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VOLUME 9 ISSUE 4

The International Journal of

Environmental Sustainability __________________________________________________________________________

Agroforestry Information Dissemination and the Social Learning Theory in Pontal do Paranapanema, São Paulo, Brazil

WENDY FRANCESCONI, PK RAMACHANDRAN NAIR, TAYLOR V. STEIN, DOUGLAS J. LEVEY, JARET C. DANIELS, AND LAURY JR. CULLEN

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THE INTERNATIONAL JOURNAL OF ENVIRONMENTAL SUSTAINABILITY http://onsustainability.com/ First published in 2014 in Champaign, Illinois, USA by Common Ground Publishing University of Illinois Research Park 2001 South First St, Suite 202 Champaign, IL 61820 USA www.CommonGroundPublishing.com ISSN: 2325-1077 © 2014 (individual papers), the author(s) © 2014 (selection and editorial matter) Common Ground All rights reserved. Apart from fair dealing for the purposes of study, research, criticism or review as permitted under the applicable copyright legislation, no part of this work may be reproduced by any process without written permission from the publisher. For permissions and other inquiries, please contact . The International Journal of Environmental Sustainability is a peer-reviewed scholarly journal.

Agroforestry Dissemination and the Social Learning Theory in Pontal do Paranapanema, São Paulo, Brazil Wendy Francesconi, National Soil Erosion Research Laboratory. USDA-ARS, USA PK Ramachandran Nair, University of Florida, USA Taylor V. Stein, University of Florida, USA Douglas J. Levey, National Science Foundation, USA Jaret C. Daniels, University of Florida, USA Laury Jr. Cullen, Instituto de Pesquisas Ecológicas, Brazil Abstract: The conversion of natural habitats to unsustainable land use practices that continues in many developing countries can further degrade the agricultural landscape and hinder the development of rural areas. Agroforestry is one of the approaches being used to addressing this problem. Acquiring the information pertaining to such sustainable practices and disseminating it to land users is a critical step in rural development. To assess whether Social Learning Theory (SLT) would be useful in understanding the dissemination of agroforestry information among farmers, a survey of farming households was conducted in the Pontal do Paranapanema region of São Paulo state, Brazil. This region was selected because of the on-going agrarian reform which has resulted in the fragmentation of natural habitat and agricultural areas. A total of 94 heads-of-households were interviewed about farming practices and sources for agriculture information. The results indicated that farmers with greater social networks and agricultural experience were more likely to adopt agroforestry practices than those who did not have such advantages. The SLT results provide partial evidence of its applicability to understanding agroforestry behavior dissemination. Two of the theory’s constructs (Imitation and Differential Reinforcement) were significantly correlated with agroforestry adoption. Yet, the other two (Differential Association and Definitions) were not. Confusion on behalf of the farmers about what constitutes an agroforestry practice could account for these results. By understanding how to motivate farmers to adopt agroforestry practices, land stewardship could be improved, making agricultural areas more conducive for environmental conservation and sustainable development. Keywords: Agrarian Reform, Cognitive Learning Theory, Diffusion of Innovation, Homegardens, Shaded Coffee

