While not significant, SOM indicators were also selected in the development of the LMM for gross mineralization rates as well. These results are congruent with previous research looking across ecosystem types that reported a relationship between N cycling rates and SOM indicators. For example, a meta-analysis published by Booth et al. that examined woody, grass, and agricultural ecosystems found a strong positive relationship between indicators for SOM and gross N mineralization. It is likely that in this prior study, the range of ecosystem types analyzed were sufficiently broad to detect a significant trend between indicators for SOM and N cycling. However, in our context, which encompasses agricultural systems only—it is possible that previously established trends are less detectable within this narrower range of ecosystem type. As shown in Figure 1 , if the range of ecosystem type is constrained to include only agricultural systems, the relationship between indicators for SOM and gross N mineralization is less evident. In summary, our results suggest that SOM indicators, while not significant, do play a role in influencing N cycling across the farm systems studied here. While initially, we found it surprising that N cycling soil indicators were not strongly linked to SOM indicators, one known limitation of measuring gross N mineralization and nitrification in the field is that while gross N production of inorganic N relay supply of available N to crops, gross rates in our case represent potential rates standardized to temperature and moisture—and therefore do not represent in situ rates found directly in the field. Moreover, using gross N production of inorganic N as an indicator for soil N cycling also poses inherent limitations for determining actual available N beyond those created by field conditions, as discussed above.
However, cannabis grow racks while measuring gross N production of inorganic N may provide a more limited applicability for quantifying N cycling than originally hypothesized, the lack of a strong relationship between common soil indicators for organic matter levels and gross rates of soil N cycling does not necessarily mean that building organic matter with intentional management does not lead to greater N availability for crops. For example, a recent study by Wade et al. that used identical indicators to measure soil organic matter levels in the midwestern region of the US found that these indicators for soil quality do indeed influence supply of N—based on crop responses . While this recent study focused on yield response to fertilizers and their relationship to soil health and soil quality and considered biogeochemical processes as intact , we speculate that the influence of soil quality on N supply determined by Wade et al. is not as detectable when measuring gross N cycling directly. We suggest that there may be circumstances where N cycling indicators are not as responsive to N supply, but soil quality is still improving. Such circumstances can arise for example when minerals in the soil lock up available N or when soil microsites create differences in N cycling that is not reflective of actual N supply to crops. In this sense, soil organic matter indicators better reflect local soil conditions, such as soil structure and root structure of crops, that overcome limitations imposed by mineralogy and/or soil microsites. For this reason, these soil organic matter indicators are both more comprehensive and more responsive for measuring N availability than N cycling indicators. As Grandy et al. point out, after a century of research, few indicators provide better insight to N availability than total soil N content . Grandy et al. also highlighted that indicators for soil organic matter, such as those used in our study, represent soil metrics with a slow turnover rate as compared to the fast turnover rate among indicators for N cycling.
This difference in soil indicator turnover rate may also be useful to consider in our study, as it is possible that gross N flows may have a faster turnover rate than SOM indicators and are therefore less responsive when compared to soil quality indicators and existing management regimes. Because our study focused on within season dynamics, the incongruity between soil indicator turnover rates is likely intensified. In addition, because our on-farm study examined cumulative impacts of diverse management approaches on N availability, it is also possible that these differences in soil indicator responsiveness lacked sensitivity not only due to differences in indicator turnover rates but also because the indicators for available N measured here may be more sensitive to management practices not explicitly captured in this study . Likewise, given the strong influence of soil texture we found, soil clay content and mineralogy may play a more dominant role in influencing N cycling, potentially obscuring links to management in this context . In particular, clay content strongly influences stabilization of organic N through the formation of aggregate protected organic matter and through the preservation of microbial biomass, which ultimately limits bioavailable N . In recent years, the concept of “soil health” in the United States has become codified as a research and policy tool to unify efforts towards 1) improving soil function on farms, and more broadly 2) building on-farm resilience . While the exact definition of “soil health” continues to evolve, the concept generally refers to “the continued capacity of soil to function” in a way that sustains ecological, environmental, and human needs . On the technical front, soil health research has focused on effective and efficient ways to measure and improve soil health, and on quantifying benefits associated with building soil health .
