Progress report for GNE21-259
The objectives of this research are:
- To visualize agricultural service providers’ mental models of soil health
- To visualize farmers’ mental models of soil health
- To identify how soil test results fit into farmers’ soil management strategies
- To visualize farmer mental models of soil health grouped by farm type
- Farm type groups include organic dairy, conventional dairy, organic vegetable & fruit, conventional vegetable & fruit, organic non-dairy animal operations, conventional non-dairy animal operations. These groupings encompass the main agricultural production systems in Vermont. Different production systems entail different soil management strategies, which may influence mental models of soil health.
- To identify whether mental models of soil health differ across farm type
- To compare farmers’ and service providers’ mental models of soil health
- To identify differences in farmers’ and service providers’ understanding and assessment of soil health, which -if unidentified- may impede collaboration in research and outreach related to soil health
- To identify complementary or shared ways of understanding and assessing soil health, which may provide leverage points to further improve collaboration and co-creation of knowledge between farmers and service providers
- To develop clear guidance for extension and other agricultural service providers in the Northeast on how to integrate farmer soil knowledge and collaboratively identify best practices for soil health.
The purpose of this project is to facilitate the integration of farmer and scientific knowledge to improve sustainable soil management and drive effective future research and extension outreach. Co-created mental models of soil health enable identification of the full suite of social and ecological factors that inform diverse ways of assessing and managing agricultural soil health (see Figure 1).
The Natural Resources Conservation Service defines soil health as “the continued capacity of soil to function as a vital living ecosystem that sustains plants, animals and humans” (USDA 2019). Restoring and maintaining soil health on farmland remains a pressing issue in the United States (Baumhardt et al. 2015; Nearing et al. 2017). Soil degradation due to agriculture drives climate change (Lal 2012). Simultaneously, degraded soils make farms more susceptible to the adverse impacts of climate change (Moebius-Clune et al. 2016) with attendant consequences for farmer livelihoods (Hatfield et al. 2014).
In the Northeast, recent weather patterns are following past projections of increasing extreme precipitation events and periods of drought (Hatfield et al. 2014, Wolfe et al. 2018). Management strategies that improve and maintain soil health can buffer against the negative impacts of these extreme weather patterns (Moebius-Clune et al. 2016; Magdoff & van Es 2009).
Since the mid-1990s, researchers and scientists have focused on identifying metrics and indicators of soil health (Stewart et al. 2018; Karlen et al. 2019). Much of this work has focused on interpreting soil data and enhancing in-field measurements. While important, this approach fails to acknowledge that soil management decisions are made by farmers in their particular local contexts (Bagnall et al. 2020). Sustainable agriculture requires moving beyond measuring disaggregated indicators and employing integrated, whole-systems approaches to soil management that center farmers’ complex decision-making context (Kibblewhite et al. 2008).
If indicators of soil health are not salient and legible for farmers, they are less likely to adopt practices that promote soil health (Ingram et al. 2016; Reimer et al. 2014). In the context of the Northeast, there is no current published research on how farmers utilize soil test data to inform decision-making and long-term soil management strategies. Not only is it vital to know whether and how farmers use this information, it is also vital to determine whether the metrics and indicators emphasized in traditional soil tests are relevant to farmers in the Northeast. If not, we risk sinking resources into research and outreach tactics that are unlikely to improve agricultural soil health in the region, with attendant consequences for farm viability and the environment.
There is a need to bridge the local knowledge of farmers with scientific knowledge and the expertise of agricultural service providers to identify the information and outreach processes that best support sustainable soil management. Doing so requires the capacity to effectively communicate across different ways of understanding, assessing, and managing soil health. Findings from this research will be used to develop clear guidance for improving collaboration between farmers and agricultural service providers working towards improving and maintaining agricultural soil health.
Methodological Background (for all research objectives)
The proposed research will use mental models to explore leverage points for further integrating farmer and service provider knowledge systems in the context of Vermont agriculture. By visualizing farmers’ and service providers’ mental models of soil health, this research aims to improve collaboration for sustainable soil management.
Mental models refer to the cognitive frameworks used by actors to understand or make sense of the world (Jones et al. 2011; for an example, see Figure 2). Cognitive frameworks are constructed and refined through knowledge acquisition processes, past experience, values, beliefs, and assumptions (Carley & Palmquist, 1992; Moon et al. 2019). They are also well-suited to efforts that attempt to identify and analyze the underlying social systems and structures that mediate ecological outcomes (Moon et al. 2019; Jones et al. 2011; van Hulst et al. 2020; Prager & Curfs 2016).