Introduction

R

esearch on diffusion of innovation has been widely conducted among rural communities to determine the spread of technical information and practices within a social system (Rogers, 2010). The agrarian reform settlers in Brazil’s Pontal do Paranapanema (hereafter Pontal) are however a special type of farming community. They are part of Brazil’s Movement of Landless Rural Workers (Movimento dos Trabalhadores Sem Terra – MST), and they are not considered traditional farmers of several generations working the same land (Stedman, 1999). Instead, they are a grassroots movement organized in cascading units that are represented by a centralized body of members. Consequently, the channels of communication and information flow back and forth through local, regional and national representatives. At the base of the movement, in each settlement there is a set of 10 to 15 families in charge of making decisions and communicating these to the rest of the community (Harnecker and Stédile, 2003). In spite of their participatory decision-making process, a pattern towards hierarchical associations exists among the members (Wright and Wolford, 2003), which might affect the dissemination of agricultural knowledge. Given that formal sources for agricultural information are limited in the Pontal region, learning through observation, imitation, and reinforcement, a learning process described in Social Learning Theory (SLT), may be an important mechanism for the dissemination of agricultural practices among these non-traditional farmers. The International Journal of Environmental Sustainability Volume 9, 2014, www.onsustainability.com, ISSN 2325-1077 © Common Ground, Wendy Francesconi, PK Ramachandran Nair, Taylor V. Stein, Douglas J. Levey, Jaret C. Daniels, Laury Jr. Cullen, All Rights Reserved. Permissions: [email protected]

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Social Learning Theory, also known as Social Cognitive Theory, has been traditionally used to explain learning of deviant behavior (Akers, 1973; Bandura, 1978). More recently the term “social learning” has also been used to describe a collaborative learning process among stakeholders that share a common interest (Reed et al. 2010). However, SLT is focused on the leaning mechanisms by the individual and the changes in behavior influenced by the social environment. The theory, originally presented by Miller and Dollard (1941), was an attempt to understand cognitive learning of any kind of behavior as long as the learning occurs within a specific social context. Bandura (1977) further developed these ideas by describing the observational learning and modeling process as a series of steps: attention, retention, reproduction, and motivation. Another version of these theoretical concepts, in combination with Sutherland’s (1947) differential association theory, has been operationalized by Akers et. al. (1979). Akers et al. (1979) were the first to provide an empirical approach to explain learned (deviant) behavior. In contrast to Bandura, Akers et al. (1979) called these steps the four major explanatory concepts of SLT, and described them as: Differential Association, Definitions, Differential Reinforcement, and Imitation. In simple terms, the concept of Differential Association refers to the peer-to-peer interactions within a social environment, the Definitions concept refers to the individual’s attitudes towards the behavior, the Differential Reinforcement concept addresses the rewards or punishments linked to the behavior, and the concept of Imitation refers to engaging in the behavior (Krohn et al. 1985). The explanatory constructs of SLT can serve as variables to describe the diffusion process of sustainable agricultural practices such as agroforestry –trees planted with crops and/or animals. Despite the numerous studies applying SLT to criminal/deviant behavior (Krohn et al. 1985; Skinner and Fream, 1997; Akers and Jensen, 2003; Fisk, 2006; Pratt et al. 2010), the theory has received little attention in the field of environmental conservation (Constanzo et al. 1986, Horsley 1995) and much less in the field of agriculture (Schmit and Rounsevell 2006). Yet, the concepts of SLT can be found throughout different adoption-diffusion studies of agroforestry. For example, (1) the degree of interaction with others discussed by Faysse et al. (2012) and Kiptot et al. (2006) is comparable to the so-called Differential Association in SLT; (2) the decision making process of incorporating an agroforestry practice can be equivalent to Defining the behavior from the individuals’ perspective in SLT (Feder et al. 1985; Matthews et al. 1993; Thangata et al. 2002; Asse and Lassoie 2011); (3) the analysis of the perceived financial contributions by the innovation can be interpreted as the Differential Reinforcement concept (Arnold 1995; Franzel and Scherr, 2002); and (4) implementing the innovation and learning by doing or by spillover is analogous to Imitation in SLT (Foster and Rosenzweig, 1995). The application of SLT to explain agroforestry adoption as an experimental approach is worth exploring due to the many similarities with diffusion of innovations type research. Furthermore, due to the perceived hierarchical flow of information among farmers within MST farming communities, social networks may serve as informal sources of agricultural knowledge (Isaac et al. 2007). The conceptual framework of SLT might be applicable to the adoption of agroforestry, and agricultural practices in general. With the purpose of understanding the learning mechanisms among MST farming settlements at the Pontal, the present study evaluated agroforestry adoption from a SLT perspective. If the adoption of agroforestry practices is related to the farmer’s interaction and observation of other farmers practicing various forms of agroforestry, then learning through the observation of models as described by SLT may be valid to explain the transfer of agricultural knowledge. The potential implication of evaluating this type of learning process could be useful for the propagation of environmentally friendly agricultural practices that also promote sustainable development. The specific objectives of this study were (1) to describe the main characteristics and sources of information of two MTS farming communities at Pontal do Paranapanama, (2) to identify characteristics of farmers who more readily engage in

