Values and adoption in regenerative grazing practices and associated wellbeing outcomes for cow-calf producers

Progress report for LNC20-437

Project Type: Research and Education
Funds awarded in 2020: $249,999.00
Projected End Date: 12/31/2024
Grant Recipient: Michigan State University
Region: North Central
State: Michigan
Project Coordinator:
Dr. Matt Raven
Michigan State University
Co-Coordinators:
Dr. Jennifer Hodbod
Michigan State University
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Project Information

Summary:

Cattle production accounted for $67.1 billion in cash receipts in 2018 and supported 913,000 US operations, of which 728,000 were small beef farms and ranches, commonly cow-calf operations on grass with under 50 animals (NCBA, 2020; USDA, 2020).  Therefore, grasslands are a crucial part of the US agricultural sector and yet demonstrate increased degradation and thus decreasing ecological wellbeing. The difficulty of making management decisions on this degraded resource base is compounded by decreasing social and economic wellbeing for producers. However, given the cultural importance of cattle production, producers continue to engage with it, putting the resource base and their livelihoods at potentially greater risk.

Regenerative grazing has been posited as a solution to this environmental, social, and economic risk. However, although the evidence base of successful regenerative management is increasing, particularly in grazing, there is little long-term study of the environmental, social, and economic benefits following adoption, and none within the North Central region. There is also little adoption of regenerative grazing across the producer population in the US. It has been hypothesized that barriers to adoption include a lack of knowledge about wellbeing outcomes (including ecosystem services, producer quality of life, and economic profitability), producer values, and uncertainty around how to adopt.

Our research and education project, ‘Values and Adoption in Regenerative Grazing Practices and Associated Wellbeing Outcomes for Cow-Calf Producers’ will create knowledge, awareness, and skills for 15-20 cow-calf producers by training them in regenerative grazing. In order to explore suspected barriers and conduits to adoption, a long-term approach is proposed including training in self-monitoring of economic, social, and ecological wellbeing and values. A control group of non-adopters and a group of established adopters (10+ years) will also participate in wellbeing training and monitoring, creating further knowledge, awareness, and skills amongst these groups. Values are crucial as there are no studies monitoring how values change through the adoption process - a long-term project will show whether values change as producers adopt regenerative methods (i.e. becoming more open to change) or whether producers need to hold these values to consider adopting such adaptive methods.

Understanding barriers and conduits to adoption will allow us to tailor education materials, fostering increased adoption of regenerative grazing in the medium-term benefiting stakeholders such as Extension and the beef and regenerative agriculture sectors, but in the long term benefiting wider society through a more sustainable cow-calf sector.

Project Objectives:

Our objective is to understand pathways to the adoption of regenerative grazing. There are multiple outcomes for multiple audiences:

  • Learning outcomes:
    • Knowledge, awareness, and skills for cow-calf producers:
      • Regenerative grazing methods
      • Methods for monitoring wellbeing:
        • Ecological - Ecological Outcomes Verification
        • Economic - enterprise budgets and improved record keeping
        • Social– values and quality of life
    • Knowledge and awareness for Extension, university researchers, beef and regenerative agriculture stakeholders:
      • Values and wellbeing
      • Barriers and conduits to adoption
  • Action outcomes:
    • Regenerative grazing adoption
    • Wellbeing monitoring
    • Regenerative grazing network
  • System outcomes:
    • Extension tools to increase adoption and wellbeing
    • More sustainable grazing practices.
Introduction:

Producers rely on grasslands – almost half of US farms have cattle, with an above-average number in the North Central region where livestock spend most of their lives on pasture. However, there are multiple challenges to the sustainability of grazing-based cow-calf operations. This project explores how different grazing management strategies influence wellbeing outcomes, to build a holistic sustainability on cow-calf operations.

