integrated planning that involves market analysis, product development, process development, hydroponic rack system and addressing regulatory issues simultaneously, which requires some decisions to be made with limited information. This generates demand for a platform to help fill in those gaps and facilitate making more informed process and technology decisions.

Process simulation models can be used in several stages of the product life cycle including idea generation, process development, facility design, and manufacturing. For instance, based on preliminary economic evaluations of new projects, they are used to eliminate unfeasible ideas early on. During the development phase of the product, as the process undergoes frequent changes, such models can easily evaluate the impact of these changes and identify cost-sensitive areas. PSMs are also useful for directing lab and pilot-scale studies into areas that require further optimization. Additionally, PSMs are widely used in designing new manufacturing facilities mainly as a tool for sizing process equipment and supporting utilities, as well as for estimating the required capital investment and cost of goods. This ultimately helps companies decide on building a new facility versus outsourcing to contact manufacturers. There are currently few published data-driven simulations of techno-economic models for plant-based manufacturing of proteins for pharmaceutical, bio-fuel, commercial enzyme, and food safety applications. However, to the best of our knowledge, no studies have proposed or assessed the feasibility of plant-based protein bio-production platforms on the commodity scale in tens of metric tons per year. The feasibility of production at this scale is critical for the emergence of thaumatin as a sugar substitute. Here, we present a preliminary process design, process simulation, and economic analysis for the large-scale manufacturing of thaumatin II variant by several different molecular farming production platforms.The base case scenario assumes an annual production capacity of 50 MT thaumatin. To achieve this level of production in a consistent manner, manufacturing is divided into 157 annual batches. Upstream production is attainable through open-field, staggered plantation of Nicotiana tabacum plants. Each batch has a duration of 45 days and a recipe cycle time of 2 days. A full list of process assumptions can be found in Table S1. The proposed design achieves the expression of thaumatin in N. tabacum leaves using magnICON® v.3. This technology developed by Icon Genetics GmbH allows for the separation of the “growth” and the “expression” phases in a manufacturing process. Moreover, this process obviates the need to use agroinfiltration, which requires more capital and operational costs for inoculum preparation and implementation of expensive units for the infiltration process, containment of the genetically engineered agrobacteria, and elimination of bacteria-derived endotoxins. In this design, transgenic N. tabacum or N. benthamiana plants carry a double-inducible viral vector that has been deconstructed into its two components, the replicon and the cell-to-cell movement protein. Background expression of recombinant proteins prior to induction remains minimal; however, inducible release of viral RNA replicons—from stably integrated DNA proreplicons—is triggered upon spraying the leaves and/or drenching the roots with a 4% ethanol solution resulting in expression levels as high as 4.3 g/kg fresh weight in Nicotiana benthamiana. Nonetheless, Nicotiana tabacum has several advantages that make it more suitable for large-scale open field production such as field hardiness, high biomass yields, well-established infrastructure for large-scale processing, plentiful seed production, while attaining expression levels up to 2 g/kg FW. Furthermore, it is unlikely that transgenic tobacco material would mix with material destined for the human food or animal feed chain, unless it is grown in rotation with a food crop, but further development of strict Good Agricultural Practice for transgenic plants should overcome these issues.An alternative upstream facility design scenario was developed to evaluate the process economics of a more controlled supply of thaumatin by growing the plant host in a 10-layer vertical farming indoor environment. Nicotiana benthamiana is chosen as a host because it is known to be a model for protein expression for both Agrobacterium and virus-based systems, but its low biomass yield and difficulties regarding adaptation in the field hinder its application for open outdoor growth. However, this species grows very well in indoor, controlled environments and has high recombinant protein production.

