2017 SWCS Annual Conference July 30-August 2, 2017 Monona Terrace Convention Center

1. Meta-Review of Barriers and
Motivations for Farmers to
Adopt Conservation Practices
Linda Prokopy, Kristin Floress, J. Arbuckle, Sarah Church, Pranay Ranjan
SWCS Symposium 2017

2. Genesis of This Project
• Prokopy et al. 2008, Baumgart-Getz et al. 2012:
• Reviewed 55 studies published from 1982-2007 in the U.S.

3. Genesis of This Project
• Prokopy et al. 2008, Baumgart-Getz et al. 2012:
• Reviewed 55 studies from 1982-2007 in the U.S.
• Findings:
• No consistent determinants of conservation adoption
• Most often positively associated with conservation adoption: education,
capital, income, farm size, access to information, positive environmental
attitudes, environmental awareness, and social networks
• Since publication:
• Increasing numbers of qualitative papers
• Overall explosion of research in this area
• Walton Family Foundation interest

4. Genesis of This Project
• Prokopy et al. 2008, Baumgart-Getz et al. 2012:
• Reviewed 55 studies from 1982-2007 in the U.S.
• Findings:
• No consistent determinants of conservation adoption
• Most often positively associated with conservation adoption: education,
capital, income, farm size, access to information, positive environmental
attitudes, environmental awareness, and social networks
• Since publication:
• Increasing numbers of qualitative papers
• Overall explosion of research in this area
• Walton Family Foundation interest

5. Overview of Symposium
• Generating data
• Preliminary vote count results
• Preliminary qualitative analysis results
• Response from agency and NGO colleagues
• Next steps
• Your questions and comments

6. Generating 4,217 Rows of Data:
Finding and Documenting
Papers
Kristin Floress
U.S. Forest Service

7. Overview
*Adapted from Card, 2012. Applied meta-analysis for social science
research. The Guilford Press, NY.
• Inclusion/exclusion criteria
• Methods
• Searching for literature
• Coding study characteristics,
determining inclusion/exclusion
• Coding study results

8. Dependent
variables
Target
population
Exclusion criteria
• Adoption/behaviors
• Willingness to adopt
• Willingness to
accept payments
• Interest in
participating
Practices, programs
• Agricultural
producers:
• Conventional
• Specialty
• Organic
• Agroforestry
• Livestock
• Row crops
• Urban
• Reviews,
discussions
• Sample selectivity
models
• >1 paper
reporting on
same model
Image credit: by Lance Cheung, taken at Sunny Ridge Farm,
MD. Courtesy of USDA NRCS.

9. Search Strategy
• Team Ag BMP collectively identified
100 articles
• 153 additional articles from 1982 -
2017
• Google Scholar: reverse searches from
2008 and 2012 studies
• SCOPUS and Web of Science: Boolean
searches with multiple criteria, needed
to include implement, adopt, willing, or
participat
Image credit: by Jeff Vanuga, residue management on cornfield – 70% residue for
erosion control. Courtesy of USDA NRCS.

10. Study Level Characteristics Coding
• Author affiliation
• Funding source
• Theoretical grounding/theories used
• General methodological approach
• Data collection and sampling methods
• Year data collected
• Population and sample sizes,
descriptions
• Geographic scope
• Crops and livestock
• DV, Barriers
• Inclusion decision
Image credit: by Jeff Vanuga. Grazing rotation, courtesy of USDA NRCS.

11. Individual Study Results Coding
• DV, DV measure type and IV/IV measure
type
• For all DVs and IVs
• Binary, categorical, ordinal, continuous as
described by authors
• Measure notes – scales used, meaning of
coding (e.g. 0/1 =not adopt/adopt; 1-5
agreement from strongly disagree to strongly
agree)
• Analysis # and method
• Vote count (pos, neg, insig)
• p-value range, threshold used in paper, p-value
• Model results (coeffcients, t statistics, R2, etc.)Image credit: by Jeff Vanuga, lagoon waste management system for 900 head
hog farm. Courtesy of USDA NRCS.

12. Coding Methods
• Primary and secondary coder for each
paper
• Coding – excel template with dropdowns
• Each study on its own sheet for easy
tracking
• Primary coded, then sent code sheet to
secondary
• Secondary reviewed coding, agreed
or disagreed with primary
• All disagreements discussed
between primary and secondary
until resolved
• Remaining issues brought to full
group
Image credit: by Stephen Kirkpatrick, organic crops in high tunnel. Courtesy of
USDA NRCS.