Cooperators

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  • Crista Derry
  • Florencia Colella
  • Jonathan Vivas Aragon
  • Sarah Hubbard
  • Zekuan Dong

Research

Hypothesis:

We are implementing a systems-based approach to ask two main research questions:

  • What are the pathways (conduits and barriers) to adoption of regenerative grazing practices? i.e. how do values, recruitment style, and ecological, social, and economic wellbeing, and knowledge of regenerative grazing influence adoption?
  • How are ecological, social, and economic wellbeing and values influenced by adoption? i.e. are producers’ values and wellbeing measures static or dynamic?
Materials and methods:

For our context, regenerative grazing is defined as practicing Holistic Planned Grazing (HPG), the grazing method within Holistic Management. HPG utilizes multiple paddocks to control livestock movements and requires the development of grazing plans of when and where to move animals with an emphasis on recovery periods for the paddocks rather than grazing periods. A crucial aspect to HPG is monitoring to adjust grazing plans given changing conditions. We will work with three cohorts, starting with 20 Michigan residents in each, anticipating some attrition to 15 – our required sample size.

C1. 15-20 new regenerative grazers, who adopt regenerative grazing through this project.

C2. 15-20 regenerative grazers with 10+ years of experience, who have previously participated in MSU-run regenerative grazing programs.

C3. 15-20 continuous (non-regenerative) grazers, our control.

Our general approach is to treat farms as social-ecological systems, which requires understanding the ecological, social, and economic components of the system, and how they are connected. To understand this, based on previous work by this team, three established wellbeing tools will be used in a longitudinal manner:

Ecological wellbeing: We will use the Ecological Outcomes Verification (EOV) Short-Term Monitoring tool, a practical and scalable soil and landscape assessment methodology that tracks annual outcomes in biodiversity, soil health, and ecosystem function (water cycle, mineral cycle, energy flow, and community dynamics) (Xu et al., 2019). Co-developed by Raven, a key principle of EOV is that it is outcomes-based – any producer can utilize it, no matter their practices. EOV measures key indicators of ecosystem function resulting in an Ecological Health Index (EHI) score, which in the aggregate indicates positive or negative trends in the overall health of a landscape. If a producer is using practices that increase the ecological wellbeing of their land, their scores will increase year-by-year. The empirical and tangible outcomes of EOV provide the producer, as a steward and manager of the land, with ongoing feedback from which to make better management decisions. By monitoring land regeneration trends, a farm or ranch is eligible for EOV verification and associated incentives if land health moves in a net positive direction, through the Land to Market Program. We will train all cohorts in EOV, so they can assess their own land’s ecological quality, and will work with them on an annual basis to monitor their land, with on-site assistance during the early years and assistance through an online platform in all years. Having gone through the EOV training, all participants will be qualified as EOV Short-Term Monitors and can then earn additional income from verifying others’ land.

Social wellbeing:  Historically, wellbeing metrics originate from within economics and derive wellbeing from census data and global surveys, conflating wellbeing with socio-economic indicators such as income, assets, and social status. This approach is lacking, as a high level of income does not necessarily reduce stress or increase happiness – indeed, often the opposite is true. Therefore, to truly measure wellbeing we have created a tool to monitor what we see as the three core components of social wellbeing - psychological, subjective, and physical wellbeing. The tool combines the Satisfaction with Life Scale developed by Diener (1994) with the Scale of Psychological Wellbeing developed by Ryff (1989), incorporating both subjective and psychological aspects. Given that psychological wellbeing is based upon the idea of ‘living within your value’ we also include a validated held values survey tool, that of Schwartz (2012), and a set of grazing-specific relational values created from our previous work (Mathison and Hodbod, 2019). Finally, we also included questions about indicators of physical wellbeing - financial status, education, sense of community, anxiety, and physical health (sleep, exercise, healthy eating), that are typically found on rural mental health surveys such as the one developed by Kelly et al. (2010). The tools will be introduced to all cohorts in a training about wellbeing and values, with a post evaluation of their knowledge. We will then introduce the survey tools for annual completion, building participant’s skills in monitoring and analyzing their own wellbeing.

Economic Wellbeing: Economic wellbeing is a synonym of present and future financial security and as such, it depends on two main variables: income and wealth. However, there is a subjective aspect to it: the degree of satisfaction or fulfillment. With each cohort of farmers, we will complete a financial wellbeing analysis in years 3 and 4 that includes both objective and subjective (feelings/perceptions) measures. For the objective measures, we will help them complete their balance sheet and income statement. In addition, we will help them complete an enterprise budget to understand the profitability of their cow-calf enterprise. They will receive training in record keeping, developing coordinated financial statements (i.e. balance sheet, income statement), and financial ratios, which can be tracked over time and benchmarked against other farms. Depending on their degree of comfort with computers, they will be asked to use digital or paper spreadsheet templates, which Colella and McKendree have already developed for other studies and farm consultations. The enterprise budget will give us information on the cow-calf enterprise economic profitability, including opportunity costs (land, labor, capital). We will also track their off-farm income, health insurance coverage, perceived economic wellbeing, and their degree of comfort with their finances in general, and with those of the cow-calf enterprise in particular – i.e. economic wellbeing measures that are not included in the farm finances. Knowing their income and their satisfaction information will allow us to look for correlations between these two variables and make programming and management recommendations.