AAFNs work “against the logic of bulk [high volume, low cost] commodity production, alternative food networks redistribute value through the food chain, reconvene ‘trust’ between producers and consumers, and articulate new forms of political association and market governance” . They are often, but not always, rooted in agroecological farming practices . AAFNs regularly use the trust and engagement generated through alternative forms of distribution to increase access to healthy, fresh, and diverse foods among consumers while providing farmers with diverse revenue streams, and risk sharing and direct marketing strategies that cut the costs of distribution and decrease reliance on industrialized agri-food systems. AAFNs generally emerge as partnerships connecting DFS farmers with citizens, consumers, governments, food and agricultural enterprises, and environmental and social justice organizations through the development of various institutions ranging from farmers’ markets, urban gardens, and community-supported agriculture at local and regional scales, to fair trade producer cooperatives, slow food movements, and peasant organizations at the global scale . These partnerships represent a new wave of social activism as Northern and Southern communities and NGOs increasingly focus on the politics and cultures of food, pipp racking system and identify economic incentives to transform industrialized agrifood into alternative systems that seek to produce and distribute healthy, environmentally sustainable, and socially just food.

The equitable treatment of producers is central to achieving broader adoption of DFS. If farmers are impoverished or are forced to compete with subsidized producers or importers from the industrialized food system, they are less likely to sustain diversified farming practices. Farmers markets are one example of efforts that more equitably support small-scale producers, as well as urban consumers. The estimated 7525 farmer markets in the U.S. offer local civic outlets that may generate social, economic, and cultural incentives for DFS among local farmers while encouraging a more diverse diet of fresh foods among eaters . Farmers markets can provide a mechanism for farmers to reach consumers directly, educate them about DFS practices, and bypass the processing and distribution infrastructure of the industrialized agri-food systems. Yet, while farmers markets and other AAFNs may help develop and maintain DFS and vice versa, they do not yet adequately recognize ecological diversification and sustainability as core values. Farmers markets often provide a venue for organic agriculture, but they rarely use ecological sustainability as a criterion for allowing producer participation, and such markets may also include organic foods harvested from industrial monoculture . In addition, while farmers markets may improve equity for smaller scale growers, they may not provide equity for consumers. Although recent policies have sought to address these challenges, less than 20% of farmers markets accepted food assistance vouchers in 2009 . Farmers markets may not reach poorer socioeconomic groups, due to both price and location.

Efforts are underway to increase the number of farmers markets accepting government food assistance vouchers . In Northern countries, environmental justice advocates have recently started to promote sustainable agriculture and/or agroecology as part of a multi-pronged, holistic strategy for pursuing food and environmental justice across the entire production chain to remedy the environmental inequalities associated with industrialized agricultural systems . These inequalities can be traced back to how, under what conditions, and by whom food is produced, processed, distributed, and consumed, and the role of corporations and governments in shaping these conditions. Food justice issues include the unfair treatment of workers in housing, health, and labor conditions ; agrochemical exposure health risks to workers, communities, and consumers ; loss of ecosystem services such as water and soil ; creation of pollution/wastes that affect surrounding communities ; lack of farm and food worker access to healthy foods ; and loss of access to land . By addressing these issues, food justice activism is evolving toward a strategy that encompasses both social justice and ecological sustainability . These local and national efforts are complemented by several international projects to create AAFNs and connect them to sustainable agriculture. One example is the global fair trade movement, which aims to enable consumers, often in developed countries, to pay more equitable prices to cover the full costs of production and ensure sustainable farmer livelihoods. Fair trade is not synonymous with DFS or sustainable agriculture because its criteria focus primarily on the social and economic aspects of trade and production.

