Interestingly, prior studies in the region found that organic fertilizer use in the early organic movement was potentially more widespread. For example, early organic farmers in Yolo County who were interviewed by Guthman et al. in the early 1990s used high nitrogen-based organic fertilizers such as pelleted chicken manure, seabird guano, and Chilean nitrate to supply fertility to soil in their organic production; based on interviews here, several decades later, farmers appear to have significantly cut back on the use of such high nitrogen-based organic fertilizer products. Several of these farmers have explicitly realized that “more is not better” when it comes to organic fertilizers; as discussed above, the majority of farmers interviewed here have shifted towards implementing a synergy of management practices that promotes good soil structure, increased soil microbial activity and soil organic matter, and adequate soil moisture rather than using high nitrogen-based organic fertilizers. Third, these organic farmers unanimously agreed that soil test results could be more useful to them if the numerical results were also provided with meaningful interpretation, ideally in the form of a direct conversation—and that importantly, moved beyond prescriptive recommendations for nutrient additions and organic fertilizer application. Farmers interviewed used a variety of rich metaphors to elaborate on this point, cannabis grow equipment such as likening soil test results to the fuel gauge in a car; both provide little insight into the actual mechanics of how well the system, be it an engine or a soil ecosystem, is actually functioning.
This key takeaway from farmers in this study suggests that available soil indicators do not fully account for the complexity of their ecological farming systems, and that farmers see the interpretation of soil test results as an essential part of addressing the underlying complexity, and holistic soil function in their broader agricultural ecosystem. Our study provides an initial window into farmer knowledge of soil function in relation to soil fertility; however, as PetrescuMag et al. emphasize, deeper research on this particular gap in farmer knowledge of soil function is essential to determine the specific content of interpretations accompanying soil test results that would be practical and informative to farmers. Another potential way to bridge this gap in applicability for farmers would be to incorporate descriptive indicators for soil fertility in conjunction with available quantitative soil indicators. As Romig et al. suggested several decades ago, descriptive indicators can integrate well with existing soil metrics, and therefore provide mutually acceptable alternatives to discuss soil health and fertility among farmers and scientists alike. Finding a common language through which to engage is at the heart of this current gap in soil health research . Indicators for soil fertility measured here provided limited effectiveness in differentiating between fields deemed by farmers as “most challenging” and “least challenging” , which suggests that current scientifically developed metrics for measuring soil fertility do not align well with farmer developed benchmarks for soil fertility. This outcome additionally suggests that nutrient availability was not the driving factor for farmer perceptions of soil performance, at least in terms of soil fertility.
Of the eight indicators for soil fertility measured in this study, total soil nitrogen was the only indicator that was able to detect differences in soil fertility ; however, fields selected by farmers as “most challenging” showed on average higher values of total soil nitrogen than fields selected by farmers as “least challenging.” Because higher total soil nitrogen values are generally equated with higher soil fertility in the soil health literature, we hypothesized that the “least challenging” fields would show on average higher values of total soil nitrogen . This alternative outcome here suggests that while this soil chemical property shows sensitivity to differences perceived by farmers in their selected fields, this commonly used indicator does not adequately capture the direction of farmer knowledge of soil fertility between their selected fields. On the one hand, it is not surprising that total soil nitrogen was the only soil indicator able to detect differences between farmer-selected “most challenging” and “least challenging” fields, especially given that after nearly a century of research total soil nitrogen remains one of the most predictive measures of soil fertility status . However, the contradictory direction of our results for total soil nitrogen between farmer-selected “most challenging” and “least challenging” fields emphasizes that current scientific application of this soil indicator does not readily transfer for use on-farm. One potential reason for this inconsistency may be because as a soil indicator, total soil nitrogen reflects both the amount of chemically stable organic matter and more active organic matter fractions, and therefore gives a rough indication of nitrogen supplying power in the soil.
