Factors Affecting Farm Operators’ Interest in Riparian Buffers and Forest FarmingCorinne Valdivia – University of Missouri

MU Center for AgroforestryChristine Poulos - Research Triangle Institute

Introduction Missouri top 1/3 in agricultural commodities

though only 11% farmers list ag. as main or sole source of income.

Multiple sources of income and household objectives: profits, quality of life, future, environment.

Agroforestry strategy to diversify the household portfolio.

The practice or field of farming is known to farm operators. Riparian buffers and forest farming belong to the field or practice of agroforestry.

Objective

Understand what factors increase the likelihood of farm operators’ interest in agroforestry.

Explore the concepts of Habitus (the values and perceptions) - and Field (the social processes and structures, the rules of the game) (Pierre Bourdieau); along with traditional variables used in studies of adoption.

Focus: northeast and southeast Missouri farm operators.

Interest in agroforestry…

Instruction: show a picture of the practice “Please indicate how interested you might be

implementing the following practices on the land you own” (6 were mentioned, we focus on two) Riparian/Stream bank plantings Forest farming

4=very interested 3=moderately interested 2=slightly interested 1=uninterested 99=not applicable

Interest = 1 if 4 or 3; =0 otherwise

Riparian Buffer or

Streamside Plantings

Planting rows of trees, shrubs and

grasses along waterways

Forest farming

Growing crops under the Shade of trees in the forest

NENEFox- Wyaconda Fox- Wyaconda

WatershedWatershed

SESEScott Co.Scott Co.Site Selection Requirements

in the Mississippi River floodplain ecological/cultural diversity accessible local resource professionals support

The Sites and Sample: 365 farm operators

From the literature on adoption A review of conservation, new technologies,

and agroforestry summarized in the paper. Models address issues of perception and

interest, as well as the importance of economics when the land is the main source of livelihood.

The literature also highlights the need to analyze adoption including factors such as biophysical characteristics and risk and uncertainty.

A proposed model on factors affecting interest in new practices

AttitudesHabitus

StructureInstitutions

Field

EnvironmentPhysical

Economic

IndividualHH

Interest

The Model Logistic regression applied to a dichotomous variable,

being interested 1 or not 0 on agroforestry on the land you own. A Maximum Likelihood estimation:

Ln (Odds) = a +B1X1 +B2X22+B3X3 +B4X 4 +B5X5

Odds = Prob/(1-Prob) ; Prob (event)= eZ/(1- eZ)

Independent Variables: X1 INDIVIDUAL X2 ECONOMIC X3 PHYSICAL X4 FIELD X5 HABITUS

Independent Variables

Individual: Age of Head of Household (Life Cycle); Education other than formal education- magazines, knowledge through groups

Economic: diversity index of the household economic portfolio

Structure: involvement in farming (full/part-time); CRP payment

Physical: trees on land, frontage without trees, bank erosion (high, very high)

Attitudes/Habitus: trees important to future generations, trees important for scenic beauty, knowledge of agroforestry (FF, RB)

Interest in Riparian Buffers: Logic Estimation Results

Individual

Age

Magazines

Coef.

-0.0352

0.4068

Z Value

-2.37

1.06

P>|Z| Odds

0.018 0.966

0.289

Economic

HH Diversity I 0.3155 1.54 0.123

Structure/Field

CRP $ 0.0081 1.35 0.176

Constant term -2.6765 -2.87 0.004

N = 336

LRchi2 = 49.87

P> chi2 =0.0000

Interest in Riparian Buffers: factor coefficients and significancePhysical

Bank Erosion

Frontage WOT

Location

Coef.

1.021

0.005

0.591

Z Value

2.89

0.35

1.47

P>|Z| Odds

0.004 2.778

0.725

0.143

Habitus/Attitudes

Trees Future G.

Trees Scenic B.

Knowledge RB.

0.933

0.730

1.481

2.43

1.85

2.96

0.015 2.543

0.064 2.075

0.003 4.401

Pseudo R2 = 0.1803

Interest in Forest Farming: Logit Estimation Results

Individual

Age

Member Inf. G.

Coef.

-0.0258

1.0850

Z Value

-1.77

1.41

P>|Z| Odds R

0.077 .97

0.159

Economic

HH Diversity I -0.170 -0.82 0.411

Structure/Field

Part time farm 0.3468 0.86 0.387

Constant term -1.4104 -1.51 0.132

N = 296

LRchi2 = 51.42

P> chi2 =0.0000

Interest in Forest Farming: Logit Estimation ResultsPhysical

Trees on the land

Coef.

0.6105

Z Value

1.67

P>|Z| Odds

0.095 1.84

Habitus/Attitudes

Trees Future G.