However, the Mesoamerican smallholders who cofounded this movement with political and religious activists manage agricultural systems that are far closer to DFS than industrial monocultures . Their shade coffee systems now often resemble native forests and help conserve biodiversity, reduce soil erosion, conserve water, improve microclimates and resist hurricane damage . Farmers’ connections to smallholder cooperatives and global fair trade networks also partially mitigated vulnerability to crashing coffee commodity prices . New social movements also increasingly promote agroecology as central to their agenda for transforming the industrialized agri-food system at local, national, and global scales . In particular, a food sovereignty agenda has emerged from the aspirations and survival needs of smallholders and indigenous social movement leaders in the Global South . Food sovereignty refers to the right of local peoples to control their own agricultural and food systems, including markets, resources, food cultures, and production modes, in the face of an increasingly globalized economic system. This approach contrasts with charity-based food security models that have occasionally buffered human populations from famines , yet do not address root causes of hunger and care little for how, where, and by whom food is produced . It also contrasts with dominant neoclassical trade liberalization policies that open up domestic markets worldwide to competition from multinational corporations, which has often resulted in import dumping, the erosion of smallholder livelihoods, and greater industrialization of agriculture . Food sovereignty movements promote agrarian reforms, resist state and corporate land grabs, and critique proposals that contribute to farmer debt and dependence . In recent decades, the food sovereignty movement has endorsed the agroecological approaches and the social process methodologies promoted through the Campesino-aCampesino movement . Despite the potential of AAFNs such as farmers markets and fair trade networks to sustain and promote DFS, many alternative agri-food activities have come to resemble the industrialized agri-food systems they set out to transform. For example, the dramatic growth in organic sales in the past two decades facilitated by product certification has promoted the expansion of large-scale industrialized organic monocultures to supply this new demand even though the founding principles of organic agriculture included DFS practices . Alternative producers sometimes justify this by arguing that large-scale, industrialized methods are the fastest way to “scale up” alternative farming practices so that they can compete in supply chains with conventionally managed systems . In search of new markets, many dominant food corporations have purchased and integrated successful organic producers and alternative food companies into their product portfolios . This trend of purchasing “sustainable” product businesses is also observed in other sectors, such as personal care, paper, and cleaning chemicals. A growing body of literature on green consumerism raises the issue of corporate “green washing”. Researchers suggest that expanding corporate control over alternative products can generate some benefits . Yet these changes may accelerate efforts to industrialize production rather than expand alternative systems . These developments call for careful scrutiny of the changing standards, price premiums, ingredients, farm level practices, and benefits to producers and consumers .In parallel, fair trade labeling organizations initially certified exports from smallholder organizations only, thus frequently supporting DFS. However, recent changes to standards now allow transnational agricultural trade companies to export certified Fair Trade products in direct and potentially unfair competition with the smallholder organizations that this system intended to empower .

The dominant U.S. Fair Trade certification agency has ignored strong protests from smallholder farmer organizations in recently allowing large coffee plantations to sell certified Fair Trade coffee. For instance, a growing portion of Fair Trade certified coffee sold in the U.S. now originates in Brazil and Colombia in production systems supporting fewer and less diverse shade trees than Mesoamerican smallholders . In this light, pipp vertical racks many enterprises and organizations within the rapidly mainstreaming AAFNs are now trying to restrengthen their connections to sustainable agriculture and their original social goals through innovative organizational reforms. They are de-emphasizing the certification systems that they once pioneered and moving toward food sovereignty and food justice that promote the power of participants to control or coordinate their parts of the larger food system. These trends could enable the spread of DFS while simultaneously promoting the often overlooked social equity and participatory process dimensions of sustainable agriculture . However, until recently, these movements have represented relatively small counter trends compared to the dominant certified and organic components of the industrialized agrifood system. Certifications and market-based incentives could be an important component of many DFS oriented transition processes. However, broader institutional support is certainly needed. Furthermore, the leading sustainability certifications increasingly do not appear to reward the diverse forms of ownership, management, and local collaboration that would be needed to ensure the landscape-scale nature of DFS, and their standards have become increasingly flexible as they increasingly include industrial production systems .The expansion of large-scale industrialized monoculture systems of agriculture often occurs at the expense of more diversified farming systems. The widespread transformation of agriculture to large-scale monoculture systems began with the European colonial plantations of the 1500-1800s , and expanded with the mechanization of agriculture in the late 1800s and the introduction of synthetic fertilizers and pesticides by the mid 20th century. By the 1960s, a wave of agricultural science and technological innovations had created the “Green Revolution,” an integrated system of pesticides, chemical fertilizers, and genetically uniform and high-yielding crop varieties that governments, companies, and foundations vigorously promoted around the world . In the subsequent fifty years, the expansion of industrialized agriculture increased global nitrogen use eight fold, phosphorus use tri-fold, and global pesticide production eleven-fold . By 2000, Green Revolution crop varieties were broadly adopted throughout the developing world, e.g., circa 90% of Latin America for the area under wheat, and circa 80 % in Asia for the area under rice , and the world’s irrigated cropland doubled in area . Encouraged by a range of economic factors, including the incentives of U.S. federal commodity programs, the pressures of global market competition, neoliberal economic reforms, historically inexpensive synthetic inputs, and the advantages of economies of scale, field and farm sizes increased in some areas, while non-crop areas in and around farms decreased, leading to higher levels of homogeneity at both the field and landscape scale . Several recent signs of the continued expansion of industrial agriculture are seen in the rapid growth of land grabs, bio-fuel production, and plantations across the Global South. Land grabbing refers to the practice of agri-food companies, commodity traders, pension funds, and nationally-owned investment banks buying land in other countries for eventual large-scale food and resource production in response to food security concerns and food speculation . For example, the provincial government of Rio Negro in Argentina recently agreed to lease up to 320,000 ha of land to Beidahuang, a Chinese government-owned agri-food company, to produce soybeans, wheat, and oilseed rape primarily for animal feed . Local farming communities are now organizing against the deal, contending that they will be displaced by the industrialized irrigation methods being planned. Estimates of the global scale of land grabbing are scarce and largely based on media reports. Whereas the International Food Policy Research Institute estimates that 20 million ha of land were sold for land grabs between 2005 and 2009, the World Bank calculates that around 57 million ha have attracted foreign interest . The expansion of large-scale commercial agriculture has also caused deforestation of some of the most bio-diverse forests in the world, such as in the Amazon, for soybean production , and in Southeast Asian rain forests, for oil palm . Since the 1990s, particularly in Brazil and Indonesia where the greatest amount of deforestation occurred, the agents of deforestation shifted from primarily smallholder to enterprise-driven agriculture for global markets . Much recent forest loss, along with agricultural land conversion, can be attributed to the rapid growth in bio-fuel production, centering in Southeast Asia and Latin America but expanding to Africa.

