Project Overview
Information Products
Commodities
Practices
- Crop Production: conservation tillage, cover crops, cropping systems, crop rotation, no-till
- Education and Training: decision support system
- Soil Management: soil quality/health
- Sustainable Communities: social psychological indicators
Abstract:
Background
The paradigm of soil health has become widely embraced in recent years by a variety of stakeholders. Increased discussion of soil health among these entities and in the farm press illustrates that soil heath knowledge is transmitted through complex networks of information exchange, rather than originating from a single source. Thus, there is a diverse set of stakeholders that are both consuming and/or disseminating soil health information. This is emblematic of a transition from the traditional model—where knowledge is thought to be created by scientists and consumed by farmers— to a more interactive, network-based model where farmers and researchers stand on more equal footing. As these networks broaden, they include increasingly diverse sets of stakeholders, who may conceptualize soil health distinctly from one another.
This project—“ I do not think it means what you think it means: Explorations of mental models of soil health”—seeks to describe the mental models of soil health within and across groups in order to facilitate communication and cooperation across these stakeholders. This will result in knowledge creation that is simultaneously valued by all stakeholders and actionable by farmers, ultimately increasing farmer adoption of practices that improve soil health. To further this goal, we will specifically target the mental models of three distinct groups of agricultural stakeholders: farmers, Natural Resource Conservation Service (NRCS) employees, and agricultural researchers involved in the fields of agronomy and/or soil science. The three primary objectives are to: 1) evaluate the perceived importance of soil health to farmers by each group, 2) compare mental models of soil health, and 3) determine the self-reported use and value of current soil testing methods.
Approach
To describe these mental models, we used a two-stage survey development. First, we performed 30 to 60 minute semi-structured phone interviews with 5 to 10 stakeholders from each group. From these interviews, we identified broad areas of conceptual agreement across groups, ultimately determining 6 emergent concepts surrounding soil health: soil fertility and biological functioning, soil physical functioning, crop productivity, profitability, environmental harm, and agrochemical inputs. From these emergent concepts, we used a mix of paper mail surveys (for farmers) and email (for NRCS employees and agricultural researchers) to understand perceived relationships between these concepts and soil health. We used multiple choice questions to ask what effect an increase in soil health has on each emergent concept, with the provided responses as “increases” (+1), “decreases” (-1), or “they are not related” (0). In order to differentiate between bidirectional (i.e. reciprocal relationships) and unidirectional relationships, we then asked this question in reverse: what effect an increase in each emergent concept has on soil health, with the same answer choices as before. For example, “what effect does an increase in soil health have on crop productivity?” would correspond to “what effect does an increase in crop productivity have on soil health?”. Thus, our respondents indicated which concepts are affected by soil health—which we refer to as unidirectional relationships (i.e. soil health → emergent concept) and which concepts also affect soil health—which we refer to as bidirectional relationships (i.e. soil health ↔ emergent concept).
In addition to understanding each group’s conceptualizations of soil health, we were also interested in perceived soil health importance to farmers and the use and efficacy of various types of soil testing. First, we asked farmer respondents to self-identify the priority of soil health on their farm from 0 (not a priority) to 10 (highest priority). To understand if this prioritization is perceived by non-farmer groups, we also asked NRCS and researcher respondents to evaluate the degree to which they believe farmers prioritize soil health. Lastly, to determine the efficacy of soil tests, we asked all groups if they had used various types of soil tests to evaluate soils (either on their farm or for their work). For respondents who used a given test, we then asked them to rate the quality of information from that test, ranging from 1 (not at all helpful) to 5 (extremely helpful).
Using our findings from the survey, we conducted focus groups with stakeholder groups of interest to verify our interpretation of the survey, communicate about each group's mental models, and to gather qualitative data on soil health conceptualizations. Focus groups were also used to evaluate changes in understanding of both in-group and out-group mental models of soil health.
Findings and Conclusions
Obj 1 &2: Soil health prioritization and conceptualization
uWe found that soil health is a potentially useful communication and framing tool. In particular, farmers prioritize soil health to a greater extent than other groups realize (Figure 1), although future work is needed to better understand the cause of this underestimation. While there are areas of shared conceptualizations of relationships between soil health and other production components, there are certain areas that differ systematically across groups (i.e. environmental harm and agrochemical inputs) (Figure 2). Interestingly, the conceptualizations of researchers were generally more closely aligned with those of farmers (5 out of 6 emergent theme) than were the conceptualizations of NRCS employees (4 out of 6 themes). Points of divergence in soil health conceptualizations represent potentially unexplored and complex areas for researchers and NRCS personnel to communicate with farmers. Therefore, when communicating about soil health across groups, framing and communication strategies should be tailored to match the target group’s conceptualization. Our results also highlight the value of soil health as a framework within which to discuss agronomic, environmental, and potentially economic considerations of on-farm decision making.
As an example of how to implement these findings, if a researcher wanted to communicate with farmers about the benefits of soil health, discussing the effect of soil health on agrochemical inputs would likely be impactful. Both researchers and farmers are more likely to see this relationship as unidirectional and therefore more straightforward. However, if a researcher used the framing of soil health to communicate with NRCS personnel about agrochemical inputs, our results suggest that the NRCS personnel are more likely to see environmental harm as both influencing and being influenced by soil health. This reciprocal relationship could stymy communication due to individualized conceptualizations of this relationship and the high potential for unintended (yet inferred) feedback loops. That is, the audience could be inferring an additional relationship due to their differing conceptualization. For concepts with broad agreement (e.g. crop productivity and profitability), communication across groups is more likely to be successful and straightforward. Therefore, careful consideration of message framing is need to match communication goals and the specific audience.
