Hemp Growing

Supermarket access studies demonstrate mixed results on whether providing a supermarket alone is sufficient to resolve problems of “food deserts”; in fact, supermarkets can contribute to displacement through “supermarket greenlining” . Critical scholarship in the food desert literature finds that revealing food access inequities “often leads to a public response that focuses on only food stores themselves [or creation of new sites for market transactions], rather than a broader focus upon the inequities in economic investment, political and economic power, and health that the food desert issue highlights” .Farmers markets as distribution sites receive critical assessments in the literature for their ability to serve as distribution channels to low-income consumers. Alison Hope Alkon writes about the closing of a farmers’ market in West Oakland, a historically African American neighborhood, juxtaposed with the white spaces of farmers markets that are thriving in neighboring Berkeley in her book Black, White and Green: Farmers Markets, Race and the Green Economy . She theorizes the promise and limitations of the “green economy” and chronicles the food movement’s anti-capitalist roots yet ultimate manifestation as reproducing capitalist inequalities. Lucan et al.’s study of farmers markets in the Bronx took issue with limited hours of operation, seasonality, affordable common produce, and availability of predominantly healthy foods among farmers markets compared to nearby stores . Accepting Electronic Benefit Transfer payments is a basic prerequisite for farmers markets to be considered accessible to low-income consumers, a concept pioneered by the GrowNYC’s Greenmarket program . While farmers markets in all 50 states now accept food stamps , indoor farming systems the price of offerings such as a bunch of kale still exceeds the price of nearby fast food options that may offer a more filling but less nutritious meal option.

Some states are moving in the direction of matching EBT funds through various “market match” policies, a step towards improving food distribution and access at farmers markets .The concept of a foodshed in the distribution literature, “like its analogue the watershed, can serve as a conceptual and methodological unit of analysis that provides a frame for action” . Foodshed analysis “provides a way to assess the capacity of regions to feed themselves” through proximate location of food production, distribution and consumption . Applying this concept, Peters et al. found that 34% of New York State’s total food needs could be met within an average distance of 49 miles, . The foodshed, embedded in the local food systems and short food supply chain concepts, is a useful organizing principle for city planners to consider when designing effective food distribution networks, such as the example highlighted in integrating a farm into a housing development project in the South under the title of a “civic agriculture community,” facilitating proximate, affordable distribution channels. This exemplifies planning with a foodshed lens by specifying areas at the neighborhood scale for semi-commercial agriculture, neighborhood CSA, residential kitchen gardens, and residential development in order to build food access and ease of distribution into the neighborhood fabric. If urban farmers aren’t able to easily distribute their produce to consumers, either through sales or other forms of distribution, questions of improving food access are jeopardized as well, revealing the interconnectedness of the food systems framework from production to distribution to consumption. Planning for improved urban food distribution includes ideas such as food hubs, agri-hood developments, public storage and transportation options, food aggregating facilities or organizations, mobile food distribution, or state investment in public markets . Mobile food distribution options are modeled and shown to increase access in Buffalo, NY, in Widener et al.’s theoretical analysis . Agri-hoods have gained increasing mention in local news outlets as a real estate trend in “Development Supported Agriculture , and as many as 200 currently exist or are under construction across the country” .

They facilitate distribution by colocating food producers and consumers on strategically planned sites, providing shared infrastructure resources, and making land access affordable for farmers by cross-subsidizing with real estate development. Cooper’s report on food hubs in the south, a form of aggregating supply to enable expanded market access, highlights grassroots solutions developed by and for farmers of color, yet “major challenges [remain] associated with developing and maintaining food hubs within a racial equity framework” . Here again, the Google Alerts provide useful insights from gray literature and local news outlets into recent and effective strategies for city planners, be it food hubs, mobile food distribution options, online platforms for gleaning, second harvest, crop swaps, or distributing excess produce from backyard gardens. These are also areas that stand to benefit from additional scholarly research in terms of quantifying impact on consumption, food insecurity, and nutrition, expanding evaluations of urban food systems to include nonmonetary and informal distribution mechanisms. Integrating the access and distribution literature from above, we identified three themes that speak to the efficacy of urban agriculture in meeting food access goals: economic viability, policy and planning models, and civic engagement.In this section, we consider the economics of urban agriculture and the “economic marginalization” that prevents many operations from meeting all the social and environmental benefits of urban agriculture within a for-profit or capitalist-oriented production scheme. The urban food justice and food sovereignty movements in the U.S. are limited inpractice in achieving their more radical or transformative goals due to the fact that they are operating within “a broader framework of [capitalist] market neoliberalism” . The challenge has not been growing enough food per se, but rather “producing and distributing food in ways accessible and affordable for the growing urban poor” while sustaining UA operations in a capitalist, production- and profit-oriented society. Daftary-Steel, Herrera and Porter declare that an urban farm cannot simultaneously provide jobs to vulnerable individuals, provide healthy food to low-income households and generate sustainable income and/or profits from sales. Therefore, what forms of urban agriculture are economically viable in today’s political economy? Operations that provide jobs, job training and professional development but sell mostly to high-end consumers , operations that are volunteer-driven or publicly funded and operations that cross-subsidize healthy food donations with revenues generated from other services besides food production or from crowd-sourced funding . When it comes to economic viability, many urban farming operations openly acknowledge that they are dependent on grants and donations to sustain their operations, which is a double edged sword. On the one hand, as long as an organization can prove itself worthy in receiving grants and donations, it may represent economic viability and longterm sustainability.

On the other, if the organization is wrapped up in a charismatic individual leader or fails to receive ongoing grant injections beyond one or two initial successes, it will not achieve long-term economic viability. Examples include redistributive business models, barter and exchange networks, food aggregators, food recovery organizations, cooperatives, food hubs, and “agrihoods” . Food hubs are reframed as both tools for provision of market access and self-determination for black farm cooperatives in the South in Cooper’s report with potential to subvert historic racism and economic marginalization of black farmers. Key to this and other food policy reports in the gray literature is elevating voices and fostering dialogue led by communities of color.While food, vertical farming equipment suppliers and urban agriculture, used to be “strangers to the planning field” or “puzzling omissions” from American Planning Association resources prior to the early 2000s , there has been an increase in academic work in the past 10 years dealing with urban food systems planning. In this section we consider the policy landscape of various city and state efforts to incentivize and create space for urban agriculture. Policy is needed to lower costs for low income consumers and urban farmers seeking land, provide strategic location of distribution sites, and encourage year-round produce supply, often enabled by greenhouse systems in urban farms. Are current policy incentives enough to create expanded food access and community food security from urban farms? Horst et al. would argue no; rather, an explicit commitment to food justice and an “equity lens” is needed for policymakers and planners to create UA spaces that benefit low income and minority communities equally if not more than already advantaged groups. Due to the current landscape of “disparities in representation, leadership and funding,and insecure land tenure,” unless these problems are explicitly addressed, “even the most well intentioned initiatives will perpetuate or even reinforce the injustices that practitioners and supporters aim to address” . This sentiment is echoed in Morales’ chapter in Cultivating Food Justice, which calls for “applied research to discover and advance policy objectives related to the antiracist and economic objectives espoused by the Growing Food and Justice Initiative” . This suggests that only by foregrounding issues of race and economic inequality can cities create UA spaces that address food insecurity. In asking the question “Can cities become self-reliant in food?” Grewal and Grewal find that, in a best-case scenario, the City of Cleveland can achieve almost 100% self-reliance in fresh produce needs, poultry and eggs, and honey, but only with huge amounts of planning support . Blum-evitts puts forth a foodshed assessment tool to allow planners to assess local farm capacity in relation to local food needs . Theoretical work such as this is important to advance ideas of what is possible and motivate efforts to make change, although it must constantly stay in dialogue with what is happening in practice and expand beyond a productivist focus on local food systems. Urban farms are, after all, producing a lot more than food, and “increasing food production in cities does not guarantee that people experiencing food insecurity will access that food” . UA is re-valued along a broader spectrum of “products” or outputs in Figure 12 below.Creating urban agriculture incentive zones is one possible approach to policy and planning, likely to benefit the propertied class via tax breaks . Policies such as California’s AB 551, the Urban Agriculture Incentive Zone act, have come under criticism for not going far enough to build a just food system, relying on private rather than public spaces to support UA. It is unclear whether incentive zones will be widely adopted by cities and counties in California, and whether they will meaningfully address food access or food sovereignty, especially when the length of time required to devote a piece of land to urban agriculture is only 5 years. In cases where tax incentives are used to promote urban agriculture, primary beneficiaries of the policy are often the privileged class of property owners rather than low-income households or non-property-owning urban farmers. Cities with some sort of food policy regulating, allowing for or promoting urban agriculture include the City of Baltimore , City of Somerville, Detroit, Portland, Madison, Seattle, San Francisco, San Jose, Los Angeles, San Diego, Austin, Minneapolis, New Orleans,Milwaukee, Boston, and Chicago12. Many policies allow for commercial sales of urban-produced food within the city as “approved sources” ; allow for value-added processing and sale of urban produced foods in people’s home kitchens ; create tax incentives for property owners to convert land into urban farms ; amend zoning regulations ; or set up urban beekeeping pilot projects . The Baltimore example is especially noteworthy for its long-term planning approach to structuring urban agriculture into the landscape of the city, with considerations for equity in place. However, legalizing the ability to grow food in cities is not enough to promote equity and justice, nor resolve all the legal conundrums related to compliance with the terms of legislation . Creating incentive zones for certain types of UA practices is not the same as creating supportive policies to allow and encourage the existence of the diverse array of practices and practitioners that constitute UA. Especially in cities with growing population and housing pressures , particular attention must be paid in policy making to avoid advancing gentrification and displacement. This is less of a concern in cities without such housing pressures , but development is always a threat that must be considered when siting urban farms on private land. A promising policy direction pioneered by the City of Seattle is to dedicate public lands in low income neighborhoods to UA, which Seattle does through its P-Patch program. Other policy recommendations gleaned from the literature include: creation of a citywide UA task force with citizen representatives; efforts to tie in local “good food” policies with city Climate Action Plans to promote UA and alternative food waste management alongside climate benefits; devote public lands to urban farms and gardens in perpetuity; “retrofit” affordable housing developments with community gardens ; provide public storage, transport, and aggregation options for urban farmers; and convert corner stores into neighborhood groceries offering fresh produce from local farms.

Doug Benoliel and Tamara Buchanan are among the most knowledgeable and skilled people to be producing and distributing diverse vegetables to the Lopez Island food bank . After 25 years of running a successful plant nursery in Kirkland, WA, the couple “retired” to Lopez Island to start their own farm. Doug has a degree in botany from UW and wrote a book titled Northwest Foraging, and Tamara has exemplary culinary skills that she developed through self-guided experience. With a 5-year crop plan in hand, they began diversified vegetable production at Sweetbriar in 2011, cultivating an array of seed varieties for each crop . They hired LCLT interns for several summers and recruited an additional crew of volunteers to help out with farm harvests and multi-person chores weekly, on Fridays throughout the growing season. Produce was sold through a farm stand at the end of the driveway, a CSA subscription, and at the island Farmer’s Market for a few seasons. However, due to personal health conditions and a series of operations, Doug and Tamara had to scale back from production-sales operations. They currently run a scaled-down farm and do not sell any vegetables; all of the harvest is used for self-consumption and processing or delivered to Lopez Fresh and specific families in need . Volunteers still come by several times a month to bring in the harvest and package it for delivery to the food bank and take home vegetables for their families. This donation-based model of farming is supported by the farm owners’ personal wealth from previous careers and life pursuits . It rests on the recognition that many of the island-grown vegetables and specialty products are unaffordable to large sectors of the island population, who work in the tourism industry and do not own land.

Food insecurity in San Juan County is estimated to affect 39% of residents, according to a United Way of the Pacific Northwest ALICE report in 2018. The island food system as a whole is precarious, hydroponic rack system and not equitable, when such large percentages of the population cannot afford to access nutritious, locally produced food. It is unclear how long Doug and Tamara will continue their mission of supplying Lopez Fresh with produce from their farm, as they are in the active process of scaling back and downsizing. Doug has offered up space for gardening on his land to other individuals, but so far no one has taken him up on the offer, for a variety of personal circumstances. Whether other farms will follow suit in donating produce as they exit market-oriented production is an open question, which might require policy incentives and nudges to facilitate a more robust food donation system. The volunteer-based gleaning operation run by the Lopez Island Family Resource Center and the LIFE program8 are two other examples that donate fresh food to low income families. Addressing food security problems with donations of food serves an important interim purpose, but larger policy and economic changes, in the form of increased living wage jobs and affordable housing, are needed to address the root cause .Two of the three farms highlighted in the section above acquired farmland in the first place due to wealth transfers from previous careers or family members. The value proposition of purchasing farmland and paying off debts through limited farm incomes is otherwise extremely difficult and disadvantages low income and minority groups who have been excluded from generational land and wealth accumulation.

