Progress report for GS24-310
Project Information
Half of all anthropogenic methane emissions and around three-quarters of anthropogenic nitrous oxide are from the global food systems. Moreover, of the 14% of total CO2 emissions from land use, agriculture is responsible for 10% of emissions. Sustainable agricultural practices (SAP) are crucial for reducing emissions and achieving net-negative production. Integrated crop-livestock systems (ICLS) are a form of SAP where land is synergistically used by plants and animals on spatial and temporal scales. Implementing ICLS has several benefits, including reducing nitrate leaching, increasing land productivity, increasing production stability, enhancing soil chemical and biological properties, and decreasing greenhouse gas emissions. Additionally, ICLS promotes economic resilience for farmers through the diversification of income. Despite its benefits, the adoption of ICLS is very low in the United States. Although many barriers to adoption have been identified globally, few studies directly examine barriers to ICLS adoption in the Southeastern United States. Therefore, it is unknown which of these challenges, or other yet unidentified challenges, are limiting adoption. This study employs a participatory modeling approach, to understand the perceptions of farmers and other stakeholders about ICLS. We used Conceptual Content Cognitive Map (3CM) (also called mental modeling) for this purpose. Data was collected with crop farmers (n = 3), ranchers (n = 3), facilitators (n = 5), Extension agents and technical support (n= 4), and industry personnel (n=2). Our findings show that only 14.28% of farmers adopted ICLS in all of their farms, while 28.57% partially adopted it and 28.57% implemented it in partnership with another farmer. Profit, risk management, soil health, diversity of income, environment conservation, and creating opportunities for the next generation were the major motivators for farmers for ICLS adoption. However, for technicians, profit, soil health, environment conservation, diversity of income, risk management are the major motivators. The next step in our study is to analyze participants’ mental models. Educational intervention will be created based on the study’s findings.
The proposed research aims to understand the perceptions of farmers about ICLS through a participatory mental modeling process, co-create knowledge for addressing the misperceptions and barriers, and develop outreach materials outlining the results of the study (Figure 1).
Figure 1: Graphical representation of the research process
The specific objectives of the project are:
- To explore farmers’ perceptions of ICLS in the Southeastern United States.
Mental modeling, a participatory mixed methods approach, will be used to identify perceptions of farmers, their perceived barriers, and motivations about ICLS. During the data collection process, prompts will be used to encourage farmers to share their perceptions related to characteristics of ICLS, such as relative advantage, complexity, compatibility, observability, and trialability (Roger, 2003); their values, i.e., egoistic, altruistic, and biospheric (Stern, 2000); and subjective norms regarding ICLS (Ajzen, 1991). Then, participants will be asked to create their individual cognitive map to represent their mental model for ICLS. During data analysis, the researcher will develop a composite/group cognitive map of the participants, as shown in Figure 2.
Figure 2. Composite maps of mental models of participants who self-identify as producers (top) and environmentalists (bottom) (Hundemer and Monroe, 2020)
- To explore the effect of sociocultural factors on the perception of ICLS among farmers in the Southeastern United States.
Two separate composite cognitive maps will be developed for White and marginalized farmers to identify differences in perceptions, barriers, and motivations for ICLS among the two groups. During data analysis, researchers will use cluster analysis, to do so.
- Develop strategies for increasing the adoption of ICLS through a collaborative knowledge generation process.
After analyzing the data from objectives 1 and 2, a workshop will be conducted with farmers, extension agents, researchers, and other agricultural stakeholders to discuss potential strategies and implementation pathways for addressing the misperceptions and barriers and leveraging the motivating factors regarding ICLS for its increased adoption.
Cooperators
Research
Research design and sampling
This study uses non-experimental and cross-sectional research design. Participants were recruited using purposive sampling. Crop farmers, ranchers, government personnel, and technical support professionals participated in the study.
Research instrument and Data collection
Conceptual Content Cognitive Map (3CM) (also called mental modeling) was used to assess the perception of participants about ICLS. The Recommendations from Kearney (2015) were followed to develop the research instrument, which included using “imagine if …” as the opening scenario, briefly introducing the topic (ICLS in our study), and asking participants to share their unique perspectives. Our opening scenario and prompt for 3CM was “Someone you know recently heard about Integrated Crop and Livestock Systems (ICLS) and is considering implementing it on their farm. They want to feel confident that ICLS will be economically and environmentally beneficial. What things would you tell them to take into account when making this decision?” Along with the prompt, instructions for 3CM were also provided to participants.
Participants were provided with a large sheet of paper, a deck of cards with pre-generated items, blank cards to write any additional items, a pen, and a marker. Participants were asked to respond to the prompts using the deck the cards containing pre-generated items. A list of items related to ICLS’s perception were generated from the literature review and findings from Dr. Wallau’s research project on ‘Ruminating Over Fallow Ground: Innovation Platform as a Strategy to Improve Adoption of Climate-Smart Agriculture’. (Dr. Wallau and his team interviewed farmers, Extension faculty, and government personnel in Northeastern Florida to explore the barriers and opportunities for ICLS adoption.)
Participants were then asked to sort the cards into two piles, one which they would use for the response and the other to discard. Also, we asked them to add any additional items not represented in the given deck by writing them on the blank cards. Then participants were asked to group the cards into categories that logically go together in their minds and label them. After the completion of mental modeling, participants were asked to complete a short survey about participants’ demographics, current adoption of ICLS, and motivations for ICLS adoption.