Obj 3: Soil test use and valuation
Overall, standard agronomic soil tests (e.g., pH, organic matter, extractable nutrients) were the most commonly used type of soil test and provided the most useful information for both farmers and researchers (Figure 3). This was followed by in-field soil tests (e.g., shovel, by feel, etc.) which were generally less common and less useful to these groups. However, these rankings were opposite for NRCS personnel, who were most likely to use in-field tests and found those the most useful. Although there were slight differences between groups, both in-field and agronomic tests were considered quite useful by all groups, often scoring at least 3.75 out of 5. Soil health tests were the least used by all groups. NRCS personnel and researchers ranked them as the least useful of the three tests, whereas farmers ranked them as more useful than in-field tests and less useful than agronomic tests.
Greater frequency of use of soil tests was generally correlated with higher reported usefulness (r = 0.96, p < 0.001; Figure 3), with the exception of farmer responses regarding soil health tests. Farmer reports of the usefulness of soil health tests were anomalously high (3.92 out of 5) given their low usage (14.8%). The close relationship between use and valuation is noteworthy, but it is unclear how or if this is causal. We cannot determine if respondents were more likely to use a soil test they deemed valuable or if tests were deemed more valuable because respondents used it more frequently. However, our results imply that low farmer use of soil health tests is not necessarily due to a lack of perceived utility. This suggests other barriers to farmer use of soil health tests, such as availability or cost of these tests.
Our results also have important implications for the development and refining of soil health tests. Conceptually, farmers see a linkage between soil health and agrochemical inputs and crop productivity. However, only a handful of studies have explored these linkages using common soil health tests, despite farmers demonstrating a greater willingness to implement information derived from a soil test than from non-test sources. Therefore, although the overall usage of soil health tests was low amongst farmers, the information farmers glean from those tests is both valuable and more likely to be implemented. This indicates that soil health testing could be effectively and broadly utilized if barriers to adoption were better understood and mitigated. An understanding of barriers to adoption will help ensure that current large-scale projects measuring and vetting soil health tests will be widely implemented by farmers.
Adoption and Learning Outcomes
The first learning outcomes of this project was to validate the survey results using qualitative data from focus groups. Focus groups showed that while the underlying explanation for conceptual linkages may vary slightly from individual to individual, our survey largely provided an accurate representation of the general mental models of each group. This is an important step towards ensuring that we have appropriately interpreted our survey results.
A second learning outcome was to increase the knowledge of stakeholders about soil health conceptualizations within their group (in-group) as well as in other groups (out-group). Although we were unable to conduct an NRCS focus group within the project timeline due to a combination of geographic and institutional obstacles, 100% of participants in both the farmer and researcher focus groups reported an increasing in learning about in-group soil health conceptualizations. Similarly, 100% of farmers and 50% of researcher participants reported increased understanding of out-group conceptualizations of soil health. Using the benchmarks from the project's inception, we consider this learning outcome a success. Farmers generally agreed with one another and therefore none of them (0%) reported changing their own conceptualization soil health. However, the differing conceptualizations among researchers led to 50% of them reporting changes in their own conceptualizations of soil health. Therefore, while the learning objective was achieved for both groups, only one reported a change in attitudes.
Collectively, this implies that within-group heterogeneity of soil health conceptualization is not evenly distributed across groups. That is, some groups are more similar in their soil health conceptualizations than others. Specifically, researchers differ from one another more than farmers differ from one another. This may contribute to the agreement and ensuing lack of attitude change reported in our farmer focus group.
Project objectives:
This project has four explicit learning outcomes. These outcomes are: 1) to describe mental models for stakeholder groups surrounding the term “soil health”, 2) determine similarities and differences in these mental models of “soil health” amongst stakeholders, 3) validate the information gleaned from these models through qualitative methods, and 4) increase knowledge of stakeholders of in-group and out-group mental models surrounding soil health. Learning Outcomes 1) and 2) were primarily accomplished by project leaders through a survey that contains closed- and open-response questions. As discussed previously (Summary > Adoption and Learning Outcomes), Learning Outcome 3 and part of Learning Outcome 4 was achieved; our initial dataset was validated for use and focus group participants reported increased knowledge of soil health conceptualizations.
Learning Outcome 4 is (as yet) incomplete. Specifically, we have not completed the desired number of public-facing outputs that we intended. This is attributable to several overlapping phenomena. First, the peer-reviewed journal article has not been officially published yet. The article has received reviewer and editor comments in the Journal of Soil & Water Conservation, which (if published) will target both researchers and NRCS personnel. There have been numerous delays in peer review with the pandemic and we expect this to be completed within the next 6 months. Next, publication in farmer trade magazines and extension-facing publications has not been finalized yet. We have been in touch with the magazines, but until the peer-reviewed article has been published, we will likely get little traction. In the meantime, we have made an effort to reach the farmer and extension-facing audiences by (1) publishing a blog post on the Soil Health Nexus blog, which has a soil health-minded audience within the north-central region and (2) sending postcard summaries of our findings to each of our survey participants. We will continue these efforts at disseminating information upon the completion of publication of our peer-reviewed article.