The Farmer First approach recognizes multiple knowledge forms and challenges the standard “information transfer” pipeline model that is often applied in research and extension contexts . We used an open-ended, qualitative approach that relied on in-depth and in-person interviews to study farmer knowledge. Such methods are complementary to surveys that use quantitative methods for capturing a large sample of responses . Because they are more open-ended, qualitative approaches allow for more unanticipated directions ; however, as Scoones and Thompson point out, removing local knowledge from its local context and attempting to fit it into the constrictive framework of Western scientific rationality is likely to lead to significant errors in interpretation, assimilation, and application. While interviews are not able to capture the quantity of farmer input that surveys do, in-depth interviews allow researchers to access a deeper knowledge base that has inherent value—despite limitations in scalability and/or transferability—as participants respond in their own words, using their own categorization, and perceived associations . Such in-depth interviews are therefore essential to research on farmer knowledge and local knowledge .In-person interviews were conducted in the winter, between December 2019 – February 2020; three interviews were conducted in December 2020. We used a two-tiered interview process, where we scheduled an initial field visit and then returned for an in-depth, semi-structured interview. The purpose of the preliminary field visit was to help establish rapport and increase the amount and depth of knowledge farmers shared during the semi-structured interviews. Farmers were asked to walk through their farm and talk more generally about their fields, their management practices, pipp drying racks and their understanding of the term “soil health.”
The field interview also provided an opportunity for open dialogue with farmers regarding management practices and local knowledge . Because local knowledge is often tacit, the field component was beneficial to connect knowledge shared to specific fields and specific practices. After the initial field visits, all 13 farmers were contacted to participate in a follow up visit to their farm that consisted of a semi-structured interview followed by a brief survey. The semistructured interview is the most standard technique for gathering local knowledge . These in-depth interviews allowed us to ask the same questions of each farmer so that comparisons between interviews could be made. To develop interview questions for the semistructured interviews , we established initial topics such as the farmer’s background, farm history, general farm management and soil management approaches. We consulted with two organic farmers to develop final interview questions. The final format of the semi-structured interviews was designed to encourage deep knowledge sharing. For example, the interview questions were structured such that questions revisited topics to allow interviewees to expand on and deepen their answer with each subsequent version of the question. Certain questions attempted to understand farmer perspectives from multiple angles and avoided scientific jargon or frameworks whenever possible. Most questions promoted open-ended responses to elicit the full range of possible responses from farmers. In the interviews, we posed questions about the history and background of the participant and their farm operation, how participants learned to farm, and to describe this process of learning in their own words, as well as details about their general management approaches.
Farmers were encouraged to share specific stories and observations that related to specific questions. Next, we asked a detailed set of questions about their soil management practices, including specific questions about soil quality and soil fertility on their farm. In this context, soil quality focused on ecological aspects of their soil’s ability to perform key functions for their farm operation ; while soil fertility centered on agronomic aspects of their soils’ ability to sustain nutrients necessary for production agriculture . A brief in-person survey that asked a few demographic questions was administered at the end of the semi-structured interviews. Interviews were conducted in person on farms to ensure consistency and to help put farmers at ease. The interviews typically lasted two hours and were recorded with permission from the interviewee. Interviews were transcribed, reviewed for accuracy, and uploaded to NVivo 12, a software tool used to categorize and organize themes systematically based on research questions . Coding is a commonly used qualitative analysis technique that allows researchers to explore, understand, and compare interviews by tracking specific themes . Through structured analysis of the interview transcripts, we identified key themes and constructed a codebook to delineate categories of knowledge. Once initial coding was complete, we reviewed quotations related to each code to assess whether the code was accurate. The final analysis included both quantitative and qualitative assessments of the coded entries. For the quantitative measure, we tallied both the number of coded passages regarding different themes or topics, and the number of farmers who addressed each theme. In addition, we examined the content of the individual coded entries to understand the nature of farmer knowledge and consensus or divergence among farmer responses for each theme. The organic farmers in Yolo County that were interviewed for this study demonstrated wide and deep knowledge of their farming systems.