There were some delays in Y1 given the travel and research restrictions in place at Michigan State University during 2021 given the COVID19 pandemic. This project requires trust between the participating farmers and the research team to support asking about social and economic wellbeing, and trust-building requires face-to-face communication. Because this wasn’t feasible, we were delayed in recruitment which occuredd in the first quarter of Y2.

To use our time efficiently, we spent Y1 preparing research protocols, priming for recruitment in cohort 1 and 2 via ecological wellbeing monitoring on farms we have previously trained in EOV, and relationship building through our MSU Extension colleagues and their networks. Below is the adapted outline for our project, summarising activities in Y1 and Y2 and the anticipated structure for Y3 and Y4 (given the No Cost Extension which we applied for in Spring 2022).

Year 1 (2021):

  • Winter and Spring: team building at MSU – We partnered with MSU Extension (Lake City Research Center; LCRC and Upper Peninsula Research and Extension Center; UPREC; Farm Management Unit; Beef Team), building relationships and familiarity amongst the team.
  • Summer: EOV (ecological wellbeing) data collection on 17 farms by Raven and Derry. 14 have been previously introduced to EOV where their long-term monitoring was completed, so monitoring in 2021 was the short-term EHI monitoring. 3 were new participants for whom Raven and Derry oversaw long-term and short-term monitoring. All 17 are likely participants in our project, likely to be members of Cohort 1 and 2.
  • Fall: Onboarding of student researchers (Jonathan Vivas Aragon and Sarah Hubbard), including their education in wellbeing theory. Deeper development of conceptual framing for the project. Literature review of wellbeing tools released since proposal was submitted. Revision of social wellbeing tools. Developing new record-keeping training modules and tools to complement established tools for economic wellbeing monitoring.

Year 2 (2022):