The uppermost section of the annulus is normally sealed with a bentonite clay and cement grout to ensure that no water or contamination can enter the annulus from the surface. The depth to which grout must be placed varies by county. Minimum requirements are defined in the California Well Standards : 50 feet for community water supply wells and industrial wells and 20 feet for all other wells. Local county ordinances may have more stringent requirements depending on local groundwater conditions. At the surface of the well, a surface casing is commonly installed to facilitate the installation of the well seal. The surface casing and well seal protect the well against contamination of the gravel pack and keep shallow materials from caving into the well. Surface casing and well seals are particularly important in hardrock wells to protect the otherwise open, uncased borehole serving as a well.Wells can be constructed in a number of ways. The most common drilling techniques in California are rotary, reverse rotary, air rotary, and cable tool. Auger drilling is often employed for shallow wells that are not used as supply wells. In unconsolidated and semi-consolidated materials, rolling benches rotary and cable tool methods are most commonly employed. Hardrock wells generally are drilled with air rotary drilling equipment. Properly implemented, all of these drilling methods will produce equally efficient and productive wells where ground water is available.

Reverse rotary and rotary drilling require large amounts of circulation water and the construction of a mud pit, something to be considered if the well is to be drilled in a remote location with no access to water. During drilling, drillers must keep a detailed log of the drill cuttings obtained from the advancing borehole. In addition, after the drilling has been completed but before the well is installed, it is often desirable to obtain more detailed data on the subsurface geology by taking geophysical measurements in the borehole. Specialized equipment is used to measure the electrical resistance and the self-potential or spontaneous potential of the geological material along the open borehole wall. The two most important factors that influence these specialized logs are the texture of the formation and the salinity of the ground water. Sand has a higher resistance than clay, while high salinity reduces the electrical resistance of the geological formation. Careful, professional interpretation of the resistance and spontaneous potential log and the drill cuttings’ description provides important information about water salinity and the location and thickness of the aquifer layers. The information obtained is extremely useful when finalizing the well design, which includes a determination of the depth of the well screens, the size of the screen openings, and the size of the gravel pack material. Because of timing issues, it is better—especially in remote areas—to drill a pilot hole a good deal ahead of the well construction date and obtain all pertinent log information early on from the pilot hole. The well design can then be completed and the proper screen, casing, and gravel materials can be ordered for timely delivery prior to the drilling of the well. Note that a copy of all well log information should be given to the person who pays for the drilling job.