There is not yet a “social safety net” in place to enable farming as an equal-opportunity, financially viable or desirable career pathway, in terms of guaranteed income, health care, and time off to support personal wellbeing. This is preventing the easy transition of farmland from current to new farmers and causing hesitancy among young people seeking to make an early career as a farmer in the San Juan Islands, ultimately challenging the sustainability of agriculture on the islands as a “way of life.” In order to avoid a situation where only the wealthy can afford to farm sustainably, policy mechanisms must be put in place to democratize land access. Promoting and facilitating cooperative ownership and buy-in to farmland is something the county has yet to address effectively; it is challenging, and yet a promising action step for enabling successful farmland transition for a more diverse array of new farmers . Opportunities exist on the production side of the Lopez food system in the form of local knowledge accumulated over decades of implementing sustainable and regenerative, agroecological practices, that is ripe for sharing and transferring to new and beginning farmers through mentorship programs or the establishment of a more formalized “farmer training program” on the islands. Additionally, on the land acquisition front, the LCLT long-term affordable lease model piloted with the Stonecrest Farm purchase could lead to other transfers of farmland at low cost to new farmers .On a small island such as Lopez, there are opportunities to share and collaborate on distribution activities especially for complementary products. However, the limited number and size of markets could prohibit entry into a channel that is already dominated by one farmer or food business; therefore, diversifying and coordinating with other farmers is an opportunity to streamline distribution activities.

Opportunities exist for farms growing fruit to partner with and distribute alongside farms growing vegetables, meat or dairy products, which would be expedited by access to enabling infrastructure such as a shared refrigerated truck, aggregated cold storage, and designated food delivery person to transport products from farms to customers and retail locations. Ideally a shared transport system could be optimized to reduce vehicle miles traveled for food distribution, and a transport vehicle could be a hybrid or electric model to meet local goals of carbon emissions reductions in all facets of the food system. Efforts to streamline distribution exist in the form of the proposed San Juan Island Food Hub, which would provide institutional support for aggregating and distributing farm products between islands, improving transparency between producers and food purveyors. According to a 2015 Food Hub Feasibility Study led by the Ag Guild and ARC, there is a strong desire and opportunity for a San Juan County Food Hub to provide an online platform for ordering, aggregated cold storage, and aggregated purchase opportunities that would help meet the unmet demand for local food products in restaurants, grocery stores, and other food businesses9. Most farmers currently do not have the time and capital to transport their produce to other islands but stand to benefit from accessing these additional markets. While food security is a stated goal of the project, it is unclear how increased access and affordability to low income consumers would be accomplished, other than through assumed improvements to local economic development and job creation. A specific plan for meeting the needs of low-income residents in the activities of the food hub would be a valuable improvement to the current planning process. The Lopez Farmer’s Market is an opportunity for farmers willing to participate weekly throughout the summer, as farmer participation has dwindled in recent years and there is interest in attracting more farmers to sell at the market. Finally, rolling tables grow the close-knit Lopez community breeds the trust and interpersonal relationships that facilitate many non-monetary forms of exchange, whereby farmers can trade food products directly for other goods and services they may need from island residents, in mutually beneficial trades that create solidarity and sovereignty from financial institutions. It is challenging to establish a successful CSA distribution on Lopez, requiring farmers to think creatively about how to structure weekly shares in a way that provides products that many residents do not grow for themselves, and accounts for the shorter-term seasonal demand of summer visitors.There are limited retail establishments on Lopez, many of which have outstanding relationships with specific farmers to supply certain goods. This can create a barrier to entry for new producers, who must either provide something that is not already present in the retail environment or establish affordable marketing opportunities off island . The school cafeteria is seeking to procure more locally sourced meat and dairy, providing a retail opportunity for producers of those products. As new restaurants, food trucks, and food businesses come to Lopez , new retail opportunities inevitably present themselves to farmers given the culture of prioritizing local food procurement.

The processing opportunities have been an active area of progress for the past several years, leading to the establishment of two commercial kitchens on the island. One is privately owned and accessible to island growers who sell their products commercially, and another is available for public use. There is a strong community desire to consume local foods year-round, supporting the expansion of the processing and preparation sector, and abundant local knowledge of creative processing techniques that could be taught or shared in community workshops. Additional cold storage is required to allow for local fruits in particular to be consumed six months out of the year, rather than just two. Food safety certification and training is required for all users of commercial kitchens and for the kitchen itself, which is time-consuming and expensive.Waste management is already fairly streamlined on Lopez due to the expense of transporting waste products off the island, and the organization of the award-winning solid waste facility . Current opportunities for improvement include the local biochar production and co-composting effort, as well as maximizing food waste recovery from all island retail stores and restaurants to be returned to local farms for composting. Food recovery from the fields and orchards occurs through a volunteer-run gleaning program, which could be scaled up with further support or participation incentives. A significant challenge for farmers is to reduce all plastic use and substitute with alternative materials, as plastic is no longer accepted at the Dump for recycling and must be paid for at time of disposal.In order to build a climate-themed farmer training program on Lopez, fundraising and/or grant-writing is needed to bring together land and human resources to execute such a program. Hiring a skilled farm-based education and other staff to support educational efforts is a challenge that must be worked out before this opportunity can be realized. Improving upon the K-12 food and climate education efforts at the school is a more easily accomplished opportunity through partnership and participation of more farms and educated adults on the island. Additionally, recognizing that several young people on Lopez are already actively farming and interested in doing so in the future presents an opportunity to strengthen countywide Young Farmer leadership programs in order to expose these aspiring young farmers to new practices and skills needed to create successful farm operations.Using data gathered from interviews and observations of current farmland operations on Lopez and referring back to Ostrom’s ten variables, it becomes clear that farmer self organization to sustain the local food system is very likely . Nevertheless, the propensity for farmers to self-organize does not guarantee that the more complex and overarching political and economic challenges will be resolved through grassroots self-organizing; farmers must integrate and collaborate with other circles of the polycentric governance structure in which they are nested to adopt necessary reforms. The ARC, for example, is a Citizen Advisory Committee tasked with advising the County Council on issues affecting the Agricultural environment comprised of 15 voting seats, at least 50% of which must be farmers. It is currently seeking to advance the goals expressed by farmers for favorable county land use policies through promoting the adoption of an “Agriculture” specific section of the Land Use Element of the Comprehensive Plan, currently under revision. A revaluation and realignment of county policy and political economy are needed to accurately account for and support the endeavors of the Lopez agricultural community. Currently, revenues from sales of local food products comprise roughly 2% of total county revenue . However, farms are contributing so much more to the island economy than sales of food products: they are attracting tourists, educating community members at farm tours, quantifying efforts to sequester carbon on working lands, creating resilience to off island food supply chain disruptions, building community health, and weaving a fabric of community land ethics that infuses the Lopez “sense of place.” Tourists, local residents, and restaurants alike attribute their desire to come to the San Juan Islands in large part to the local food scene and pastoral island character.

Significant to the presentation of results and discussion is the supremacy of private property in the United States legal system. When comparing the Lopez agricultural case study to “idealized” visions of agroecological food systems, many steps towards the “ideal” are thwarted by private property “enclosures” of the agricultural commons, which is more pronounced in the United States than in other geographic contexts. Thus, progress towards visioning and establishing agroecological local food systems must reconcile with unique challenges in the U.S. land tenure system, and ultimately promulgate strategies for loosening the supremacy of private property if real power is to be restored to those growing our food. Through a compilation of fieldwork, ethnographic notes, participant-observation, and immersion into the community, this chapter presents data on the Lopez Island sustainable foodsystem case study, and constructs analysis of food system transformation framed by the paradigm of agroecology . I draw on social science research methods including semi-structured interviews and ethnographic techniques to bring forward ideas and solutions from leaders in the agricultural community of the San Juan Islands. Research partners include the San Juan Island Agricultural Resource Committee , the San Juan Islands Agricultural Guild , the Lopez Community Land Trust , the Lopez Island Farm Education program, Washington State University San Juan County Extension, San Juan Islands Conservation District , Midnight’s Farm, Stonecrest Farm, Sweetbriar Farm, and Lopez Harvest. I find that the Lopez food system transformation towards resilience, sustainability, plant grow trays and equity is a work in progress, requiring political and economic shifts in order for regenerative food production practices to spark regeneration and equity in other branches of the food system.

Significantly, farmland transition barriers and land access challenges3 combined with new and beginning farmer training are areas requiring further investment, investigation, and institutional capacity in order to secure the progress made to date into subsequence generations of sustainable farmers.It is already well established in the agroecology and sustainable food systems literature that the chemical-industrial farming system causes adverse human health, labor, social justice, environmental and climate outcomes . Thus, alternatives to the chemical-industrial farming system are imperative to develop and advance for environmental and social justice reasons. The current dominant food system is driven towards yield-maximizing outputs enabled by increasingly consolidated, mechanized monocultures, which are in turn reliant on a potent mix of chemical fertilizers, pesticides, and fossil fuels. This system functions at the expense of human health, fair labor conditions, equitable food distribution, and environmental preservation. Furthermore, the current food system contributes significantly to the problem of climate change, emitting approximately 25% of the global greenhouse gas emissions portfolio . Conversely, regenerative agroecological food systems have the potential to store more carbon annually in the soil than what is emitted through processes like respiration and plant decay, which at scale could amount to significant global carbon offsets , buying time for theplanet to adopt other necessary technological and social changes to reduce carbon emissions . Agroecological, sustainable, and organic farmers are leading the way towards demonstrating new ways to both produce sufficient quantities of food and mitigate climate change through soil C sequestration.

Regenerative agriculture 4’s climate mitigation potential is highlighted in a recently released report from the Rocky Mountain Institute, stating that “negative emissions technologies—natural and engineered strategies for actively removing CO2 from the atmosphere such as agroforestry and silvopasture, biomass gasification and biochar—deployed at scale in the United States could sequester between 0.6 and 1.4 gigatons of C annually by 2050” . A report by Terra Genesis International further breaks down the mitigation potential of regenerative agriculture practices per hectare as depicted in Figure 4. According to Silver, “plants, and the soils they live in, are tremendous resources in the battle against climate change… soils have the potential to be deep, long-term repositories of some of the carbon captured by plants, keeping it from returning to the atmosphere for years to decades or longer” . Silver and her team of researchers quantify the impact of existing “agricultural mitigation practices” as potentially lowering global temperatures by 0.26°C by 2100, under RCP 2.6 . Other researchers helped develop the “Soil C 4 per Mille” initiative, launched at the COP21 talks in Paris in 2015, calling for all nations to increase soil carbon storage on agricultural lands by 0.004%, which would create a significant global carbon drawdown effect of 2-3 Gt C annually, offsetting 20-35% of anthropogenic emissions . What are these “agricultural mitigation practices” and how exactly can they be scaled across global agricultural acreage? Undoubtedly, local geography and context matter, along with available social, intellectual, and financial resources. This chapter will explore the first half of the question and explore the application of mitigation practice in the San Juan Island geographical context. A selected list of practices most relevant to Lopez Island farms are listed in Table 1 below. It is worth noting that many of these practices, in particular no-till and cover cropping, are broadly relevant to agricultural producers in both the conventional and organic industry, offering opportunities to build a “big tent” in the agriculture sector’s response to climate change.

In the face of climate change and its accelerating impacts, solutions and strategies for adapting and mitigating climate change through island farming are clear. What is needed is governance structures and skillfully crafted policy change to fund and scale these practices democratically. So, this chapter examines Lopez governance structures, from farms to island to county and state scales, and asks: What are the strengths and barriers to realizing a truly sustainable local food system on Lopez? How do perceptions of strengths and barriers differ or align among different governance scales? What are opportunities for immediate action or next steps to move towards the county vision for a sustainable local food system? As Figure 5 illustrates, farms and farmers on Lopez are nested within island, county, and state governance scales. Farms can and do relate to each other horizontally, coming up with mutually beneficial and differentiated roles, responsibilities, and practices, where for example one farm may supply compost to others, while others provide woody debris back to that farm, and all farmers share strategies for eradicating common pests/weeds, taking care of animals in the absence of an island large animal vet, and securing inputs/supplies from both on island and off island sources . Farmers who raise meat share access to a USDA-inspected, certified organic Mobile Processing Unit for slaughtering animals on the island, the first of its kind in the nation and an example of polycentric governance involving island, county, and federal coordination. Each of these levelsof governance are relevant to the conversation, research, and process of working towards a sustainable, equitable and resilient local food system on Lopez. Ultimately, state- and county level political reforms are needed to unlock goals and changes sought by island organizations and farmers at the grassroots level, who are already attempting to self-organize to ensure sustainability of their SES. Governing and “understanding a complex whole requires knowledge about specific variables and how their component parts are related. Thus, we must learn how to dissect and harness complexity, custom grow rooms rather than eliminate it from such systems” .In addition to policy and governance structures, education is a key component surrounding food systems that can unlock transformative change. In this case study, a range of environmental and food systems education research are relevant, most significantly: 1) farmer to farmer education on regenerative agricultural practices and 2) climate change education for youth, farmers, and the general public.