13. Coding Methods
• DV, IV category and
subcategories NOT assigned
during coding
• Full team meeting – 2 days in-
person
• Weekly calls with majority
Attitudes
(10 subcategories)
Awareness
(3 subcategories)
Farm Characteristics
(21 subcategories)
Economic Factors
(18 subcategories)
Farmer Characteristics
(12 subcategories)
Behaviors
(10 subcategories)

14. 253 Total Study Abstracts
170 Fully Reviewed (so far)
67 Excluded (from today’s/vote
count analysis)
103 Included in (today’s) Vote
Count
3 incomplete data
2 duplicate studies
7 no models
9 qualitative*
3 review/discussion papers
26 wrong DV
10 wrong population
7 willingness**
14 willingness to adopt
program/practice**
9 both actual adoption and
willingness
81 actual adoption

15. Characteristics Included Excluded
Population
size
Min 27 310
Max 2,000,000 745,000
Mean 93,636 68,497
Med 3205 1300
NR 63 48
Sample size Min 14 11
Max 42,229 4778
Mean 2099 683
Med 625 277
NR 9 3
Year data
collected
Min 1983 1977
Max 2015 2015
Median 2007 2001
NR 12 11

16. Other general trends
• 98 of the reviewed studies noted funding source
• EPA, NSF, USDA (NIFA, NRCS, ERA, CSREES…), state governments
• Foundations
• Author affiliations
• 132 academic
• 20 government
• 18 not specified
• Lack of clear description of population (size, crops grown)
• Sampling methods often not fully described

17. Making Sense of 4,217 Rows
of Data
J. Arbuckle
Iowa State University

18. Emerging results: What have we done and
found so far?
• Preliminary vote count
• Cross-tabulation of statistical significance (positive,
negative, not significant) of relationships between
independent variables and dependent variables, by
independent variable subcategory
• We present results for selected variables that appear in
numerous studies

19. Types of independent variables:
76 categories and subcategories so far

20. Types of practices adopted (200+, A to W):
To be categorized for further analysis

21. Type of dependent variable
employed (percent of studies)
Ordinal
3%
Other
8%
Categorical
5%
Continuous
16%
Binary
68%
• Binary: Adopted or not
• Ordinal/categorical: Degree
of stages of adoption,
number of practices
• Continuous: Acres, linear
feet, number of practices
Reimer et al. (2014) called for greater use of
continuous measures of adoption

22. Overall Vote Count: Statistical Significance of IVs, All
Models, All Studies (n=4217)
13%
61%
26%
0%
10%
20%
30%
40%
50%
60%
70%
1
Negative Non-sig Positive

23. Attitudes towards practices, environment
15%
5%
18%
47%
59%
64%
38%
36%
18%
0%
10%
20%
30%
40%
50%
60%
70%
Attitudes toward the
practice/behavior
Attitudes toward other
(related) practices
General environmental
attitudes
Negative Nonsig Positive

24. Networking, information seeking
8%
6%
69%
47%
23%
47%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Networking (m/l passive, e.g., Contacts with
actors)
Info seeking (active, e.g., attend field day)
Negative Nonsig Positive

25. Adoption of other practices, cost-share payments
17%
4%
55%
38%
28%
58%
0%
10%
20%
30%
40%
50%
60%
70%
Adoption of other (related) practice Payment/cost-share
Negative Nonsig Positive

26. Farm economics
4%
31%
63%
55%
33%
14%
0%
10%
20%
30%
40%
50%
60%
70%
Farm income Cost of production (inputs, etc.)
Negative Nonsig Positive

27. Farm characteristics
8%
10%
20%
64%
47%
62%
28%
43%
18%
0%
10%
20%
30%
40%
50%
60%
70%
Acres Grain Livestock
Negative Nonsig Positive

28. Crop/livestock diversity
9%
13%
54%
50%
37% 38%
0%
10%
20%
30%
40%
50%
60%
Diversity Other crops (e.g., fruit, veg)
Negative Nonsig Positive

29. Vulnerability
11%
9%
17%
51%
60%
44%
38%
30%
38%
0%
10%
20%
30%
40%
50%
60%
70%
Vulnerability (e.g., HEL) River, stream, other water Experienced weather
Negative Nonsig Positive

30. Farmer characteristics
24%
21%
7%
68%
75%
62%
8%
4%
31%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Age Farming experience Education
Negative Nonsig Positive