The Department of Water Resources keeps copies of all well logs and has a large collection of past well logs. These can be requested by a well owner if the original records are unavailable. The well log contains important information about construction details and aquifer characteristics that can be used later for troubleshooting well problems.After the well screen, well casing, and gravel pack have been installed, the well is developed to clean the borehole and casing of drilling fluid and to properly settle the gravel pack around the well screen. A typical method for well development is to surge or jet water or air in and out of the well screen openings. This procedure may take several days or perhaps longer, depending on the size and depth of the well. A properly developed gravel pack keeps fine sediments out of the well and provides a clean and unrestricted flow path for ground water. Proper well design and good well development will result in lower pumping costs, a longer pump life, and fewer biological problems such as iron-bacteria and slime build-up. Poorly designed and underdeveloped wells are subject to more frequent pump failures because sand and fines enter the well and cause significantly more wear and tear on pump turbines. Poorly designed and underdeveloped wells also exhibit greater water level draw down than do properly constructed wells, an effect referred to as poor well efficiency. Poor well efficiency occurs when ground water cannot easily enter the well screen because of a lack of open area in the screen, a clogged gravel pack, bacterial slime build-up, or a borehole wall that is clogged from incomplete removal of drilling mud deposits. The result is a significant increase in pumping costs. Note that well efficiency should not be confused with pump efficiency.

The latter is related to selection of a properly sized pump, given the site-specific pump lift requirements and the desired pumping rate. Once the well is completed and developed, it is a good practice to conduct an aquifer test . For an aquifer test, the well is pumped at a constant rate or with stepwise increased rates, typically for 12 hours to 7 days, while the water levels in the well are checked and recorded frequently as they decline from their standing water level to their pumping water level. Aquifer tests are used to determine the efficiency and capacity of the well and to provide information about the permeability of the aquifer. The information about the pumping rate and resulting pumping water levels is also critical if you are to order a properly sized pump. Once the well development and aquifer test pumping equipment is removed, it may be useful to use a specialized video camera to check the inside of the well for damage, to verify construction details, and to make sure that all the screen perforations are open.The construction of the final well seal is intended to provide protection from leakage and to keep runoff from entering the wellhead . Minimum standards for surface seals have been set by the California Department of Water Resources . It is also important to install back flow prevention devices, especially if the well water is mixed with chemicals such as fertilizer and pesticides near the well. A back flow prevention device is intended to keep contaminated water from flowing back from the distribution system into the well when the pump is shut off.The development of multi-benefit land use practices that reconcile the needs of human societies with ecosystem function are critically important to biodiversity conservation given human population growth and the concurrent expansion of terrestrial land surface dedicated to agriculture. Accordingly, reconciliation ecology, which is the practice of encouraging biodiversity in the midst of human dominated ecosystems by specifically managing the landscape for the benefit of fish and wildlife has become an increasingly important component of global conservation efforts. This is especially true in freshwater habitats which constitute less than 1% of Earth’s land surface yet support freshwater fish species that make up approximately one third of all known vertebrates and where loss of biodiversity appears to be more rapid than in any other habitat type. Even among imperiled freshwater habitats, rivers and their associated floodplains stand out as among the most altered ecosystems in the world. They are also among the most desirable and agriculturally productive landscapes globally and therefore ideal locations for case-studies on innovative reconciliation ecology-inspired, multi-benefit land use innovations. Furthermore, these lands are managed to perform economically valuable functions of human food production and flood risk mitigation while simultaneously providing critical ecosystem benefits such as nutrient cycling, aquifer recharge, habitat creation, rolling grow table and conservation of biodiversity in heavily altered landscapes. Managing agricultural floodplain habitats in ways that approximate natural riverine processes re-exposes native species to physical habitat conditions similar to those to which they are adapted and may therefore enhance fitness and survival. To date, most North American work to reconcile working agricultural floodplain farmlands with the needs of wildlife has focused on waterfowl conservation. However, in Asia fish have been reared in rice fields for thousands of years, providing a valuable protein resource, natural fertilizer for agricultural fields, and refugia/food for native fishes. This paper explores means by which fish conservation can be integrated into the management of actively farmed rice fields on the agricultural floodplains of the Sacramento Valley, California. Chinook Salmon are in steep decline throughout California. A conservative pre-European establishment fish population estimate in the Central Valley was 2 million annual adults returning to spawn, which sustained a sizable commercial ocean fishery.

