Across all farmers interviewed, including both first- and second-generation farmers, farmers stressed the steep learning curves associated with learning to farm alternatively and/or organically. While these farmers represent a case study for building a successful, organic farm within one generations, the results of this study beg the question: What advancements in farm management and soil management could be possible with multiple generations of farmer knowledge transfer on the same land? Rather than re-learning the ins and outs of farming every generation or two, as new farmers arrive on new land, farmers could have the opportunity to build on existing knowledge from a direct line of farmers before them, and in this way, potentially contribute to breakthroughs in alternative farming. In this sense, moving forward agriculture in the US has a lot to learn from agroecological farming approaches with a deep multi-generational history . To this end, in most interviews—particularly among older farmers—there was a deep concern over the future of their farm operation beyond their lifetime. Many farmers lamented that no one is slated to take over their farm operation and that all the knowledge they had accumulated would not pass on. There exists a need to fill this gap in knowledge transfer between shifting generations of farmers in order to safeguard farmer knowledge and promote adaptations in alternative agriculture into the future.Most studies often speak to the scalability of approach or generalizability of the information presented. While aspects of this study are generalizable particularly to similar farming systems in California such as the Central Coast region, the farmer knowledge presented in this study is not generalizable and not scalable to other regions in the US. To access farmer knowledge, pots with drainage holes relationship building with individual farmers leading up to interviews as well as the in-depth interviews themselves require considerable time and energy.

While surveys often provide a way to overcome time and budget constraints to learn about farmer knowledge, this study shows that to achieve specificity and depth in analysis of farmer knowledge requires an interactive approach that includes—at a minimum—relationship building, multiple field visits, and in-depth, multi-hour interviews. Accessing farmer knowledge necessitates locally interactive research; this knowledge may not be immediately generalizable or scalable without further locally interactive assessment in other farming regions. Local knowledge among farmers in US alternative agriculture has often been dismissed or overlooked by the scientific community, policymakers, and agricultural industry experts alike; however, this study makes the case for inclusion of farmer knowledge in these arenas. In-depth interviews established that farmers provide an important role in translating theoretical aspects of agricultural knowledge into practice. It is for this reason that farmer knowledge must be understood in the context of working farms and the local landscapes they inhabit. As one of the first systematic assessments of farmer knowledge of soil management in the US, this research contributes key insights to design future studies on farmer knowledge and farmer knowledge of soil. Specifically, this study suggests that research embedded in local farming communities provides one of the most direct ways to learn about the substance of farmer knowledge; working with the local UCCE advisor in combination with community referrals provided avenues to build rapport and relationships with individual farmers—relationships that were essential to effective research of farmer knowledge. Farmer knowledge of soil management for maintaining healthy soils and productive, resilient agriculture represents an integral knowledge base in need of further scientific research. This study provides a place-based case study as a starting point for documenting this extensive body of knowledge among farmers.

It is our hope that this research will inspire future studies on farmer knowledge in other contexts so that research in alternative agriculture can widen its frame to encompass a more complete understanding of farming systems and management motivations—from theory to practice. A fundamental challenge in agriculture is to limit the environmental impacts of nitrogen losses while still supplying adequate nitrogen to crops and achieving a farm’s expected yields . To balance among such environmental, ecological, and agronomic demands, it is essential to establish actual availability of nitrogen to crops . A holistic, functional understanding of plant N availability is particularly imperative in organic agriculture, as in this farming context, synthetic fertilizers are not applied and instead, production of inorganic N—the dominant form of N available to crops—depends on internal soil processes . In organic agricultural systems, farmers may seasonally apply cover crops or integrate livestock as alternative sources of nitrogen to crops—in addition to or in place of using organic fertilizers. In applying these alternative sources of nitrogen to soil, organic farmers rely on the activity of soil microbes to transform organic N into inorganic forms of N that are more readily available for crop uptake . Currently, the predominant way crop available N is measured in organic agricultural systems tends to examine pools of inorganic N in soil . Inorganic N, or more specifically ammonium and nitrate , represents the predominant forms of N taken up by crop species in ecosystems where N is relatively available, such as in non-organic agricultural systems that apply inorganic fertilizers . However, in organic systems, crop available N is largely controlled by complex soil processes not adequately captured by simply measuring pools of ammonium and nitrate. First, because nitrogen made available to crops is controlled by soil microbes—wherein crops only have access to inorganic forms of N after microbial N transformations occur to first meet microbial N demand—pinpointing the flow of N moving through inorganic N pools as a result of these microbial N transformations is necessary to accurately measure actual N availability to crops . Second, extensive recycling of N among components of the plant-soil-microbe system complicates relying solely on measurements of inorganic N pools, which do not reflect these dynamics .