  • Winter:
    • We used our relationships with MSU Extension (Lake City Research Center; LCRC and Upper Peninsula Research and Extension Center; UPREC) to prime these organizations to be ready to distribute our recruitment materials.
    • We prepared recruitment materials – email language, social media posts, magazine articles, and flyers (i.e., https://www.canr.msu.edu/news/wellbeing-on-beef-farms-in-michigan)
    • Dr. McKendree (lead of economics components) was on maternity leave
    •  
  • Spring:
    • We distributed our recruitment materials and survey link widely. There were 98 responses in March 2022.
    • We invited 61 to participate in the project, anticipating some attrition.
      • 11 declined between April and November 2022
      • 13 were removed in Summer 2022 for lack of response
      • 37 farms remain as active participants (sometimes with multiple participants per farm, given multi-generational or partner management).
    • The participants didn’t evenly fit between the three cohorts, with initial classifications as:
      • 6 adapting
      • 20 already adaptive
      • 11 conventional
    • During the recruitment process we discussed with participants what they would like to achieve through the project and integrated further components if feasible or connected them (through MSU Extension) to relevant programs or staff.
    • As a first packet of information, we shared an ‘intro to wellbeing’ document with all participating producers while scheduling their intake interview for May 2022.
    • Intake interviews with 34 of the participating farms were held by zoom or phone in May 2022
      • After interviews 1 farm was moved into the ‘adapting’ group:
        • 7 adapting
        • 19 already adaptive
        • 11 conventional
    • Immediately following the interview, participants completed the social wellbeing survey, either independently online after being emailed the link or on the phone with one of our team. 38 people representing 35 of the farms completed the survey. The survey elicited information about psychological, subjective, and physical wellbeing along with values, for the letter we integrated a replacement for the New Ecological Paradigm (NEP) Scale (which we originally planned to use).
        • The survey will be repeated annually so we can study change in wellbeing and values over time for all cohorts.
    • Dr. McKendree (lead of economics components) was on maternity leave
  • Summer:
    • EOV training was offered to all participants by the Ecol WB team. There were 3 Short Term Monitoring (STM) workshops taught during the summer of 2022 at Lake City Research Centre (5/25 – 5/27; 6/15 – 6/17; 7/6 -7/8; 7/27 – 7/29). These 3-day workshops taught participants to identify and score leading ecological indicators on their farm.
      • A total of 31 producers participated in the three STM workshops.
      • On the last day producers scored four sites and had to be within a standard deviation of the official score of the instructors.
      • Furthermore, they received additional instruction when their farm was monitored.
    • The Ecol WB team conducted Ecological Monitoring on 39 farms during the 2022 growing season using the Ecological Outcomes Verification (EOV) protocol developed by the Savory Institute in conjunction with Ovis21 and Michigan State University. EOV consists of Short Term Monitoring (STM) which evaluates 15 leading ecological indicators on an annual basis and Long Term Monitoring (LTM) which measures lagging ecological indicators every five years.
      • LTM and STM were conducted on 27 farms during the summer of 2022 (mostly in Cohort 1 and 3) while 12 farms were monitored only with STM as they had previously been monitored and LTM site was already established (mostly in Cohort 2).
      • As part of the LTM, these 27 farms (newly monitored in 2022) were offered the opportunity to have additional monitoring conducted, including soil-testing (the Cornell Comprehensive Assessment of Soil Health), done at reduced rate through MSU which will establish baseline lagging ecological indicators such as soil health beyond that which the EOV Short-Term Monitoring will collect. This would allow producers to join the Land to Market program, the world’s first verified regenerative sourcing label, if they so desire.
    • The Ecol WB team offered a series of other trainings:
      • A Holistic Management training course was offered to C1 (6/22 – 6/24), with a specific focus on Holistic Planned Grazing.  This workshop provided the foundation to managing holistically and served as the pre-requisite for the remaining HM workshops.
          • 14 producers completed the course.
      • A specific Holistic Planned Grazing was taught to 23 producers during the height of the growing season (7/14 – 7/15).
        • Producers left the workshop with a grazing plan for the remaining portion of the 2022 growing season.
      • A Holistic Land Planning course was offered and had 17 producers participating (8/16 – 8/17).
        • They left with a forward-thinking plan for their farm leveraging concepts learned from the previous workshops.
    • The Social WB team analysed the survey data.
    • The Econ WB conducted a literature review on financial wellbeing to begin developing a farmer-specific financial wellbeing framework that includes both objective and subjective measures of financial wellbeing.
  • Fall:
    • Producers who attended a STM workshop and at least one HM workshop were eligible to apply for a mini-grant, distribute by the Ecol WB team. There were 16 producers eligible, 15 applied for and received a $2,500 mini-grant.
      • Five spent their funds on fencing, five spent it on improving water for livestock, four for hay bale unrollers, and one for seeding.
      • All expenses were appropriate for moving their operations towards a more adaptive approach to grazing.
    • The Social and Ecol WB research assistants led data analysis for the annual social and ecological wellbeing data, along with the creation of summary documents to share with the participants.
      • EOV summaries specific to each farm were shared in November 2022.
    • The Econ WB team developed and distributed a financial record keeping survey to understand the current state of the financial records of the participants as well as their level of record keeping knowledge. Additionally, we continued to develop the financial wellbeing framework.

Year 3 (2023):