Prior to the mid-1800s, California’s Central Valley was estimated to contain more than 4 million acres of seasonal floodplain and tidal wetlands which provided abundant food resources for rearing juvenile Chinook Salmon. Of the historic wetland habitats in California, approximately 95% of floodplain habitat has been disconnected from rivers by levees and channelization, drastically reducing quality rearing conditions for out-migrating salmon. Though most of the historical alluvial floodplain in California is now inaccessible to salmon, some productive seasonal wetlands persist, presenting opportunities for conservation. In particular, winter-flooded rice fields within the Sacramento Valley flood protection bypasses–flood ways which route floods away from cities and which are designed to drain floodwaters rapidly in order to accommodate agricultural production–hydrologically connect to the river and can be managed to promote environmental conditions that resemble natural off channel habitat. Use of existing berms and water control structures used in rice propagation to prolong the duration of floodplain inundation on these managed floodplain wetlands during the winter and early spring seasons approximates the long-duration inundation of floodplains that typically occurred on Central Valley floodplains prior to the widespread wetland reclamation and levee construction in the 19th and 20th centuries. Inundation duration of several weeks facilitates the development of highly productive invertebrate food webs and improved foraging opportunities for fish. Chinook Salmon reared in floodplain and off channel habitats experience more rapid growth rates compared to those rearing in adjacent leveed river channels rivers due to more abundant invertebrate prey. For anadromous salmonid species such as Chinook Salmon improved growth during the freshwater juvenile stage is correlated with larger size at ocean entry and increased survivorship to adulthood. While the potential benefits to juvenile Chinook Salmon rearing on flooded bypasses is well established, there is little published research testing methodologies for establishing the optimal physical and biological conditions to achieve maximal benefit on these managed floodplains. Such is the primary goal of this study: to compare potential management practices intended to enhance the habitat benefits to juvenile Chinook Salmon of winter-inundated, post-harvest rice fields on the Yolo Bypass floodplain of the Sacramento Valley of California. This paper reports results from work conducted on a 7.3-hectare agricultural floodplain laboratory over four consecutive years beginning in 2013 and ending in 2016. Studies were built on an adaptive framework in which each year’s results are used to refine experimental approaches in subsequent field seasons. Listed sequentially, annual investigations included studying the effects of 1) post-harvest field substrate; 2) depth refugia; 3) duration of field drainage; and 4) duration of rearing occupancy on in-situ diet, growth and survival of juvenile salmon. It is our hope that the data produced by these controlled, field-scale experiments will inform farm, water, and flood resource managers as they continue to develop multi-benefit land use practices designed to improve habitat quality for salmon and other native fishes of conservation concern provided California’s system of water supply and flood protection infrastructure.Experiments took place in the Yolo Bypass, a 24,000-ha flood bypass along the Sacramento River in California, USA. Nine 0.81-ha replicated fields were constructed on Knaggs Ranch—a farm predominantly producing rice . An inlet canal routing water from the Knights Landing Ridge Cut canal independently fed each of the nine fields, and all fields drained into an outlet canal. The outlet canal ultimately emptied into the Tule Canal, which runs north to south along the east side of the bypass. Each field had rice boxes on the inlet and outlet of each field.

As outlined in Sumner and Leiby and Sumner , the human capital element remains prevalent through economic explanations of farm exit. Of course, age of the farm operators plays key role. Macdonald et al. discuss the role of the advanced age of many dairy farmers and the fact that many dairy farms are family-run, suggesting that there will be an increase in exits as more farmers choose to retire. Furthermore, the study relates the probability of exit to farm size, finding that not only does the age of the operator increase the likelihood of exit, but the smaller the farm size also increases the probability of exit.This section discusses the sample used in this analysis and details changes in the COA questions that are relevant to this analysis. The research utilizes COA data from 2002, 2007,2012, and 2017 for six select states: California, Idaho, New Mexico, New York, Texas, and Wisconsin. The results presented have gone through a disclosure review process and no data on individual/farm-specific is specific to individual farms and instead characterizes them more generally. Although the COA is federally mandated, it does not collect data on every U.S. farm and as such weights responses to create the most accurate sample that reflects the true U.S. farm sample. As discussed in Chapter 2, I use a specific definition of a commercial dairy in order to capture dairies with significant engagement with the dairy industry. A commercial dairy for the purposes of this analysis is defined as a farm with at least 20 milk cows on the farm as of December 31 of the Census year and the farm must have dairy or milk sales revenue above the dollars of milk sale revenue that would have been generated by 30 milk cows.