Results show that white, first- and second-generation farmers in alternative agriculture do accumulate substantive local knowledge of their farming systems—even within a decade or two of farming. These particular organic farmers demonstrated a complex understanding of their physical environments, soil ecosystems, and local contexts that expands and complements other knowledge bases that inform farming systems. In order to integrate the wide range of knowledge shared in the results, a theoretical framework that incorporates emergent characteristics of the process of farmer knowledge formation is helpful to consider. In the first section of the discussion, we outlined a framework for farmer knowledge formation is outlined. For the latter half of the discussion section, we elaborate on key aspects of farmer knowledge that emerged from results of this study. Figure 1 summarizes a proposed theoretical framework for farmer knowledge formation. This framework recognizes the importance of linking social and ecological processes in order to capture interactions between humans and the environment, and is therefore informed by and extends existing frameworks in the social-ecological literature and can be applied to other farming contexts . The framework encapsulates both social and ecological ways of knowing through an adaptive feedback process, wherein farmers are considered the primary actors in this process of knowledge formation. As shown in Figure 1, farmer knowledge forms through both social and ecological mechanisms. Social mechanisms refer to social and cultural phenomena that influence farmer knowledge and their personal ethos interactively; ecological mechanisms represent how farmers’ observations of and experiences with environmental conditions and ecological processes on their farms influences their knowledge and ethos . Here, farmer ethos is broadly defined as a farmer’s worldview on farming—a set of social values or belief system that a farmer aspires to institute on their farm . As highlighted in yellow, social mechanisms play a central role in producing a farmer’s ethos and in integrating ecological knowledge into their farm operation. At the same time, ecological mechanisms contribute to a farmer’s local ecological knowledge base, and importantly, place limits on the incorporation of social values in practice on farms. Together, these social and ecological mechanisms provide the filter through which farmer ethos and ecological knowledge is re-evaluated over time. As outlined in green, farmer ethos also mutually informs ecological knowledge, and vice versa, in a dynamic, dialectical process as individual farmers apply their ethos or ecological knowledge in practice on their farm. Based on results of this study, pipp horticulture social mechanisms include inherited wisdom from and informal conversations with other local farmers . Likewise, direct observation, personal experience, and on-farm experimentation—wherein a farmer applies the scientific method to make abstract science concrete—are central to developing farmers’ specific ecological knowledge . In general, farmers interviewed tended to rely less on abstract, “basic” science and more on concrete, “applied” science that is based on their specific local contexts and environment . In this way, social and ecological mechanisms were key in translating abstract information into concrete knowledge among farmers interviewed. Findings suggest that experimentation codifies direct observations to generate farmer knowledge that is both concrete and transferable. To a lesser degree, personal experience enhanced farmer knowledge and guided the process of experimentation.This framework is useful for categorizing and tracking farmer learning on working farms. As an example, farmers with a stewardship ethos viewed themselves as caretakers of their land; one farmer described their role as “a liaison between this piece of land and the human environment.” Farmers that self-identified as stewards or caretakers of their land tended to rely most heavily on direct observation and personal experience to learn about their local ecosystems and develop their local ecological knowledge. This knowledge directly informed how farmers approached management of their farms and the types of management practices and regimes they applied.
That said, farmer ethos did not always completely align with farming practices applied day-today due to both social and ecological limits of their environment. For example, one farmer, who considered himself a caretaker of his land expressed that cover crops were central to his management regime and that “we’ve underestimated how much benefit we can get from cover crops.” This same farmer admitted he had not been able to grow cover crops the last few seasons due to early rains, heavy clay in his soil, and the need to have crops ready for early summer markets. In another example, several farmers learned about variations in their soil type by directly observing how soil “behaved” using cover crop growth patterns. These farmers discussed that they learned about patchy locations in their fields, including issues with drainage, prior management history, soil type, and other field characteristics, through observation of cover crop growth in their fields. Repeated observations over space and time helped to transform disparate observations into formalized knowledge. As observations accumulated over space and time, they informed knowledge formation across scales, from specific features of farmers’ fields to larger ecological patterns and phenomena. More broadly, using cover crop growth patterns to assess soil health and productivity allowed several farmers to make key decisions that influenced the long-term resilience of their farm operation . This specific adaptive management technique was developed independently by several farmers over the course of a decade of farming through long-term observation and experimentation and, at the time, was not widely accessible in farming guidebooks, policy recommendations, or the scientific literature. For these farmers, growing a cover crop on new land or land with challenging soils is now formally part of their farm management program and central to their soil management. While some farmers considered this process “trial and error,” in actuality, all farmers engaged in a structured, iterative process of robust decision making in the face of constant uncertainty, similar to the process of adaptative management in the natural resource literature . This critical link to adaptative management is important to consider in the broader context of resilience thinking, wherein adaptive management is a tool in the face of shifting climate regimes and changing landscapes . Specifically, the framework provided in this paper is useful to understand some of the underlying social and ecological mechanisms that produce farmer knowledge, and that may in turn inform adaptive management and pathways toward more resilient agriculture . In this sense, farmer knowledge represents an untapped source for informing concrete adaptative management techniques that are initially adapted to local contexts but also have the potential to be widely applied. Farmer knowledge provides an extension to scientific and policy knowledge bases, in that farmers develop new dimensions of knowledge previously unexplored in the scientific literature. Farmers offer a key source of and process for making abstract knowledge more concrete and better grounded in practice, which is at the heart of adaptive management . Farmer knowledge accumulation, at least among organic farmers in this study, is mostly observational and experiential. Most farmers considered themselves separate from scientific knowledge production and though scientific knowledge did at times inform their own knowledge production, they still ultimately relied on their own direct observation and personal experiences to inform their knowledge base and make decisions. This finding underscores the importance of translating theory into practice in alternative agriculture. Without grounding theoretical scientific findings or policy recommendations in practice, whether that be day-to-day practices or long-term management applied, farmers cannot readily incorporate such “outsider” knowledge into their farm operations.