  • Winter
    • The Ecol WB team created an online EOV training platform and accompanying material, secured supplemental funding from SARE through the conference funding line to subsidize the HPG workshops, and began planning for Spring and Summer courses. 
    • The Social WB team prepared a methods publication with the data from Spring-Summer 2022 and made some edits to the survey for clarity/efficiency, working with the econ WB team to integrate concepts related to financial wellbeing. 
    • The Econ WB team worked on finalizing the financial wellbeing framework (including having the framework reviewed by other experts) and development of the financial record keeping educational modules.
  • Spring:
    • The Ecol WB team ran a 4-hour planning session in March of 2023, which 8 producers took advantage of to develop their grazing plan for the 2023 growing season.
    • The Social WB team will collect social and economic wellbeing data (i.e. psychological, subjective, and physical wellbeing; values; perceptions of financial risk) in April-May 2023, to update the social wellbeing dataset with a second time point and add the first time point to the economic wellbeing dataset. Data will be collected online or via a telephone-based survey, depending on the comfort of the producer.
      • They will also prepare a 3 page summary for producers about the results of the Y1 social wellbeing data collection, to be shared when producers complete the Y2 survey.  
      • We will also submit the methods publication which includes amalgamated Y1 social wellbeing data.
    • The Econ WB team will make the online financial record keeping training available for participants.
  • Summer:
    • The Ecol WB team will oversee the EOV assessment by C1, 2, 3. Participants will carry out assessment by themselves and submit photos to the online platform. MSU team will do quality assurance by looking at photos on the platform and will follow up in-person with any required producers.
    • Social WB team will analyse the Y2 data and prepare summaries for each farm that presents the Y1 and Y2 data for their farm and any changes. 
    • The Econ WB team will work with participants to create their financial statements that are needed for the wellbeing framework and for the enterprise budget exercise. This will include either an in-person or virtual visit to each farm.
  • Fall:
    • The Ecol WB team will analyse the EOV data and share summaries specific to each farm in November 2023.
    • The Social WB team will work on a new publication analyzing any change over Y1-Y2 and will work with the economic and ecological wellbeing teams to create a framework for a combined wellbeing index and analysis.
    • The Econ WB team will begin drafting an online survey for a larger cow-calf producer sample in the North Central Region. Additionally, we will anlayze the wellbeing data collected from the wellbeing survey and financial statements. 
      • They will also carry out a record keeping check-in via phone/email/zoom/mail with each farm.

Year 4 (2024):

  • Winter:
    • The Econ WB team will distribute the larger survey.
    • The social wellbeing team will facilitate a networking event, particularly to focus on conduits and barriers to adoption of regenerative methods given the experiences through this project and through other resources participants have sought out.
  • Spring:
    • The Social WB team will distribute a final iteration of the socio-economic wellbeing data collection (online or by phone).
    • The Economic WB team will run an in-person one-day record keeping training for all cohorts. This training will be hands-on in a computer lab with their own accounting records. During this training the main goal will be to learn how to develop financial statements. They will be required to turn in their enterprise budget, balance sheet, and income statement one month after the training. Certificates of completion will be provided in exchange for all completed budgets.
  • Summer:
    • The Ecol WB team will oversee a final EOV assessment by C1, 2, 3. Participants will carry out assessment by themselves and submit photos to online platform, MSU team will do quality assurance looking at photos on the platform and follow up in-person with any required producers.
    • The Econ WB team will carry out a final record keeping check-in by phone/email/zoom. 
    • All teams will analyze annual social, economic, and ecological wellbeing data and contribute to an overarching evaluation to answer research questions:
      • Analyze relationships between cohorts – how does management relate to social, ecological, and economic wellbeing?
      • Analyze within cohort temporal patterns - How are ecological, social, and economic wellbeing and values influenced by or influence adoption? i.e. are producers’ values and wellbeing measures static or dynamic?
      • Synthesize the pathways (conduits and barriers) to adoption of regenerative grazing practices.
  • Fall:
    • Dissemination of initial findings at in-person network events with participants and representatives of our secondary audience, i.e. Extension educators, university faculty & researchers, beef sector stakeholders including the Cattleman’s Association, consumer representatives, and policy makers, SARE.
      • During this event we will host a private networking event to introduce C1 and C2 in person
      • We will also hold evaluative focus groups within these events for representatives from primary and secondary audiences.

We anticipated conducting five producer trainings and over 180 producer check-ins with our participants, as well as a regional online survey to understand social/economic wellbeing and views on regenerative grazing across a representative population of cow-calf producers. We have already (April 2023) conducted 6 producer trainings and 46 producer check-ins.

Inputs required to achieve this are SARE grant funds; land, facilities, and equipment of two MSU Research and Extension Centers; time, labor, and expertise of the researchers, Extension personnel, and producers.

Research results and discussion:

Initial social WB results showed that producers were generally well. As observed in Table 1, overall farmers scored higher in relational wellbeing, followed by eudaimonic wellbeing and physical wellbeing as the three highest categories. This suggests that farmers are highly satisfied with their accomplishments, social support, health, and finances. When farmers were asked in a follow-up question which domains of wellbeing were most important to them, all groups consistently ranked relationships and purpose and meaning (eudaimonic wellbeing) as the first and second most important domains. 