The survey questions asked of farmers and ranchers by the COA change slightly every Census round, hydroponic flood tray although most remain the same across time. Below are descriptions of question changes for relevant variables to the analysis. First, in 2002 and 2007, farms were asked for the total amount of dairy sales in that year, but in 2012 and 2017, this question was dropped and replaced with the total amount of milk sales. Furthermore, whether the dairy farm had any level of organic production was only asked in 2007, 2012, and 2017. Second, operator characteristic questions have become more detailed over the years and allowed more information about operators to be collected. In 2002, 2007, and 2012, the COA asked detailed operator characteristic questions about up to three operators, but only one operator was identified as the principal operator. In 2017, the COA expanded its detailed operator questions to include up to four operators and allowed for up to four operators to be identified as principal operators. In this Chapter, the operators for which the number per farm is limited and detailed information is provided will be referred to as the “core operators.”There is other no limit to the number other operators listed per farm and only the gender of each such operator and the total number per farm are provided in the Census. The COA has three potentially relevant farm size variables for dairy farms, the number of milk cows, the value of farm production, and the value of milk or dairy sales. I utilize all three in this chapter. However, I focus particular attention on the number of milk cows for the kernel density graphs. I characterize the distributions of number of milk cows per commercial dairy farm using two approaches. One approach is to fit a nonparametric distribution by year, and by state for each year to the data on milk cow herd size per farm. The other approach is to fit two commonly used parametric distributions to characterize dairy farm size distributions for the national and individual states over census years.

One aim of my thesis is to characterize the farm size distribution of dairy farms and fitting parametric density functions serves as a starting point for characterizing and analyzing dairy size distribution. As explained above, there is previous literature that utilizes parametric distributions to characterize farm size and this research provides evidence that commonly used distributions do not fit well with the U.S. commercial dairy industry. It is common in farm size analysis to fit parametric density functions to characterize farm size distribution . I create kernel density plots for the herd size distribution by state across the years and then find and fit two common parametric density functions to the distribution. This section will be structures as follows: a brief overview of the mathematics used in fitting parametric density functions. First, I hypothesize based on the kernel density plots what distributions seem reasonable. For this analysis I use the log normal and the exponential function, as those are two common distributions used in farm size literature and are likely shapes for most farm size distributions. Lognormal is the typical selection, as it is referenced in Gibrat’s Law. The exponential distribution was selected because it can account for the same skewed shape but has more flexibility. Second, I estimate the parameters of interest needed to form that distribution in order to create an estimated distribution of random numbers that follow the specific distribution. For this analysis, the measures of farm size, the number of milk cows for each farm, are random variables x1, x2, x3, …, xn, where n is the sample size of farms, for which the joint distribution depends on distribution parameters. For example, using the log normal the parameters are the mean and variance, and there are two related parameters for the exponential distribution.