Farmer to farmer education is a cornerstone of the agroecological paradigm, which recognizes the vast knowledge stores held by experienced farmers as well as trust and value created when farmers share information with each other in horizontal knowledge transfers . Farmer to farmer, or Campesino a Campesino networks are seen as essential to scaling up and out agroecological practices that “enhance the resiliency of agroecosystems” . This educational form shares much with critical pedagogy, popularized by Paolo Freire in Brazil in the 1970s, which similarly emphasizes horizontal relationships between teacher and student, where both teachers and students are encouraged to ask and answer questions in an anti-oppression, anti-hierarchical “classroom” that aspires to higher goals of transformational social change and justice . Farmers hold unique and practical forms of knowledge that have developed historically in the United States context through both firsthand experience and institutions such as land-grant universities, Cooperative Extension, and the Farmer’s Bureau. Farmer knowledge in the United States has become centralized in the hands of institutions and corporations who exercise power over large aspects of the food system, from production to consumption. This consolidation of knowledge is related to corporate consolidation and corporate funding of agricultural sciences in research institutions including land-grant universities and Cooperative Extension offices . Corporate and institutional influence over farmer knowledge and practices intersects with the National Farm Bill policies and system of subsidies and crop insurance, policies over which corporations also exercise influence, thereby dictating a pattern of mechanized, chemical intensive farming that is practiced on a large scale in the United States, a pattern that is self reinforcing. Unsurprisingly, as part of this top-down knowledge transfer funded by fossil fuel interests, farmers as a population demographic in the United States have been skeptical about human-caused climate change and expressed reluctance to take mitigative action . However, there has been a notable shift recently due to extreme weather impacts on the Midwest and California that are making climate change a harder reality to ignore, and leading some farmers to declare that “farmers and rural Americans, that’s who’s going to solve this; We have the land for renewable energy, and we have the farming systems to sequester carbon” . A farmer in Missouri informed The Guardian that “as climate change bites, farmers are increasingly accepting of the science as they are forced to spend more money on equipment and seeds to maintain current crop yields” . Importantly,research indicates that “farmers who were concerned about the impacts of climate change on agriculture were more supportive of adaptive and mitigative action and those who attributed climate change to human activities were more likely to support government action on mitigation” . Experiential education in climate resilient agriculture for farmers will be important to translating research into action, enabling sustainable local food systems transformation. Improving farmer and future farmer climate literacy is a crucial component of scaling and handing off climate friendly practices such as those identified in the literature , yet remains an area that has been under explored in food systems research. There is little mention of training or educating farmers about climate change, and minimal mention in the K-12 educational arena of incorporating climate change into school food programs like Farm to School. Farm to School programs refer broadly to environmental literacy in their education program element, but there is much room to grow for both FTS and adult beginning farmer training programs to incorporate coherent standards and curricula around climate literacy. Like all forms of environmental literacy, it comprises knowledge, attitude, and engagement/action dimensions . Concepts like environmental and climate literacy are notoriously difficult to measure and quantify but are nevertheless important educational objectives to build into both K-12 and farmer education spaces coherently through content and activities aligned with the best available science. While the Lopez farmer population is already largely climate-engaged and active, the development of climate and environmental literacy among young people and aspiring farmers is important and in need of development, outlined further below and in Chapter 4, which focuses on education. The following sections apply literature on agroecology, agriculture and climate change, SES, and climate education to the past, present, and potential futures for the Lopez Island farming community.Historically, Lopez was an island of woodlands and native prairie, populated with Coast Salish communities who used regular burning practices to clear land for subsistence cultivation, hunting, and fire risk management. European settlers arrived in the mid-1800s, some fleeing the Irish potato famine to resume a life of farming and fishing on Lopez. Following the European theft of native land and the settlement of a boundary dispute between the United States and Great Britain in 1872, the islands were surveyed into 160-acre parcels and opened up to homesteading under the Homestead Act .

Initially, we reviewed the title of the first 60 documents resulting from each search. If the document was a manuscript, we then examined its abstract and conclusion. If the content of either the abstract or conclusion was relevant to the subjects of interest , the manuscript was selected for further review of the entire manuscript. For the cases in which the document was not a manuscript , we skimmed through the document to assess its content. Content relevance to the topics of interest was evaluated manually and individually by two researchers to establish inter-rater reliability.30 When both researchers agreed on a certain content, the document was further reviewed. The third step of the review process was performed by searching for specific keywords within each document selected in step 2. For example, for each source found in the search for the required physical and mental capabilities of youth, keywords such as force, anthropometry, body size, weight, and strength were searched to identify the relevant material. In the last step , experts in youth and ATV safety reviewed and categorized the relevant information in each document in a table. Based on our search terms, we retrieved 182 documents from Google Scholar and 1,189 from Google. As expected, some documents were repeated due to the five separate queries in two search engines. After filtering the titles, we identified 649 unique documents. Among those, 115 documents were selected for further review based on the inclusion/exclusion criteria. Our findings are outlined in the next section of this manuscript.A summary of the literature review process is illustrated in Figure 1. In addition to the initial literature review , hemp drying racks we also evaluated documents that were directly cited by the original 115 selected documents that emerged from our search. For those documents, we repeated steps two , three , and four .

After filtering the titles, we identified four additional documents.ATVs can weigh up to nearly 1,200 pounds31 and reach speeds up to 80 mph.32 The engine size ranges from 50 cc to approximately 1,000 cc for youth and adult-size ATVs. Controlling heavy, fast, and powerful vehicles require physical and mental capabilities that youth operators may not possess. For this matter, several consensus-derived guidelines, rules, and recommendations have been developed regarding the minimum age for operating ATVs on farms. These guidelines include age limitations for youth to ride utility ATVs and youth models. Nevertheless, these recommendations are inconsistent and may be affected by laws that vary among states. The American National Standard Institute/ Specialty Vehicle Institute of America propose age limitation based on the abilities of children from different age groups and the ATV’s maximum speed. Furthermore, based on the medical associations and safety experts’ concerns about child safety and health, some have concluded that permitting children younger than 16 years-of-age to operate or ride ATVs could be construed as a form of child neglect or endangerment. According to ANSI/SVIA, youth under the age of 6 should not be allowed to operate ATVs, and youth aged 6–10 should be limited to motorized vehicles that can go no faster than 24 km/h and require constant adult supervision. Youth between the ages of 11 and 12 can ride ATVs with a maximum speed of 48 km/h . In the U.S., ATV manufacturing and sales are regulated by the U.S. Consumer Product Safety Commission and not by the U.S. Department of Transportation . The DOT regulates motor vehicles designed to be used on public roads, and ATVs are not intended for public roadway use. In 2002, nine consumer groups petitioned the CPSC to ban the sales of adult-size ATVs for use by children under the age of 16. 

However, the petition was denied. The CPSC, theindustry, and many consumer advocates recommend selling only youth-model ATVs for children. Nevertheless, there are no ATVs designed/manufactured for children younger than 6. Vehicles for children 6 years-of-age and older have traditionally had engine sizes less than 70 cc, and those for children 12 years-of-age and older have been 90 cc or less. The CPSC recommends that these vehicles be used by children with adult supervision. Previous recommendations based on engine size by operator’s age are given in Table 2.  In the case of ATVs, the CPSC currently has adopted the 2017 voluntary standard developed by the Specialty Vehicle Institute of America and the American National Standards Institute , which is the most up-to-date standard regarding ATV-youth fit. The American National Standard for Four Wheel All-Terrain Vehicles42 is a “voluntary” standard that provides definitions for youth category ATVs . Based on this standard, the criterion determining age-designated youth labels is the maximum speed of the vehicle. For example, Y-10+ ATV models should only be used by children aged 10 and older. The maximum speed associated with each ATV category is presented in Table 3. The European standard titled “ATV Safety requirements and test methods” determined several requirements that ATVs should meet to be commercialized in Europe. This standard categorized youth-ATVs into four groups, including, Y-6+, Y-10+, Y-12+, Y-14+ based on the speed limits, similar to the standard from ANSI/SVIA . In addition, the European standard suggests that only operators older than 16 should ride adult-sized ATVs for utility or recreational purposes. Despite the recommendations based on age categories, several national and international organizations prohibit youth under 16 from riding ATVs of any size . Moreover, several medical associations inthe U.S., including the AAP40 and the ACS,41 warn that all ATVs are unsafe for youth, and no one under 16 years should ride ATVs at all. 

Some also indicate that youth under 12 have neither the required physical capabilities nor the motor skills to safely handle an ATV. They also indicate that youth under 16 do not possess the cognitive capabilities required to control highpower motorized vehicles. Lastly, Franklin et al. advocated that the sales of youth-size ATVs should be stopped in Australia for safety reasons. There are different regulations and laws at the state and federal levels. However, most rules/laws do not pertain to operations on private land. In addition, most laws are exempted if the vehicle is used for agricultural purposes. For instance, operators can ride without a helmet if they are farming in North Carolina or Wisconsin. In addition, ATVs in Pennsylvania used exclusively for agricultural purposes are classified in the Pennsylvania Vehicle Code as multipurpose agricultural vehicles and are exempt from the Pennsylvania ATV law. None of the states’ regulations address the physical or mental capabilities required to ride the ATVs. Numerous studies related to youth’s age and ATV use have been conducted; two key studies regarding the age of youth’s involvement in agricultural activities and age-based patterns in youth ATV riding behaviors are summarized in .The ATV operator should be strong enough to activate the ATV controls, including the throttlelever, hand gearshift lever, foot gearshift pedal, ignition switch, headlight switch, handlebar, hand brake lever, and foot brake pedal. An operator’s inability to consistently activate these critical ATV components could increase the injury risk to operators and bystanders. Several reviewed documents discussed the required strength to activate different ATV controls. However, most of these documents relied on qualitative criteria for evaluating the required youth strength. For instance, the National Children’s Center for Rural and Agricultural Health and Safety ATV guidelines state that “youth should be strong enough to operate the controls without straining and be able to push the ATV off if pinned underneath.” Furthermore, the ATV Safety Institute ’s “readiness checklist” recommends that “youth should have enough strength to activate the hand controls, shift lever, parking brake, choke and fuel valve, and the brake lever with sufficient pressure.” In contrast, industrial rolling racks the British Standard Institution , provides quantitative data for actuation forces of some ATV controls. For example, BSI recommends hand lever brake activation forces between 22 N and 245 N for all adult-sized ATVs. In an ongoing study, Araujo and Khorsandi measured the forces required to activate the main ATV controls. The activation forces were then compared to the corresponding strength of youth of various strength percentiles , genders , and ages . The authors found a significant mismatch between the forces required to operate the ATV controls and the corresponding strength of most youth. Furthermore, several study articles and guidelines reviewed in this manuscript recommended that youth should be capable of performing active riding, which refers to the operator moving their pelvis on or off the seat to counterbalance forces while holding the handlebars and keeping both feet on the footrests. 