There is no standard way to construct or analyze mental models; rather, appropriate methods for constructing and analyzing mental models are determined by the context and intended applications of the research (Jones et al. 2011). Research design is therefore variable, but often includes common methods for collecting qualitative data, such as interviews, participant observation, document analysis, and focus groups (Jones et al. 2011). This wide array of methods for eliciting and constructing mental models allows for the methodological flexibility necessary to study complex social-ecological systems.
Van Hulst et al. (2020) note, however, that common methods for constructing mental models prioritize expert knowledge over farmer knowledge. This undermines processes of knowledge co-construction and social learning, which have been identified as crucial for effective soil health management strategies (Schneider et al. 2009; Bennett & Cattle 2013). To better enable collaboration between farmers and other stakeholders, Van Hulst et al. (2020) propose an innovative approach to co-constructing mental models. The authors co-constructed mental models with farmers during elicitation interviews using visual displays and concept sorting (see Figure 3). Typically, researchers conducting elicitation interviews produce mental models afterwards based on their own analysis of interview data.
I will utilize mixed methods within an iterative process of co-constructing and comparing farmers’ and agricultural service providers’ mental models of soil health. I will triangulate across methods to generate mental models that visualize the diverse beliefs, perspectives, experiences, and relationships that inform farmer and agricultural service provider strategies for improving and maintaining soil health. Institutional Review Board (IRB) approval will be obtained before research begins.
Objectives 1 & 2
I will conduct semi-structured interviews to elicit farmers’ and agricultural service providers’ mental models of soil health. I will utilize purposive sampling (Tongco 2007) to interview farmers who represent organic and non-organic dairy, vegetable/fruit, and non-dairy animal operations. These farm types employ diverse practices and face unique social and environmental constraints and accordingly, may have different ways of understanding, assessing, and managing soils. I will also utilize maximum variation sampling to include participants within each farm group represent a diversity of farm sizes and farmer identities (Collins 2010). To recruit interviewees, I will rely on recommendations from agricultural extension agents, government employees, and key informants within Vermont’s agricultural networks.
Interviews will include elicitation questions as well as visual concept sorting, following van Hulst et al. (2020) and their methods for co-constructing mental models. Elicitation questions will encourage participants to discuss the factors, beliefs, and concepts that inform their understanding of soil health. Concept sorting will include visually displaying and arranging concepts that emerge during the interview and further exploring how these concepts relate to each other qualitatively (see Figure 3). This process will allow researcher and participant to co-create a mental model of soil health. Van Hulst et al. (2020) note that the “co-constructed mental model method proved to be a useful tool for eliciting individuals’ internal cognitive depictions of the world regarding concepts, practices and beliefs, and their qualitative relationships” (p. 184). Interviews will be recorded and transcribed for future reference. If pandemic restrictions prevent in-person interviews, I will conduct interviews virtually using Mural digital workspace for content sorting. Following completion of elicitation interviews, I will digitize mental models using NVivo software (see Figure 1).
I will comparatively analyze farmers’ individual mental models of soil health to identify how farmers’ use soil test results to inform soil management strategies. Methods for this include comparing mental models using data displays and arrays (Creswell & Clark 2007) as well as comparative matrix analysis using NVivo software. Data displays and arrays are an analytical method for iteratively comparing across multiple data sources to identify connections and patterns. In this context, I will be identifying similarities and differences in how soil test results fit into farmers’ mental models of soil health. I will traingulate this analysis with comparative analysis in NVivo to assess similarities in the concepts or practices that farmers mention as directly connected to or informed by soil test results.
Objectives 4 & 5
I want to know if farmers’ mental models of soil health differ across farm types. This could have implications for tailoring research, outreach, and best management practices related to soil health. To tackle this research objective, I will compare and integrate individual mental models to create 7 grouped mental models: 1 for service providers and 6 for the main farm types I identified earlier. The farm type for each individual mental model will be recorded during the original elicitation interview, and purposive sampling will ensure that all interviews fit into one of the 7 established groups. Hoffman et al. (2014) note that grouped mental models can examine “collective knowledge and understanding of a particular domain held by a specific population of individuals” (p. 13016). Grouping mental models also helps make the findings of this work more broadly relevant and helps control for variability across individuals.
Again, I will triangulate across analytical methods, using visual displays and arrays (Creswell & Clark 2007) as well as comparative analysis in NVivo to identify the connections, concepts, practices, barriers, and other factors and themes that emerge as common across the individual mental models within each group. See Figure 4 for an example of the process for combining individual mental models to create grouped mental models.
