This broader finding is significant because it supports emergent research that suggests that while management certainly contributes to soil quality, inherent characteristics of the soil in a given field may place limits on achievable organic matter levels on organic farms . Based on our findings, it is evident that even along minimal gradients in soil texture class, organic matter levels strongly differ. It is not surprising that soil texture is an important determinant of SOM in these organic systems. Soil texture is known to be a strong control on soil organic matter dynamics across diverse ecological systems—not just agricultural systems—in part because organic compounds, particularly those derived from soil microbes, are among those capable of stabilization by physical and chemical mechanisms, including aggregation, sorption on mineral surfaces, and entrapment within fine pores . At a fundamental level, soils with greater amounts of clay tend to stabilize SOM on surfaces more than soils with high sand and/or silt content , as clay particles provide greater surface area through organo-mineral associations than other particle sizes . For example, it has been shown in numerous previous studies that as clay content increases, indoor grow shelves the relative abundance of total soil N also increases . Further other studies have shown that soil texture and structure can influence SOM chemistry, and therefore, SOM stabilization .
Our study takes previous research in agricultural contexts one step further to show that while management is important to consider, soil texture may be the more dominant factor; however, based on our results, it is still unclear which direction soil texture may be driving SOM. Nonetheless, our results highlight that contextualizing management in the native soil texture is essential to understand the limits of management imposed by pre-existing constraints of the soil. In practice, current emphasis in on-farm soil health research and quality assessments tends to focus on the importance of changing management to build healthy soils and improve soil quality without explicit consideration for soil texture . In this study, the gradient of soil textures across the farm fields sites was relatively limited and even so—soil texture still explained a significant component of the variance observed compared to management. Given this outcome, our findings here reinforce the importance of using soil texture as a starting point for evaluating soil quality. Knowing the soil textural class of different fields may help farmers determine the management practices that have greatest potential for improving soil quality on farms with even small variances in soil textures; soil texture class may also help farmers better contextualize results of their soil health tests. Our study suggests that moving forward, soil texture should be more explicitly considered when making management recommendations to improve soil quality on organic farms. That said, understanding the interactive effects between management and soil texture continues to be a gap in on-farm research and soil health assessment.
Future studies might build on our approach and examine whether applying a similar suite of indicators to capture soil organic matter levels may yield similar connections with management in other organic farming contextsin California—and elsewhere in the US. Our study provides a potentially widely applicable method for developing a functional understanding of soil organic matter in complex agricultural landscapes. In this sense, the overall significance of the results of the cluster analysis highlights the efficacy of developing typologies to provide a useful tool for understanding the complexity of working agricultural landscapes. Importantly, the development of farm typologies allowed for additional analysis of other soil indicators for N cycling an availability—by using the farm types as a central tool for further investigation.Though the range of gross N cycling rates from this study are comparable to N cycling values reported from previous studies in organic agricultural systems , we found that farm types did not have significantly different gross N mineralization and nitrification rates—contrary to our initial hypothesis and despite that farm types strongly differentiated based on soil organic matter levels. These hypotheses were in part based on prior work with organic farms in this region that reported instances where inorganic N pools were low—well below established soil nitrate threshold sufficiency values—but that the crops themselves showed high production of, and sufficient N .
Fields in which this trend was observed had the highest levels of soil C, and so in this previous study, it was hypothesized that higher rates of N production explained this observed trend. However, nitrogen bio-availability for crops is not just a function of the gross production of inorganic N by microbes but is also influenced by physical soil characteristics within the rhizosphere, such as the local soil structure and mineralogy, plant root structure and associated mycorrhizal pathways, as well as accessibility of water to plants and soil microbes . These variable conditions in the rhizosphere are not captured by measuring N cycling rates but still directly influence bio-availability of N. For these reasons, the N cycling results of this study may not follow prior findings from Bowles et al. . Still, we did observe an influence of soil organic matter levels on N cycling, particularly in terms of gross nitrification rates. As shown in the Linear Mixed Model results in Table 12, SOM indicators do appear to have an influence in predicting gross nitrification rates , even as the proportion of variation explained is modest . This slight trend is also evident in the boxplots . The weak but significant link between soil organic matter levels and gross nitrification rates is important to highlight because these results suggest that building soil organic matter presents one way to increase nitrification rates and potentially crop N availability. Because the plant-soil-microbe N cycling system is strongly influenced by soil water content and soil structure, it is possible that gross N cycling indicators lack the responsiveness that SOM indicators exhbiti especially in scenarios where improved soil quality allows for crops to continue accessing soil microsites with available N . Similarly, crops with more abundant and active mycorrhizal community associations can extend into smaller Ncontaining aggregates that may be otherwise locked up for crops with less root proliferation andhyphal associations. Additionally, it is also possible that changing microbial community composition in the soil may lead to greater immobilization of N, locking up available N but not necessarily impacting gross production of N. These plant-soil-microbe interactions that control availability of N may not be detectable solely by measuring gross N flows. 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, indoor garden table 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, 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 actualN 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 .