Some researchers reported that active riding increased the stability of the ATV and decreased the chance of a rollover. However, the capability of performing effective active riding requires that the youth weight be significant compared to the ATV weight. Based on the CPSC, the appropriate child to ATV weight ratio should be 1:3.44 Figure 2 shows the weight of the lightest and heaviest youth in each age group compared to the mean weight of an age appropriate ATV. Based on the youthATV weight ratio recommended by the CPSC, 95th percentile kids as young as 7 years old are too heavy for the ATV recommended for their age , and by age 14, most kids are too heavy for ATVs designed for 12–15-year-olds. Based on the CPSC youth-ATV ratio recommendations , adolescent youth aged 12 to 15 years old might be too tall or heavy for the youth-model ATVs currently on the market and approved by the CPSC. If a youth is too tall or overweight, their knees may interfere with the handlebars, and they will be unable to control the ATV properly. Moreover, overly tall or heavy youth may significantly raise the center of gravity when on youth-size ATVs, affecting their stability and riding. A higher center of gravity likely increases the probability of the vehicle rolling over, posing a risk of injury or fatality. Different standards and organizations have developed recommendations to evaluate youth’s ability to effectively reach the ATV’s main controls: handlebar, hand brake, foot brake, hand gearshift, foot gearshift, and throttle lever. A summary of youth-fit criteria for ATVs proposed by various organizations and a research manuscript are shown in Table 5. In addition to reaching different controls, the European standard and the N4-HC55 suggest evaluating hand reach to hazardous zones on the ATV . This recommendation is based on another standard , which determines safety distances required to prevent hazard zones that could burn operators from being touched by upper and lower limbs. A previous study evaluated the fit of one adultsized ATV and one youth-model ATV for male youth aged 6–15 years old based on 5 of the safety recommendations mentioned in Table 5. The study found that most youth aged 6–15 years did not anthropometrically fit the ATVs based on the fit criteria used. Furthermore, the study suggests that rider age and ATV engine size are poor indicators of youth-ATV fit, and quantitative metrics would improve the assessment of which rider can anthropometrically fit which ATV. Furthermore, Araujo et al. evaluated youths’ ability to reach the main controls of various ATVs following some of the safety recommendations presented in Table 5. The authors developed virtual 3D mockups of ATVs and youth and simulated their interaction using an ergonometric software. The study’s major finding was that most youth failed to pass at least one of the ATV-youth fit recommendations.The field of vision of an ATV operator is the visible area they can scan from their seated position on the vehicle. Many believe that youth operators have a reduced field of vision compared to adults. Youth’s limited stature and eye height while seated on an ATV may affect their field of vision. Previous studies have shown that a restriction in an operator’s field of vision significantly increases the likelihood of a crash and/or loss of control which can lead to rider and bystander injuries. The ATV operator should have a wide field of vision to better access ATV controls, keep the ATV on the path, and detect shapes, sizes, and distances of obstacles. This ensures that the operator can react to unexpected riding situations and make decisions about riding strategies. The ASI youth “readiness checklist” includes a section to help parents assess their children’s visual perception. This part of the checklist evaluates youth’s capability to see, perceive depth, have adequate peripheral vision, judge the speed of moving objects, estimate the distances of objects , and follow the movement of objects.

For growth and broodstock, fish prevalence stabilizes around 100% from late 2013 until the end of the simulation .When the effect of local spread was removed from the simulation , a model that includes spread between farms is only possible via fish movement . In this scenario, the spread of PMCV slows down, but the overall pattern remains of an increasing trend reaching a between-farm prevalence of 100%. This level of prevalence was reached for the first time in late 2015, compared to the full model where 100% prevalence was reached 1 year earlier in 2014. For the model where transmission was only possible via local spread , between-farm prevalence never reached a 20% level until mid 2017, and oscillated most of the time around 10%. Under this scenario, the only time that between-farm prevalence is higher than in the scenario with spread only via fish movement is at the beginning of the epidemic , indicating that local spread was the main driver of the transmission between farms at this early time .Of the evaluated centrality based interventions, the most effective were the ones based on out degree and outcloseness, for both the reactive and proactive approaches . For the former, after all spread via fish movement from the targeted nodes is stopped in July 2012, the increasing trend in between-farm prevalence immediately stops, stabilizing around 60% until the end of the simulation for both out degree and outcloseness based interventions. The between-farm prevalence obtained with these interventions was slightly higher than the prevalence obtained when pathogen spread via fish movements from all fish farms was stopped, the difference being clearer from 2016 until the end of the simulation . In terms of the time required to reach set prevalence benchmarks, vertical farming system both out degree and outcloseness based targeted interventions are virtually indistinguishable, with the former being slightly better .

Regarding the targeted interventions based on the other centrality measures, the one based on incloseness was the one that performed worst, with virtually the same result as when no intervention is applied, followed by the ones based on indegree and betweenness, with the latter being similar to the ones based on out degree and outcloseness until early 2014, after which it produces a higher between-farm prevalence. Similarly, when targeted interventions are applied from early on in the proactive approach , the most effective targeting strategies are those based on out degree and outcloseness, which are virtually indistinguishable from the one based in removing spread via fish movement from all nodes. The strategies based on these centrality measures produced between-farm prevalences around 10% from their implementation through the end of the simulation. Similar to the reactive approach, the worst performing strategy here is the one based on incloseness, which produces virtually the same result as if no intervention was applied, although with a slight delay in the increase of between-farm prevalence from 2010 through mid 2014. The strategy based on indegree was second to last, reaching a between-farm prevalence of around 90% in early 2016 and stabilizing around that value until the end of the simulation. A betweenness-based strategy did not show a clear difference with the best performing strategies based on out degree and outcloseness until late 2012, where between-farm prevalence increased slightly above the value for the other two strategies, andthis difference remained until the end of the simulation .In this paper, we describe the use of data-driven network modeling as a framework to evaluate the transmission of PMCV in the Irish farmed Atlantic salmon population, and the impact of targeted intervention strategies.

To do this, we have simulated the introduction and spread of PMCV in the Irish Atlantic salmon farming industry using real data of live fish movements, compulsorily reported to local authorities during 1 January 2009 to 23 October 2017, and data from a prevalence study conducted from 30 May 2016 to 19 December 2017. Additionally, using the fish movement data set, we have imputed population dynamics events at the farms by using a set of rules based on domain knowledge of the fish production cycle. We were able to reproduce population dynamics and the observed PMCV prevalence in the observational study that was used to estimate model parameters, evaluate the importance of infection spread via fish movement and local spread, and evaluate the effects of different farm centrality based control strategies. Parameter estimation showed that the best fitting model was the one with increasing transmission rates as fish aged and with a rate of decay of the environmental infectious pressure that varied each quarter . In common with other viral infections of farmed Atlantic salmon, studies have shown that fish have increased PMCV prevalence and higher concentration of the virus in fish tissues as they age during the production cycle. Further, the probability of developing CMS increases with the length of time at sea . In the freshwater phase, viral particles are detected in low quantities, and CMS outbreaks and CMS-related pathological lesions have not been described . In a study to evaluate vertical transmission of the agent, PMCV was found in 128 of 132 broodfish, and later detected in all stages of progeny, but only at prevalences of < 25% and with concentrations close to the detection limit of the method .In the observational study used for estimating the parameters in our model, PMCV was found at higher concentrations in broodstock fish and lower concentrations in younger age groups . Although pathogen concentration was not part of our model, a possible extension would be to allow α, the rate of viral shedding, to vary by age group. In our modeling, simulation was initialized at two broodstock farms.

Within these farms, transmission was horizontal . As highlighted in the model, horizontal transmission between farms is important, but only via fish transfer and not via local spread. Our results indicate that the introduction of the agent in two specific farms during the second half of 2009, coupled with the structure of the network of live fish movements in the country, is enough to account for the widespread occurrence of PMCV currently observed in the country. These findings are in agreement with the recent work of Tighe et al. , who found that PMCV strains in Ireland are largely homogenous, without evidence of geographically linked clustering, consistent with a hypothesis of agent spread through fish movement . If local spread were the main driver, several locally distinct viral strains would be more likely. In addition, Tighe et al. suggests that the Irish strains from cluster I could have arrived in Ireland between 2010 and 2012, while the strains from cluster IV could have arrived between 2007 and 2009. This is very close to our simulated introduction during 2009 based on the results of archived samples. This study also suggests that these dates are supported by the testing of archived heart samples from Irish Atlantic salmon broodstock which showed that all samples collected prior to 2009 were PMCV negative, whereas those tested from 2009 onwards were positive. It is these data, from Morrissey et al. that form the basis for the current simulation study. PMCV is observed at low levels during the freshwater phase. Further, it is unclear whether persistent virus in these fish is a substantial contributor to mortality at sea compared to the infection pressure that is exerted from neighboring farms and other factors, external to the farm, that are associated with infection and disease . In recent work, Jensen et al. have highlighted a possible pathway of transmission from broodstock to smolt, a pathway that is not explicitly modeled in the current study. We consider that our modeling approach would be well-suited to evaluate the plausibility of alternative transmission routes. Although current parameter estimates appear to reproduce age-varying fish susceptibility, it was not possible to reproduce the observed drop in prevalence during the May-July period. There are reports of slight seasonal variations of clinical CMS in seawater farms, with an increase in cases in autumn and spring , but no reports on seasonal patterns in the detection of PMCV via RT-PCR or other diagnostic tests, let alone seasonality of detection in freshwater. The fact that all model parameterizations used were not able to reproduce the observed drop during the month of June leads us to think that further observational data is required, possibly with a study with sampling conducted evenly throughout the year, so it can include the months where no samples were taken and a more homogeneous number of farms and fish sampled at each time. Nonetheless, we believe that our model is valuable, and that important lessons could be learned from it, like the major importance of spread via fish movement and the best intervention strategies in order to prevent extensive infection spread. These lessons would apply not only to PMCV, vertical farming racks but also to infectious diseases whose spread is predominantly via fish movement . The decision to use a susceptible-infected over a susceptible-infected-susceptible model for within-farm spread was based on the fact that different experimental studies have found the viral genome present in tissues of challenged fish throughout the whole duration of the study, indicating that the salmon immune response may be unable to eliminate the virus .

This, together with studies where PMCV has been consistently found in cohorts of fish sampled through long periods of time, indicating that PMCV can be present in fish for some months , provides further support for the modeling approach used here. Nevertheless, more research is required to further validate or refute this modeling choice, as it is possible that fish clear the infection beyond the time frames used in both experimental and observational studies. The model was sensitive to changes in the values of the indirect transmission rate, rate of decay in environmental infectious pressure, and the rate of viral shedding from infected individuals, but not to changes in the level of spatial coupling . Model outputs were also not substantially influenced by different parameter assumptions regarding either distance or seasonality , noting that information about distance thresholds was derived from other viral infections such as infectious salmon anemia , where estimates have varied from 5 to 20 km or more . Collectively, these results suggest that local spread may play a secondary role in the spread of PMCV across the Atlantic salmon farms in the country. When local spread was removed completely from the model , it was even clearer that this transmission pathway under current model assumptions was not the most important. On the basis of these results, we hypothesize that the widespread presence of PMCV in Ireland is most likely a product of the shipments of infected but subclinical fish through the network of live fish movements that occur in Ireland. This is consistent with fish being infected but subclinical for months prior to manifesting signs of disease , and by the structure of the network of live fish movements in the country . There is limited knowledge of agent survival of PMCV in the aquatic environment. Infection risk is higher on farms with a history of CMS outbreaks , which could suggest survival of the causal agent in the local environment. Further, infection pressure from farms within 100 km of seaway distance was found to be one of the most important risk factors for clinical CMS diagnosis , although this study did not evaluate spread via fish movement. It is noted that the distance over which infection can be transmitted via water is determined by an interaction between hydrodynamics, viral shedding and decay rates . Further research on PMCV survival in the environment is needed to guide parameterization of future models. The most effective intervention strategies are based on out degree and outcloseness , with the highest impact being observed when using these intervention strategies with a proactive approach . Note that all outgoing shipments from selected farms are assumed to include only susceptible fish , which can be equated with high levels of bio-security. The out degree and outcloseness based strategies are comparable, most likely because both strategies refer to outgoing shipments from a farm , the former with the number of farms receiving fish from a given source, and the latter inversely related to the number of intermediaries between the source and the rest of the farms in the network. Both centrality measures were moderately correlated with each other, with a Pearson correlation of 0.53 for the proactive approach when including all farms for each time window used.

Many papers have tried to address this issue in their own unique ways. A common method seen is a polygonal representation of the boundary. With these polygons, Guirguis et al. uses the nearest edge to define an equivalent circular constraint. Risco et al. uses the nearest edge of the polygon to define the signed distance function. Note that both of these method’s use of the nearest edge in their formulation, which means that the constraint function is non-differentiable when there are two edges of equal distance away from the wind turbine. Additionally, there is a trade-off between computational cost and accuracy in the constraint function with respect to the number of edges in the polygon. The unique approach by Reddy poses an interpolation problem using a support vector domain description to describe the boundaries in an optimal way. This approach is continuous and differentiable, but the report does not provide any accuracy and scaling studies, so it is unknown how it may perform with increasingly complex boundaries.To the author’s knowledge, no other wind farm boundary constraint has taken the unique implicit surface reconstruction perspective as was described in Section 2.1. Implicit surface reconstruction constructs a level set function that represents the wind farm boundary by its zero level set. The inputs to most surface reconstruction methods is a point cloud, which is easily obtainable from the polygonal representations of previous studies. Note that Reddy’s SVDD method is very similar to the interpolation formulations in surface reconstruction. In this way, SVDD may suffer from the aforementioned limitations, including blobby reconstructions and significant computational expense for large scale SVDDs . The SDF is useful when the feasible zones are disconnected.