Once the grouped mental models are completed, I will compare the 6 grouped mental models for major farm types. I will use similar processes of visual displays and arrays paired with NVivo analysis to identify similarities and differences across the grouped mental models of soil health by farm types.
To compare farmer and service provider mental models of soil health, I will compare the 7 grouped mental models. I will use an iterative, mixed methods approach that incorporates my own analysis with participatory analysis. For my own analysis, I will again use a combination of visual displays and arrays combined with digital comparative analysis of grouped mental models using NVivo software. This will identify major similarities and differences in mental models of soil health.
Next, I will incorporate participatory analysis of mental models. I will conduct 7 focus groups: 6 with farmers (grouped by farm type) and 1 with agricultural service providers. I will recruit focus group participants from the individuals who participate in interviews. Within the focus groups, I will ask each farmer group to compare their grouped mental model to that of the service providers’. I will ask service providers to compare their group’s mental model to farmer groups. Participants will be asked to identify what they see as important differences and similarities across the grouped mental models of soil health. In addition, participants will be asked to discuss why they think similarities or differences exist, whether communication of knowledge across farmer and service providers is effective, and what might improve integration of farmer and service provider knowledge. Focus groups will be recorded, transcribed, and qualitatively coded using NVivo software. Within my final analysis, I will integrate my comparative analysis with the participatory analysis and qualitative data gathered in focus groups.
The methods described above will identify similarities and differences in understandings of soil health across farm type groups and between farmers and agricultural service providers. The final analysis will yield recommendations for integrating farmer and agricultural service provider knowledge to improve sustainable soil management. This will draw largely from the focus groups and farmers’ own assessments of how soil knowledge can be more effectively integrated, communicated, and co-created between farmers and agricultural service providers. I will work with a graphic design consultant to create an infographic flyer that presents recommendations along with visual examples of diverse mental models of soil health. This will be designed to communicate the research results, guidance for agricultural service providers, and the importance of visualizing the full suite of social-ecological factors that inform approaches to soil health. The flyer will be distributed to farmer networks and agricultural service providers throughout the Northeast.
Data collection and analysis are ongoing.
Education & Outreach Activities and Participation Summary
I approach this work with a strong background in participatory action research (PAR). I will therefore apply PAR principles within this work. Specifically, I am committed to centering farmer knowledge and ensuring that research findings are shared with relevant stakeholders in a way that is directly applicable to on-farm management and extension services.
To this end, I will present the results of this research at multiple practitioner-oriented conferences, including NOFA-VT, NOFA-NY, and the UVM Extension No-Till and Cover Crop Symposium. As a member of the Vermont Soil Health Policy Network, I will also present my results to this group, along with an infographic flyer of research results that can be circulated widely. Through my participation in the Vermont Soil Health Policy Network, I will also share findings with key members of the Northeast Healthy Soil Network coordinated by Tufts University, so that they can share research results and guidance with their networks throughout the Northeast.
To reach an even wider audience, I will submit an article for peer-reviewed, scholarly publication in the Journal of Extension or a similar open-access journal that focuses on sustainable agriculture. I am dedicated to open-access scholarship.
In addition to scholarly publication, I plan to write three ‘popular’ pieces based on this project. First, I will write a blog post on the importance of facilitating collaborative processes between farmers and agricultural service providers, to be published on the Agroecology and Livelihood Collaborative’s (ALC) website. Second, I will write a blog post on the importance of integrating social science within soil science and research; this will be published on the Leadership for the Ecozoic (L4E) blog, which explores the intersection of environmental sustainability and social justice. The L4E project is a partnership between UVM and McGill University in Montreal. The ALC and the L4E project are both communities of practice that bring together a wide range of stakeholders across a broad geographic region. As a member of both communities, I can share the findings and implications of my research with a broad audience of farmers, scholars, extension agents, and educators.
Finally, I will write an opinion editorial to submit for publication on the Civil Eats website. This piece will explain why understanding the sociocultural factors that inform soil management is vital for sustainable agriculture. Specifically, I will explore how a more integrated approach to soil health could enable extension and other agricultural service providers to support a wider range of farmers who may bring different values, beliefs, and norms to their management of agricultural soils (e.g. see Figure 5). In this way, the methods applied in this research may be a tool for improving equity in agricultural outreach services.
Data collection and analysis are ongoing.
Interviews were mainly switched to virtual in response to Covid 19 concerns. Co-creating mental models with participants virtually remains possible with the real-time use of online data visualization tools.