As an example, one previous study in organic vegetable systems showed examples where inorganic N pool sizes in the soil were measured to be low, yet there existed high production and consumption rates of inorganic N . This outcome highlighted that if the turnover of inorganic N is high—for instance, high rates of soil ammonium production exist in the soil with simultaneously high rates of immobilization by soil microbes and high rates of uptake by plants—measured pools of inorganic N may still be low . This study also showed that conversely, there may also exist situations when inorganic N pools are low and rates of ammonium and nitrate production are also low, in which case N availability would limit crop production. In organic systems especially, higher carbon availability as a result of organic management can increase these microbially mediated gross N flows, thereby increasing N cycling and turnover of inorganic N . Thus, we hypothesize that measuring total production of ammonium from organic N, or gross N mineralization, and subsequent total production of nitrate from ammonium, or gross N nitrification, may provide a more complete characterization of crop available N in the context of organic systems . Though the application of such diverse management practices on organic farms is known to affect rates of N cycling in soil , drainage pot measuring N flow rates as a proxy for crop available N is currently uncommon on working organic farms. The current historical emphasis on measuring inorganic pools of N in organic agriculture was originally imported from non-organic farming, wherein the Sprengel-Liebig Law of the Minimum was a widely accepted agronomic principle . In practice, this Law of the Minimum placed particular importance on using artificial fertilizers to overcome so-called “limiting” nutrients—namely, inorganic forms of N. Because inorganic N is relatively straightforward to measure, focus on quantifying pools of inorganic N has since become common practice among agronomists and agricultural researchers . However, the continued acceptance of the Law of the Minimum in organic agriculture underscores the gap in a functional understanding of organic agricultural systems, in particular the role of soil microbes in mediating N cycling. To understand crop available N more holistically, there is a need to measure actual flow rates of soil N—in addition to—static pools of inorganic N . Soil indicators that adequately capture N availability to crops are therefore necessary to move beyond the legacy of the Law of the Minimum in organic agriculture. Unpacking the soil processes that mediate flows of N may ultimately provide a more accurate characterization of soil N cycling and in turn, N availability to crops. Unfortunately, gross N mineralization and nitrification rates are very difficult to measure in practice, particularly on working organic farms . While net N flows are easier to measure in comparison to gross N flows and can provide a useful measure of N cycling dynamics as a complement to measurements of inorganic N pools, net N flows still pose serious limitations— namely that net rates cannot detect plant-soil-microbe interactions and therefore are not adequate as metrics for determining crop available N . In particular, relying on net N flows as a measure of N availability does not account for the ability of plants to compete for inorganic N, and assumes plants take up inorganic N only after microbial N demands are satisfied .

It is also possible that measuring soil organic matter pools could help indicate N availability because SOM supports microbial abundance and activity, and because SOM is also the source of substrates for N mineralization . Several studies have proposed measuring soil organic matter levels to complement measuring inorganic N pools, understand soil N cycling, and infer N availability . Assessing the total quantity of organic carbon and nitrogen within soil organic matter represents one established method for measuring levels of soil organic matter, and is more readily measurable than gross N rates. Additional indicators for quantifying “labile” pools of organic matter, such as POXC and soil protein, have also become more widely studied in recent years, and applied on organic farms as well . When used in combination with more established soil indicators that measure organic C and N pools , this suite of indicators may potentially provide added insight to understanding crop available N . Importantly, applied together these four indicators for soil organic matter levels may also more readily and accurately serve as a proxy for soil quality—generally defined as a soil’s ability to perform essential ecological functions key to sustaining a farm operation . Despite the availability of these soil indicators, very few studies have systematically examined the way in which SOM levels on working farms compare to N cycling processes, and specifically how SOM levels compare to microbially mediated gross N rates. Further, it is still unclear to what degree the interactions between soil edaphic characteristics and soil management influence N cycling and N availability to crops . For instance, soil texture may play a mediating role in N cycling, where soils high in clay content may limit substrate availability as well as access to oxygen, which in turn, may restrict the efficiency of N cycling . In this sense, it is important to understand the role that soil edaphic characteristics play in order to identify the underlying baseline limits imposed by the soil itself. Equally important to consider is the role of soil management in mediating N cycling. Compared to controlled experiments, soil management regimes on working farms can be more complex and nonlinear in nature due to multiple interacting practices applied over the span of several years, and even multiple decades. To date, a handful of studies conducted on working farms have examined tradeoffs among different management systems , though few such studies examine the cumulative effects of multiple management practices across a gradient of working organic farms. However, understanding the cumulative effects of management practices is key to link soil management to N cycling on working farms . Likewise, it is important to examine the ways in which local soil edaphic characteristics may limit farmers’ ability to improve soil quality through management practices. Though underutilized in this context, the development of farm typologies presents a useful approach to quantitatively integrate the heterogeneity in management on working organic farms . Broadly, typologies allow for the categorization of different types of organic agriculture and provide a way to synthesize the complexity of agricultural systems . Previous studies that make use of farm typologies found that differences in total soil N across farms are largely defined by levels of soil organic matter.