In gradient-based optimization, it is not possible for wind turbines to move across disconnected domains in a continuous way, however, drain trays for plants a relaxation approach to the boundary constraints can allow for wind turbines to move freely across regions until the true constraint is represented. The relaxation approach is shown to work well in avoiding turbines getting stuck within disconnected domains. With the SDF approximation described in Chapter 3, the relaxation approach is easily repeatable using the surface reconstruction method. We identify three of these frameworks relevant to the work within this thesis: PyWake, TOPFARM, and FLORIS. PyWake is an open-source Python library that contains many engineering wake models to calculate the annual energy production of wind farms. TOPFARM is an Open MDAO-based Python library that performs gradient-based optimization on wind farms using PyWake as its backend for modeling turbine wakes and calculating annual energy production. FLORIS is an open-source Python library that is controls-focused framework that models the wakes of yawed turbines and supports gradient free and gradient-based optimization. Gradient-based optimization within FLORIS is at alimited capacity, as it only supports automatic differentiation on some models. Otherwise, the finite difference method is used for derivative calculation. The finite difference method is less accurate and requires many more model evaluations. This section, in part, is currently being prepared for submission for publication of the material. The authors of this work are Anugrah Jo Joshy, Ryan C. Dunn, and John T. Hwang. The thesis author was a contributor to this material.We now apply our formulation to a number of geometric shapes involved in novel aircraft design. Aircraft design optimization is a long standing problem and has been the subject of recent interest in problems involving geometric non-interference constraints, e.g., the layout optimization of air cargo and aerodynamic shape optimization.

To enable gradient-based design optimization involving these constraints, a new generic method is required to represent numerous components within an aircraft’s design. We recognize the potential for our formulation and demonstrate its capabilities by conducting an experiment. In this experiment, we apply our formulation and quantify the resultant errors of five geometric shapes commonly associated with aircraft design. The geometries we model include a fuselage and a wing from a novel electric vertical take-off and landing concept vehicle, a human avatar, a luggage case, and a rectangular prism representing a battery pack within the wing. A visualization of these components in a feasible design configuration is illustrated in Fig. 4.7. Table 4.3 tabulates the on-surface error of the energy minimized LSF for each geometry. We observe that the smallest relative on-surface error is of the smooth fuselage shape, while the largest relative error is of the human avatar. We note from this example that geometries with features reasonably proportioned to their minimum bounding box diagonal are easier to represent using our method, hence our formulation poorly represents small scale features of the human avatar while it can represent the smooth fuselage very well. We observe that the bounding boxes of the fuselage, wing, and battery pack are poorly proportioned, yet they do not result in an increase of relative error compared to other geometries. However, their longer minimum bounding box diagonals will result in larger absolute errors.We now apply our method for enforcing geometric non-interference constraints to a medical robot design problem involving concentric tube robots . CTRs are composed of two or more long and slender pre-curved tubes made of super elastic materials. They can be designed to reach points in a large region of interest by rotating and translating the tubes relative to each other at their bases.

These characteristics make them ideal for minimally invasive surgeries where a surgeon can operate on a small region of interest with high dexterity through actuation at the base. In the foundational works of Sears and Dupont and Webster et al., expressions for the shape and tip position of the CTR are derived with respect to the robot’s geometric and control variables. Bergeles et al.use these expressions to perform gradient-free optimization of the CTR’s geometric and control variables with anatomical constraints. These anatomical constraints, i.e., geometric non-interference constraints, enforce that the CTR does not interfere with the anatomy during operation. Recent work by Lin et al. shows that gradient based optimization enables an efficient and scalable solution to simultaneously optimize the large set of the tube’s geometric and control variables while enforcing anatomical constraints. The experiment we now present follows the workflow of Lin et al., however, using our new formulation for representing the anatomical constraint function. The presented workflow involves the solution of multiple optimization problems, including an initial path planning problem, and the geometric design and control of the CTR . The path planning problem solves for a parametric 3D curve that represents an optimal collision-free path to the surgical site within the anatomy. Then, points along this path serve as inputs to the geometric design and control optimization of the CTR, which involve a kinematic model of the robot. In both subproblems, the non-interference constraints are enforced by evaluating a discrete set of points along the path or physical CTR to ensure that no points lie outside of the anatomy. We begin our experiment with an investigation in the heart anatomy which represents the non-interference constraint of the problem. The initial oriented point cloud of the heart is obtained from segmentation and 3D reconstruction by magnetic resonance imaging scans. Due to the limited machine accuracy, error introduced by aligning multiple scans, and normal approximation, the oriented point cloud is noisy, nonuniform, and contains poorly oriented normals. We perform a simple and necessary smoothing step on this point cloud as illustrated in Fig. 4.8. Although less precise at capturing small scale features, 4 x 8 grow tray the smoothing step assists our method in reconstructing a smooth zero contour for constraint representation.The smooth representation has relative errors 3.1×10−3 and 1.9×10−2 compared to the original noisy representation. The error in our energy minimized function obtained from the smoothed heart model is tabulated in Table 4.4. We observe that the on-surface RMS and max error of our representation is an order of magnitude less than the error introduced by the smoothing step. This implies that our representation of the smooth model is no worse than the smoothing step itself. We see that our method generates a function with a reliable zero level set of the smooth heart geometry, with an on-surface RMS error of 2.1×10−4 .

This error is lower compared to all the other examples in Table 4.2, and we attribute this to the smoothness of the heart geometry. We also note that the max on- and off-surface absolute errors of our representation are of the same order as the diameter of the CTR itself, typically 0.5-2.0 mm.Models of the wind turbine are necessary for characterizing the flow field in its wakes and for the power production of an individual turbine. For the analytical wake models and the calculation of annual energy production, we solely need a wind turbine to provide coefficient of thrust and power production . For simplicity and computational efficiency, the wind turbine model is simplified to a surrogate model where CT and P are simply functions of the wind speed experienced at the rotor. We note that any increase to the fidelity of the model will improve the power and CT accuracy, however the analytical wake models used in this study do not consider varying thrust/power at different radial sections of the blades. We do recommend a more accurate turbine model in the future work that will account for structural loading and fatigue on the blade structures. The two wind turbines considered in this study are the National Renewable Energy Laboratory 5MW open-source turbine model, and the International Energy Agency Wind Task 37 15MW turbine model. These wind turbines were selected for their size and viability in off-shore wind farms on small and large scale. The power and coefficient of thrust curves for the NREL 5MW and IEA37 15MW reference wind turbines are shown in Fig. 5.1 and Fig. B.1, respectively. The parameters of each wind turbine are also tabulated in Table 5.1. Note the significant diameter size.While this thesis does not provide validation with ground-truth, verification is provided to the existing models within PyWake and FLORIS. The major assumptions with this model depends on the accuracy of models individually. Validation studies are important and would be a valuable future work to this thesis. A study on flexible and stiff blades found that low fidelity models have significant discrepancies at low wind speeds and small inter-turbine spacing. Additionally, we rely heavily on the assumption an accurate thrust coefficient curve for the given wind turbine. An example to verify the Bastankhah wake model in a simple 3 turbine row is done in Fig. B.3. The error in the AEP calculated from our model on the order of machine precision, confirming the model’s accuracy. Derivative calculation is automatically done in CSDL, but for additional validation it is verified with finite differencing during optimization, and is confirmed to be on the order of the step length of the finite difference O. A verification of the Gaussian wake model in a simple 3 turbine row is done in Fig. B.4. The net AEP calculated from our model has a normalized error on the order of machine precision, confirming the model’s accuracy. Derivative calculation is automatically done in CSDL, but for additional validation it is confirmed to be on the order of the step length of the finite difference O. This chapter, in part, is currently being prepared for submission for publication of the material. The authors of this work are Anugrah Jo Joshy, Ryan C. Dunn, and John T. Hwang. The thesis author was a contributor to this material.In this optimization study, we perform a yaw misalignment optimization with the Lillgrund site. We utilize FLORIS’s built in boolean optimization tool called Serial Refine in order to initialize our optimization. Serial Refine reduces the design space by considering wind turbines in order of upwind to downwind, and recursively discretizes the design space and checks the model evaluations for the maximum value. In this way, it is a gradient-free optimizer, and it has shown to be very fast at finding a near-optimal solution and not susceptible to local minima. Because SR is fast and robust to local minima, we may apply it to get a good initial guess for our optimization. Our new model can take this suboptimal initial guess and improve it further using gradient-based optimization by considering yaw as a fully continuous variable. The yaw optimization problem is shown in problem 5.27, and the Gaussian wake model was used with the Crespo and Hern´andez turbulence intensity model. Using the Lillgrund site, the optimization problem has a total of 3,456 design variables.

Distance-based redundancy analysis is an extension of PCoA to model multivariate data and it was used to assess the amount the main food groups and confounding factors together explain of the compositional variation of gut microbiomes between individuals and visualizing the direction of the associations. PERMANOVA, factorfit, and dbRDA were run with 999 permutations. In per-taxa analyses we used a multivariate analysis by linear models to analyze associations of each main food group and their subgroups with all taxa at species level. Benjamini-Hochberg false discovery rate corrected P vlues were used to adjust for multiple comparisons. Prior to analysis the relative abundances of the taxa were centered log-ratio –transformed. For the cluster analyses, the taxa with significant associations with the main food groupsfrom per-taxa analysis were clustered based on proportionality using Ward minimum variance method and the optimal number of clusters was determined using KelleyGardner-Sutcliffe penalty function. The results were visualized with a heatmap. A pathway analysis was conducted between Kyoto Encyclopedia of Genes and Genomes orthology groups and the food groups using linear regression analysis. The relative abundances of KO-groups for each sample were obtained from the strain-level outputs of SHOGUN and the data on KO-groups were log10-transformed prior to analysis. Benjamini-Hochberg FDR corrected P values were used to adjust for multiple comparisons. Statistically significant associations of main food groups were further visualized using FuncTree 2. Analyses were controlled for potential confounding factors based on prior literature. These included age, sex, BMI, smoking status, 4×4 grow tray usage of possible microbiome-altering medications and total energy intake. The level of statistical significance for analyses was set at a P value<0.05 . Statistical analyses were performed using R version 3.6.3 and the following packages phyloseq, microbiome, vegan, maptree and ComplexHeatmap. 

The method of engaging deeper spatio-historical understandings is not just to explain the multiple processes/forces driving China’s agrarian change, but more importantly to suggest a different analytical and political frame that “shed[s] light on the slippages, openings, and contradictions where pressure might be applied, as well as connections and alliances from which new possibilities might emerge”. In other words, my research marks a distinct approach by ‘denaturalizing’ social science bounded fields that operate in a bounded concept of space, place, and identity. The major difference between my theoretical and methodological approach and that of the authors just mentioned involves my open, non-teleological understanding of rural transformation in China, and the spatial dimension of possibilities within a globalizing world.Let me begin with the first form—the introduction of machinery to rice production. Just a few years ago, in Xialongkou and the surrounding hill counties, oxen constituted an indispensable animal power in small-scale household agricultural production. Its’ significance was not only in the ancient past, but also during the Maoist collectivization period, and continued after agricultural de-collectivization in 1978. This use of animal traction was of course not confined to western Jiangxi province. In Shanxi Province in the northwest, oxen were important in both traditional times and under the socialist era, as made clear in Liu Qing’s novel Epic of Creating Enterprise . Published at the height of the socialist collectivization movement, Liu describes how, for the first time, privately-owned oxen and other draft animals were leashed and placed under the roofs of collectivized pens, a key step towards collective agriculture. Liu Qing illustrates how dramatic and revolutionary an event it was. When the collective agriculture system was dismantled in the late 1970s, the important role of oxen was unaffected. In the case of Xialongkou and surrounding counties, oxen continued to be used in agricultural work until 2011 . What has been the impact of applying agricultural machines in Xialongkou? In the past, each family took from seven to fourteen days to plough rice paddies by oxen. Plouging was mostly men’s work. Now, villagers can hire a tractor to plough the entire village’s land in two to three days. 

The mechanizing process was also noted in rural Taiwan in the 1990s . In Xialongkou, villagers generally agree that there has been no impact on output per unit of rice paddy. Experienced rice cultivators estimate that about one mu yields around five hundred kilograms of unhusked rice, whether using oxen or machines. However, for the same output per unit of land, each household, and especially its men, clearly now invests fewer workdays in the task of ploughing. In terms of harvesting, machines have also replaced hand-held sickles, by means of which it normally took seven to ten days for all family/household members working together to deal with this “agricultural busy work” . With a hired harvesting machine , the entire village’s “agricultural busy work” can now be finished in one or two days. Of course, hiring machines cost money. As of 2019, one mu cost 80 RMB for ploughing and 100 RMB for harvesting, though prices for hiring machines have been increasing over the past few years and will presumably continue to do so in the near future. The application of agricultural machinery is commonly associated with increasing economies of scale and efficiency, a sign of modern progress and science. The phenomenon of agribusiness companies, a new trend in China’s agrarian capitalism, has attracted considerable attention in scholarship . But large-scale agribusiness is rare in the hill country. What one encounters most commonly are small household farms that remain small and fragmented due to the socialist legacy and topographical conditions. On the surface, agricultural machines seem to accelerate agricultural capitalism in China. Ever since China’s economic reforms of the 1980s, concerns have grown about the rise of capitalist relations and its destruction of agriculture and land commodification in rural China . In Xialongkou, however, changes brought about by machinery like datian ji and gedao ji are integrated into small household agriculture. In the hill country, machines have merely replaced two tasks of rice production: ploughing and harvesting. Rather than expand cultivation, the net effect has been agricultural de-intensification—a decrease in annual agricultural work per person, especially men’s work. As a result, men now have the time to engage in diverse odd jobs in villages and small towns since the late 2000s.