Social science researchers and agronomists were involved throughout the instrument development process and their comments were used to revise and update the instrument. Further, the instrument was pilot tested with four researchers. Two of these researchers were very familiar with ICLS and had worked in ICLS before. The other two researchers were not familiar with ICLS. Having participants with varied levels of familiarity with ICLS represented our target audience for the study, i.e., those who have and have not adopted and are aware of ICLS. After completing the 3CM activity with pilot test participants, they were asked to share their feedback on the prompt, instructions, and items. The pilot test participants’ feedback was used to revise the prompt, instructions, and items. The instrument is attached- FInal_instrument used.
Data collection began after approval from the University of Florida’s Institutional Review Board’s exempt approval (Protocol #: ET00044472). Data collection was done as a part of a two-day event where crop producers, ranchers, government personnel, and technical support were invited. The first day was the workshop and the second day was a symposium - First Southeastern Integrated Crop-Livestock System Symposium. Data was collected on the first day. The event was organized in the Jackson County Extension Office in Marianna, Florida. Participants were asked for their consent to participate in the study before starting data collection. Then, the steps for doing 3CM or mental modeling were described to all the participants. Afterward, participants were divided into five groups and were asked to individually develop their mental model and complete the survey: crop farmers (n = 3), ranchers (n = 3), facilitators (n = 5), Extension agents and technical support (n= 4), and industry personnel (n=2). Each group had a moderator and an assistant moderator that facilitated the session and answered the questions from participants. At the end of the process, assistant moderators clicked pictures of completed mental models, and collected survey from participants.
Data analysis
The survey data was entered into Qualtrics and exported as a csv file. Statistical software R was used to run the descriptive statistics. The data collected from mental modeling is yet to be analyzed. Statistical software UNICET and Anthropac will be used for mental modeling.
Demographics
The mean age of participants was 42.81 ± 10.956, with participants age ranging from 25 to 67. A total of 7 farmers (crop farmers and ranchers) and 10 support technicians (technical support and government personnel) participated in the study. Details about demographics or participants are in Table 1.
Table 1. Demographics of participants
|
|
Frequency |
|
Gender Male Female |
13 4 |
|
Ethnicity Hispanic/Latinx Not Hispanic/Latinx |
4 13 |
|
Race American Indian or Alaska Native Asian or Asian American Black or African American Native Hawaiian or Pacific Islander White |
0 1 0 0 16 |
|
Occupation Crop farmer Rancher Technical support Government personnel |
2 6 5 6 |
Implementation of ICLS by farmers
Regarding implementation of ICLS, only 14.28% of participants adopted it in all of their farms, while 28.57% partially adopted it and 28.57% implemented it in partnership with another farmer (Table 2).
Table 2. Implementation of ICLS
|
|
Frequency |
Percentage |
|
Yes, on all of my land |
1 |
14.28% |
|
Yes, on some of my land |
2 |
28.57% |
|
Yes, in partnership with another farmer |
2 |
28.57% |
|
No |
1 |
14.28% |
|
Not relevant to me |
1 |
14.28% |
Motivation for ICLS adoption
The scores of farmers and technicians were grouped to compare their motivations for ICLS adoption. Profit, risk management, soil health, diversity of income, environment conservation, and creating opportunities for next generation were the major motivators for farmers with mean of 10 or above. For technicians, profit, soil health, environment conservation, diversity of income, risk management are the major motivators with mean of 10 or above (Table 3).
Table 3. Motivators for ICLS adoption
|
|
Farmers |
Technicians |
||||
|
|
Minimum |
Maximum |
Mean ± SD |
Minimum |
Maximum |
Mean ± SD |
|
Available technical support |
5 |
10 |
6.43±2.44 |
0 |
20 |
8.3 ± 5.48 |
|
Creating opportunity for next generation |
5 |
20 |
10 ± 5.77 |
0 |
10 |
6.7 ± 3.80 |
|
Diversity of income |
5 |
25 |
14.29 ± 8.38 |
5 |
20 |
12.0 ± 4.22 |
|
Environment conservation |
5 |
15 |
11.43 ± 3.78 |
0 |
35 |
14.7 ± 10.10 |
|
Influence from peers or other farmers |
0 |
10 |
5.00 ± 4.08 |
0 |
15 |
5.3 ± 3.7 |
|
Profit |
10 |
40 |
25.00 ± 9.57 |
10 |
70 |
24.5 ± 17.39 |
|
Risk management |
0 |
50 |
15.00 ± 16.33 |
5 |
20 |
12.0 ± 5.87 |
|
Soil health |
5 |
20 |
14.29 ± 6.07 |
5 |
50 |
16.5 ± 13. 55 |
Educational & Outreach Activities
Participation Summary:
We are still collecting data. After completion of data collection and analysis, research findings will be shared with participants and other stakeholders through workshops and outreach materials. Educational and outreach activities are planned for the second year of implementation because they will be informed by the research findings.
Project Outcomes
The project has been running for less than seven months. After completion of data collection and analysis, research findings will be shared with participants and other stakeholders through workshops and outreach materials. Through these activities farmers will be encouraged to adopt ICLS. Also, recommendations for designing programs for ICLS adoption will be provided.
We are in the process of analyzing the data. The findings of this study will provide insights about the existing perception of ICLS (a sustainable agriculture practice). This will inform our decision regarding design of outreach materials and will also help us share some recommendations about ways to encourage ICLS adoption.