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agroforestry practices, and (3) to test the applicability of SLT constructs on the propagation of agroforestry practices.

Methods Study Site The Pontal used to be a continuous semi-deciduous forest prior to its conversion to agriculture (Veloso et al. 1991). Today, scattered forest fragments are evidence of the pre-anthropogenic landscape; they constitute about 18% of the original vegetation that made up what was once known as the Pontal do Paranapanema Great Reserve (PEMD 2006). The region is located in the western-most section of the state of São Paulo, where the Parana and Paranapanema rivers meet (Figure 1A). The landscape is characterized by a combination of shallow hills and slopes, and elevation is between 250 and 500 m above sea level. The weather is dry subtropical with an average temperature of 21°C and annual precipitation ranges from 1,100 to 1,300 mm (PEMD 2006).

Figure 1: A) Study site in Pontal do Paranapanema, São Paulo State, Brazil. B) & C) Geographical distribution of farms with different number of agroforestry practices at Riberão Bonito (RB) and Agua Sumida (AS) settlements (respectively). Source: © 2009 ESRI and © 2012 Google Earth The creation of farming settlements as a consequence of agrarian reform in Pontal do Paranapanema has resulted in the degradation of the remaining natural areas in some regions, as well as in the integration of conservation efforts and sustainable development in other areas (Cullen et al. 2005). Many of the appropriated and government re-distributed lands were marginal natural areas unsuitable for agriculture and therefore had not been used for that purpose (Romeiro and Reydon, 1994). The official recognition of land reform settlements in these areas resulted in their inevitable conversion to agriculture and to the deforestation, fragmentation and isolation of nearby forest remnants (Heredia et al. 2003). However, in some areas where previous landowners had practiced poor land stewardship, agrarian reform settlers have tried to ameliorate the environmental conditions by planting trees (both natives and exotic). Upon arrival (during the mid-1980’s until now), agrarian reform settlers began developing the land by building their houses and working the land for agricultural purposes. Given the ecological importance of the remaining forest fragments in the Pontal region, the Institute for Ecological Research (Instituto de Pesquisas Ecológicas-IPÊ) became heavily involved at integrating the farmers into landscape conservation initiatives (Albernaz, 1997, Mielke and

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Cassagrande, 1997). Through the development of nurseries, workshops, and tree planting events, IPÊ has conducted a large share of the dissemination of sustainable agricultural practices such as agroforestry. Among the agroforestry practices present in the landscape, homegardens (the planting of vegetables and fruit trees surrounding the homestead) are the most common (Figure 2). Shaded coffee (coffee planted under trees), silvopastoral systems (grazing pastures with trees), living fences (fences made with trees instead of dead posts), and alley cropping (intercropping of crops and trees), were less common, but also present. The adoption of agroforestry practices in combination with the establishment and protection of forest reserves along with other landscape ecology strategies, might be improving the chances for native and endemic species to survive in this region (Cullen et al. 2001; Cullen et al. 2004).