The next section discusses the second form of agricultural de-intensification, land fallowing.Unlike the effect of agricultural machinery, de-intensification through land fallowing requires taking into consideration both temporal and spatial dimensions. One thing to note is that in Xialongkou, all rice fields are irrigated by hill streams flowing down from higher ground via natural gravity, not by the river that runs in front of the village yearlong. As will become clearer later, this water source is crucial to understanding both temporal and spatial aspects of land fallowing. Seen from a temporal perspective, de-intensification comes in three types: 1) shifting from multi-cropping to single cropping ; 2) shifting from multi-cropping to short fallowing; and 3) shifting from single cropping to short fallowing, bush fallowing, or forest fallowing. The first form is really a seasonal fallowing within an annual cycle, whereas the latter two involve a much longer fallow time extending beyond the yearly cycle. All three of these forms involve, fundamentally, greenhouse racking the reduction in agricultural intensity per unit of land. As Table 3 shows, in Xialongkou and its surrounding villages, at least from the 1980s to 2008, there were four major crops cultivated in paddy fields in a traditional lunar calendar year cycle. They were “early rice” , “big rice” , “second rice” , and “rape” . The “early rice” was transplanted from a seedling bed in early March and harvested in June. The “big rice” was transplanted from a seedling bed in early May and harvested around the time of the MidAutumn Festival . The “second rice” was transplanted from a seedling bed in June and harvested in October. It is called “second rice” because the rice is grown on a paddy where “early rice” has just been reaped; the paddy is immediately re-tilled and covered with a layer of animal manure and night soil . Thus, rice crops were formerly transplanted and harvested three times per year in this hill country, though not all of the three harvests made use of the same rice plots. From the perspective of rice cultivation, land use involved a mixture of single-cropping and double-cropping. It was labor intensive agricultural production that is not unusual in rural China. After the third harvest, some of the rice paddies were tilled again and fertilized once more with animal manure, with rapeseed then broadcasted on top as a winter crop. The agricultural calendar cycle came to an end when the rape crop was harvested in late February. As shown in Table 3,“early rice” and “second rice” have been largely eliminated since 2008. The three distinct rice crops have been reduced to just one—“big rice”—which is now grown after a winter rape crop.The daughter-in-law works at the Township post office, which was sub-contacted to her father one year ago. Regarding the family ox, the young couple believes using machinery is the way to go. It is the modernization process. The Daniu couple kept the family ox to save on the unnecessary expense of hiring “smashing field” machines. Many older villagers who praise the Daniu family for their industriousness and thrifty ethic share their views. At the heart of the generational divide lies the difference between waged labor and agricultural work as life styles. Although the Daniu couple lives at a level of semi-subsistence, making few purchases from the market, they are by no means resisting the market and consumption. The couple seeks market opportunities to sell their labor by doing varied odd jobs, just like the rest of Xialongkou residents. The difference is that the Daniucouple keeps agricultural work as their core way of life and other odd jobs as sidelines, while the younger generation like the son and daughter-in-law reverses the relationship between the family farm and outside waged labor. It is not uncommon to observe young adults remaining idle at their village home while their older parents work hard in the rice fields. One common reason is that they are uninterested in non-monetary returns as an alternative to waged jobs.5 But the generational tension is more complicated than simply the divide between different values and attitudes towards agricultural work. An interesting twist involves how both young and old integrate the traditional value of filial piety into agricultural work. Let me illustrate this point with the story of Shaogang. In brief, not all young villagers could avoid the “soil” —a pun in both vernacular and official discourse that refers both to agriculture and to family responsibility. Shaogang, an ex-migrant, in his late 30s, has had a middle school education. For many years, he worked and lived in Zhejiang province. He came back to Xialongkou Hamlet to till the family land with a small tractor in 2012. He is the youngest son and now has the duty to look after his elderly parents, the result of a collective decision made with his two older brothers. Although his peers have a low opinion of agricultural work, tilling the family land has become a moral duty linked to filial piety and family responsibility. Shaogang believes that village elders should “enjoy life” by not working in the rice fields. He came back to farm with the help of machines. Van de Ploge et al. have rightly pointed out the importance of family land that glued three generations of rural family/households. Yet their analysis falls short on rural population’s attachment to the land, especially the elderly generation that tirelessly reinvests and works on the family land for their adult children. They overlook the impact of the existing generational divide on work and lifestyles. The generational divide is real. Unlike Shaogang, most young people do not choose to return to till the land, even if they have the option now to use tractors. Instead, migrants can fulfill their filial duties and family responsibility through remittances, and by persuading their elderly parents to take a rest from hard physical work . One often overhears elderly villagers speaking highly of elderly who do not need to work under the sun: “Look at yourself.

The most harmful diseases are mastitis and foot rot , which reduce the quality of dairy products, inhibit the development of the dairy industry, and have a negative impact on food security and human health. Bovine mastitis is a major disease affecting the dairy industry worldwide with huge economic losses and decreased animal health. Furthermore, it is a common but complicated disease in high-yielding dairy farms. During the course of dairy cow breeding, it is quickly spread and difficult to cure, resulting in serious economic losses. Farm management, particularly proper treatment of manure, has become an issue of concern in many farms. China has the largest population of livestock animals of any country in the world; however, many livestock farms have poor animal manure management facilities for the treatment and disposal of manure. It is therefore suggested that manure management needs to be improved in China. An increasing number of studies have found that poor farm management can lead to severe environmental problems such as the pollution of air, water, and land. The milk industry is one of the five leading strategic industries in the Ningxia region of China. However, few studies have examined the effect of poor dairy farm management on microbial community compositions and diversity among the dairy farm matrix in this region. By using pyrosequencing of metagenomic 16S rDNA, grow trays the objective of this study was to characterize bacterial diversity in feces, manure, and soils in dairy farms in the Ningxia region of China.Three dairy farms representative of typical dairy farm operations in the Ningxia region were enrolled in this study. Farms 1, 2, and 3 were located in the suburbs of Xingqing , Jinfeng , and Xixia districts of Yinchuan City, respectively. Between April and July of 2016, fresh feces, manure, and soil samples were collected from these farms.

Fresh fecal samples were collected within 30 seconds of excrement from lactating cows. Manure samples were collected from piles of accumulated manure without further treatment. Soil samples were collected from around the farms at different depths . To eliminate error caused by individual differences or unrelated factors, fresh fecal samples were a blend of at least six cow feces and manure and soil samples were a blend of at least six sampling sites or depths. Each sample from each farm was mixed separately, with a total of 27 samples being generated after mixing. All samples were refrigerated immediately after collection and during transportation to the laboratory. Upon arrival at the laboratory, samples were stored at −80° C until processing.Metagenomic DNA was extracted from all types of samples using a QIAampR DNA Stool Mini Kit according to the manufacturer’s instructions. Sequencing by synthesis was performed on an Illumina HiSeq 250 platform .Sequence analysis was performed using the Sparse software . Sequences with ≥97% similarity were assigned to the same operational taxonomic unit . The representative sequence for each OTU was screened for further annotation. Sample reads were assembled using mothur v1.3213. Moreover, high-quality sequences were aligned against the SILVA database. Sequences were further qualitatively trimmed using a 2% cluster error, and chimeras were removed using UCHIME. Assignment of OTUs was performed at 97% identity using the furthest neighbor algorithm. Taxonomic assignments were made against the Ribosomal Database Project database. For comparisons, groups were normalized to include 27 samples, each randomly subsampled to 25,000 sequence reads . For determination of the percentages of sequence reads and OTUs unique to each group, no normalization was performed.

The UniFrac distances were calculated using QIIME software , and these data were used to build the UPGMA sample cluster tree. Jackknifed beta diversity included both unweighted and weighted UniFrac distances calculated with 10 times subsampling, and these distances were visualized by principal coordinate analysis. Principal component analysis , PCoA, and non-metric multidimensional scaling analysis graphs were drawn using the R software . Taxonomy assignment of OTUs was performed by comparing sequences to the Greengenes database . The Mann–Whitney U test was used to test for the significance of alpha diversity. Two-sided Student’s t-test was conducted to determine the significance of beta diversity between sample groups. Linear discriminant analysis coupled with effect size was performed to identify the bacterial taxa represented between groups at the genus or higher taxonomy levels. The functional profiles of microbial communities were predicted using PICRUSt. The bootstrap Mann–Whitney U test with 1000 permutations wasalso used to identify gene pathways or OTUs with significantly different abundances between groups. The R packages “phyloseq” and “heat map” were used for data analysis and plotting .In total, 2.2 million strands of 16S rDNA amplicon data were generated from the 27 samples using pyrosequencing. After trimming and cleaning, this number was reduced to 69,065 high-quality reads with a median length of 253 bp. Only 1.5% of the sequences were identified as chimeras and were excluded from further analysis. The number of sequences in the 27 filtered samples was in the range of 47,924 to 83,624 sequences, and after homogenizing these sequences, the sequences were concentrated to around 45,000. An OTU table was generated by clustering all of the sequences into OTUs with a 97% similarity level. The species observed among the samples showed that the same samples from different farms possessed the same patterns, with the number of microbial notes in soil being higher than that in other samples.

The samples were grouped by category, and the main annotations are shown in Table 1. A bacterial community bar chart of all samples was constructed at the phylum level, from which 47 units were annotated from fecal samples, 44 units were annotated from manure samples, and 50 units were annotated from soil samples . The percentages of each of the top 10 phyla in all of the samples are shown in Table 1. These phyla were abundant and accounted for >94.63% of the entire bacterial communities in all of the samples. Therefore, these 10 phyla of bacteria were chosen for further analysis. In the class-level analysis, 75 classes of bacteria were detected among the 10 phyla . At the order level, 63 bacterial orders were noted from the Proteobacteria.The distribution of the relative abundances of bacteria at the phylum level varied among fresh feces, manure, and soil samples. The dominating phylum of bacteria in fresh feces was Firmicutes , followed by Bacteroidetes , Proteobacteria , and Spirochaetes . In manure, the dominating phylum was Proteobacteria , followed by Firmicutes , Bacteroidetes , and Actinobacteria . In soil, the dominating phylum was Proteobacteria , followed by Bacteroidetes , Actinobacteria , and Firmicutes . Data show that Proteobacteria, Bacteroidetes, and Firmicutes were the main phyla in all types of samples, although the percentage of Firmicutes was slightly lower than that of Actinobacteria in the soil samples. The three phyla were distributed at approximately similar ratios in the two manure samples , while Proteobacteria dominated in one manure sample . In contrast to the fecal and manure samples, Proteobacteria dominated the bacterial communities in all of the soil samples . In fresh feces, the phylum Firmicutes was predominantly composed of the three classes Clostridia, Bacilli, and Erysipelotrichi, the phylum Proteobacteria was comprised mainly of the classes Gammaproteobacteria, Betaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, and Epsilonproteobacteria, the phylum Bacteroidetes was mainly composed of the classes Bacteroidia, Cytophagia, Sphingobacteriia, Saprospirae, Rhodothermi, and Flavobacteria, and the phylum Spirochaetes was mainly composed of the classes Spirochaetes, MVP-15, Brevinematae, and Leptospirae . In manure, the compositions of the classes in the phyla Proteobacteria, Firmicutes, pruning cannabis and Bacteroidetes were similar to those in fresh feces. However, the phylum Firmicutes in manure consisted of an additional class called AHT28. In addition, the phylum Actinobacteria in manure was mainly composed of the classes Actinobacteria, Acidimicrobiia, Thermoleophilia, Rubrobacteria, Nitriliruptoria, and Coriobacteriia . The data within the OTU table was compared between 5,000 randomly selected samples each at a 97% nucleotide identity level. To investigate variations in the distributions within microbial communities, all OTUs were assigned taxonomically using the RDP classifier. Among a total of 8819 OTUs, most bacteria were concentrated into five phyla, namely, Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes, and Actinobacteria. The heat map results showed that the compositions of the microbes in the same types of samples appeared to be similar .PCA profiles indicated that microbial communities varied depending on the type of sample. Principal components 1 and 2 demonstrated 14.11% and 11.91% of the total variance, respectively . PCA profiles showed significant separations between F1, F2, and F3 and M1, M2, and M3 treatments at three sites, especially for S1, S2, and S3. Treatments M1–M3 had higher scores than the corresponding treatments F1–F3 along the PC1 axis. According to the PC2 axis, PCA profile scores for treatment S3 were higher than those for both of the corresponding treatments S1 and S2.