31. Summary of emerging findings: Consistently positive variables?
• Attitudes towards specific practices
• Evaluation of practice being adopted and related practices yes
• General measures of environmental attitudes not so much
• Active information seeking
• Attendance of field days, demos, workshops most consistent
• Passive measures such as number of contacts not so much
• Farm type
• Grain, row crop generally positive when significant
• Diverse operations, specialty crop producers
• Payments, cost share, technical assistance
• Vulnerability
• However, “not significant” usually highest proportion

32. Next steps
• Finish article data input
• Finish independent variable coding into categories and subcategories
• Code dependent variables to do practice type-specific analysis
• Expectation that we will see higher rates of significant relationships with
certain practices types and categories of independent variables
• e.g., HEL and cover crops
• Analysis and reporting

33. Motivations and Barriers to
Conservation Adoption
Evidence from Qualitative Research
Sarah Church and Pranay Ranjan
Purdue University

34. Qualitative data: What and why?
• More and more qualitative studies since 2008
• Additional perspective for the 2017 study
• Farmer voice
• Provides understanding and nuance
• To inform conservation programs, plans, and policies

35. Qualitative data analysis: How?
Arbuckle and Roesch-McNally 2015

36. Qualitative data analysis: How?
Arbuckle and Roesch-McNally 2015

37. Challenges
Nuance in farmer responses“Filter strips and habitats were most
often viewed as inconvenient, because
they required breaking up fields or
changing management practices. One
farmer did not intend to adopt many
filter strips because he knew his landlord
would not permit it, and he preferred to
use cover crops in this situation because
they would not take land out of
production.” (Kalcic et al. 2015, p.986).
– Decision making is complex!

38. Results
• 36 qualitative or mixed methods articles
• 20 articles coded to date
• Articles published between 1997 and 2017

39. Results: Coding themes
Motivations Barriers
Economic Economic
Farm management Farm management
Soil health Government programs
Government programs Risk
Social norms Other
Water quality
Nutrient loss reduction

40. Results: Motivations/Barriers
• Coding theme (e.g., Economic)
o Subcode (e.g., Reduced input costs)
Applicable practices described in the paper (e.g., cover crops; controlled drainage; nutrient
management; etc.)

41. Results: Motivations
• Economic
o Reduced input costs
Conservation tillage; general conservation practices; nutrient management; perennial
wheat
o Profitability themes – including improved yield
Conservation and no-till; controlled drainage; conservation practices; nutrient
management; perennial wheat
o Favorable commodity markets
Grassland; perennial conservation practices; perennial wheat

42. Results: Motivations
• Farm management
o Farm compatibility – including farm goals
Cover crops; filter strips; grassed waterways; nutrient management; wildlife habitat
o Integration into a livestock system
Cover crops; perennial wheat; trees
o Time savings and lower maintenance
Conservation program participation; conservation tillage; perennial wheat

43. Results: Motivations
• Soil health
o Reduced erosion
Buffer strips; conservation and no-till; cover crops; general conservation practices; grassed
edges; grassed waterways; hedgerows; nutrient management; perennial wheat; tailwater
ponds; vegetated ditches
o General soil health
Conservation program participation; conservation tillage; cover crops; general conservation
practices; perennial wheat

44. Results: Motivations
• Government programs
o Availability of cost-share payments
CRP participation; cover crops; filter strips; general conservation practices; grassed
waterways; hedgerows; manure storage; nutrient management; perennial conservation
practices; wildlife habitat
o Technical assistance
General conservation practices; perennial conservation practices

45. Results: Motivations
• Social norms
o Farmer leaders and neighbor success
Cover crops; hedgerows
o Subjective norms
General conservation practices; nutrient management
"Well, we had a neighbor that used to put rye
on corn he chopped…and I kind of laughed. But
then we had a winter where the frost went out
the first part of February and…the top two
inches thawed out and then we had heavy rain.
And it started washing where there was
nothing…I didn’t laugh anymore. I was like,
‘we have to do something.’ So that’s how we
got started." (Arbuckle and Roesch-McNally 2015, p. 425)

46. Results: Motivations
• Water quality and nutrient loss
o Water quality improvements
Buffer strips; filter strips; general conservation practices; grassed edges; hedgerows;
tailwater ponds; vegetated ditches
o Nutrient loss reduction
Cover crops; filter strips
"…[we] put in winter rye so we can sequester
the nitrogen. And then go ahead and kill it off
in the spring and… it will release that nitrogen
naturally. And we put a lot of that nitrogen on,
our rates of nitrogen dropped from 225 lb.
down to 125 lb. to 100 lb. So we’re trying to
number one, reduce costs, and two, be better
stewards and trying to keep that nitrogen out
of the water supply." (Reimer et al. 2012, p. 37)