Figure 1: Two MST homegardens at Pontal do Paranapanema. A) depicts a homestead on a farm with four different types of agroforestry practices. B) depicts a farm without agroforestry practices Source: Francesconi (2009)

Data Collection A survey of closed and open-ended questions was conducted to obtain quantitative and qualitative contextual information about farming practices. Within the Pontal region, the study was conducted in two farming settlements (Riberão Bonito (RB) and Agua Sumida (AS)), which were created during the 1990s through the government’s agrarian reform led by Brazil’s landless social movement. The settlements are similar in size, population, and location in terms of distance to markets and towns. The surveyed farms were selected randomly and one adult per farm, usually the head of household was interviewed and asked questions about their relations with neighbors and about sources of agricultural information. The interviews were conducted during the months February and March, 2010, and consisted of 40 questions that included personal information such as age, gender and years living in the settlement, as well as questions design to measure their interaction with other farmers and the four explanatory constructs of SLT. To test the SLT constructs, questions related to Differential Association, Definitions, Imitation and Differential Reinforcement in relation to information acquisition and adoption of agroforestry practices were incorporated in the survey (Table 1). The format of the social construct questions were based on the survey instruments developed by Akers (1977) and Fisk (2006). Since the questionnaires in these surveys were created to evaluate the theory of Social Learning for criminal or deviant behavior, the questions were modified to relate to the adoption of agroforestry techniques. Responses were measured as categorical data. Some questions required participants to choose from fixed percentages (i.e., 5%, 25%, 50%, 75% and 95%), others a series of options (Excellent, Good, Fair, Poor, Awful), and some provided a semi-

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structured list of items to choose from. For subsequent analysis the responses were coded on a 5 point Likert-like scale ranging from 1 to 5. Table 1: Social Learning Theory constructs and survey questions to evaluate the model Social Learning Theory Survey Instrument Questions Constructs

Differential Association

What percentage of your friends/relatives/neighbors has agroforestry practices in their farms?

Definition

What do you think about Agroforestry practices?

Imitation

With what frequency have you incorporated different agroforestry practices in your farm?

Differential Reinforcement (Benefits)

What types of benefits do you think incorporating Agroforestry Practices have?

Differential Reinforcement

What types of disadvantages do you think incorporating Agroforestry practices have?

(Cost)

Data Analysis Some of the questions in the survey instrument were analyzed with descriptive statistics to understand the basic structure of the populations studied and the flow of agricultural information. The descriptive statistics data included mean and percentage values for the demographic variables such as age, level of education, years living in the Pontal region, etc. Other data such as the main sources of income and principal agricultural practice were described as a percentage, but not compared statistically. A regression analysis was run in SAS 9.2 (SAS Institute Inc. 2011) to identify the farmer characteristics that could explain agroforestry adoption in the Pontal region. The regression model was built with a total of 12 independent variables (Table 2). The regression analysis was conducted to identify farmer characteristics that might result in agroforestry adoption. The number of agroforestry practices within a single farm was set as the dependent variable (from zero to a maximum of four), and a backward elimination model was used to test the different potential indicator variables. Among the variables examined in the regression analysis, distance to the nearest farm containing the highest number of different agroforestry practices had to be estimated. According to SLT, observation of the behavior in question, in this study an agroforestry practice, serves as a model. To evaluate if greater visual exposure might lead to greater adoption, distance to the nearest farm containing the highest number of different agroforestry practices was estimated. Distance between farms was measured using ArcGIS 9.3 (Copyright © 2009 ESRI). The ArcMap extension was used to create a map and locate all the farm polygons in the settlements (Figure1B and 1C). Distance to the nearest farm with the highest number of different agroforestry practices was measured as the Euclidean distance from the center of each farm (which was calculated using zonal geography in ArcMap). This variable was included in the backward elimination regression model, and analyzed separately for each settlement using a Spearman Rho correlation given that the parameter is a function of the spatial arrangement of each landscape. To evaluate the applicability of the SLT among the MTS farming settlements, the questions addressing the theory’s explanatory constructs were compared to the number of agroforestry

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practices adopted. A Spearman’s Rho correlation procedure was conducted in SAS 9.2. As in the regression analysis, the number of agroforestry practices within a single farm was set as the dependent variable, and the different SLT explanatory constructs were set at the explanatory variables. In addition, the correlation coefficients between the SLT constructs were described to compare the relation between the theory’s explanatory variables. The level of significance for the different statistical analyses was an alpha of 0.05.