Table 1. Wellbeing constructs and overall index

 Wellbeing constructs

Mean

Sd

Cronbach’s Alpha

Life Satisfaction

0.76

0.14

0.79

Hedonic Wellbeing

0.71

0.13

0.82

Eudaimonic Wellbeing

0.80

0.11

0.75

Relational Wellbeing

0.86

0.14

0.79

Physical Wellbeing

0.77

0.11

0.15

Social WB Index

0.78

0.10

0.84

Table 2. Correlation matrix

 

Life Satisfaction

Hedonic Wellbeing

Eudaimonic Wellbeing

Relational Wellbeing

Physical Wellbeing

Social WB Index

Life Satisfaction

1.00

         

Hedonic Wellbeing

0.64

1.00

       

Eudaimonic Wellbeing

0.58

0.50

1.00

     

Relational Wellbeing

0.54

0.46

0.39

1.00

   

Physical Wellbeing

0.60

0.52

0.50

0.38

1.00

 

Social WB Index

0.87

0.81

0.74

0.73

0.75

1.00

 

We then computed a correlation matrix to observe the strength of the relationship between constructs to assess divergent validity. In general, we observe that the strength of the correlation between the constructs is low to moderate and in the expected direction considering our theoretical expectations. Surprisingly, relational, eudaimonic, and physical wellbeing showed the lowest correlation with the social wellbeing index. Despite having similar levels of variability in their scores, life satisfaction and hedonic wellbeing had the strongest relationship with the index. In other words, farmers with a high social wellbeing index were more likely to score high in life satisfaction and hedonic measures, even though the farmers self-identify relational, eudaimonic, and physical constructs as the main contributors to their wellbeing (see table 1). Our initial thought was the effect of the support received from their interpersonal relationships was expressed as the absence of negative motions (anxiety, sadness, and anger) and the presence of positive ones (joy, contentment, and positivity) captured through Hedonic wellbeing. However, the correlation matrix does not indicate a strong relationship between the scales used to measure these domains. A more plausible explanation is that the relationship between relational wellbeing and the social wellbeing index is not fully captured by our estimation approach, in other words assigning equal weights to each category to create the index does not reflect the farmer's understanding of “relationships”.  Further research with larger sample sizes and alternative reliability analyses could provide additional insights into the multidimensional nature of social wellbeing.

 

Table 3. Wellbeing and farmers' groups (there is no evidence that differences in mean between groups are statistically significant.)

 

Life Satisfaction

Hedonic Wellbeing

Eudaimonic Wellbeing

Relational Wellbeing

Physical Wellbeing

Social WB Index

Non-adaptive

0.82

0.74

0.83

0.89

0.83

0.82

Adaptive

0.75

0.69

0.78

0.79

0.76

0.75

Adopting

0.73

0.71

0.79

0.82

0.75

0.77

Pairwise-comparison (p-value -adjusted)

 

 

 

 

 

 

Adaptive - Adopting

0.44

1.00

0.63

0.79

0.85

0.44

Adaptive - Non

0.51

1.00

0.22

0.14

0.25

0.11

Adopting - Non

0.20

0.73

0.38

0.13

0.23

0.33

 

Table 3 displays the scores for the five constructs and the wellbeing index, along with the results of multiple pairwise comparisons. Our objective was to determine whether any of the cohorts scored significantly different from the others for any of the wellbeing constructs, including the social wellbeing index. Considering the limitation of our sample size, we compare the differences among the three cohorts of farmers using the post-hoc non-parametric Dunn test since it is an appropriate option when the ANOVA assumptions of equal variance or normal distribution are not fulfilled (Dinno, 2015). Moreover, p-values were adjusted to control for the family-wise error rate (FWER, rejecting the null hypothesis when it is true) using Holm's correction.