Trees Scenic B.

Knowledge FF.

1.0404

0.7481

2.5254

2.64

1.84

4.10

0.008 2.83

0.066 2.11

0.000 12.49

Pseudo R2 = 0.1936

Model of Interest Findings Attitude variables are significant in both practices,

those that believe that trees are important to future generations and for scenic beauty are more likely to be interested in agroforestry

Knowledge of the practice has the strongest positive effect indicating that farm operators familiar with the field of agroforestry are more likely to be interested

The physical characteristics of farm operator’s land (bank erosion; trees) increase the likelihood of interest in the practices

Economic variables, diversification of the portfolio and part time farming, and CRP payments have no effect on the likelihood of being interested

Conclusions/Implications Economics: on the one hand for most operators

land is not the only source of livelihood which may explain why it is not significant in interest. It may be significant when estimating actual adoption. On the other, several variables were correlated, so further work on proxies for economic and field/structural variables.

The findings on the positive effect of knowledge point to the importance of information delivery networks.

Knowledge reduces uncertainty and risk about new technologies (Pattanayak et al).

Implications/further research

In this particular case knowledge pertains to the field of agroforestry, not traditional farming. The habitus concept appears to be useful in understanding interest.

The significance of physical characteristics indicates these should be included in the information provided to farm operators with the practices.

Further research using ecological characteristics to identify the sample frame as well as formulate interest questions will be tested.

Thank you!

Questions, suggestions.

Literature review of adoption: Agriculture and Agroforestry

Interest in new technologies when “awareness, feasibility, in line with objectives” (Pannel)

Attitudes strongest effect on decision to adopt (Matthews)Familiarity with practice stronger than education (Matthews)Type of operation, age, gender, and size No Effect (M)Economic: monetary and non monetary significant when

livelihood depends on land (Koontz); length of returns relevant in case of trees (Raintree); competitive uses of land significant (Alig et al)

Institutions: Up front costs in RB significant, cost share important (Lyn and Brown)

Services of AFP: Aesthetics, shade, wildlife, soil conservation (perceived benefits) (Workman et al)

The Literature on Adoption: Conservation

Study of perceptions, decision to use, effort, phases in the adoption process (Ervin and Ervin; Cooper and Keim; Konyar and Osburn; Skaggs et al; Jansen and Grebemicael; Hagan) Personal: education and attitudes (Ervin and Ervin; Clearfield

and Osgood); age and education (Konyar and Osburn) Physical: soil erosion (E&E); perception of erosion (C&O) (K&O) Economic: returns, debt free assets; off-farm; risk (E&E;K&O);

farm structure (K&O;C&O); income from farming (H); returns, competition among different activities (Johnson et al)

Institutions: Level of incentives (C& K); reverting to farming (S) technological assistance/extension; government cost share; level of incentives (E&E;C&O; C&K; J&G)

Non monetary motivations a driving force in adoption when the practice is not the main or sole source of income (Koontz)

Attitudes

Disposition to change (Schucksmith) Bourdeau’s habitus and field: accumulators,

conservatives, disengagers Attitude toward agroforestry: paths within the

field of farming (windbreaks and riparian buffers) and in the field of agroforestry (forest farming, alley cropping) (Raedeke et al)

Attitudes shaped by awareness, willingness to take risks, and physical characteristics

Literature Review Adoption of Agroforestry (Pattanayak et al) Farmer preferences: education, age, gender, socio-

cultural status Resource endowments: income, assets, labor, livestock,

credit/savings Market incentives: potential income gain, distance to

market, price effect Bio-physical factors: soil quality, slope, plot size,

irrigation Risk and uncertainty: tenure, experience, extension and

training, membership Need to increase the studies focusing on bio-

physical and on risk and uncertainty

Interest in Riparian Buffers Results Individual: Age was significant (P<0.1) and had a

negative effect, while education captured by magazines had no effect.

Physical: Bank erosion was positive and significant (P<.01) while other variables had no effect.

Habitus/attitude: Knowledge of Riparian Buffers had the strongest positive effect (P<.01). Trees for future generations and scenic beauty had both a positive and significant effect (P<0.05)

Economic and structure variables had no effect on interest in establishing riparian buffers in their land.

Interest in Forest Farming Results Individual characteristics, age has a negative and

significant (P<.10) effect on interest in forest farming Physical characteristics, trees was significant and

positive (P<.10) Habitus/attitude, highly significant (P<.001) if they

believe trees are important for future generations; and significant (P<.10) for those stating that trees are important for scenic beauty

Knowledge of Forest Farming has the strongest positive effect (P<.001) on likelihood of being interested

Economic and structure/field variables had no effect on the likelihood of being interested in forest farming