However, in practice it is possible that fields deemed by farmers as “least challenging” have depleted their nitrogen supplying power due to more frequent crop plantings, for example— compared to fields that are “most challenging” and therefore may be less frequently planted with crops throughout the year. This finding underscores the current lack of interpretation of soil test results in community with both agricultural researchers and farmers present together; the current gap in interpretation of soil testing results was repeatedly emphasized by farmers during interviews, and suggests that— moving forward, contextualizing and interpreting soil test results in local farming contexts is key to disentangling potential mismatches between farmer knowledge systems and agricultural researcher knowledge systems. To move toward this outcome requires deep listening and relationship building on the part of agricultural researchers not currently widely applied . Whereas another similar study found that active carbon was the singular most sensitive, repeatable, and consistent soil health indicator able to differentiate between fields in their study on organic farms in Canada , we highlight that one potential reason for this difference in our results might be as a result of differences in management in each study. While our study consisted of farms along a gradient of organic management , the prior study focused on three organic farms with similar management. This divergence in results highlights the importance of accounting for a gradient in management when evaluating the efficacy of soil health indicators on working farms. Much remains to be learned about how inherent soil properties and dynamic soil processes interact with complex management systems on working farms . Limited prior research that has looked at the effects of multiple soil management practices indicates that metrics for soil health are a product of both inherent soil properties and dynamic soil properties . Whether available soil indicators could translate these soil properties and processes when management systems are complex remains unclear. As an added layer of complexity, field variability is hard to distinguish from management-induced changes in soil properties . To address this challenge, prior studies have suggested increasing samples, the number of sites, and sampling strategies that account for spatial and temporal variability ; however, as farmers themselves expressed in this study, such an approach requires additional time and resources, and may not increase their utility—at least to farmers—in the end. In this sense, vertical grow rack farmer knowledge may serve as an important mechanism for ground-truthing soil health assessments, particularly when management is synergistic and does not rely heavily on organic fertilizers. As emphasized by our results above, farmer involvement in soil health assessment studies is imperative to better converge soil indicators with farmer knowledge of their soil. Lastly, our results also highlight the utility of incorporating information about nitrogen-based fertilizer application on sampled field sites, particularly when assessing soil indicators on working farms with a large variation in the quantity of N-based fertilizers applied . Farms on the low end of additional organic fertilizer application showed minimal differences between farmer selected fields for soil fertility, particularly in terms of soil inorganic nitrogen —which suggests that differences in soil fertility in fields with more circular nutrient use may be less detectable using commonly available soil indicators. This cursory finding here corroborated farmer observations touched on in the previous section above, and requires further investigation to see if similar trends extend to other organic systems. Here, we have identified several gaps in the utility of commonly available indicators for soil fertility among a unique group of organic farmers in Yolo County, California using interviews with farmers and field surveys. Our study highlights that if available soil indicators are to be considered effective by farmers, they must be grounded in farmers’ realities. Moving forward, working in collaboration with farmers to close this continued gap in soil health research will be essential in order to ground widely available soil indicators in real working farms with unique management systems and variable, local soil conditions. This approach is particularly needed among organic farms that do not rely extensively on nitrogen-based organic fertilizers and additional nutrient input to supply their fertility, as available soil indicators do not adequately reflect farmers’ descriptive metrics for soil fertility.
Moreover, our research elevates concerns that currently available soil indicators used in soil health and fertility assessments may not fully capture the complex plant-microbe-soil interactions that regulate soil fertility, particularly on organic farms that use minimal organic fertilizer application. Moving forward, additional studies that pursue a deeper dive into nutrient dynamics across a gradient of management and varying nitrogen-based fertilizer input is needed. Overall, the strong overlap between farmer knowledge in this study and ongoing soil health research speaks to the opportunity to further engage with farmers in developing useful indicators for soil health and fertility that are better calibrated to local contexts and draw on local farmer knowledge. A deeper investigation of farmers knowledge systems, in particular farmer understanding of soil function in connection with crop productivity, soil health, and soil fertility, represents a critical path forward for this research arena. Additionally, we recommend placing greater emphasis on developing descriptive indicators for soil health and fertility in collaboration with farmers that are better integrated with ongoing qualitative soil health and fertility metrics. These descriptive indicators should not be developed in isolation to ongoing research on soil health and fertility assessment, but rather as an integrated research process among scientists, farmers, and extension agents—importantly, with scientists as listeners working toward a shared language. The Tanaka Farm is located in Skagit County, Washington, employing approximately 500 people during the picking season, May through November. During the winter and early spring, the farm employs approximately 80 workers. The farm is well known for strawberries, many from the ‘‘Northwest variety’’ cultivated by the founder of the family farm. The business is vertically integrated, from seed nursery to berry fields to processing plant, with almost all berries produced on the farm sold under larger labels. The farm consists of several thousand acres, much of the land visible west of Interstate-5. Most of the land consists of long rows of strawberry plants, although several fields are dedicated to raspberries, apples, and organic or ‘‘traditional’’ blueberries. At the base of a forested hill on the edge of the farm lies the largest migrant labor camp on the farm, housing approximately 250 workers and their families during the harvest . Immediately above this camp are five large houses partially hidden by trees with floor-to-ceiling views of the valley. Two other labor camps are partially hidden behind the large, concrete processing plant and the farm headquarters. The camp closest to the road houses 50 year-round employees and the other, a few hundred yards away, holds almost 100 workers and their families during the harvest. Diagonally across from these two labor camps and the processing plant are the houses of some of the Tanaka family. The one most visible from the main road is a semi-Jeffersonian, one-story, brick house with white pillars behind a white, wooden fence. The Tanaka Farm advertises itself as ‘‘a family business spanning four generations with over 85 years experience in the small fruit industry.’’ On a more subtle level, farm work is produced by a complex segregation, a conjugated oppression . In Bourgois’s analysis of a Central American banana plantation, ethnicity and class together produce an oppression phenomenologically and materially different than that produced by either alone. In contemporary US agriculture, the primary lines of power fall along categories of race, class, and citizenship. The complex of labor on the Tanaka Farm involves several hundred workers occupying distinct positions from owner to receptionist, crop manager to tractor driver, berry checker to berry picker . People on the farm often describe the hierarchy with vertical metaphors, speaking of those ‘‘above’’ or ‘‘below’’ them or of ‘‘overseeing.’’ Responsibilities, anxieties, privileges, and structural vulnerability differ from the top to the bottom of this hierarchy .