The estimates of the parameters are functions of the milk cow herd size variable in question. From there, we can calculate the estimates of these parameters to create a different distribution with those same parameters and compare them to the actual distribution of the number of milk cows. Some estimated parametric distributions appear to have slight irregularities, this is due to the number of observations and the impose parameters.This section will summarize the resulting farm size graphs and detail the trends across time and states. Overall, when looking at the six select states together commercial dairy farm distributions have shifted towards larger dairies. In 2002, there was a clear peak in the number of farms with less than 200 milk cows, but the peak falls significantly from 2002 to 2017 . Whereas farm size distribution shows a clear increase in the farms with larger herd sizes in 2017. Although this graph gives interesting detail about the trends in herd size for the U.S. overall it is mostly characterized by Wisconsin and New York which have a significantly larger share of the number of commercial dairies and tend to have smaller herd sizes relative to other states. This graph clearly shows that there remains a large share of dairies that have a herd size of less than 200 milk cows, despite the relative shift in herd size.Moving to state-specific trends, overall California dairies have had larger herd sizes than other states, such as New York or Wisconsin across all years . California had a peak in the share of dairies with less than 1,000 milk cows from 2002 to 2017, but the peak fell significantly between 2007 and 2012. There was a clear shift in 2012 with an increase in the 1,000 to 2,000 milk cow herd size in 2012 and then another shift in 2017 in the 2,000 to 3,000 milk cow herd size. This documents a clear movement of California dairies towards larger herd sizes and a decrease in smaller herd sizes. Idaho had a large peak in commercial dairies with less than 500 milk cows in 2002 and then a significant drop in that peak in 2007 with smaller subsequent decreases in 2012 and 2017 . Interestingly, in 2007 there was an increase in the number of dairies with a milk cow herd size between 500 to 1,000, hydro flood table but then a subsequent decrease the following year. In 2017 there was a clear increase in the number of commercial dairies with a milk cow herd size between 1,500 and 2,000. New Mexico had one of the more unique herd size distributions with no clear peak in the smaller herd size ranges . From 2002 to 2007, there was a clear drop in the density of commercial dairies with less than 1,000 milk cows and a relative increase in the density of commercial dairies with 1,000 milk cows. Then in 2012, there was a shift towards commercial dairies with more than 2,000 milk cows and a downward shift in commercial dairies in the 500 to 1,000 milk cow herd size range. This trend continued in 2017 with even further shifts in each direction. From 2002 to 2017, New York has seen a slight decrease in the smaller herd sizes and a little increase in the larger herd sizes .In Texas, the most distinct trend was a significant drop in the density of commercial dairies with herd sizes of less than 500 milk cows between 2012 and 2017 .

There has previously been a trend of decreases in this herd size range, but these follow a similar pattern as compared to most other states. However, in other states, there was not such a significant drop. In 2017, there was an increase in commercial dairies with more than 1,000 milk cows. There was a significant decrease the commercial dairies in Wisconsin with less than 100 milk cows from 2007 to 2012 and then again from 2012 to 2017 . In 2017, there was an increase in commercial dairies with a herd size of between 150 and 200 milk cows. Wisconsin’s dairy industry is characterized by a significant number of smaller dairies and few dairies with large milk cow herd sizes. Across the states, there is a trend of consolidation with few commercial dairies and an increase in the number of dairies with larger herd sizes. Despite the decrease in the number of farms in each state, the number of milk cows increased in some states and broadly remained relatively stable . California had a 6.7% increase in the number of milk cows from 2002 to 2017, but Idaho had a 55% increase. The number of milk cows in New Mexico and Wisconsin both remained roughly the same. There was a 6% decrease in the number of milk cows in New York and number of Texas grew by more than 70%. Neither of the two parametric distributions fit the national data well. In particular, both the log normal and exponential distributions failed to capture the very high mode at the low herd size in 2002. The herd sizes in California did not fit any distribution well in 2002 or 2017 . Idaho has a large peak in the smaller ranges that is well above either the log normal or the exponential distribution in 2002 . The herd size does fall significantly when looking at the Idaho herd size distribution in 2017, this does some what follow a log normal pattern, but not very well . New York follows a similar pattern with the smaller herd size peak being significantly higher than either the log normal or the exponential peaks in 2002 or 2017 . As we saw across years in Texas, the herd size shifted dramatically. In 2002, the herd size distribution slightly resembled a log normal trend but had definite deviations and in 2017 did not follow any distribution well . Wisconsin follows a similar pattern to New York with no clear distribution trend in 2002 or 2017, but with significantly high peaks in the lower herd size range that deviate from the distributions.As explained above there are several possible influences, but given the Census data, I have chosen the following variables: characteristics of the operators , farm sales diversification across commodities, and share of farm operators who have off-farm employment. I also account for state fixed effects and Census year fixed effects. Clearly sales diversification and off farm work are jointly determined with dairy farm size, so I do not claim to be measuring a causal impact in the regressions presented discussed in this section. The aim here is to discuss statistical relationships between these characteristics and the farm size measures because although they cannot be thought of as directly influencing farm size the relationship between such measures is of interest and allows for discussion about the characteristics of the U.S commercial dairy.