To determine the similarity between different samples, a clustering tree was constructed using UPGMA , which is a commonly used method for cluster analysis. Interestingly, the same type of samples from different farms clustered within the same branches . Further, beta analysis of microbial diversity showed that the diversity of species within the fecal, manure, and soil groups was rather small, in contrast to the large differences among the fecal and soil groups . In the analysis of human pathogenic bacteria, this trend was also detected. The boxplot showing the phylum level classification in terms of both bacterial diversity and the diversity of zoonotic pathogens revealed that the fresh feces contained a great abundance of Firmicutes, but a low diversity of zoonotic pathogens. By contrast, little change in diversity was observed in the accumulated manure or soil samples .The diversity and relative abundance of zoonotic pathogens in the manure and soil samples are shown in Figure 8. In total, 32 species of pathogenic bacteria were found in feces, manure, and soils. Acinetobacter calcoaceticus and Bacillus cereus were the dominant zoonotic species in feces, followed by Enterococcus faecalis, Streptococcus uberis 0140J, Escherichia coli O26: H11, Corynebacterium diphtheria, Staphylococcus aureus C0673, and Pseudomonas aeruginosa. The relative abundance of B. cereus in feces was 3 to 17 times higher, respectively, compared with that in manure and soil. Among the 32 pathogens, the relative abundance of 20 pathogens varied significantly in feces and manure, with the relative abundance in manure 2 to 19 times higher than that in feces. The number of Actinomycetes in manure was much higher than that in fresh feces. Further, at the genus level, although the number of genera in manure decreased, the number of bacteria and Pseudomonas increased significantly. This phenomenon was closely correlated with the abundances in feces and manure. In a more detailed classification order, the first dairy farm was detected having 27 zoonotic species, of which five species were increased in abundance in manure,including S. aureus M0406, Clostridium perfringens B str. ATCC 3626, A. calcoaceticus, Bacteroides fragilis NCTC 9343, and Bacteroides vulgatus CL09T03C04. In the second dairy farm, 34 zoonotic species were found, of which 14 species were increased in abundance in manure, namely, B. cereus, Listeria monocytogenes FSL R2-503, S. aureus M0406 and C0673, E. faecalis, S. uberis 0140J, Streptococcus dysgalactiae, Clostridium botulinum, A. calcoaceticus, Acinetobacter baumanii BIDMC 57, Proteus mirabilis BB2000, and Vibrio cholera VCC19. Finally, in the third dairy farm, 29 zoonotic species were found, of which 15 species showed increased abundance in manure, namely, B. cereus, L. monocytogenes FSL R2-503, S. aureus M0406 and C0673, B. cereus, S. uberis, S. dysgalactiae, E. faecalis, P. aeruginosa, Klebsiella pneumoniae, C. diphtheria, Yersinia pestis biovar Antiqua B42003004, V. cholera VCC19, and B. fragilis 3725-D9-ii. Statistical analysis of the OTU at the order level shows that the number of zoonotic bacteria in dairy farm 1 and dairy farm 2 was significantly higher in the manure than in the fresh fecal samples .In the Ningxia region, manure from most of the dairy farms is used as an organic fertilizer by local farmers without proper treatment. However, to our knowledge, the composition, diversity, and abundance of bacterial communities in the manure that has not been properly treated in this region are poorly understood, but this manure is being used as a fertilizer. Livestock and poultry manure contains feces, urine, litter, nose stains, blood stains, shed skin, hair, and placental material.

The sample types included skin-on/bone-in chicken, ground beef, ground turkey, and pork chops . Meat samples in different packages , vacuum packing, and paper wrapping were placed on ice immediately after purchasing, transported to the lab in refrigerated conditions, and processed within 72 hours after collection. Samples were processed according to the NARMS Retail Meat Surveillance protocol . Briefly, 50 g of each sample was placed into 250 ml buffered peptone water in whirl-pak bags and massaged by hand for 3 minutes. After massaging, the homogenates were incubated at 35°C for 18–24 h. Then, 0.1 ml overnight enrichment was transferred to 10 ml RVR10 and incubated at 42°C for 20-24 hours. The RVR10 enrichments were streaked onto XLT-4 . Two colonies of presumptive Salmonella based on colony morphology were then streaked onto blood agar plates  and incubated at 35°C for 20-24 hours. Presumptive Salmonella isolates were banked in Brucella broth with 15% glycerol tubes and shipped to the FDA’s Center for Veterinary Medicine for antimicrobial susceptibility test, whole genome sequencing , and other analysis.R statistical software Statistical Computing, Vienna, Austria was used to do all the analysis. The statistical significance is defined at an alpha level of 0.05. Descriptive statistics for the prevalence of Salmonella and distribution of antimicrobial susceptibility test results were conducted in R. Data analysis was conducted on a total of 132 Salmonella isolates from 130 different meat samples due to two Salmonella isolates of different serotypes recovered from 2 pork samples. The reduced antibiotic use category is composed of samples with label claims of no antibiotic ever and/or organic in packages. The association between Salmonella prevalence in retail meat samples and sampling region, season, meat type, pots for cannabis plants package type, label claim, and store types based on their size were assessed using Fisher’s exact test.

Post-hoc analysis was performed using the cldList function of the R package companion . The correlation between phenotypical and genotypical AMR was calculated by dividing the number of phenotypical antimicrobial-resistant Salmonella isolates by the number of Salmonella isolates with corresponding resistant genes. A heatmap of hierarchical clustering was generated utilizing the heatmap3. package in R .The occurrence of Salmonella in retail meat in California in this study was higher than both the national average  and that from the previous year in California . This overall higher prevalence was likely due to higher recovery rate by 1) changes in the NARMS protocol the high number of whole chicken carcasses samples collected in Southern California than Northern California in 2019 . Previous research has also reported a higher prevalence of Salmonella in whole chicken carcasses compared to cut samples of chicken . In addition to the higher number and higher prevalence of Salmonella in whole chicken carcasses from Southern California, other chicken parts such as breasts, wings, and legs from Southern California also had a higher prevalence of Salmonella compared to those from Northern California, which collectively contributed to the significant higher Salmonella prevalence in chicken in Southern California in contrast to that in Northern California . Meat types in this study were not collected in identical proportions: chicken samples – 479 , ground turkey samples – 240 , ground beef samples – 65 , and pork samples – 65 . The disproportionate distribution of samples among the meat types might affect the Salmonella recovery rate from different types of meat. For instance, a larger variety of chicken samples were purchased as compared to turkey and beef, where only ground samples were collected. Our data indicated the highest recovery of Salmonella was in chicken samples , followed by ground turkey and pork samples , and zero recovery from ground beef samples. The cause of the higher prevalence of Salmonella in chicken was aforementioned.

With respect to prevalence in other types of meat, ground turkey samples were lower compared to the national average , pork and ground beef samples were close to the national averages of 4.00% in pork and ~1% in ground beef . The high prevalence of Salmonella in chicken compared to other types of retail meat has been well-documented in previous studies . In general, chicken is a significant source of Salmonella, as contamination can potentially occur throughout the entire production chain, from farm to transportation, during processing in slaughterhouses, and on retail shelves . The prevalence of Salmonella in chicken also varied by U.S. states . For example, Zhao et al. reported that higher prevalence in chicken might be caused by sample type , while Nyirabahizi et al. found that regional factors may impact the prevalence of Salmonella. The current study revealed a notably greater prevalence of Salmonella in samples with reduced antibiotics claim compared to those from conventional production . These findings differ from previous NARMS data, which reported a slightly higher prevalence of Salmonella in samples with conventional production compared to those with reduced antibiotics claims. . One possible explanation might be attributed, at least in part, to the survival and propagation of Salmonella on these farms, which may be favored by conditions associated with reduced antibiotic use. For example, reduced antimicrobial use might result in fewer interventions to control bacterial infections on farms, and lack of routine antimicrobial treatments might increase the prevalence of Salmonella. Moreover, lack of antimicrobial use can affect the competitive balance between beneficial and harmful bacteria in the gut of animals, leading to an increased Salmonella prevalence .

It is also worth noting that larger numbers of pork, ground beef, and ground turkey samples from conventional production had low or zero recoveries of Salmonella, which contributed to the overall low prevalence of Salmonella in meat samples from conventional raise in our study. More than 2,600 Salmonella serotypes have been identified, with specific serotypes frequently associated with severe illnesses . The present study classified the 132 Salmonella isolates into 25 serotypes. Among these serotypes, those frequently implicated in foodborne illness are S. Typhimurium and S. Enteritidis. In the present study, both S. Typhimurium and S. Enteritidis were found in chicken samples. Salmonella Infantis accounted for 64.29% of MDR isolates and was the most prevalent MDR serotype in retail meat in California in 2019, which was different than the national NARMS data. In 2019, the most common MDR Salmonella serotype was I 4,[5],12:i: which comprised 26% of nationwide MDR isolates . However, the rise of MDR S. Infantis caused the national average of MDR Salmonella strains in retail chicken to increase from 20% in2018 to 32% in 2019 . In our study, all the S. Infantis isolates were from chicken samples, which was consistent with the national trend. Finally, the prevalence of MDR Salmonella isolates in our study in California was at the same level as the national average from the NARMS 2019 surveillance data . In the present study, a high prevalence of resistance to tetracycline and streptomycin in Salmonella isolates from poultry samples was observed. This is consistent with the results of the NARMS retail meat surveillance in California in 2018 and the NARMS national AMR data of Salmonella from retail poultry in 2008-2017 . Tetracycline has been commonly used in poultry farming to prevent and cure different poultry illnesses, such as respiratory problems, gut inflammation, and joint infection . Streptomycin, as one of the earliest aminoglycosides developed for combating bacterial infections in the poultry industry, has been utilized against various pathogens including E. coli, Salmonella, Mycoplasma, and Staphylococcus . A notable observation in the current study is that the majority of S. Infantis isolates were resistant to ciprofloxacin and nalidixic acid despite restrictions in fluoroquinolone use in food animal production in the U.S. We attempted to determine the relationships between the occurrence of Salmonella resistance and the claims of antibiotics use. However, indoor cannabis grow system no significant difference was found between isolates with reduced antibiotic claims and conventional in single and multidrug resistance despite the fact that resistance to two drugs was higher in isolates with claims of reduced antibiotics than in isolates with claims of conventional production. Whole genome sequencing has been an essential tool for the characterization and confirmation of AMR in bacteria, especially in the identification of resistance mechanisms where AST has limitations . Our results showed that genotypic resistance was highly corellated with phenotypic resistance, with a sensitivity of 96.85%. Only one of the three Salmonella isolates that exhibited resistance to gentamicin by AST lacked the corresponding resistance gene by WGS analysis. This discordance might be due to the presence of undetected AMR genetic determinants or misclassification of the isolate from AST . On the other hand, the ability of WGS to detect only known AMR genetic determinants highlights the importance of continuous traditional AST for comprehensive AMR assessment .

Consequently, it remains valuable to incorporate both WGS and AST to assess AMR patterns in pathogens, particularly given the potential of new resistance genes continuing to emerge. Plasmid replicons are essential genetic elements that play a crucial role in the dissemination of antimicrobial resistant genes within and between bacterial species . Therefore, the identification and characterization of plasmids can provide insight into the transmission potential of AMR genes between or within bacteria species . In the present study, we discovered various plasmid replicons among various Salmonella serovars. Many of these plasmid replicons have previously been associated with AMR genes. Seventy-six of these isolates were from chicken samples, and one isolate was from the ground turkey sample. Previous studies reported plasmid replicon IncX1 being associated with beta-lactam, quinolones, and tetracycline resistance genes . Additionally, in the present study, plasmid replicon IncFIB was found in 7 MDR, ESBLproducing S. Infantis isolates, and all these isolates came from poultry samples. This is worrisome because previously, plasmid replicon IncFIB has been linked to S. Infantis clone with large megaplasmid, which has been disseminating quickly in the U.S. and worldwide during the last nine years . In the present research, all the MDR S. Infantis genes harbored a gyrA mutation that confers resistance to fluoroquinolone, and four MDR S.Infantis had the extended-spectrum beta-lactamase gene blaCTX-M-65. The fast spread of this MDR S. Infantis clone is concerning as it might undermine the existing treatment options to treat infections.Antimicrobial resistance has become a serious issue worldwide, challenging existing treatment options in human and veterinary medicine. Identifying the transmission routes of antimicrobial-resistant bacteria and the characterization of resistance patterns in antimicrobial resistant bacteria is crucial in combatting the antimicrobial resistance problem. The first study tried to identify probable transmission routes of bacteria from poultry farm environments to farm workers. According to previous studies, farm workers were exposed to antimicrobial resistance via direct contact with farm animals or indirectly through farm environments such as urine or feces, water, and soil. We isolated E. coli from environmental samples and worker’s outwear and footwear samples. Then, antimicrobial patterns in E. coli isolates were characterized. The results showed that E. coli isolates from environmental and worker’s samples shared similar resistant patterns, implying that antimicrobial-resistant bacteria might be transmitted to workers. The results also indicated that the door handles of the facilities pose a serious risk to worker’s health, and worker’s outwear and footwear an important defense to limit the transmission of ARB or ARG. Occupational exposure of farm workers to antimicrobial resistance has been long neglected, and further studies are needed to raise awareness among policymakers and farm workers. The objective of the second study was to characterize antimicrobial resistance patterns in Salmonella from the collected retail meat samples in California. The study found that whole chicken samples had a higher prevalence of Salmonella compared to other chicken parts. Overall, Salmonella isolates from chicken samples were resistant to most of the tested antimicrobial drugs. Resistance to streptomycin and tetracycline was very high in Salmonella isolates. The multi-resistance pattern was most prevalent in S. Infantis isolates.Phenotypical resistance in Salmonella was confirmed by using Whole Genome Sequencing , and WGS accurately found resistance in bacteria with a sensitivity of 96.85 %. Additionally, WGS allowed us to find plasmid replicons that play a crucial role in the transmission of antimicrobial resistance. The study identified resistance genes mutation and plasmid replicons which were associated with the previous outbreaks in North America. The study characterized antimicrobial resistance patterns in Salmonella and identified resistant genes and plasmid replicons that play crucial roles in the dissemination of AMR. Additionally, this comprehensive study helped to identify regional patterns of antimicrobial resistance in Salmonella and established a baseline understanding of the current resistance patterns.