Results Farming Community and Sources of Information A total of 94 out of approximately 315 households were surveyed: 49 at Agua Sumida and 45 at Riberão Bonito. Out of the total number of households approached, the response rate was 98%. Analysis of the data indicated that 38% of the interviewees were female and 62% were male. The average age of the respondents was 51 years, and the average number of years attending school was 4.4. Among the farmers interviewed, migration to their government assigned or purchased land began in 1984, and continued until the year prior to when this study was conducted in 2010. For 41% of the farmers interviewed, 1998 was the year when they acquired their property. Yet, the number of years the respondents had been living in the Pontal region precedes this date by an average of 30 years. This suggests many respondents’ had long histories in the area, even though they have owned property for only a little over a decade. All the landowners interviewed were engaged in agricultural activities and for most respondents their farms were their primary livelihood (59%). Other sources of income included government pensions or food assistance programs, non-farm jobs, and financial support from family members outside the farm. Among the income-producing agricultural practices, milk production was the most profitable and widespread, and was followed by cassava production. As a consequence of the higher income associated with milk production, in the last decade many farmers have switched from cassava as their main agricultural practice to becoming small dairy producers. In terms of farming experience, the majority of the settlers in the Pontal region have worked in agriculture related jobs for most of their lives. The average number of years the respondents have been working in agriculture is 36. Many of them had been engaged in agricultural activities since childhood. Among the sources of knowledge of agricultural practices, family members were the group most frequently mentioned; following were friends or neighbors in the Pontal region, their own experience through trial and error, and extension agents ranked forth. Prior to living in the Pontal, the settlers migrated to the region from many different locations in the country, some came from far away states in the Northwest, to neighboring farming communities and towns. When asked if they were planning to move somewhere else in the future, all but a couple of respondents said they were planning to stay and continue to farm in the Pontal for the rest of their lives. When asked about agroforestry, 93% said they had heard about the concept. Furthermore, without being asked to name an example, many of the farmers mentioned a type of agroforestry known as shaded coffee. Out of the total number of farmers, 88% said they have incorporated agroforestry practices in their farms. Of the total number of agroforestry practices inventoried on the 94 farms, 46% were homegardens, 21% living fences, 16% silvopastures, 9% shaded coffee systems, and 8% alley-copping systems (usually cassava-Manihot esculenta Crantz- intercropped with corn- Zea mays L.). When asked if they could remember who first mentioned the term “agroforestry” to them, 49% said an agricultural organization or institution such as IPÊ or the São Paulo State Land Institute - ITESP. Closely following, 39% said they first heard about agroforestry from a friend or neighbor. A small group of farmers also mentioned family or other sources of information such as television or off-farm work environments. A different question