It can be seen from the data that non-adaptive farmers generally scored higher in all constructs compared to the adapting and adopting groups, with the largest differences observed in life satisfaction between non-adaptive and adopting (-0.09), relational wellbeing between non-adaptive and adaptive (-0.1), and overall social wellbeing index (-0.07). However, despite these differences, none of them were found to be statistically significant, except for the difference in social wellbeing index between the adaptive and non-adaptive groups was borderline significant at 90% level (p-adj = 0.11 < 0.10). Despite the no statistically significant difference, it is interesting to observe the variation in the ranges – min and max values -for each group and discuss this in the view of the theory of subjective wellbeing homeostasis. Cummins et al., (2003) and Cummins & Wooden, (2014) suggests “homeostasis” as an analogy to explain why the mean values for subjective wellbeing metrics in the western world are about 75% of the scale score, arguing that subjective wellbeing is “actively controlled and maintained” with a form of steady-state affective set-point. Thus, this implies that we would observe little variation if people's homeostatic systems are normally functioning.

Considering Cummins’ theory, we could ask what is the “set-point” around which social wellbeing variations are interesting to interpret despite their non-statistical significance.  Looking at the prior cited literature, we observe that subjective wellbeing scores for farmers in Sherren, Brown and Brown studies were in a range of 70 to 80% of the scale's maximum scores used on those studies. Such values are consistent with what we observed for the adaptive and adopting groups but not for the non-adaptive ones. There could be two possible scenarios, the first one is that the non-adaptive farmers' higher scores in all constructs reflect their current homeostatic state, where they have adapted to their existing circumstances and have found a way to maintain their overall social wellbeing, despite not adopting new agricultural practices. An alternative scenario may suggest that the adaptive and adopting groups may be going through a period of adjustment due to the adoption of new practices, which may temporarily disrupt their homeostatic equilibrium. This suggests that there may be some differences in social wellbeing between the adaptive and non-adaptive groups relate to the adoption of regenerative grazing, but more data would be needed to confirm this.

Y2 EOV scores ranged from 9.1 to 61.50. Individual analyses were shared with each farm in the following format: EOV_APF_2022

Collated analyses are still in progress. 

Research conclusions:

TBD

Participation Summary
17 Farmers participating in research

Education

Educational approach:

Summarised in detail above, but educational activities in 2022 were:

  • 3 Short Term Monitoring (STM) workshops (3 days each) – 31 participants
  • 1 Holistic Management workshop (3 days) – 14 participants
  • 1 Holistic Planned Grazing workshop (2 days) – 23 participants
  • 1 Holistic Land Planning workshop (2 days) – 17 producers

Project Activities

Wellbeing guide for participants – completed and disseminated in Spring 2022 with social wellbeing tools
CANR MSU News article
Voices of Sustainable Agriculture
Integrating wellbeing into resilience assessment for working agricultural landscapes
Presentation to President Stanley, MSU
Preparing research materials
EOV monitoring
Record keeping course
Journal article: Regenerative Grazing: A Pathway to Improved Wellbeing for Michigan Ranchers?
EOV summaries

Educational & Outreach Activities

56 Consultations
35 Curricula, factsheets or educational tools
1 Journal articles
1 Published press articles, newsletters
1 Tours
2 Webinars / talks / presentations

Participation Summary:

92 Farmers participated
35 Ag professionals participated
Education/outreach description:

In 2021-22, the focus was on outreach to aid recruitment (newsletter articles, presentations etc.). We carried out education and outreach through the project activities described above - presentations to audiences in MSU as well as at international conferences, MSU news articles, and tours of Lake City to senior leadership at MSU.  

In 2022-23, the focus was on training and data collection. 

In 2023-24, the focus will begin to shift to dissemination of Y2 results to participating producers as well as to other audiences - other producers, ag educators, academia. We are prepping summary reports to share widely through CANR and SARE as well as journal articles for academic audiences in extension and research. 

 

 

Learning Outcomes

85 Farmers reported changes in knowledge, attitudes, skills and/or awareness as a result of their participation
Key areas taught:
  • Holistic approach to wellbeing
  • Social wellbeing
  • Economic wellbeing
  • Ecological wellbeing
  • Regenerative agriculture
  • Short Term Monitoring
  • Holistic Management
  • Holistic Planned Grazing
  • Holistic Land Planning
  • Financial Record Keeping

Project Outcomes

26 Farmers changed or adopted a practice
Key practices changed:
  • Financial record keeping

  • Regenerative agriculture

  • Ecological Outcome Verification monitoring

  • Increased consideration of wellbeing when making farm management decisions

3 Grants applied for that built upon this project
2 Grants received that built upon this project
30 New working collaborations
Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.