The drinking water standard has since been changed to 50 mg/L, but the STLC was not adjusted. Since wildlife must be protected at concentrations that are orders of magnitude less than the STLC, raising the STLC would have no impact on hazards to wildlife. Indeed, increasing the legally defined STLC would have an insignificant impact on environmental hazards but would facilitate opportunities to maintain an economically sustainable agriculture production system in the western San Joaquin Valley.Microorganisms, including bacteria, have developed mechanisms to protect themselves from the effects of antibacterial substances for several billion years . Antimicrobial resistance is the capability of microorganisms to survive the effects of antimicrobial agents via various mechanisms, such as a mutation in an existing gene or obtaining resistant genes through horizontal gene transfer . Four main mechanisms of AMR in bacteria are limiting the uptake of a drug, modifying a drug target, inactivating a drug and active drug efflux . Additionally, there are two main biological pathways that enable the evolution and dissemination of resistance: vertical gene transfer and horizontal gene transfer . Although the widespread usage of antibiotics began in the middle of the last century after the discovery of penicillin by Alexander Fleming, antimicrobial resistance has been recognized as a global threat and one of the leading public health problems of the 21st century only over the last two decades . The World Health Organization’s first report on worldwide surveillance of AMR, cannabis equipment which was released in April 2014, showed the seriousness of the AMR problem Many factors are attributed to the emergence and spread of AMR, including overuse and misuse of antimicrobial drugs, poor sanitation, poor practice of disease prevention and control, lack of knowledge, public awareness, legislation and lack of innovation and development of drug resources .

However, overuse or misuse of antimicrobial drugs is considered the leading cause of the emergence and spread of AMR or accelerated development of AMR . Especially, the usage of antimicrobial drugs in food animal production has been considered as one of the contributors to the AMR problem . In the U.S., approximately 2.8 million clinical infections and 35,000 human deaths occur annually . According to an estimate, by 2050, AMR could be the leading cause of mortality, with 10 million deaths, surpassing cancer in the mortality rate . Besides taking polls on people’s lives, AMR causes an economic burden to the patients. It makes diseases and hospital stays longer, medical costs higher, and treatments ineffective and sometimes impossible to treat . Making exact estimates of the burden of AMR is challenging. According to the recent review by Naylor et al. , the economic burden from AMR per case is around $21832 and over $ 3 trillion in GDP loss. The economic burden from AMR in the U.S.,as reported by the Centers for Disease Control and Prevention , is around 4-5 billion dollars every year. It is expected that by 2050, a total global economic cost of US$100 trillion will be attributed to AMR . Long-term exposure to antibiotics might weaken the immune system in humans, cause digestive problems, and have carcinogenic effects . Some infectious diseases easily treatable with penicillin in the past now require second and third-line antibiotics due to AMR. Other medical areas, such as chemotherapy for cancer treatment, organ transplantation, hip replacement surgery, intensive care for pre-term newborns, and many others, depend on the availability of efficient antibiotic drugs. Infections triggered by MDR bacteria are the main contributors to morbidity and mortality in people undergoing the above mentioned procedures. For example, studies have shown high AMR rates in infections in patients with cancer and liver transplantation .

Antimicrobial agents are a semi-synthetic or synthetic substance that kills or inhibits microorganisms . Since the 1940s, antibiotic agents have been used in the livestock industry for disease prevention and treatment and growth promotion. Antimicrobial agents in livestock have yielded healthier and more productive animals with lower disease incidence and reduced morbidity while lowering the cost of animal food production . However, this honeymoon period was short-lived, and these benefits have yielded adverse outcomes: overuse and misuse of antimicrobials in food animal production resulted in an accelerated increase in antimicrobial resistance, and food animals have become reservoirs of antibiotic-resistant bacteria . Antibiotic-resistant bacteria and their genetic determinants can be transferred from food animals to humans via direct or indirect contact or food chains . Increased demand for protein led to the global spread of intensive farming , and antimicrobial usage has become an essential part of intensive farming . Global food animal production increased 4-5-fold since 1961. In turn, intensive farming expansion has led to increased consumption of antimicrobials worldwide . Two-thirds of the total medically important antimicrobials in the U.S. are associated with food animal production . In 2019 alone 11,000 tons of antibiotics were used in animal production . It is projected that the consumption of antimicrobials will rise by 67% by 2030 worldwide, and the rise is likely caused by expected consumer demand for livestock products as the global population and affluent people are increasing in developed countries . According to the Bayesian regression framework conducted by , antimicrobial consumption is expected to increase in pigs and chickens compared to cattle. Antibiotics in food animals can be divided into three categories: therapeutic use, disease prevention, and growth promotion .

Usage of antibiotics for disease prevention and growth promotion in food animals are distinct practices, and they are differentiated based on the purpose of usage, stage of lifecycle, timing of antibiotic administration, and dosage levels. For example, in disease prevention, antibiotics are administered at therapeutic levels , while in growth promotion, antibiotics are administered at subtherapeutic levels . Another example antibiotics for disease prevention are administered for a short period of time before outbreaks, while antibiotics for growth promotion are administered continuously during the animal’s growth phase or over a long period . However, there might still be a blurred line between these two practices. There are still possibilities to use antibiotics as growth promoters despite the U.S. banned growth promoters in 2017. For example, dosing food animals continuously with antibiotics for disease prevention has been used in large-scale farming . Antibiotics are administered via feed, water, or intramuscular injection . Antimicrobials are administered to the entire flock or group in intensive farming via feed or water. The purpose of this practice is to prevent the spread of the disease. However, this practice sometimes results in overuse or misuse of antimicrobials, increasing ARB in animals. Additionally, the occurrence of infectious diseases and usage of antimicrobials depends on endogenous risk factors and farmers’ decision-making, which can be influenced by cost-benefit analysis, farmer’s expertise, and behavior .WHO has recognized the necessity of coordinated global efforts to mitigate the AMR spread and recommended avoiding using antimicrobials in food animal production . New European regulations on veterinary medicine and medicated feed are expected to substantially reduce antimicrobial usage in food animal production throughout Europe in the future . In the U.S., the FDA has been regulating antimicrobial drug prescriptions by implementing stricter policies on using antimicrobials over the years. For example, in 2017, the FDA banned the usage of growth promoters in the production of food animals, vertical grow shelf and in the same year, it also required veterinary prescriptions for “important antimicrobials” defined as Veterinary Feed Directive drugs. Therefore, banning antimicrobials as growth promoters in Europe in 2003, followed by the U.S. in 2017, helped to reduce antimicrobial consumption . For example, in the Netherlands, consumption of antimicrobials decreased by 70 % between 2009 and 2019, and the resistance of some species of bacteria decreased compared to the previous years . FDA has been developing strategies to reduce the usage of antimicrobials in food animal production . For example, in 2015, the FDA updated the new animal drug regulations to put into practice the veterinary feed directive , and according to this update, VFD drugs have been allowed only under the professional oversight of a licensed veterinarian. Recent studies have shown the effectiveness of reducing the usage of antimicrobials in food animal production in taming AMR. For example, the literature review conducted by Tang et al. has shown that restricting antimicrobial usage in food animal production might reduce animal ARB by up to 39 %. However, with an increase in global population and wealthy people in developing countries, demand for animal protein is expected to increase, further challenging the combat to reduce AMR.

Critically important antimicrobials play an essential role in treating life-threatening infectious diseases in humans and animals, and they are considered the last line of defense against some serious infectious illnesses . The List of Critically Important Antimicrobials of WHO for Human Medicine was developed in 2005 and has been updated since, the latest being updated in 2018 . Since its development, the CIA List has been the benchmark for food animal producers worldwide by providing essential guidance . WHO classified antimicrobials into three groups: important, highly important, and critically important. . Most antimicrobial classes on the WHO CIA list belong to the “Critically Important” category, and fewer belong to other groups. Apart from the WHO CIA list, the World Organization for Animal Health created a CIA list, which is a list of essential antimicrobials for veterinary medicine. Additionally, the WHO encourages countries to have their own CIA list, and the U.S. The CIAs have been further classified into high-priority and highest-priority CIAs based on the number of people with infections for which limited antimicrobials are available and the rate of usage among high-risk groups in human medicine . The highest priority CIAs are the quinolones , 3rd and higher-generation cephalosporins, macrolides and ketolides, glycopeptides, and polymyxins . High-priority CIAs are aminoglycosides, penicillins, ansamycins, penems, glycylcyclines, lipopeptides, monobactams, oxazolidinones, and mycobacterial drugs. Highly important antimicrobials are tetracyclines, amphenicols, cephalosporins , lincosamides, pseudomonic acids,riminofenazines, steroid antibacterials, streptogramins, sulfonamides, sulfones. Important antimicrobials are aminocyclitols, cyclic polypeptides, nitrofurantoin, nitroimidazoles, and pleuromutilins . Most antimicrobial classes are common in both veterinary and human medicine; nevertheless, the importance of some antimicrobials might differ based on species and application . According to the World Health Organization’s categorization, critically important antibiotics for human medicine are fluoroquinolones, thirdand fourth-generation cephalosporins, macrolides, glycopeptides, and polymyxins . Penicillin, macrolides, and fluoroquinolones are mainly used to treat human infections, while tetracyclines, penicillin, and sulfonamides are frequently used to treat food animal infections . Not long after its invention, penicillin was used to treat bovine mastitis to sustain the sustain milk supplies during World War II. In 1948 sulfaquinoxaline was used in poultry for the prevention of coccidiosis. In the U.S., antibiotics in livestock were first approved in 1951, giving birth to antibiotic-reliant large-scale food animal production operations . In recent years, in the U.S., antibiotic consumption in chicken production is decreased dramatically. For example, in 2018, ninety-two percent of broilers were produced without using medically important antimicrobials . Penicillin and tetracycline are mostly used in pigs worldwide . In 2012, tetracycline accounted for 41 % of total sold antimicrobials in the U.S. . Extended-spectrum cephalosporins, macrolides, fluoroquinolones, and polymyxins are classes of CIA usedin pigs and cattle worldwide . In the U.S., 43% of all medically essential antimicrobials were consumed in cattle in 2016 In 2017, WHO released recommendations on the utilization of medically important antimicrobials in animal agriculture to keep the effectiveness of medically important antimicrobials. In 2018, the WHO issued guidelines on using HP-CIAs in food-producing animals; the guidelines recommended not to use HP-CIAs for human medicine in treating food animals with infectious disease diagnoses . These measures have been taken to fight antimicrobial resistance and preserve the effectiveness of CIAs.Occupational exposure of animal farm workers to AMR has been largely neglected and unrecognized due to different reasons such as scarce knowledge about AMR burden, lack of adequate regulations, lack or insufficiency of surveillance and monitoring, and economic factors . The chance of transmission of ARB or antibiotic resistance genes from food animals to farm workers is very high based on previous research, which reported that occupational exposure poses a risk to farm workers . Specifically, ARB can be transmitted from animals to farm works through various ways, including direct contact with animals or animal feces or products, inhalation of dust or aerosols containing ARB or ARG, contact with ARB or ARG contaminated surfaces, equipment, tools, water, or food .