Concurrent research has also placed particular emphasis on the role of “innovative” on-farm management practices in building soil health and promoting on-farm resilience . This research has taken a practice-centric approach that primarily uses social science methods to examine farmers’ views or farmers’ uses of specific practices, and has— importantly—generated insight into the adoption of key management practices related to soil health . Despite this work, to date, very few studies in the US explicitly incorporate farmer knowledge of soil health and soil management beyond farmer perspectives on the topic and/or farmer motivations for adopting soil health practices . However, farmers possess wide and deep place-based knowledge of their soils that has the potential to advance work on soil health beyond its currently limited scope . Inclusion of farmer knowledge is integral if one outcome of ongoing research on soil health is to address both social and ecological resilience. Farmers are uniquely positioned to share their onthe-ground social realities and their local ecological knowledge of their soils and farming systems . To be clear, inclusion of farmers in this research arena is essential if only to contribute farmer knowledge and farmer voices to the existing body of work—which to date has been lacking . This call for inclusion of farmer knowledge represents: 1) a departure from the majority of prior research in the US that tends to emphasize the advancement of research and policy agendas aimed at behavioral change ; and 2) simultaneously, a shift towards explicit inclusion of farmer knowledge in the knowledge-making of emergent soil health research. While farmer knowledge is certainly important and underutilized, cannabis drying racks consideration for quantitative assessments of soil health remains a critical component of advancing soil health. Available indicators to quantify soil health already exist and are widely applied both on farms and in scientific studies. These soil indicators prioritize so-called “principles of soil health” to assess health through evaluating soil function, usually emphasizing metrics for organic matter quality, nitrogen availability, soil biological activity, and water cycling . Currently, our understanding of how local farmer knowledge of soil To investigate these questions, we applied a case study approach, engaging in on-farm research of 13 organic farms and their respective farm owners in Yolo County, California, USA—a region where this type of farmer inclusive soil health research has been limited to date. We used qualitative, in-depth field interviews in combination with quantitative field sampling and subsequent laboratory analysis. This research focused on Yolo County in particular, because of its unique role as a hub for innovative, high-value organic vegetable production . These thirteen organic farmers specifically—because of their historical relationship to their land and their intimacy with the physical place they farm—collectively represented a salient case study through which to understand soil health and fertility from a grounded perspective. More broadly, we led this work with a Farmer First approach in order to give voice to organic farmers of this region, and to provide a model for future inclusivity of farmer knowledge in the growing body of work on soil health.We conducted our experiment on 13 farms in Yolo County, California, on unceded Patwinspeaking Wintun Nation tribal lands—located along the western side of the Sacramento Valley between late March 2019 and December 2020. The region is characterized by Mediterraneantype climate with cool, wet winters and hot, dry summers. Precipitation in the 2019 water year 2019 was 807 mm—the fifth wettest winter on record.
The mean maximum and minimum temperatures were 33.9oC and 15.5oC, respectively for July 2019. Mean annual maximum and minimum temperatures for 2019 were 24oC and 9.8oC, respectively. All farm sites were on similar parent material . Most farms were situated on either loam, clay loam, or silty clay loam. All 13 farms selected for this soil health study were located in Yolo County . The organic farms represent a majority of the farms in the region with a diversified array of vegetable and fruit crops that sell to a variety of consumer markets, including farmers’ markets, wholesale markets, and restaurants. The 13 farmers interviewed represent 13 individuals who oversee management and operations on their farms. These individuals were most often the primary owner and operator of the farm, and made key management decisions on their farm. To identify potential participants for this study, we first consulted the USDA Organic Integrity database and assembled a comprehensive list of all organic farms in the county . Next, with input from the local University of California Cooperative Extension Small and Organic Farms Advisor for Yolo County, we narrowed the list of potential farms by applying several criteria for this study: 1) organic operation on the same ground for a minimum of 5 years; 2) a minimum of 10 years of experience in organic farming; and 3) a focus on growing diversified fruit and vegetable crops. These requirements significantly reduced the pool of potential participants. In total, 16 farms were identified to fit the criteria of this study . These 16 farmers were contacted with a letter containing information about the study and its scope. To establish initial trust with farmers identified, we worked directly with the local UCCE advisor. Because this research is informed by a Farmer First approach—which emphasizes multiple ways of knowing and challenges the standard “information transfer” pipeline model that is often applied in research and extension contexts—farmers were viewed as experts and crucial partners in this research . As a result, farmers were considered integral to field site selection, and were not asked to change their management or planting plans. In addition to the Farmer First approach, we intentionally used a two-tiered interview process, in which we scheduled an initial field visit and then returned for an in-depth, semi-structured interview at a later date—after summer field sampling was complete. The overall 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. The initial field visit typically lasted one hour and was completed with all 13 participants. Farmers were asked to walk through their farm and talk generally about their fields, their fertility programs, and their management approaches. The field interview also provided an opportunity for open dialogue with farmers regarding specific management practices and local knowledge . Because local knowledge is often tacit, the field component was beneficial to connect knowledge shared by each farmer to specific fields and specific practices. During the initial field visit, field sites were selected in direct collaboration with farmers. First, each farmer was individually asked to describe their understanding of soil health and soil fertility. Based on their response, farmers were then asked to select two field sites within their farm: 1) a field that the farmer considered to be exemplary in terms of their efforts towards building soil fertility ; and 2) a field the farmer considered to be a challenge in terms of their efforts towards maintaining soil fertility .