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addressed who taught the farmers the agroforestry practices they currently have in their farms. The most frequent answer was family members, closely followed by extension agents from IPÊ, alone through trial and error, and friends or neighbors from the Pontal region. To compare the perceived influence exerted by friends or neighbors that practice agroforestry, the farmers were asked to approximate the percentages of their neighbors who engaged in agroforestry practices. The majority of the farmers thought a lower proportion of their friends and neighbors were engaged in agroforestry than what the data indicated. Only 40% thought almost all their friends and neighbors had agroforestry practices in their farms. On the other hand, 80% thought that almost all of their friends and neighbors were agricultural producers. None of the respondents said they did not have friends or neighbors engaged in agriculture, yet 1% said they did not know anyone that practice agroforestry. Even though most of the farmers had a positive attitude towards the different agroforestry practices (good or very good), shaded coffee agroforestry practices was the exception. Almost half (45%) the farmers had a neutral or negative opinion on shaded coffee. In contrast, homegardens were most commonly viewed as positive (96%). Among the other agroforestry practices present in the region, silvopastures, living fences, and alley cropping were thought by most in a positive way (85%,83, and 54% , respectively) , but there were also respondents who perceived them as not being worth incorporating. The farmers were also asked about the frequency of their agricultural interactions with other farmers, and their opinion about exchanging agricultural knowledge. When asked to select the group with whom they usually discuss agricultural practices, most answered family (39%) and neighbors (37%), and a smaller percentage (24%) answered friends. As far as the frequency in which these interactions take place, the most common answer was once a week, closely followed by less than once a month. The third most common answer was between the latter two: once a month. These responses appear to have a bimodal distribution. Among the farmers that more frequently discussed agricultural topics with family, friends and neighbors, about half (43%) had a single or no agroforestry practices in their farms. In addition to the frequency of these interactions, the respondents were asked what would be the advantages of discussing agricultural practices with friends, neighbors, and family members. The most common response was that they were a source of information that was easily accessible (31%), while others explained that these groups could provide demonstrations (20%) and that they could be a source of new ideas (22%). About 3% responded that there were no advantages in discussing agricultural practices with friends, neighbors or family members as they might provide misleading information.

Characteristics Associated with Agroforestry Adoption The stepwise regression analysis resulted in a model with three significant parameters (Table 2). The regression analysis was initially built with a total of 12 candidate variables; however through the backward elimination procedure only three were significant in explaining the difference in number of agroforestry practices adopted. The total number of families known by the famers (P = 0.012), along with the total number of years working in agriculture (P = 0.006), and the frequency of agroforestry system incorporation (P = 0.001), were parameters that explained some of the variability in agroforestry practice adoption. The significant parameters in the regression model explained 28% of the data variability. The regression procedure had nine steps and the initial model with all the candidate variables had a model fit of 31%. Distance to the nearest farm containing the highest number of different agroforestry practices was the last parameter removed in the backward elimination stepwise regression procedure. Hence, it was analyzed separately for each farming settlement. The results for the Spearman Rho correlation analysis indicate that the number of agroforestry practices per farm and the distance of these to the nearest farm with the highest number of agroforestry practices was significant only at the Agua Sumida farming settlement (r = −0.341 P = 0.017), but not at Riberão Bonito (r = 0.039 P = 0.766). The negative correlation coefficient at Agua Sumida 7

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indicated that as the distance to the nearest farm with the highest number of agroforestry practices increases, the number of agroforestry practices adopted decreases. Table 2: Variables evaluated using backward stepwise regression in SAS 9.3. The number of agroforestry practices incorporated was set as the dependent variable. The questionnaire by Fisk, (2006) was use as a guide to define the variables used. No.

Model Variable

1

Head of household age

2

Head of household gender

3

Number of years of education

4

Number of years living in the Pontal do Paranapanema region

5

Estimate of total number of products produce by the farm

6

Number of social groups with whom farmer discusses agriculture topics

7

Frequency discussing agricultural practices with friends and neighbors

8

Number of families the farmer knows that practice agroforestry

9

Distance to farms with the highest number of different agroforestry practices†

10

Number of families in the settlement the farmer knows and interacts with*

11

Number of years farming*

12

Have you incorporated agroforestry practices in the past*

*Significant parameter in predicting agroforestry adoption †In addition to the other significant variables, distance was significant at the farming settlement Agua Sumida (AS) when the analysis was run separately for each community.

Social Learning Theory Evaluation The results from the evaluation of the SLT constructs provide evidence of the application of this theory as an explanatory framework for the diffusion of agroforestry among farmers (Table 3). Of the total possible pairwise comparisons between the SLT constructs and the number of agroforestry practices per farm, five were significant. The relation between the number of agroforestry practices per farm and the frequency in which these were incorporated (r = 0.436, P