47. Results: Barriers
• Economic
o Implementation costs
Bioreactors; controlled drainage; filter strips; nutrient management; organic
farming; perennial conservation practices; subsurface drainage; vegetated edge
management; wetlands; wildlife habitat
o Themes of profitability (Drip irrigation; general conservation practices; nutrient
management subsurface drainage)
o Favorable commodity market (Conservation program participation)
o Unfavorable commodity market (Crop rotations; organic farming)

48. Results: Barriers
• Farm management
o Incompatibility (existing physical or business operations)
Conservation and no-till; controlled drainage; cover crops; filter strips; grassed waterways;
perennial conservation practices; vegetated edge management; wildlife habitat; wetlands
o Increased management/effort
Conservation tillage; general conservation practices; nutrient management; perennial
conservation practices; subsurface drainage
o Timing issues
Cover crops; spring apply fertilizer

49. Results: Barriers
• Farm management “…spring operations (cover crop termination
and residue incorporation) were inconvenient
and risky because of the demand on farmers’
time and potentially wet conditions…also time
conflicts with planting the cover crop in the fall,
as one farmer said ‘[its] hard to pull the [seed]
drill out of the shed while the combine is
running’…Timing…of spring fertilizer
application [was a concern], while potential
yield reductions for reduced fertilizer
application rates were the most frequent
‘con’…” (Christianson et al. 2014, p.147)

50. Results: Barriers
• Government programs
o Inflexibility, burdensome requirements, application process, on-going
contract maintenance, complexity
Conservation program participation; CRP; general conservation practices; nutrient
management; subsurface drainage
o Distrust in government
General conservation practices
o Programs favor landowners over operators and eligibility requirements
CRP; general conservation practices

51. Results: Barriers
• Government programs “…One current CRP participant was not
planning to re-enroll due to burdensome
requirements. While this farmer indicated that
his interactions with government agencies were
positive, he had a negative view of the contract
requirements involved in CRP: ‘It was like some
big brother was looking over my shoulder the
whole time.’” (Reimer and Prokopy 2014, p. 326)

52. Results: Barriers
• Risk
o Uncertain benefits
Cover crops; vegetated edge management
o Uncertainty surrounding crop yield
Cover crops; nutrient management; perennial conservation practices; subsurface drainage;
no-till; wetlands
o Dangerous debris, fire, spread of invasives
Hedgerows; vegetated edge management

53. Results: Barriers
• Other themes
o Blame shifting
o Distrust of information
o Equipment issues
o Learning curve (complex and time consuming)
o Leased land/unsupportive landlords
o Neighbor’s issues/problems

54. Results: Barriers
“…I do not think it is just farmers. Actually I
think in general farmers or agriculture probably
is less damaging to the water supply than
industry and even home owners. There is
probably more fertilizer and chemical dumped
on yards in town per acre than what there is on
a farm.” (Kalcic et al. 2014, p. 805)
• Other themes
o Blame shifting

55. Results: Barriers
“One farmer stated he would prioritize
conservation on owned lands, and only
consider conservation on rented land
if the rental contract was long term…In four
cases, the farmer saw the landowner’s lack of
interest in conservation as an impediment to
using conservation practices that he would like
to use on rented land.” (Kalcic et al. 2014, p. 805)
• Other themes
o Blame shifting
o Distrust of information
o Equipment issues
o Learning curve (co
o Leased land/unsupportive landlords

56. Agency and NGO
Perspectives
Jimmy Bramblett, Deputy Chief for Programs, USDA-NRCS
Katie Flahive, Environmental Scientist, USEPA
Moira Mcdonald, Senior Program Officer, Walton Family Foundation

57. Next Steps
Linda Prokopy
Purdue University

58. Lots more to do!
• Finish reviewing articles
• Continue coding
• Collate final coding
• Code dependent variables to do practice type-specific analysis
• Examine difference between “willingness to adopt” and adoption papers
• Look at longitudinal and spatial effects
• Recommendations for future studies
• Statistical meta-analysis
• Publish dataset online

59. Acknowledgments
• Study Team: J. Arbuckle, Kristin
Floress, Ben Gramig, Sarah
Church, Francis Eanes, Yuling
Gao, Linda Prokopy, Pranay
Ranjan, Ajay Singh
• Discussants: Jimmy Bramblett,
Katie Flahive, Moira Mcdonald
• Funding: Walton Family
Foundation